New Advances in Multi-Agent Systems: Control and Modelling

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Systems & Control Engineering".

Deadline for manuscript submissions: 15 July 2024 | Viewed by 851

Special Issue Editors


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Guest Editor
Department of Informatics and Data Science, Sanyo-Onoda City University, Yamaguchi 756-0884, Japan
Interests: multi-agent systems; multi-robot systems; delay tolerable networks; ad hoc communication; AI and its social implications
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Guest Editor
Department of Maritime Safety Technology, Japan Coast Guard Academy, Hiroshima 737-8512, Japan
Interests: artificial intelligence; agent based modeling

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Guest Editor
Department of Computer Science, National Defense Academy, Hashirimizu 239-8686, Japan
Interests: artificial intelligence; agent based modeling and simulation

Special Issue Information

Dear Colleagues,

The notions of agents and multi-agent systems are understood in both academic and industrial domains. Research on these fields is advanced, but they are too extensive to easily grasp. The purpose of this Special Issue is to provide a comprehensive research summary of the theory and application in the field of agent- and multi-agent-based systems. The scope includes, but is not limited to: agent-based modeling and simulation, agent-based software construction and software engineering, frameworks of artificial intelligence based on agents, agent-based software platforms, distributed problem solving and distributed artificial intelligence, and agents and multi-agent systems in general.

Dr. Yasushi Kambayashi
Dr. Saori Iwanaga
Dr. Hiroshi Sato
Guest Editors

Manuscript Submission Information

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Keywords

  • multi-agent systems
  • multi-agent-based systems
  • distributed artificial intelligence

Published Papers (1 paper)

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Research

14 pages, 1027 KiB  
Article
Caching Method for Information-Centric Ad Hoc Networks Based on Content Popularity and Node Centrality
by Masaki Koide, Naoyuki Matsumoto and Tomofumi Matsuzawa
Electronics 2024, 13(12), 2416; https://doi.org/10.3390/electronics13122416 - 20 Jun 2024
Viewed by 382
Abstract
In recent years, most internet communications have focused on accessing content such as video, web services, and audio. Conversely, traditional Internet communications are inefficient because they are primarily designed for data transfer between hosts. In response, Information-Centric Networking (ICN) has emerged as a [...] Read more.
In recent years, most internet communications have focused on accessing content such as video, web services, and audio. Conversely, traditional Internet communications are inefficient because they are primarily designed for data transfer between hosts. In response, Information-Centric Networking (ICN) has emerged as a content-oriented networking model. The impact of ICN in reducing the location dependency of data and its high compatibility with ad hoc networks has led to research on realizing Information-Centric ad hoc Networks (ICANET). There has also been extensive research into caching content in the network, which is one of the features of ICN. In static networks, methods have been proposed to cache highly popular content in nodes that are more likely to be used for shortest paths. However, in dynamic networks, content with high popularity should be cached on nodes that are more likely to reach all nodes, as missing nodes need to be taken into account. In this study, we propose a cache control scheme for content caching in ICANET that utilizes both content popularity and the closeness centrality of nodes within the ad hoc network as indicators. To realise the proposed method, a new packet flow based on the Pending Interest Table (PIT) and Content Store (CS) was implemented in the forwarding strategy of ICN. The experiments used ndnSIM, a protocol implementation of NDN based on Network Simulator3, which is widely used in wireless network research. The experimental results showed that the cache hit rate could be increased by up to 4.5% in situations with low content bias. In the same situation, the response delay was also reduced by up to 28.3%. Full article
(This article belongs to the Special Issue New Advances in Multi-Agent Systems: Control and Modelling)
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