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SWARM-based data delivery in Social Internet of Things

机译:社交物联网中基于SWARM的数据交付

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Social Internet of Things (SIoTs) refers to the rapidly growing network of connected objects and people that are able to collect and exchange data using embedded sensors. To guarantee the connectivity among these objects and people, fault tolerance routing has to be significantly considered. In this paper, we propose a bio-inspired particle multi-swarm optimization (PMSO) routing algorithm to construct, recover and selectk-disjoint paths that tolerates the failure while satisfying quality of service (QoS) parameters. Multi-swarm strategy enables determining the optimal directions in selecting the multipath routing while exchanging messages from all positions in the network. The validity of the proposed algorithm is assessed and results demonstrate high-quality solutions compared with the canonical particle swarm optimization (CPSO), and fully particle multi-swarm optimization (FPMSO).
机译:社交物联网(SIoT)是指连接对象和人员的快速增长的网络,它们能够使用嵌入式传感器收集和交换数据。为了保证这些对象和人员之间的连通性,必须认真考虑容错路由。在本文中,我们提出了一种生物启发式粒子多群优化(PMSO)路由算法,以构建,恢复和选择不相交的路径,从而在满足服务质量(QoS)参数的同时容忍故障。多群策略可在选择多路径路由时确定最佳方向,同时从网络中的所有位置交换消息。与标准粒子群优化(CPSO)和全粒子多群优化(FPMSO)相比,该算法的有效性得到了评估,结果证明了高质量的解决方案。

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