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Distributed Management of Data Laboratory (D.M.O.D.)
Monday July 16, 2018

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Last revision date:
Wednesday February 05, 2014



Distributed Data Management

As databases get larger and become accessible to a more diverse and less technically-oriented audience, exploration or recommendation style database interactions are attractive and useful. Our research aims at assisting users in database exploration by recommending to them additional items that are highly related with the items in the result of their original query. Our recommendations are based solely on the result of the user query and the database instance.
A great amount of information becomes available to users every day through a number of on-line sources. However, locating valuable or important information can prove out to be an overwhelming task, due to the great volume of accessible data. Therefore, in addition to traditional web search methods, proactive search models are becoming increasingly popular and used by a continuously growing portion of Internet users. Our research concerns the development, implementation and evaluation of models, algorithms and techniques for supporting the ranking of information being forwarded towards the users of large-scale network-centric information management systems, such as publish/subscribe systems. Ranking is based on the importance of each piece of information. We consider that importance is influenced by two main factors: (i) relevance to user interests and (ii) diversity. Relevance is important so that users are only notified about the most interesting events according to their specified subscriptions, while diversity ensures that the received notifications are not referring to the same or similar events.
» Distributed Overlays
» Social Networks
» Past Research Topics
Mobile agents are software processes capable of migrating from one site to another. We study their potential use in designing more flexible and extensible database architectures as well as distributed systems for wireless computing.
Peer-to-peer (p2p) computing refers to a new form of distributed computing that involves a large number of autonomous computing nodes (the peers) that cooperate to share resources and services. P2p systems are gaining popularity as a way to effectively share huge, massively distributed data collections. XML is rapidly emerging as the new standard for data representation and exchange on the Internet. Currently, a vast amount of information is published and made accessible in the form of XML documents. In our research, we assume that the data sources in the peer-to-peer network store XML documents that we wish to index, query and retrieve.
» Pervasive Computing
We have developed a middleware framework that unifies access to GSM-enabled sensor devices. Typically, communication with mobile sensors relies on proprietary protocols, involving the exchange of SMS and MMS messages. We use XML-based control descriptions that abstractly specify these protocols to generate proxies and corresponding WEB-based (HTML, WAP and WEB services) interfaces that realize them. Thus, we provide access transparency over different kinds of mobile sensors.
See also: "On Accessing GSM-enabled Mobile Sensors, by Z. Plitsis, I. Fudos, E. Pitoura and A. Zarras" presented in ISSNIP 2005: presentation in ppt format and proceedings paper in pdf format.

Graphics and CAD Systems

» Geometric Constraints in CAD and VLSI
Geometric Constraints are used in Manufacturing, Biology, Robotics, Graphics and VLSI to express topological relations among elements of a configuration. We derive representations for CAD and VLSI configurations and we design efficient algorithms for solving the resulting systems of geometric constraints utilizing domain knowledge.
» Feature-based and Constraint-based CAD Models
We derive editable CAD models from point clouds with or without user interaction. Thus we may reconstruct and modify a certain part for which there is no CAD model or even blue prints.
» Shape-based Image Retrieval
We develop shape-based image retrieval methods for large image bases.
» Visualization
We design and develop thin client access systems for modular visualization environments. Heavy visualization operations may be performed distributed on a grid or cluster.

Parallel Processing

» Interconnection Networks
The interconnection network is the single most important resource in a parallel system. Our research focuses on various aspects of the interconnection network, including architectural, topological and communication issues as well as performance analysis.
Information dissemination is a prevailing issue in multicomputers with private memories, as well as in general distributed systems. Collective communications involve groups of nodes that want to disseminate data items among them. Our research has proposed solutions for various types of collective communication and in the context of diverse classes of topologies.
The tedious task of parallel programming has been alleviated significantly by the adoption of OpenMP, an easy and incremental API for expressing parallelism, in shared-memory environments. We have designed and implemented an open-source research compiler for C with OpenMP directives. The compiler comes with a run-time support library, produces code with competitive performance and is under constant development.

Information Systems Architecting

A main theme of our researsch involves the construction of tools and methods that facilitate the principled modeling and construction of database-centric information systems. Particular topics under this broad theme involve the principled modeling of IS architecture, the management of the evolution of databases & related software in a IS, the metrics-based design of IS's, etc.
Data Warehouses are vast collections of data coming from various sources that are cleansed, integrated and queried for decision making purposes. Currently, the core of our research aims to facilitate, manage and optimize the design and implementation of the data warehouse back-stage processes (responsible for the collection, cleansing and reconciliation of data under a common strucutre) both during the initial design and deployment stage and during the continuous evolution of the data warehouse.


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Computer Science Dept.
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