Talks
Colloquia
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Query Operators and Systems for the Mobile Big Data Era, Demetris Zeinalipour (University of Cyprus, Cyprus), Monday, January 15, 2018, 10.30-11.30 EET.
Speaker: Demetris Zeinalipour
Affiliation: University of Cyprus, Cyprus Category: Colloquium Location: Room 148, Faculty of Pure and Applied Sciences (FST-01), 1 University Avenue, 2109 Nicosia, Cyprus (directions) Date: Monday, January 15, 2018 Time: 10.30-11.30 EET Host: George Papadopoulos (george-AT-cs.ucy.ac.cy) URL: https://www.cs.ucy.ac.cy/colloquium/index.php#cs.ucy.2018.zeinalipour -
Dealing with Emerging Data Challenges in Query Processing, Dr. Ekaterini Ioannou (Open University of Cyprus, Cyprus), Tuesday, December 5, 2017, 11:00-12:00 EET.
Speaker: Dr. Ekaterini Ioannou
Affiliation: Open University of Cyprus, Cyprus Category: Colloquium Location: Room 148, Faculty of Pure and Applied Sciences (FST-01), 1 University Avenue, 2109 Nicosia, Cyprus (directions) Date: Tuesday, December 5, 2017 Time: 11:00-12:00 EET Host: Demetris Zeinalipour (dzeina-AT-cs.ucy.ac.cy) URL: https://www.cs.ucy.ac.cy/colloquium/index.php#cs.ucy.2017.ioannou -
Recommending Interesting Visualizations for Data Exploration, Prof. Panos K. Chrysanthis (University of Pittsburgh, USA), Wednesday, June 1, 2016, 11:30-12:30 EET.
Speaker: Prof. Panos K. Chrysanthis
Affiliation: University of Pittsburgh, USA Category: Colloquium Location: Room 148, Faculty of Pure and Applied Sciences (FST-01), 1 University Avenue, 2109 Nicosia, Cyprus (directions) Date: Wednesday, June 1, 2016 Time: 11:30-12:30 EET Host: Demetris Zeinalipour (dzeina-AT-cs.ucy.ac.cy) URL: https://www.cs.ucy.ac.cy/colloquium/index.php#cs.ucy.2016.chrysanthisAbstract:
As the amount of data being generated every day increases exponentially, the term “Big Data” has been adopted to represent the challenge of large-scale data processing. Given the volume of data, the challenge is how to avoid overwhelming the users with irrelevant results. In this talk, we will discuss recent research challenges and opportunities in the emerging area of Data Exploration that aim to guide users to reveal valuable insights from large volumes of data (e.g., financial and scientific databases). We will particularly focus on solutions that can automatically recommend interesting visualizations, which reveal useful insights into the analyzed data.Short Bio:
Panos K. Chrysanthis is a Professor of Computer Science and a founder and director of the Advanced Data Management Technologies Laboratory at the University of Pittsburgh. He is also an adjunct Professor at Carnegie-Mellon University. His research interests lie within the areas of data management (Big Data, Databases, Data Streams & Sensor networks), distributed & mobile computing, workflow management, operating systems and real-time systems. He has fostered interdisciplinary collaborations between computer science, medicine, astronomy and mechanical engineering, both within and outside the University of Pittsburgh. His research contributions in principles, algorithms and prototypes to data management have been documented in more than 150 papers in top journals and prestigious, peer-reviewed conferences and workshops. In 1995, he was a recipient of the U.S. National Science Foundation CAREER Award for his investigation on the management of data for mobile and wireless computing. His editorial service includes VLDB J (2001-2007), IEEE TKDE (2012-present) and DAPD (2011-present). Chrysanthis is an ACM Distinguished Scientist and a Senior Member of IEEE. He was honored with seven teaching awards and in 2015, he received the University of Pittsburgh's Provost Award for Excellence in Mentoring (doctoral students). For more information please visit: http://panos.cs.pitt.edu/ or http://db.cs.pitt.edu/Note:
Additional tutorial by Prof. Panos K. Chrysanthis: "Graph Partitioning in Distributed Graph Computation", Thursday, June 2, 2016 between 10:00-12:00, Room #148, New Campus, University of Cyprus. Tutorial abstract: https://www.cs.ucy.ac.cy/colloquium/abstracts/2016-Chrysanthis-Series.pdf Web: https://www.cs.ucy.ac.cy/colloquium/ Mailing List: https://listserv.cs.ucy.ac.cy/mailman/listinfo/cs-colloquium RSS: https://www.cs.ucy.ac.cy/colloquium/rss.xml Calendar: https://www.cs.ucy.ac.cy/colloquium/schedule/cs.ucy.2016.chrysanthis.ics -
Big Data meets Internet of Things, Prof. Arkady Zaslavsky (CSIRO, Australia), Thursday, November 5, 2015, 18:00-19:00 EET.
Speaker: Prof. Arkady Zaslavsky
Affiliation: CSIRO, Australia Category: Colloquium Location: Room 148, Faculty of Pure and Applied Sciences (FST-01), 1 University Avenue, 2109 Nicosia, Cyprus (directions) Date: Thursday, November 5, 2015 Time: 18:00-19:00 EET Host: Demetris Zeinalipour (dzeina-AT-cs.ucy.ac.cy) URL: https://www.cs.ucy.ac.cy/colloquium/index.php#cs.ucy.2015.zaslavskyAbstract:
The Internet of Things (IoT) is one of the major disruptive technologies and is on top of Gartner’s hype curve for 2014/2015. IoT will connect billions of "things", where things include computers, smartphones, sensors, objects from everyday life. IoT will be the main source of big data according to predictions of many experts. This talk focuses on challenges of the IoT and disruptively big data it generates. The talk will also showcase a CSIRO IoT technology which brings together sensing and cloud computing and is an efficient open platform for handling IoT data streams of high volume, velocity, value and variety. A case study built on the basis of the OpenIoT platform will also be presented.Short Bio:
Dr Arkady Zaslavsky is a Senior Principal Research Scientist in Data61 @ CSIRO. He is leading the scientific area of IoT at Data61 and leads a number of projects and initiatives. He was one of the leaders of EU FP7 project OpenIoT and is now leading a WP4 in EU H-2020 project bIoTope. Before coming to CSIRO in July 2011, he held a position of a Chaired Professor in Pervasive and Mobile Computing at Luleå University of Technology, Sweden where he was involved in a number of European research projects, collaborative projects with Ericsson Research, PhD supervision and postgraduate education. He currently holds the titles of a Research Professor at LTU (Sweden), Adjunct-Professor at UNSW (Sydney), Adjunct Professor at La Trobe University (Melbourne), Visiting Professor at St. Petersburg University of ITMO. He chaired and organised many international workshops and conferences, including Mobile Data Management, Pervasive Services, Mobile and Ubiquitous Multimedia and others. Arkady made internationally recognised contribution in the area of disconnected transaction management and replication in mobile computing environments, context-awareness as well as in mobile agents and Internet of Things. He made significant internationally recognised contributions in the areas of data stream mining on mobile devices, adaptive mobile computing systems, ad-hoc mobile networks, efficiency and reliability of mobile computing systems, mobile agents and mobile file systems. Arkady Zaslavsky has published more than 400 research publications throughout his professional career and supervised to completion more than 35 PhD students. Dr Zaslavsky is a Senior Member of ACM and a Senior Member of IEEE Computer and Communications Societies. Web: https://www.cs.ucy.ac.cy/colloquium/ Mailing List: https://listserv.cs.ucy.ac.cy/mailman/listinfo/cs-colloquium RSS: https://www.cs.ucy.ac.cy/colloquium/rss.xml Calendar: https://www.cs.ucy.ac.cy/colloquium/schedule/cs.ucy.2015.zaslavsky.ics -
Geospatial Search and Mobility, Dr. Dirk Ahlers (Norwegian University of Science and Technology, Norway), Wednesday, September 9, 2015, 18:00-19:00 EET.
