Distributed Computing for Sensor Networks
A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Sensor Networks".
Deadline for manuscript submissions: 30 September 2026 | Viewed by 2
Special Issue Editors
Interests: multi-agent networks; distributed optimization and games; machine learning; social networks; nonlinear systems and control; autonomous systems; smart grid; software reliability
Special Issues, Collections and Topics in MDPI journals
Interests: wireless networks; performance evaluation; distributed systems; context-aware environments; IoT; next-generation wireless systems
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Multi-agent systems (MASs) represent a rapidly evolving class of engineered systems that bridge natural sciences and practical engineering applications. A typical MAS consists of multiple autonomous agents equipped with sensors, computing units, and actuators, interconnected through communication networks. In many real-world scenarios, system-level objectives must be achieved through distributed computing, relying on local sensing and information exchange among neighboring agents.
By integrating sensing, computation, communication, and control, MASs with distributed computing capabilities introduce new scientific and technical challenges arising from limited information, constrained resources, and decentralized decision-making. Addressing these challenges is essential for the reliable and efficient deployment of MASs in complex and dynamic environments. In this context, key research topics such as distributed estimation, learning and optimization, game theory and security, and cooperative control warrant particular attention.
This Special Issue aims to collect original, unpublished, high-quality contributions that are not under review by other conferences or journals. We welcome theoretical advances and engineering-oriented solutions related to distributed computing in sensor networks and multi-agent systems, including, but not limited to, the following:
- Distributed artificial intelligence (e.g., machine learning and data mining);
- Distributed optimization and game-theoretic approaches (e.g., resource allocation, security, and safety);
- Distributed estimation and control (e.g., filtering, tracking, and regulation).
Dr. Yiguang Hong
Prof. Dr. Francisco Falcone
Guest Editors
Manuscript Submission Information
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Keywords
- distributed computing
- sensor networks
- multi-agent systems
- distributed optimization and learning
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