CS Other Presentations

Department of Computer Science - University of Cyprus

Besides Colloquiums, the Department of Computer Science at the University of Cyprus also holds Other Presentations (Research Seminars, PhD Defenses, Short Term Courses, Demonstrations, etc.). These presentations are given by scientists who aim to present preliminary results of their research work and/or other technical material. Other Presentations serve as a forum for educating Computer Science students and related announcements are disseminated to the Department of Computer Science (i.e., the csall list):
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Presentations Coordinator: Demetris Zeinalipour

PhD Defense: Algorithms and Indexing Structures for Spatial Big Data, Mr. Constantinos Costa (University of Cyprus, Cyprus), Monday, July 2, 2018, 10:00-11:00 EET.

The Department of Computer Science at the University of Cyprus cordially invites you to the PhD Defense entitled:

Algorithms and Indexing Structures for Spatial Big Data

Speaker: Mr. Constantinos Costa
Affiliation: University of Cyprus, Cyprus
Category: PhD Defense
Location: Room 148, Faculty of Pure and Applied Sciences (FST-01), 1 University Avenue, 2109 Nicosia, Cyprus (directions)
Date: Monday, July 2, 2018
Time: 10:00-11:00 EET
Host: Prof. Marios D. Dikaiakos (mdd-AT-cs.ucy.ac.cy)
URL: https://www.cs.ucy.ac.cy/colloquium/presentations.php#cs.ucy.pres.2018.costa

We live in the big data era where heterogeneous data is produced and stored at an exponential rate. Recently, many solutions have emerged to handle big data for which traditional data management systems are not capable to capture, manage, and process the data within a tolerable elapsed time. A significant portion of big data is Spatial Big Data (SBD), which represents massive geographic objects that again exceed the capability of traditional spatial computing systems due to volume, variety and velocity characteristics. SBD brings many new challenges for novel SBD management architec- tures. Particularly, recent works are utilizing distributed environments to implement spatial operators like kNN, Joins, Aggregations and Selections on top of big data archi- tectures. Additionally, several of the previous solutions are using distributed indexing techniques to enhance the storing process and the spatial operators. Unfortunately, the proposed architectures are agnostic of underline processing and storage capabilities failing to maintain optimized storage efficiency and satisfy the requirements for online analytical and operational queries. In this PhD thesis we present algorithms and indexing structures that tackle critical challenges brought forward by SBD, namely query response time and storage efficiency. We frame our research contributions in the context of a novel performance-driven architecture, named SPATE+, where the storage, indexing, query processing and application components of the architecture can achieve better utilization and efficiency than the state-of-the-art. SPATE+ uses lossless data compression to ingest recent streams of SBD in the most compact manner retaining full resolution for data exploration tasks. More importantly, it takes care of the progressive loss of detail in information, called decaying, as data ages with time. Particularly, we present a novel decaying operator for Telco Big Data (TBD), coined TBD-DP (Data Postdiction). TBD-DP relies on existing machine learning algorithms to abstract TBD into compact models that can be stored and queried when necessary. SPATE+ is conceptually divided into three layers: (i) storage and indexing, where high storage efficiency is achieved using the compression and decay components. This category also includes a spatio-temporal index with four levels of temporal resolutions minimizing the query response time for data exploration queries; (ii) operators, where a high performance AkNN query operator outperforms state-of-the-art techniques in terms of efficient partitioning, replication and refinement; and (iii) applications, where an efficient query exploration framework, called SPATE, provides novel data explo- ration functionalities to the user. We also present an anonymous crowd messaging application, called Rayzit, which utilizes SBD to connect the users instantly to their k Nearest Neighbors (kNN) as they move in space, to expose the contributions of the components that are part of SPATE+.

Short Bio:
Constantinos Costa is a full-time Ph.D. Candidate and a Research Assistant at the Department of Computer Science (UCY), being involved in research at the Data Management Systems Laboratory (DMSL). He holds a M.Sc. degree in Computer Science (2013) and a B.Sc. degree in Computer Science (2011) from the University of Cyprus. His research interests include databases and mobile computing, particularly distributed query processing for spatial and spatio-temporal datasets. Costa has contributed extensively to open source projects for indoor navigation, crowd messaging and telco big data. For more information please visit: https://www.cs.ucy.ac.cy/~costa.c/.

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