Speaker: Dr. Dirk Ahlers
Affiliation: Norwegian University of Science and Technology, Norway Category: Colloquium Location: Room 148, Faculty of Pure and Applied Sciences (FST-01), 1 University Avenue, 2109 Nicosia, Cyprus (directions) Date: Wednesday, September 9, 2015 Time: 18:00-19:00 EET Host: Demetris Zeinalipour (dzeina-AT-cs.ucy.ac.cy) URL: https://www.cs.ucy.ac.cy/colloquium/index.php#cs.ucy.2015.ahlersAbstract:
Location helps us to understand, map, and navigate the world we live in. The growing availability of geospatial data has already enabled a vast range of services. With advancing sensing technology and mapping on the one side and increased volume of user-generated geospatial data on the other side, the granularity of geospatial data has been pushed down beyond the building level towards high-quality indoor locations. This talk will first give an overview of geospatial search engines and geographic information retrieval and discuss experiences in developing geospatial search in various environments. It will continue to discuss quality issues for different types of geospatial data. A final focus will be put on recent work on human mobility and campus movement analysis in the context of Smart Cities and in collaboration with NTNU's MazeMap system. A discussion of open question and future work will open the floor for discussion.Short Bio:
Dirk is a researcher in the field of geospatial Web retrieval and analysis. He is currently a research scientist at NTNU, the Norwegian University of Science and Technology, where he works on geospatial Web mining and mobility data. He first came to Norway as a Marie Curie postdoc. Previously, after having received his Ph.D. from the University of Oldenburg, Germany, with a thesis on Geographically Focused Web Information Retrieval, he did an extended research stay at Unitec, Honduras. Dirk was the project lead on multiple geospatial search and mobility projects and recently co-organized the LocWeb2014 and LocWeb2015 workshops. More details are available at http://www.ntnu.edu/employees/dirk.ahlers Web: https://www.cs.ucy.ac.cy/colloquium/ Mailing List: https://listserv.cs.ucy.ac.cy/mailman/listinfo/cs-colloquium RSS: https://www.cs.ucy.ac.cy/colloquium/rss.xml Calendar: https://www.cs.ucy.ac.cy/colloquium/schedule/cs.ucy.2015.ahlers.ics -
Preference-based Big Data Exploration, Prof. Panos K. Chrysanthis (University of Pittsburgh, United States), Wednesday, July 15, 2015, 11:00-12:00 EET.
Speaker: Prof. Panos K. Chrysanthis
Affiliation: University of Pittsburgh, United States Category: Colloquium Location: Room 148, Faculty of Pure and Applied Sciences (FST-01), 1 University Avenue, 2109 Nicosia, Cyprus (directions) Date: Wednesday, July 15, 2015 Time: 11:00-12:00 EET Host: Demetris Zeinalipour (dzeina-AT-cs.ucy.ac.cy) URL: https://www.cs.ucy.ac.cy/colloquium/index.php#cs.ucy.2015.chrysanthisAbstract:
As the amount of data being generated every day increases exponentially, the term “Big Data” used to represent the challenge of large-scale data processing, is being mentioned more and more frequently in everyday life. This reflects the fact that people are increasingly relying on using data to drive their daily activities and decisions. Given the volumes of data, the challenge is how to avoid overwhelming the users with irrelevant results. Query personalization is a well-known technique in dealing with this challenge by utilizing user preferences with the goal of providing relevant results to the users. Along with preferences, diversity is another important aspect of query personalization which reduces the amount of redundant information included in the results. In this talk, we will present two new personalization techniques that significantly improve big data exploration by utilizing all types of user preferences in ranking and diversification. We will first present the HYPRE graph model and prototype system that integrate qualitative and quantitative preferences by means of preference strength or intensity. In the HYPRE model, users submit both qualitative and quantitative preferences along with an intensity value, both of which are used to filter and rank the query results. Then we will introduce a new framework called Preferential Diversity (PrefDiv), which is capable of generating results that are not only relevant to users' preference but are also diverse. Our framework provides users with a fine control over the trade-off between relevancy and diversity through intuitive tunable parameters. We design and implement a prototype of a real system for PrefDiv and design algorithms to work with the HYPER hybrid preferences model. Our experimental evaluations show that PrefDiv can successfully increase coverage of the result set compared to other alternatives, and achieves a significantly better Relevancy-Diversity trade-off ratio than other models. This work was in collaboration with Roxana Gheorghiu, Xiaoyu Ge and Alexandros Labrinidis.Short Bio:
Panos K. Chrysanthis is a Professor of Computer Science and the founder and director of the Advanced Data Management Technologies Laboratory at the University of Pittsburgh. Among his research interests are big database systems, data stream processing, mobile and pervasive data management, and distributed computing. He has fostered interdisciplinary collaborations between computer science, medicine, astronomy and mechanical engineering, both within and outside the University of Pittsburgh. His research contributions in principles, algorithms and prototypes to data management have been documented in more than 150 papers in top journals and prestigious, peer-reviewed conferences and workshops. In 1995, he received one of the first NSF CAREER Awards for his pioneer work on mobile data management and in 2010, he was recognized as a Distinguished Scientist by ACM. In 2007, he was also elevated to the level of a Senior Member of IEEE. The impact of his work is also evident in his appointment to the editorial board of several journals, his selection as a General and Program Chair of conferences and workshops and his invitations as a keynote speaker in various meetings. He was invited to offer tutorials, contribute book chapters, and organize and participate in NSF and Dagstuhl planning meetings. He has repeatedly served as a Program Committee member in all major data management conferences and his work has appeared in textbooks. For more information, please see http://db.cs.pitt.edu.Note:
Slides available at the following URL: https://www.cs.ucy.ac.cy/colloquium/slides/2015-chrysanthis-talk-slides.pdf Web: https://www.cs.ucy.ac.cy/colloquium/ Mailing List: https://listserv.cs.ucy.ac.cy/mailman/listinfo/cs-colloquium RSS: https://www.cs.ucy.ac.cy/colloquium/rss.xml Calendar: https://www.cs.ucy.ac.cy/colloquium/schedule/cs.ucy.2015.chrysanthis.ics -
ECM-sketches and Multi-cloud MapReduce, Dr. Odysseas Papapetrou (Technical University of Crete, Greece), Wednesday, July 8, 2015, 15:00-16:00 EET.
Speaker: Dr. Odysseas Papapetrou
Affiliation: Technical University of Crete, Greece Category: Colloquium Location: Room 148, Faculty of Pure and Applied Sciences (FST-01), 1 University Avenue, 2109 Nicosia, Cyprus (directions) Date: Wednesday, July 8, 2015 Time: 15:00-16:00 EET Host: Demetris Zeinalipour (dzeina-AT-cs.ucy.ac.cy) URL: https://www.cs.ucy.ac.cy/colloquium/index.php#cs.ucy.2015.papapetrouAbstract:
In this talk I will present my recent work on big data management. I will start with ECM-sketch, a compact and efficient sketch that enables a wide range of sliding window queries over distributed high-dimensional data streams. The sketch allows effective summarization of streaming data over both time-based and count-based sliding windows, and enables point and inner-product queries with probabilistic accuracy guarantees. It can be employed to address a broad range of problems over centralized and distributed data streams, such as maintaining frequency statistics, finding heavy hitters and computing quantiles in the sliding-window model. The ECM-sketch is recently published in VLDB and VLDB journal. Furthermore, we are currently working towards an FPGA-based implementation of the sketch, which can further increase performance and reduce energy cost drastically. In the second part of the talk, I will introduce a new programming model that enables better utilization of the computational and network resources of multiple distributed clouds. Existing cloud programming models (e.g., MapReduce), assume that all cloud resources (consequently, also all data) are located within a single data center that supports high-speed network, e.g., infiniband. This is a restrictive assumption for many real-world scenarios, where the data to be processed is physically distributed, e.g., over cloud resources hosted by different providers, or even over multi-site data centers. I will explain why existing programming models fail in such scenarios, and describe a novel model suitable for this distribution. The model enables scalability of MapReduce computations across large distributed cloud federations, and requires a very small learning curve for existing MapReduce developers. The core innovation of the model is that it enables developers to clearly distinguish between local and holistic reductions, i.e., reductions that can be performed in isolation, inside each individual cloud, vs reductions that need to incorporate data from all clouds. This information can then be exploited by the execution engine, in order to alleviate network and processing bottlenecks and to increase parallelism. This work is currently under preparation.Short Bio:
Odysseas Papapetrou received his PhD in Computer Science from University of Hannover, after obtaining an M.Sc. from Saarland University, and a B.Sc. and M.Sc. from the University of Cyprus. Since 2011, he is a researcher at the Software Technology and Network Applications Laboratory of the Technical University of Crete. His research focuses on big data management, with a special interest on distributed data. Web: https://www.cs.ucy.ac.cy/colloquium/ Mailing List: https://listserv.cs.ucy.ac.cy/mailman/listinfo/cs-colloquium RSS: https://www.cs.ucy.ac.cy/colloquium/rss.xml Calendar: https://www.cs.ucy.ac.cy/colloquium/schedule/cs.ucy.2015.papapetrou.ics -
Indoor Data Management: Status and Challenges, Dr. Demetris Zeinalipour (University of Cyprus, Cyprus), Tuesday, February 17, 2015, 18:00-19:00 EET.
