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Dimitrios J. Vergados

Researcher at National Technical University of Athens

Publications -  62
Citations -  1026

Dimitrios J. Vergados is an academic researcher from National Technical University of Athens. The author has contributed to research in topics: Scheduling (computing) & Wireless network. The author has an hindex of 15, co-authored 62 publications receiving 914 citations. Previous affiliations of Dimitrios J. Vergados include University of Western Macedonia & University of the Aegean.

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Energy efficiency in wireless sensor networks using sleep mode TDMA scheduling

TL;DR: The proposed scheme achieves the reduction of the end-to-end delay caused by the sleep mode operation while at the same time it maximizes the energy savings.
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Approximate Consensus in Stochastic Networks With Application to Load Balancing

TL;DR: The upper bounds for mean square distance between states of the initial stochastic system and its approximate averaged model are derived and these upper bounds are used to obtain conditions for approximate consensus achievement.
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A Survey of TDMA Scheduling Schemes in Wireless Multihop Networks

TL;DR: The scope of this article is to classify the existing TDMA scheduling algorithms based on several factors, such as the entity that is scheduled, the network topology information that is needed to produce or maintain the schedule, and the entity or entities that perform the computation that produces and maintains the schedules, and to discuss the advantages and disadvantages of each category.
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Prosumer clustering into virtual microgrids for cost reduction in renewable energy trading markets

TL;DR: In this article, the problem of orchestrating the energy prosumers into virtual clusters, in order to participate in the market as a single entity and to reduce the total energy cost, through the reduction of the total relative forecasting inaccuracies, was studied.
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CorpWiki: A self-regulating wiki to promote corporate collective intelligence through expert peer matching

TL;DR: The proposed CorpWiki, a self-regulating wiki system for effective acquisition of high-quality knowledge content, aims to create new inferences regarding corporate issues, thus promoting the collective organizational intelligence.