Game-theoretic solutions through intelligent optimization for efficient resource management in wireless visual sensor networks
作者：
Highlights：
• Network resources are allocated among the nodes of a DS-CDMA visual sensor network.
• Two variants of the Nash bargaining solution (n.NBS, c.NBS) are utilized.
• n.NBS (c.NBS) treats each node (class of nodes) as equally advantaged.
• The resulting optimization problems are solved using particle swarm optimization.
• NBS variants outperform schemes that minimize average or maximum video distortion.
摘要
Highlights•Network resources are allocated among the nodes of a DS-CDMA visual sensor network.•Two variants of the Nash bargaining solution (n.NBS, c.NBS) are utilized.•n.NBS (c.NBS) treats each node (class of nodes) as equally advantaged.•The resulting optimization problems are solved using particle swarm optimization.•NBS variants outperform schemes that minimize average or maximum video distortion.
论文关键词：Bargaining powers,Game theory,Nash bargaining solution,Particle swarm optimization,Resource allocation,Visual sensor network
论文评审过程：Received 30 July 2013, Revised 14 December 2013, Accepted 4 February 2014, Available online 22 February 2014.
论文官网地址：https://doi.org/10.1016/j.image.2014.02.001