Speaker: Dr. Demetris Zeinalipour
Affiliation: University of Cyprus, Cyprus Category: Colloquium Location: Room 148, Faculty of Pure and Applied Sciences (FST-01), 1 University Avenue, 2109 Nicosia, Cyprus (directions) Date: Tuesday, February 17, 2015 Time: 18:00-19:00 EET Host: Yannis Dimopoulos (yannis-AT-cs.ucy.ac.cy) URL: https://www.cs.ucy.ac.cy/colloquium/index.php#cs.ucy.2015.zeinalipourAbstract:
People spend 80-90% of their time in indoor environments such as offices, undergrounds, shopping malls and airports. On the other hand, the uptake of interesting applications in indoor spaces (e.g., navigation, inventory management and elderly support) has so far been hampered by the lack of technologies that can provide indoor location (position) accurately, in real-time, in an energy-efficient manner and without expensive additional hardware. Modern smartphones currently rely on cloud-based Indoor Positioning Services (IPS), which can provide the location of a user upon request but those are both inaccurate and additionally raise important location privacy concerns, as the IPS can know where the user is at all times. In this talk, I will start out by overviewing the building blocks of Anyplace, our in-house IPS that recently won several international research awards for its accuracy (i.e., less than 2 meters) and utility. Anyplace deploys a number of innovative concepts, including crowdsourcing, big-data management, energy-aware processing, multi-device optimization and mobile data management, in order to realize a power-efficient and accurate indoor localization and navigation technology. In the second part of this talk, I will focus on an algorithm we developed for protecting users from location tracking by the IPS, without hindering the provisioning of fine-grained location updates on a continuous basis. Our algorithm exploits a k-Anonymity Bloom filter and a generator of camouflaged localization requests, both of which are shown to be resilient to a variety of privacy attacks.Short Bio:
Demetris Zeinalipour (PhD, University of California, Riverside, 2005) is an Assistant Professor of Computer Science at the University of Cyprus, directing the Data Management Systems Laboratory (DMSL). Before his current appointment, he served the University of Cyprus and the Open University of Cyprus as a Lecturer of Computer Science and was also a Visiting Researcher at the network intelligence lab of Akamai Technologies, Cambridge, USA. Demetris has served as the PC Co-Chair of IEEE MDM'10, VLDB's DMSN'10 and ACM MobiDE'09, the General Chair for ACM MobiDE'10, the Contest Chair of IEEE ICDM'10, the Organization Chair of HDMS'10, the Demo Co-Chair for IEEE MDM'13 and the Panel Co-Chair for IEEE MDM'14. Currently, he serves as the Workshops Co-Chair for IEEE MDM'15. His primary research interests include Data Management in Computer Systems and Networks, in particular Mobile and Sensor Data Management; Big Data Management in Parallel and Distributed Architectures; Spatio-Temporal Data Management; Network and Web 2.0 Data Management; Crowd and Indoor Data Management; Data Privacy Management. He is a member of ACM, IEEE and USENIX. For more information, please visit: https://www.cs.ucy.ac.cy/~dzeina/ Web: https://www.cs.ucy.ac.cy/colloquium/ Mailing List: https://listserv.cs.ucy.ac.cy/mailman/listinfo/cs-colloquium RSS: https://www.cs.ucy.ac.cy/colloquium/rss.xml Calendar: https://www.cs.ucy.ac.cy/colloquium/schedule/cs.ucy.2015.zeinalipour.ics -
Dataflow Systems for Large-scale Data Analytics, Dr. Herodotos Herodotou (Cyprus University of Technology, Cyprus), Monday, November 24, 2014, 16:30-17:30 EET.
Speaker: Dr. Herodotos Herodotou
Affiliation: Cyprus University of Technology, Cyprus Category: Colloquium Location: Room 148, Faculty of Pure and Applied Sciences (FST-01), 1 University Avenue, 2109 Nicosia, Cyprus (directions) Date: Monday, November 24, 2014 Time: 16:30-17:30 EET Host: Demetris Zeinalipour (dzeina-AT-cs.ucy.ac.cy) URL: https://www.cs.ucy.ac.cy/colloquium/index.php#cs.ucy.2014.herodotouAbstract:
Timely and cost-effective analytics over “big data” has emerged as a key ingredient for success in many businesses, scientific and engineering disciplines, and government endeavors. Web clicks, social media, scientific experiments, and datacenter monitoring are among data sources that generate vast amounts of raw data every day. The need to convert this raw data into useful information has spawned considerable innovation in systems for large-scale data analytics, especially over the last decade. This talk covers the design principles and core features of recent dataflow systems for analyzing very large datasets using massively-parallel computation and storage techniques on large clusters of nodes. The dataflow systems are described along a number of dimensions including data model and query interface, storage layer, execution engine, query optimization, scheduling, resource management, and fault tolerance.Short Bio:
Herodotos Herodotou is a tenure-track Lecturer in the Electrical Engineering and Computer Engineering and Informatics (EECEI) department at the Cyprus University of Technology. He received his Ph.D. in Computer Science from Duke University in May 2012. His Ph.D. dissertation work received the SIGMOD Jim Gray Doctoral Dissertation Award Honorable Mention as well as the Outstanding Ph.D. Dissertation Award in Computer Science at Duke. His research interests are in large-scale Data Processing Systems and Database Systems. In particular, his work focuses on ease-of-use, manageability, and automated tuning of both centralized and distributed data-intensive computing systems. In addition, he is interested in applying database techniques in other areas like scientific computing, bioinformatics, and numerical analysis. His work experience includes research positions at Microsoft Research, Yahoo! Labs and Aster Data as well as software engineering internships at Microsoft and RWD Technologies.Note:
The presentation will be recorded and become available through the following URL: https://www.cs.ucy.ac.cy/index.php/en/cs-video-gallery/cs-colloquiums-videos Multimedia File Available: Multimedia File Web: https://www.cs.ucy.ac.cy/colloquium/ Mailing List: https://listserv.cs.ucy.ac.cy/mailman/listinfo/cs-colloquium RSS: https://www.cs.ucy.ac.cy/colloquium/rss.xml Calendar: https://www.cs.ucy.ac.cy/colloquium/schedule/cs.ucy.2014.herodotou.ics -
Load Management for Big Streaming Data, Prof. Panos K. Chrysanthis (University of Pittsburgh, USA), Thursday, July 31, 2014, 11:00-12:00 EET.
Speaker: Prof. Panos K. Chrysanthis
Affiliation: University of Pittsburgh, USA Category: Colloquium Location: Room 148, Faculty of Pure and Applied Sciences (FST-01), 1 University Avenue, 2109 Nicosia, Cyprus (directions) Date: Thursday, July 31, 2014 Time: 11:00-12:00 EET Host: Demetris Zeinalipour (dzeina-AT-cs.ucy.ac.cy) and George Samaras (cssamara-AT-cs.ucy.ac.cy) URL: https://www.cs.ucy.ac.cy/colloquium/index.php#cs.ucy.2014.chrysanthisAbstract:
For the past few years, our group has been working on problems related to Big Data through several projects. After briefly discussing these projects, the rest of this talk will present DILoS, which focuses on three of the eight Big Data's Vs, i.e., volume, velocity and variability. Today, the ubiquity of sensing devices as well as of mobile and web applications continuously generates a huge volume of data which takes the form of streams that are typically high-velocity (speed) and high-variability (bursty). In order to meet the near-real-time requirements of the monitoring applications and of the emerging ``Big Data'' applications, data streams need to be continuously processed and analyzed. Such processing happens inside Data stream management systems (DSMSs), which efficiently support continuous queries (CQs). CQs inherently have different levels of criticality and hence different levels of expected quality of service (QoS) and quality of data (QoD). In order to provide different quality guarantees to different client stream applications, we developed DILoS, a novel framework that exploits the synergy between scheduling and load shedding in DSMS. In overload situations, DILoS enforces worst-case response times for all CQs while providing prioritized QoD, i.e., minimize data loss for query classes according to their priorities. We further propose ALoMa, a new adaptive load manager scheme that enables the realization of the DILoS framework. ALoMa is a general, practical DSMS load shedder that outperforms the state-of-the-art in deciding when the DSMS is overload and how much load needs to be shed. We implemented DILoS in our real DSMS prototype system (AQSIOS) and evaluate its performance for a variety of real and synthetic workloads. Our experiments show that our framework (1) allows the scheduler and load shedder to consistently honor CQs' priorities and (2) maximizes the utilization of the system processing capacity to reduce load shedding.Short Bio:
Dr. Panos K. Chrysanthis is a Professor of Computer Science and the founding director of the Advanced Data Management Technologies Laboratory (ADMT Lab) [http://db.cs.pitt.edu] at the University of Pittsburgh. His lab has a broad focus on user-centric data management for scalable network-centric and collaborative applications and has fostered interdisciplinary collaborations between computer science, medicine and astronomy, both within and outside the University of Pittsburgh -- he is an Adjunct Professor at the Carnegie Mellon University and at the University of Cyprus, Cyprus. In 1995, he received one of the first NSF CAREER Awards for his pioneer work on mobile data management and in 2010, he was recognized as a Distinguished Scientist by ACM. In 2007, he was also elevated to the level of a Senior Member of IEEE. He is currently on the editorial board of IEEE TKDE and the Parallel and Distributed Databases Journal. DILoS was developed in collaboration with Thao N. Pham (as part of her PhD thesis) and Alexandros Labrinidis who is the co-director of the ADMT lab. This work has been funded in part by two NSF Awards and a gift from EMC/Greenplum. Web: https://www.cs.ucy.ac.cy/colloquium/ Mailing List: https://listserv.cs.ucy.ac.cy/mailman/listinfo/cs-colloquium RSS: https://www.cs.ucy.ac.cy/colloquium/rss.xml Calendar: https://www.cs.ucy.ac.cy/colloquium/schedule/cs.ucy.2014.chrysanthis.ics -
Running with scissors - Fast queries on just-in-time databases, Prof. Anastasia Ailamaki (École Polytechnique Fédérale de Lausanne, Switzerland), Wednesday, May 7, 2014, 10.30-11.30 EET.
