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Ioannis V. Loumiotis

dblp:143/9723 · DBLP profile ↗
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4ranked-venue papers
3as first author
0since 2021 · last 2019
0000-0002-0936-4017ORCID · reported

Domains — the database's venue-derived domains; a paper can count in several

Computer networks · 3 · 3 first-authorArtificial intelligence and machine learning · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer networks
2 papers
Network optimization and economics · 50% Optical networks · 30% Cellular and mobile networks · 20%

Topics — the 6 heaviest of 6, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Optical networks › optical access network
passive optical network
0.322017
Dynamic Allocation of Backhaul Resources in Converged Wireless-Optical Networks · IEEE J. Sel. Areas Commun. 2017
Dynamic Backhaul Resource Allocation: An Evolutionary Game Theoretic Approach · IEEE Trans. Commun. 2014
Network optimization and economics
resource allocation
0.312017
Dynamic Allocation of Backhaul Resources in Converged Wireless-Optical Networks · IEEE J. Sel. Areas Commun. 2017
Cellular and mobile networks
radio access networks
0.322017
Dynamic Backhaul Resource Allocation: An Evolutionary Game Theoretic Approach · IEEE Trans. Commun. 2014
Dynamic Allocation of Backhaul Resources in Converged Wireless-Optical Networks · IEEE J. Sel. Areas Commun. 2017
Network optimization and economics
dynamic resource allocation
0.212014
Dynamic Backhaul Resource Allocation: An Evolutionary Game Theoretic Approach · IEEE Trans. Commun. 2014
Network optimization and economics › game theory
evolutionary game theory
0.212014
Dynamic Backhaul Resource Allocation: An Evolutionary Game Theoretic Approach · IEEE Trans. Commun. 2014
Optical networks › optical access network
fiber-wireless integration
0.112014
Dynamic Backhaul Resource Allocation: An Evolutionary Game Theoretic Approach · IEEE Trans. Commun. 2014

Methods — techniques the papers use, named apart from their topics

replicator dynamics · 0.5evolutionary game theory · 0.5
YearPublicationVenuePosition
2019 The Identification and Creation of Ontologies for the Use in Law Enforcement AI Solutions - MAGNETO Platform Use Case
Rafal Kozik, Michal Choras, Marek Pawlicki, Witold Holubowicz, Dirk Pallmer, Wilmuth Müller, Ernst-Josef Behmer, Ioannis V. Loumiotis, Konstantinos P. Demestichas, Roxana Horincar, Claire Laudy, David Faure
ICCCI (2)8
2017 Dynamic Allocation of Backhaul Resources in Converged Wireless-Optical Networks
abstract
The market uptake of the 4th Generation networks is expected to support the increasing demand for wireless broadband services and ensure an enhanced mobile user experience. In this direction, the convergence of a wireless access network with an optical backhauling has been proposed. However, in such a converged architecture, the traditional fixed commitment of the backhaul resources does not prove to be as efficient, and novel dynamic schemes are required that consider both the needs of the base stations and the limitations of the passive optical network. This paper is concerned with the topic of resource allocation in two competing base stations that belong to different operators and share a common optical backhaul network infrastructure. An approach based on evolutionary game theory is proposed and employed, with a view to examining the interactions among the base stations and the passive optical network. Using the model of replicator dynamics, the proposed system design is proved to be asymptotically stable. In addition, this paper studies and reveals the extent to which time delay can have an impact on the proposed system design.
Ioannis V. Loumiotis, Pavlos Kosmides, Evgenia F. Adamopoulou, Konstantinos P. Demestichas, Michael E. Theologou
IEEE J. Sel. Areas Commun.1
2016 Road to Next Generation Mobile Networks: An Evolutionary Dynamics Approach
Ioannis V. Loumiotis, Evgenia F. Adamopoulou, Konstantinos P. Demestichas, Chara Remoundou, Pavlos Kosmides, Vasileios Asthenopoulos, Michael E. Theologou
Mob. Networks Appl.1
2014 Dynamic Backhaul Resource Allocation: An Evolutionary Game Theoretic Approach
abstract
The recently deployed 4G access technology promises to satisfy the increasing demand of bandwidth consuming applications by providing high network capacity, low latency and seamless mobility. Towards this direction, concept solutions concerning the integration of wireless and optical networks have been proposed. However, the majority of these approaches assume the conventional fixed commitment of resources to the base stations, an inefficient and costly process, especially in case the Passive Optical Network (PON) belongs to a different operator. As a result, new, more dynamic backhaul resource allocation approaches are required. In this paper, the authors study the problem of committing resources of the backhaul network to a base station by employing evolutionary game theory in order to model the interactions between the subscribers and the base station. The asymptotic stability of the proposed scheme is proven under the replicator dynamics model. Finally, the impact of time delay in the proposed scheme is also investigated.
Ioannis V. Loumiotis, Evgenia F. Adamopoulou, Konstantinos P. Demestichas, Theodora A. Stamatiadi, Michael E. Theologou
IEEE Trans. Commun.1