Coalition Formation for Outsourced Spectrum Sensing in Cognitive Radio Network

Sardar, Asif Ahmed; Roy, Dibbendu; Mondal, Washim Uddin; Das, Goutam

doi:10.1109/tccn.2023.3254512

Cited by 4 publications

(2 citation statements)

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“…Specifically, coalition formation mechanisms have been tailored for IoT device coalitions [ 23 ], aiming at optimizing energy and resource utilization in IoT environments. Many authors also approach coalition formation from a game theoretic perspective [ 24 , 25 , 26 ]. For example, in [ 24 ], an anti-jamming coalition formation game was proposed for Satellite-Enabled Army IoT, while [ 25 ] proposed machines that perform the task of IoT nodes forming clusters through a coalition formation game.…”

Section: Introductionmentioning

confidence: 99%

“…For example, in [ 24 ], an anti-jamming coalition formation game was proposed for Satellite-Enabled Army IoT, while [ 25 ] proposed machines that perform the task of IoT nodes forming clusters through a coalition formation game. Similarly, in [ 26 ], IoT operators formed coalitions to avoid intra-coalitional interference in terms of spectrum sensing. Despite this progress, the establishment of coalitions among SPs for effective service delivery remains a relatively underexplored area, with limited existing literature.…”

Section: Introductionmentioning

confidence: 99%

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Dynamic Coalition Formation among IoT Service Providers: A Systematic Exploration of IoT Dynamics Using an Agent-Based Model

Shakya,

Chopin,

Merghem-Boulahia

2024

Sensors

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This paper introduces an Agent-Based Model (ABM) designed to investigate the dynamics of the Internet of Things (IoT) ecosystem, focusing on dynamic coalition formation among IoT Service Providers (SPs). Drawing on insights from our previous research in 5G network modeling, the ABM captures intricate interactions among devices, Mobile Network Operators (MNOs), SPs, and customers, offering a comprehensive framework for analyzing the IoT ecosystem’s complexities. In particular, to address the emerging challenge of dynamic coalition formation among SPs, we propose a distributed Multi-Agent Dynamic Coalition Formation (MA-DCF) algorithm aimed at enhancing service provision and fostering collaboration. This algorithm optimizes SP coalitions, dynamically adjusting to changing demands over time. Through extensive experimentation, we evaluate the algorithm’s performance, demonstrating its superiority in terms of both payoff and stability compared to three classical coalition formation algorithms: static coalition, non-overlapping coalition, and random coalition. This study significantly contributes to a deeper understanding of the IoT ecosystem’s dynamics and highlights the potential benefits of dynamic coalition formation among SPs, providing valuable insights and opening future avenues for exploration.

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