Speaker: Prof. Anastasia Ailamaki
Affiliation: École Polytechnique Fédérale de Lausanne, Switzerland Category: Colloquium Location: Room 148, Faculty of Pure and Applied Sciences (FST-01), 1 University Avenue, 2109 Nicosia, Cyprus (directions) Date: Wednesday, May 7, 2014 Time: 10.30-11.30 EET Host: Demetris Zeinalipour (dzeina-AT-cs.ucy.ac.cy) URL: https://www.cs.ucy.ac.cy/colloquium/index.php#cs.ucy.2014.ailamaki
Abstract:
The amount of data collected in the last two years is higher than the amount of data collected since the dawn of time. We collect data much faster than they can be transformed into valuable information and are often forced into hasty decisions on which parts to discard, potentially throwing away valuable data before it has been exploited fully. The reason is that query processing, which is the mechanism to squeeze information out of data, becomes slower as datasets grow larger. At the same time, the continuously increased number of hardware contexts ends up slowing processing down further, as keeping all cores busy with doing useful computation is difficult. Today's query engines cannot harness but a fraction of the potential of new hardware platforms. Is it possible to decouple query processing efficiency from the data growth curve? This talk advocates a departure from the traditional "create a database, then run queries" paradigm. Instead, data analysts should run queries on raw data, while a database is built on the side. In fact the database should become an implementation detail, imperceptible by the user. To achieve this paradigm shift, query processing should be decoupled from specific data storage formats. Ad-hoc primitives and dynamically synthesized operators are key for just-in-time query optimization and processing. Finally, exploitation of compute and memory resources should be seamless and based on hardware hints; extreme vertical integration is an enemy to forward compatibility.Short Bio:
Anastasia Ailamaki is a Professor of Computer and Communication Sciences at the Ecole Polytechnique Federale de Lausanne (EPFL) in Switzerland. Her research interests are in database systems and applications, and in particular (a) in strengthening the interaction between the database software and emerging hardware and I/O devices, and (b) in automating data management to support computationally- demanding and data-intensive scientific applications. She has received an ERC Consolidator Award (2013), a Finmeccanica endowed chair from the Computer Science Department at Carnegie Mellon (2007), a European Young Investigator Award from the European Science Foundation (2007), an Alfred P. Sloan Research Fellowship (2005), eight best-paper awards in database, storage, and computer architecture conferences (2001-2012), and an NSF CAREER award (2002). She holds a Ph.D. in Computer Science from the University of Wisconsin-Madison in 2000. She is a senior member of the IEEE and a member of the ACM, serves as the ACM SIGMOD vice chair, and has served as a CRA-W mentor. Multimedia File Available: Multimedia File Web: https://www.cs.ucy.ac.cy/colloquium/ Mailing List: https://listserv.cs.ucy.ac.cy/mailman/listinfo/cs-colloquium RSS: https://www.cs.ucy.ac.cy/colloquium/rss.xml Calendar: http://testing.in.cs.ucy.ac.cy/louispap/XCS-3.0/schedule/cs.ucy.2014.ailamaki.ics -
Data Science – the Case of Mobility Data, Dr. Yannis Theodoridis (University of Piraeus, Greece), Monday, November 12, 2012, 14:00-15:00 EET.
Speaker: Dr. Yannis Theodoridis
Affiliation: University of Piraeus, Greece Category: Colloquium Location: Room 148, Faculty of Pure and Applied Sciences (FST-01), 1 University Avenue, 2109 Nicosia, Cyprus (directions) Date: Monday, November 12, 2012 Time: 14:00-15:00 EET Host: Demetris Zeinalipour (dzeina-AT-cs.ucy.ac.cy) URL: https://www.cs.ucy.ac.cy/colloquium/index.php#cs.ucy.2012.theodoridisAbstract:
From raw location recordings to mobility patterns; how can we exploit on the ubiquitous GPS technology (that is found everywhere; from vehicles and vessels to smartphones) in order to get knowledge about our movement behavior? What are the most representative examples of mobility patterns that can be found in mobility datasets? How can we address the big volumes of mobility data? In this talk we overview issues and solutions on data science, focusing on the mobility data case.Short Bio:
Yannis Theodoridis is Assoc. Professor at the Department of Informatics, University of Piraeus, where he currently leads the Information Management Lab. Born in 1967, he received his Diploma (1990) and Ph.D. (1996) in Electrical and Computer Engineering, both from the National Technical University of Athens, Greece. Before joining the University of Piraeus, he was member of the research staff at the Hellenic Research Foundation (1997-98) and the Computer Technology Inst. (1999-2002). His research interests include Data Science (management, analysis, mining) for mobility data, whereas he teaches databases, data mining and GIS at under- and post- graduate level. Apart from several national-level projects, he is or was scientist in charge and coordinator of two European projects, namely PANDA (FP6/IST, 2001-04) and CODMINE (FP6/IST, 2002-03), and principal investigator in GeoPKDD (FP6/IST, 2005-09), MODAP (FP7/ICT, 2009-12; member of the management board), MOVE (COST, 2009-13; vice-chair of the management committee), DATASIM (FP7/ICT, 2011-14) and SEEK (FP7/PEOPLE, 2012-15). He has served as general co-chair for SSTD'03, ECML/PKDD'11 and PCI'12, vice PC chair for IEEE ICDM'08, organizing chair for the 2010 summer school on “Mobility, Data Mining, and Privacy”, member of the editorial board of the Int'l Journal on Data Warehousing and Mining – IJDWM (2005-), and member of the SSTD endowment (2010-). He has offered several tutorials in top conferences (with the most recent being at EDBT’09) and invited lectures in Greece and abroad (including PhD/MSc courses at Venice, Milano, KAUST, Aalborg, Trento and Ghent) on the topic of Mobility Data Management and Exploration. He has co-authored three monographs and more than 100 refereed articles in scientific journals and conferences, receiving more than 800 citations. For more information: http://www.unipi.gr/faculty/ytheod and http://infolab.cs.unipi.gr.Note:
Additional Talks by Dr. Theodoridis: Schedule (https://www.cs.ucy.ac.cy/colloquium/lectures/theodoridis12.pdf): [ Lecture 1: Mobility Data Management, Date: Monday, Nov. 12, 2012, Time: 16:30 – 18:00 | Lecture 2: Mobility Data Exploration, Date: Thursday, Nov. 15, 2012, Time: 13:30 – 15:00 | Lecture 3: Mobility Data Privacy, Date: Thursday, Nov. 15, 2012 Time: 15:00 – 16:30 ] Slides: [ https://www.cs.ucy.ac.cy/colloquium/lectures/theodoridis12-slides/00.pdf | https://www.cs.ucy.ac.cy/colloquium/lectures/theodoridis12-slides/01.pdf | https://www.cs.ucy.ac.cy/colloquium/lectures/theodoridis12-slides/02.pdf | https://www.cs.ucy.ac.cy/colloquium/lectures/theodoridis12-slides/03.pdf ] Web: https://www.cs.ucy.ac.cy/colloquium/ Mailing List: https://listserv.cs.ucy.ac.cy/mailman/listinfo/cs-colloquium RSS: https://www.cs.ucy.ac.cy/colloquium/rss.xml Calendar: https://www.cs.ucy.ac.cy/colloquium/schedule/cs.ucy.2012.Theodoridis.ics -
Querying Sensor Data in Smartphone Networks, Dr. Demetris Zeinalipour (University of Cyprus, Cyprus), Thursday, October 11, 2012, 09.15-10.15 EET.
Speaker: Dr. Demetris Zeinalipour
Affiliation: University of Cyprus, Cyprus Category: Colloquium Location: Room 148, Faculty of Pure and Applied Sciences (FST-01), 1 University Avenue, 2109 Nicosia, Cyprus (directions) Date: Thursday, October 11, 2012 Time: 09.15-10.15 EET Host: Andreas Pitsillides (cspitsil-AT-cs.ucy.ac.cy) URL: https://www.cs.ucy.ac.cy/colloquium/index.php#cs.ucy.2012.zeinalipourAbstract:
Smartphones have emerged as powerful computational platforms equipped with multitude of sensors that are capable of generating vast amounts of data (geo-location, audio, video, etc.) Collections of smartphones connected to the Internet are nowadays proposed for opportunistic and participatory sensing applications in intelligent transportation systems, social networking applications, city planning and many other domains, prompting undeniably the post-PC era. In this talk, I will present distributed architectures for querying and managing such sensor data by taking into account energy, data disclosure and networking aspects. I will particularly focus on SmartTrace, a powerful query processing framework for finding similar smartphone trajectories without disclosing the traces of participating users. I will also present SmartLab, a first-of-a-kind programmable cloud of 40+ smartphones deployed at our department enabling a new line of systems-oriented research on smartphones. Finally, I will also overview other related smartphone data management frameworks we've developed for peer-to-peer search, crowdsourcing and indoor positioning, concluding with an outlook to our future research agenda.Short Bio:
Demetris Zeinalipour (PhD, University of California, Riverside, 2005) is a Lecturer of Computer Science at the University of Cyprus. Before that he was a Lecturer at the Open University of Cyprus, a Visiting Lecturer at his current department and a Visiting Researcher at the network intelligence lab of Akamai Technologies (MA, USA). Demetris has served as the PC Co-Chair of ACM MobiDE'09, IEEE MDM'10 and VLDB's DMSN'10, the General Chair for ACM MobiDE'10, the Contest Chair of IEEE ICDM'10 and the Organization Chair of HDMS'10. His primary research interests include Data Management in Systems and Networks, in particular Distributed Query Processing, Storage and Retrieval Methods for Sensor, Smartphone and Peer-to-Peer Systems, Mobile and Network Data Management, Energy-aware Data Management. For more information, please visit: https://www.cs.ucy.ac.cy/~dzeina/Note:
This colloquium is part of the speaker's procedure for evaluation and promotion from Lecturer to Assistant Professor. Web: https://www.cs.ucy.ac.cy/colloquium/ Mailing List: https://listserv.cs.ucy.ac.cy/mailman/listinfo/cs-colloquium RSS: https://www.cs.ucy.ac.cy/colloquium/rss.xml Calendar: https://www.cs.ucy.ac.cy/colloquium/schedule/cs.ucy.2012.Zeinalipour.ics -
Stepwise kNN Search on Vertically Stored Time Series, Dr. Panagiotis Karras (National University of Singapore, Singapore), Friday, June 24, 2011, 12:00-13:00 EET.
Speaker: Dr. Panagiotis Karras
Affiliation: National University of Singapore, Singapore Category: Colloquium Location: Room 148, Faculty of Pure and Applied Sciences (FST-01), 1 University Avenue, 2109 Nicosia, Cyprus (directions) Date: Friday, June 24, 2011 Time: 12:00-13:00 EET Host: Demetris Zeinalipour (dzeina AT cs.ucy.ac.cy) URL: https://www.cs.ucy.ac.cy/colloquium/index.php#cs.ucy.2011.karrasAbstract:
Nearest-neighbor search over time series has received vast research attention as a basic data mining task. Still, node of the hitherto proposed methods scales well with increasing time series length. This is due to the fact that all methods encounter the curse of dimensionality. In particular, traditional methods utilize an index to search in a reduced-dimensionality feature space; however, for high timeseries length, search with such an index yields many false hits that need to be eliminated by accessing the full records. An attempt to reduce false hits by indexing more features exacerbates the curse of dimensionality, and vice versa. A recently proposed alternative, iSAX, uses symbolic approximate representations accessed by a simple file-system directory as an index. Still, iSAX also encounters false hits, which are again eliminated by accessing records in full: once a false hit is generated by the index, there is no second chance to prune it; thus, the pruning capacity iSAX provides is also one-off. This paper proposes an alternative approach to time series kNN search, following a nontraditional pruning style. Instead of navigating through candidate records via an index, we access their features, obtained by a multi-resolution transform, in a stepwise sequential-scan manner, one level of resolution at a time, over a vertical representation. Most candidates are progressively eliminated after a few of their terms are accessed, using pre-computed information and a tight double-bounding scheme (i.e., not only lower, but also upper distance bounds). Our experimental study with large-scale long time-series data confirms the advantage of our approach over both the current state-of-the-art method, iSAX, and classical index-based methods.Short Bio:
Panagiotis Karras is an LKY Postdoctoral Fellow at the National University of Singapore. He earned a Ph.D. in Computer Science from the University of Hong Kong and an M.Eng. in Electrical and Computer Engineering from the National Technical University of Athens. In 2008, he received the Hong Kong Young Scientist Award. He has also held positions at the University of Zurich and the Technical University of Denmark. His research interests are in data mining, algorithms, data streams, spatial data management, anonymization, indexing, and similarity search. His work has been published in major database and data mining conferences and journals. Multimedia File Available: Multimedia File Web: https://www.cs.ucy.ac.cy/colloquium/ Mailing List: https://listserv.cs.ucy.ac.cy/mailman/listinfo/cs-colloquium RSS: https://www.cs.ucy.ac.cy/colloquium/rss.xml Calendar: http://testing.in.cs.ucy.ac.cy/louispap/XCS-3.0/schedule/cs.ucy.2011.karras.ics -
Cost-aware Data Management in the Cloud, Dr. Verena Kantere (Cyprus University of Technology, Cyprus), Thursday, April 7, 2011, 11:00-12:00 EET.
Speaker: Dr. Verena Kantere
Affiliation: Cyprus University of Technology, Cyprus Category: Colloquium Location: Room 148, Faculty of Pure and Applied Sciences (FST-01), 1 University Avenue, 2109 Nicosia, Cyprus (directions) Date: Thursday, April 7, 2011 Time: 11:00-12:00 EET Host: Demetris Zeinalipour (dzeina AT cs.ucy.ac.cy) URL: https://www.cs.ucy.ac.cy/colloquium/index.php#cs.ucy.2011.kantereAbstract:
The term ‘cloud computing’ is nowadays synonymous to computing services offered by large-scale infrastructures. The key to the success of cloud computing is to provide seamless and efficient management of large dynamic disseminated data collections, such as scientific data, in order to maximize their availability while minimizing capital expenditure. This talk leverages lessons learned from financial management to solve the problem of both cost- and time-efficient management on clouds offering online data services. We propose a novel economy model for a cloud where users pay on-the-go for the data services they receive and user payments can be used for service provision, infrastructure maintenance and profit. The economy employs a cost model that takes into account all the available resources in a cloud, such as disk space and I/O operations, CPU time and network bandwidth. In order to ensure the economic viability of the cloud, the cost of offering new services has to be amortized to prospective users that will use them. We propose a novel cost amortization model that predicts the extent of amortization in time and number of users. The economy is completed with a dynamic pricing scheme that achieves optimal cloud profit while ensuring user satisfaction with service prices. The talk concludes with future research directions on the provision of online data services.Short Bio:
Verena Kantere is a tenure-track lecturer at the Department of Electrical Engineering and Information Technology at the Cyprus University of Technology. She has received a Diploma (2000) and a Ph.D. (2007) from the National Techincal University of Athens, (NTUA) and a M.Sc. degree from the Department of Computer Science at the University of Toronto (2003). During her graduate studies her research interests focused on problems of data exchange and coordination in Peer-to-Peer (P2P) overlays with structured and unstructured data, as well as multidimensional data sharing. She has proposed frameworks and techniques that deal with the heterogeneity problem, query processing and rewriting, as well as managing continuous queries. Furthermore, she has shown interest and work in the field of Semantic Web, concerning the problem of semantic similarity, annotation, clustering and integration. After the completion of her PhD studies and until recently, she worked as a postdoctoral researcher (2008-2010) at the Ecole Polytechnique Federale de Lausanne (EPFL). Her research focuses on the provision of cloud data services, focusing on the special needs of large analytical data, such as scientific data. She is working towards the incorporation of cost in existing and new data management techniques and has designed a novel data-aware economy model for cloud data services. Web: https://www.cs.ucy.ac.cy/colloquium/ Mailing List: https://listserv.cs.ucy.ac.cy/mailman/listinfo/cs-colloquium RSS: https://www.cs.ucy.ac.cy/colloquium/rss.xml Calendar: https://www.cs.ucy.ac.cy/colloquium/schedule/cs.ucy.2011.Kantere.ics -
Learning in a Partially Observable World, Dr. Loizos Michael (Open University of Cyprus, Cyprus), Monday, April 4, 2011, 11:00-12:00 EET.
Speaker: Dr. Loizos Michael
Affiliation: Open University of Cyprus, Cyprus Category: Colloquium Location: Room 148, Faculty of Pure and Applied Sciences (FST-01), 1 University Avenue, 2109 Nicosia, Cyprus (directions) Date: Monday, April 4, 2011 Time: 11:00-12:00 EET Host: Demetris Zeinalipour (dzeina AT cs.ucy.ac.cy) URL: https://www.cs.ucy.ac.cy/colloquium/index.php#cs.ucy.2011.michaelAbstract:
Agents sensing their environment obtain information that is often incomplete in some shape or form. Examples abound: (1) certain tests may be too expensive to perform to complete a patient's medical record; (2) responders to a market survey may choose not to reveal certain information about themselves; (3) the author of a piece of text may choose not to explicitly state information that she believes can be inferred by the readers; (4) a packet may be routed through a private network and that route segment may not be tracked; (5) a dynamic system may transition through certain states too quickly to be monitored; (6) a user's preferences in support of a decision may be kept secret for privacy reasons. From a learning point of view, the challenge is to design algorithms that deal with incomplete information in a principled manner. We shall consider two broad settings: The static setting (examples 1-3) builds upon typical supervised learning scenarios, where, however, attributes are hidden in arbitrary ways. The dynamic setting (examples 4-6) deals with scenarios where an initial and a final state of a process are observed, while the intermediate states remain hidden. We shall discuss conditions under which algorithms are known to exist in these settings and can be shown to be efficient, be accompanied by predictive guarantees, and make limited assumptions on how information is hidden.Short Bio:
Loizos Michael is a Lecturer in Information Systems at Open University of Cyprus (since 2009). Before joining OUC he held a Visiting Lecturer position at University of Cyprus (2008-2009). He was educated at University of Cyprus, where he received a B.Sc. in Computer Science with a minor degree in Mathematics (2002). He continued his education at Harvard University, where he received an M.Sc. and a Ph.D. in Computer Science (2003 and 2008, respectively). His research focuses on the formal and principled understanding of cognitive processes such as learning and reasoning, and how those are employed by humans and other biological organisms in their everyday lives. Specific areas of interest include: commonsense reasoning, temporal and default reasoning, computational learning theory, computational evolution theory, text and narrative understanding, nature-inspired computation, distributed computation, and game theory. Web: https://www.cs.ucy.ac.cy/colloquium/ Mailing List: https://listserv.cs.ucy.ac.cy/mailman/listinfo/cs-colloquium RSS: https://www.cs.ucy.ac.cy/colloquium/rss.xml Calendar: https://www.cs.ucy.ac.cy/colloquium/schedule/cs.ucy.2011.Michael.ics -
Mining Compressed Web Search Usage Patterns, Dr. Michail Vlachos (IBM Research Zurich, Switzerland), Monday, November 29th, 2010, 10:30-11:30 EET.
Speaker: Dr. Michail Vlachos
Affiliation: IBM Research Zurich, Switzerland Category: Colloquium Location: Room 148, Faculty of Pure and Applied Sciences (FST-01), 1 University Avenue, 2109 Nicosia, Cyprus (directions) Date: Monday, November 29th, 2010 Time: 10:30-11:30 EET Host: Demetris Zeinalipour (dzeina AT cs.ucy.ac.cy) URL: https://www.cs.ucy.ac.cy/colloquium/index.php#cs.ucy.2010.vlachosAbstract:
Analysis of historical search patterns holds great importance for web search engines, because it can help to better understand the users' search behavior. Capturing the user search preferences over time can provide useful insights in applications such as discovery of news events, keyword recommendation and personalized ad targeting. A major bottleneck in analyzing historical sequential data is the growing size of data repositories. Therefore, there is a need to enable search and mining operations directly on the compressed data. In this talk we will present how to facilitate efficient search over compressed sequential data, with specific focus on weblog query patterns. Our approach guarantees optimally tight distance bounds, while at the same time being efficient and lightweight. This helps drastically reduce the search time compared to previous state-of-the-art techniques. Additionally, we will explicate how to support other types of knowledge discovery operations, such as burst detection, query-by-burst and query-by-periodicity. We will demonstrate extensions and applications of the presented technique for a multitude of areas.Short Bio:
Michalis Vlachos is a Research Member at IBM Zurich Research Laboratory. Previously he was with IBM Research, NY, and has also visited Microsoft Research, Seattle. Dr Vlachos’ research interests include data mining, machine learning, databases, time-series analytics and data visualization. For his contributions at IBM he has received two Research Division Awards and three Invention Plateau Awards. He holds or has applied for 15 patents. Web: https://www.cs.ucy.ac.cy/colloquium/ Mailing List: https://listserv.cs.ucy.ac.cy/mailman/listinfo/cs-colloquium RSS: https://www.cs.ucy.ac.cy/colloquium/rss.xml Calendar: https://www.cs.ucy.ac.cy/colloquium/schedule/cs.ucy.2010.Vlachos.ics -
Query Optimization in Wireless Sensor Networks, Dr. Georgios Chatzimilioudis (University of Cyprus, Cyprus), Monday, Sept. 27th, 2010, 14:00-15:00 EET.
Speaker: Dr. Georgios Chatzimilioudis
Affiliation: University of Cyprus, Cyprus Category: Colloquium Location: Room 148, Faculty of Pure and Applied Sciences (FST-01), 1 University Avenue, 2109 Nicosia, Cyprus (directions) Date: Monday, Sept. 27th, 2010 Time: 14:00-15:00 EET Host: Marios Dikaiakos (mdd AT cs.ucy.ac.cy) and Demetris Zeinalipour (dzeina AT cs.ucy.ac.cy) URL: https://www.cs.ucy.ac.cy/colloquium/index.php#cs.ucy.2010.chatzimilioudisAbstract:
The objective of this work is to optimize query execution in wireless sensor networks. To answer a query, data generated by the sensors need to be collected and processed. The cost of query execution is measured in the energy spent by the wireless sensor network. We minimize the energy needed by constructing sophisticated query trees that determine how data will be routed towards the sink and where the data will be processed inside the network. We propose query trees for optimizing two types of queries: queries that need data from all the nodes in the network and queries that need data from a subset of nodes only. For the former type of queries we minimize the energy consumption using communication balancing to minimizing the collisions during query execution. We propose a distributed algorithm to construct a near-optimal balanced communication tree with minimum overhead. Our algorithm outperforms previous work both in tree construction overhead and in tree balance. For the latter type of queries use operator trees and dynamic operator placement that minimize the bytes transmitted during query execution. We propose a centralized algorithm for constructing an operator tree and an initial operator placement based on an adaptation of the Fermat point problem (1-median problem) for a weighted graph. We also propose an optimal parameter-free decentralized algorithm to adapt the placement of a single operator.Short Bio:
Georgios Chatzimilioudis received his Ph.D. in Computer Science in University of California Riverside in June 2010. His work focused on data management in wireless sensor networks and query otpimization in sepcific. He has also completed long-term internships at the R&D units of Siemens (2007) and Siemens Corporate Research (2008). Currently he is a post-doctoral fellow at the Computer Science department in University of Cyprus under the Marie Curie Transfer of Knowledge program. His primary research interests include data management and distributed query processing in wireless sensor networks, vehicular networks peer-to-peer systems. Web: https://www.cs.ucy.ac.cy/colloquium/ Mailing List: https://listserv.cs.ucy.ac.cy/mailman/listinfo/cs-colloquium RSS: https://www.cs.ucy.ac.cy/colloquium/rss.xml Calendar: https://www.cs.ucy.ac.cy/colloquium/schedule/cs.ucy.2010.Chatzimilioudis.ics -
Towards Energy Efficient Database Computing, Dr. Stavros Harizopoulos (HP Labs, Palo Alto, USA), Tuesday, June 15th, 2010, 11:00-12:00 EET.
Speaker: Dr. Stavros Harizopoulos
Affiliation: HP Labs, Palo Alto, USA Category: Colloquium Location: Room 148, Faculty of Pure and Applied Sciences (FST-01), 1 University Avenue, 2109 Nicosia, Cyprus (directions) Date: Tuesday, June 15th, 2010 Time: 11:00-12:00 EET Host: Demetris Zeinalipour (dzeina AT cs.ucy.ac.cy) URL: https://www.cs.ucy.ac.cy/colloquium/index.php#cs.ucy.2010.harizopoulosAbstract:
Rising energy costs in large data centers drive the agenda for energy efficient computing. Towards this goal, it is critical to understand the interplay between energy consumption and performance in database servers. In the first part of this talk, I will focus on quantifying the role of database software in the overall energy efficiency of a server. Then, I will present the results of a recent study (SIGMOD'10) on the power usage profiles of database operators and I will explore the effect of different configuration parameters in the energy efficiency of a database system. Finally, I will discuss our work on query processing on solid state drives (SIGMOD'09), which have emerged as a primary building block for energy efficient storage.Short Bio:
Stavros is an HP Labs researcher in the Intelligent Information Management Lab which is focused on enabling near real-time business intelligence with robust, scalable data management and data-intensive analytics. He received his Ph.D. in Computer Science from Carnegie Mellon, in 2005, and, through 2007, he worked as a Post-Doctoral researcher at the DB group of MIT. Stavros's research interests are in energy-efficient data management systems, query processing on new processor and storage technologies, main-memory transaction processing, and column-oriented databases. For more information: http://nms.csail.mit.edu/~stavros/ Web: https://www.cs.ucy.ac.cy/colloquium/ Mailing List: https://listserv.cs.ucy.ac.cy/mailman/listinfo/cs-colloquium RSS: https://www.cs.ucy.ac.cy/colloquium/rss.xml Calendar: https://www.cs.ucy.ac.cy/colloquium/schedule/cs.ucy.2010.Harizopoulos.ics -
Adaptive Resource Location and Query Processing for Peer-to-Peer Networks, Dr. Dimitrios Tsoumakos (NTUA, Greece and University of Cyprus, Cyprus), Wednesday, November 4th, 2009, 15:00-16:00 EET.
Speaker: Dr. Dimitrios Tsoumakos
Affiliation: NTUA, Greece and University of Cyprus, Cyprus Category: Colloquium Location: Room 148, Faculty of Pure and Applied Sciences (FST-01), 1 University Avenue, 2109 Nicosia, Cyprus (directions) Date: Wednesday, November 4th, 2009 Time: 15:00-16:00 EET Host: Demetris Zeinalipour (dzeina AT cs.ucy.ac.cy) URL: https://www.cs.ucy.ac.cy/colloquium/index.php#cs.ucy.2009.tsoumakosAbstract:
Peer-to-Peer (P2P) computing has gained a lot of attention from both the scientific and the large Internet user community. Popular applications utilizing this new technology offer many attractive features to a growing number of users while taking up a large amount of everyday network traffic. This talk presents bandwidth-efficient and adaptive algorithms to facilitate data location and processing for massive data management applications that operate on P2P overlays. The basis of these schemes is their ability to learn from past interactions, increasing their performance with time. In the first part of the talk, previous work in efficient content location and distribution for Unstructured Peer-to-Peer overlays is described. The Adaptive Probabilistic Search (APS) scheme utilizes directed walkers to forward queries on a hop-by-hop basis. Peers store success probabilities for each of their neighbors in order to efficiently route towards object holders. In the GrouPeer project, we apply many of these techniques in order to identify and group peers with similar schemas in an interconnected network of autonomous databases. In the second part of the talk I will present some of my current work which focuses on indexing methods for data and query-intensive applications over P2P overlays. HiPPIS and PASSION are systems that utilize adaptive algorithms that automatically adjust the level of indexing (for hierarchically organized data or ranges respectively) according to the granularity of the incoming queries, without assuming any prior knowledge of the workload. Brown Dwarf is a complete system for distributing and querying data-cubes w.r.t. load and network/node failures.Short Bio:
Dimitrios Tsoumakos is a visiting lecturer at the Computer Science Department of UCY. He received his Diploma in Electrical and Computer Engineering from NTUA in 1999, joined the graduate program in Computer Sciences at the University of Maryland in 2000, where he received his M.Sc. (2002) and Ph.D. (2006). He has been collaborating as a senior researcher with the Computing Systems Laboratory in the Department of Electrical and Computer Engineering of the National Technical University of Athens (NTUA) since 2006. Web: https://www.cs.ucy.ac.cy/colloquium/ Mailing List: https://listserv.cs.ucy.ac.cy/mailman/listinfo/cs-colloquium RSS: https://www.cs.ucy.ac.cy/colloquium/rss.xml Calendar: https://www.cs.ucy.ac.cy/colloquium/schedule/cs.ucy.2009.Tsoumakos.ics -
Small Sweeping 2NFAs Are Not Closed Under Complement, Dr. Christos Kapoutsis (University of Cyprus, Cyprus), Friday, April 3, 2009, 15:00 - 16:00 EET.
Speaker: Dr. Christos Kapoutsis
Affiliation: University of Cyprus, Cyprus Category: Colloquium Location: Room 148, Faculty of Pure and Applied Sciences (FST-01), 1 University Avenue, 2109 Nicosia, Cyprus (directions) Date: Friday, April 3, 2009 Time: 15:00 - 16:00 EET Host: Demetris Zeinalipour (dzeina AT cs.ucy.ac.cy) URL: https://www.cs.ucy.ac.cy/colloquium/index.php#cs.ucy.2009.kapoutsisAbstract:
Understanding the power of nondeterminism is one of the major goals of the theory of computation. The most important problem in this respect is the famous P vs NP question: does nondeterminism make a difference on Turing machines that use only "small" (i.e., polynomial) time? Another important problem is the L vs NL question: does nondeterminism make a difference on Turing machines that use only "small" (i.e., logarithmic) space? In 1978, Sakoda and Sipser proposed the following analogue to these questions: instead of full-fledged Turing machines, focus only on those which cannot write on their tape; instead of time or space, focus on size. That is: does nondeterminism make a difference on two-way finite automata that use only a "small" (i.e., polynomial) number of states? Also known as the 2D vs 2N question, where 2D (resp., 2N) is the class of problems that can be solved by small deterministic (resp., nondeterministic) two-way finite automata, this problem remains open. The conjecture is that indeed 2D and 2N are different. Given that 2D is closed under complement, one way to confirm the conjecture is to show that this closure fails for 2N; namely, that complementing a nondeterministic two-way finite automaton involves an exponential blow-up in the number of states, in general. In this colloquium, we will sketch a proof of this claim for the special case of automata that are sweeping, in the sense that they can change the direction of their head only at the two ends of the tape.Short Bio:
Christos Kapoutsis began his graduate studies at MPLA, Athens and continued to receive his PhD from the MIT EECS Department in 2006, for work on the size complexity of finite automata. After two years as a postdoctoral researcher at the Chair for Information Technology and Education at ETH, he is now a visiting lecturer at the Department of Computer Science, University of Cyprus. Web: https://www.cs.ucy.ac.cy/colloquium/ Mailing List: https://listserv.cs.ucy.ac.cy/mailman/listinfo/cs-colloquium RSS: https://www.cs.ucy.ac.cy/colloquium/rss.xml Calendar: https://www.cs.ucy.ac.cy/colloquium/schedule/cs.ucy.2009.Kapoutsis.ics -
On Two Network Measurement Problems: Inferring Autonomous System Relationships and Computing Network Traffic Heavy Hitters, Dr. Xenofontas Dimitropoulos (ETH Zurich, Switzerland), Monday, May 11th, 2009, 11:00 - 12:00 EET.
Speaker: Dr. Xenofontas Dimitropoulos
Affiliation: ETH Zurich, Switzerland Category: Colloquium Location: Room 148, Faculty of Pure and Applied Sciences (FST-01), 1 University Avenue, 2109 Nicosia, Cyprus (directions) Date: Monday, May 11th, 2009 Time: 11:00 - 12:00 EET Host: Demetris Zeinalipour (dzeina AT cs.ucy.ac.cy) URL: https://www.cs.ucy.ac.cy/colloquium/index.php#cs.ucy.2009.dimitropoulosAbstract:
Contractual relationships between Autonomous Systems (AS) affect inter-domain packet routing and shape the evolution and properties of the global AS-level topology of the Internet. In this talk, I will first describe the problem of inferring AS relationships and then will introduce novel inference heuristics finding customer-to-provider, peer-to-peer, and sibling-to-sibling relationships. I will outline validation results based on a survey with network operators showing inference accuracy between 82.8% and 96.5%. Finally, I will discuss an AS relationships repository we have opened to make our results useful for the community where we archive periodically the Internet AS-level topology annotated with inferred AS relationships. In the second part of the talk, I will switch to discussing the problem of computing network traffic heavy hitters using limited memory resources. I will briefly introduce the IBM Aurora system, which provides the context of our interest and then I will present an algorithm called Probabilistic Lossy Counting (PLC) for finding network traffic heavy hitters. PLC enhances the well-known lossy counting algorithm using on a tighter error bound on the estimated sizes of traffic flows providing probabilistic rather than deterministic guarantees on its accuracy. Performance comparison experiments show that PLC has between 34.4% and 74% lower memory consumption and between 37.9% and 40.5% fewer false positives than other state-of-the-art algorithms.Short Bio:
Xenofontas Dimitropoulos is a Senior Researcher in the Communication Systems Group (CSG) of ETH and an Associate Tutor in the Open University of Cyprus (OUC). He received a PhD degree in Electrical and Computer Engineering from Georgia Tech. In the past, he was a post-doc in the IBM Zurich Research Laboratory, where he worked in the IBM Aurora traffic flow collector project (now part of the IBM Tivoli suite), and a visiting scholar in the Cooperative Association for Internet Data Analysis (CAIDA). His research interests focus on traffic flow measurements, inter-domain routing, and network simulation. He has had various honors, like leading the graduation oath in his BSc degree for the highest GPA, a Fulbright scholarship, a Marie Curie scholarship, a best paper award, and a best paper nomination. Web: https://www.cs.ucy.ac.cy/colloquium/ Mailing List: https://listserv.cs.ucy.ac.cy/mailman/listinfo/cs-colloquium RSS: https://www.cs.ucy.ac.cy/colloquium/rss.xml Calendar: https://www.cs.ucy.ac.cy/colloquium/schedule/cs.ucy.2009.Dimitropoulos.ics -
System Architecture Implications of some Elementary Questions about m-learning, Prof. Thanasis Hadzilacos (Open University of Cyprus, Cyprus), Tuesday, April 7th, 2009, 15:00 - 16:00 EET.
Speaker: Prof. Thanasis Hadzilacos
Affiliation: Open University of Cyprus, Cyprus Category: Colloquium Location: Room 148, Faculty of Pure and Applied Sciences (FST-01), 1 University Avenue, 2109 Nicosia, Cyprus (directions) Date: Tuesday, April 7th, 2009 Time: 15:00 - 16:00 EET Host: Demetris Zeinalipour (dzeina AT cs.ucy.ac.cy) URL: https://www.cs.ucy.ac.cy/colloquium/index.php#cs.ucy.2009.hadzilacosAbstract:
What is m-learning about? Is it about delivering information on smaller screens via lesser bandwidth? Is it about giving just-on-time and just-acceptable education to those unfortunate ones outside a classroom, distant from their classmates and a 'real' teacher? We shall argue in this presentation that hardware, software and communication properties and restrictions -valid and important computer science and technology research issues as they may be- are incidental to the deeper problems and opportunities that m-learning presents. We shall argue that m-learning provides an opportunity to bridge a classic gap in education, that between "library learning" and "field learning", a gap as old as the written word. "Content" is to education as "instruments" is to music: essential, indispensable, but a far cry from being the whole. Learning is not information presentation. An architecture for m-learning should be conceived and designed around complex learners' educational activities and not around content browsing -a vital but very simple learning activity. We shall discuss architectural issues and propose an architecture based on constructive m-learning activities. Is context awareness a desirable characteristic, a necessary one, something already achieved, or a pie in the sky? Is 'context' a stand-alone concept or is it context dependent? Does 'context awareness' for m-learning systems simply mean 'learner location dependence'? We shall argue that there are indeed m-learning system architectural implications of context awareness which depend on the answer we give to such questions.Short Bio:
Professor of Information Systems, Open University of Cyprus (http://www.ouc.ac.cy) academic director of the graduate program in Information Systems, 55 years old. Until September 2007 he was Dean of the School of Science and Technology at the Hellenic Open Univer-sity (HOU, http://www.eap.gr) where he served (2000-2007) as associate professor of Software Engineering, directed (2003-2007) the Open and Distance Laboratory for Educational Material and Educational Methodology, the graduate course on Information Systems (2003-2007) and the undergraduate Computer Science course (2001-2003). Educated at Harvard, USA (1971-76), he had substantial industrial experience before joining Computer Technology Institute (http://www.cti.gr) in 1986, where he continues as a researcher with the responsibility of the Educational Technology and the e-Learning Sectors and R&D Unit III "Applied Information Systems" (http://www.cti.gr/RD3). He has taught at the Universities of Patras and Thessaly before joining the Hellenic Open University in 2000. During 1996-2001 he designed and managed the Greek national project "Odysseia" (http://odysseia.cti.gr/) for the utilization of Information and Communication Technologies in secondary education. He has served as a member of the Council of Europe working group for Teaching and Learning in the Communication Society (2002-2004) and the Greek national representative to E.U. DG Education and Culture for building the European portal on educational opportunities (2002-2005). He has published over 80 papers in international journals and conferences, including a chapter on "Teaching and Learning in the Communication Society" published by the Council of Europe. He has given over 60 invited talks and presentations in scientific conferences, training seminars, university seminars, and professional or technical events. He has coordinated, directed and participated in over 40 research and development projects funded by the European Commission (IST, Esprit, Brite-Euram, eContentplus, Lingua, Minerva, e-Learning), the three Community Support Framework Programs for Greece, private companies, the Greek Secretariat for R&D and the Greek Ministry of Education. His research interests are related to education and to large-scale information and database systems and in particular system design for non-standard application areas such as education, GIS, and multimedia. His real interest is people, and he is currently studying theology at HOU. Web: https://www.cs.ucy.ac.cy/colloquium/ Mailing List: https://listserv.cs.ucy.ac.cy/mailman/listinfo/cs-colloquium RSS: https://www.cs.ucy.ac.cy/colloquium/rss.xml Calendar: https://www.cs.ucy.ac.cy/colloquium/schedule/cs.ucy.2009.Hadzilacos.ics -
Adaptive Join Processing, Dr. Vasilis A. Vassalos (Athens Univ. of Economics and Business, Greece), Thursday, February 12th, 2009, 16:30 - 17:30 EET.
Speaker: Dr. Vasilis A. Vassalos
Affiliation: Athens Univ. of Economics and Business, Greece Category: Colloquium Location: Room 148, Faculty of Pure and Applied Sciences (FST-01), 1 University Avenue, 2109 Nicosia, Cyprus (directions) Date: Thursday, February 12th, 2009 Time: 16:30 - 17:30 EET Host: Demetris Zeinalipour (dzeina AT cs.ucy.ac.cy) URL: https://www.cs.ucy.ac.cy/colloquium/index.php#cs.ucy.2009.vassalosAbstract:
Adaptive join algorithms have recently attracted a lot of attention in emerging applications where data is provided by autonomous data sources through heterogeneous network environments. Their main advantage over traditional join techniques is that they can start producing join results as soon as the first input tuples are available, thus improving pipelining by smoothing join result production and by masking source or network delays. I will describe Double Index NEstedloops Reactive join (DINER), a new adaptive join algorithm for result rate maximization. DINER combines two key elements: an intuitive flushing policy that aims to increase the productivity of in-memory tuples in producing results during the online phase of the join, and a novel re-entrant join technique that allows the algorithm to rapidly switch between processing in-memory and disk-resident tuples, thus better exploiting temporary delays when new data is not available. I will present experimental results using real and synthetic data sets that show that DINER outperforms previous adaptive join algorithms in producing result tuples at a significantly higher rate, while making better use of the available memory.Short Bio:
Prof. Vasilis Vassalos (PhD in CS, Stanford University, 2000) is an Associate Professor in the Department of Informatics at AUEB. His research is on infrastructure and algorithmic issues for the integration of data and Web services in different environments, including XML query processing, specification-driven interface generation, adaptive query processing, and query rewriting using views. He is also working on sensor data management. Vassalos is the recipient of numerous awards, including a Marie Curie Outgoing International Fellowship for 2007-2008, and has been Principal Investigator for 8 funded research and advanced development projects since his arrival at AUEB in 2004. He is the author of over 25 technical publications and two US patents. He is or has been a member of the Program Committees of numerous international conferences, including SIGMOD 2008 and VLDB 2007. He is the co-founder of software company Enosys Software (sold to BEA Systems in 2003), maker of the first XQuery-based data integration platform and XQuery engine. Before joining AUEB he was an Assistant Professor of Information Systems at the Stern School of Business at NYU. Web: https://www.cs.ucy.ac.cy/colloquium/ Mailing List: https://listserv.cs.ucy.ac.cy/mailman/listinfo/cs-colloquium RSS: https://www.cs.ucy.ac.cy/colloquium/rss.xml Calendar: https://www.cs.ucy.ac.cy/colloquium/schedule/cs.ucy.2009.Vassalos.ics Presentations
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Invited Course Lecture: Big Data - What Is It?, Dr. Demetris Zeinalipour (University of Cyprus, Cyprus), Tuesday, March 19, 2013, 16:30-18:00 EET.
Speaker: Dr. Demetris Zeinalipour
Affiliation: University of Cyprus, Cyprus Category: Invited Course Lecture Location: Room 148, Faculty of Pure and Applied Sciences (FST-01), 1 University Avenue, 2109 Nicosia, Cyprus (directions) Date: Tuesday, March 19, 2013 Time: 16:30-18:00 EET Host: Yannis Dimopoulos (yannis-AT-cs.ucy.ac.cy) URL: https://www.cs.ucy.ac.cy/colloquium/presentations.php#cs.ucy.pres.2013.zeinalipourAbstract:
Big data refers to data sets whose size and structure strains the ability of commonly used relational DBMSs to capture, manage, and process the data within a tolerable elapsed time. Big data sizes commonly range from a few dozen terabytes to many petabytes in a single database and their underlying data model might be anything from structured (relational or tabular) to semi-structured (XML or JSON) or even unstructured (Web text and log files). Big data architectures are highly parallel and distributed in order to cope with the inherent I/O and CPU limitations. Such systems typically perform on mid-scale private clouds, offering higher privacy, to large-scale public clouds, both exposing operational and analytic functionality stand-alone or as-a-Service. This talk aims to overview the current big-data management landscape, the underlying technologies and their provenance, the latest NoSQL and NewSQL trends, possible applications of big-data management systems for online and offline processing of sensor data, text data, social data and medical data in enterprise environments. The talk will also overview ongoing big-data research and teaching activities at the University of Cyprus.Short Bio:
Demetris Zeinalipour (PhD, University of California, Riverside, 2005) is an Assistant Professor of Computer Science at the University of Cyprus. Before that he was a Lecturer at the Open University of Cyprus, a Visiting Lecturer at his current department and a Visiting Researcher at the network intelligence lab of Akamai Technologies (MA, USA). Demetris has served as the PC Co-Chair of ACM MobiDE'09, IEEE MDM'10 and VLDB's DMSN'10, the General Chair for ACM MobiDE'10, the Contest Chair of IEEE ICDM'10, the Demo Chair for IEEE MDM'13 and the Organization Chair of HDMS'10. His primary research interests include Data Management in Systems and Networks, in particular Distributed Query Processing, Storage and Retrieval Methods for Sensor, Smartphone and Peer-to-Peer Systems, Mobile and Network Data Management, Energy-aware Data Management. For more information, please visit: https://www.cs.ucy.ac.cy/~dzeina/ or http://dmsl.cs.ucy.ac.cy/ Other Presentations Web: https://www.cs.ucy.ac.cy/colloquium/presentations.php Colloquia Web: https://www.cs.ucy.ac.cy/colloquium/ Calendar: https://www.cs.ucy.ac.cy/colloquium/schedule/cs.ucy.pres.2013.Zeinalipour.ics
