Solving the controller placement problem (CPP) in an SDN architecture with multiple controllers has a significant impact on control overhead in the network, especially in multihop wireless networks (MWNs). The generat...Solving the controller placement problem (CPP) in an SDN architecture with multiple controllers has a significant impact on control overhead in the network, especially in multihop wireless networks (MWNs). The generated control overhead consists of controller-device and inter-controller communications to discover the network topology, exchange configurations, and set up and modify flow tables in the control plane. However, due to the high complexity of the proposed optimization model to the CPP, heuristic algorithms have been reported to find near-optimal solutions faster for large-scale wired networks. In this paper, the objective is to extend those existing heuristic algorithms to solve a proposed optimization model to the CPP in software-<span>defined multihop wireless networking</span><span> (SDMWN).</span>Our results demonstrate that using ranking degrees assigned to the possible controller placements, including the average distance to other devices as a degree or the connectivity degree of each placement, the extended heuristic algorithms are able to achieve the optimal solution in small-scale networks in terms of the generated control overhead and the number of controllers selected in the network. As a result, using extended heuristic algorithms, the average number of hops among devices and their assigned controllers as well as among controllers will be reduced. Moreover, these algorithms are able tolower<span "=""> </span>the control overhead in large-scale networks and select fewer controllers compared to an extended algorithm that solves the CPP in SDMWN based on a randomly selected controller placement approach.展开更多
为了延长多跳网络的网络寿命,将无线能量传输(wireless energy transfer,WET)技术应用于多跳网络,并提出基于蜂拥算法的最优WET时间的延长网络寿命算法(FENL)。FENL算法先建立基于WET的多跳传输系统模型,并构建最大化网络寿命的目标优...为了延长多跳网络的网络寿命,将无线能量传输(wireless energy transfer,WET)技术应用于多跳网络,并提出基于蜂拥算法的最优WET时间的延长网络寿命算法(FENL)。FENL算法先建立基于WET的多跳传输系统模型,并构建最大化网络寿命的目标优化函数。然后,利用蜂拥算法求解目标函数,进而获取每个节点的最优WET时间,进而最大化网络寿命。仿真结果表明,相比于传统的未采用无线能量采集和WET技术,FENL算法有效地延长了网络寿命,且FENL算法的网络寿命逼近于穷搜索法的网络寿命。展开更多
文摘Solving the controller placement problem (CPP) in an SDN architecture with multiple controllers has a significant impact on control overhead in the network, especially in multihop wireless networks (MWNs). The generated control overhead consists of controller-device and inter-controller communications to discover the network topology, exchange configurations, and set up and modify flow tables in the control plane. However, due to the high complexity of the proposed optimization model to the CPP, heuristic algorithms have been reported to find near-optimal solutions faster for large-scale wired networks. In this paper, the objective is to extend those existing heuristic algorithms to solve a proposed optimization model to the CPP in software-<span>defined multihop wireless networking</span><span> (SDMWN).</span>Our results demonstrate that using ranking degrees assigned to the possible controller placements, including the average distance to other devices as a degree or the connectivity degree of each placement, the extended heuristic algorithms are able to achieve the optimal solution in small-scale networks in terms of the generated control overhead and the number of controllers selected in the network. As a result, using extended heuristic algorithms, the average number of hops among devices and their assigned controllers as well as among controllers will be reduced. Moreover, these algorithms are able tolower<span "=""> </span>the control overhead in large-scale networks and select fewer controllers compared to an extended algorithm that solves the CPP in SDMWN based on a randomly selected controller placement approach.
文摘为了延长多跳网络的网络寿命,将无线能量传输(wireless energy transfer,WET)技术应用于多跳网络,并提出基于蜂拥算法的最优WET时间的延长网络寿命算法(FENL)。FENL算法先建立基于WET的多跳传输系统模型,并构建最大化网络寿命的目标优化函数。然后,利用蜂拥算法求解目标函数,进而获取每个节点的最优WET时间,进而最大化网络寿命。仿真结果表明,相比于传统的未采用无线能量采集和WET技术,FENL算法有效地延长了网络寿命,且FENL算法的网络寿命逼近于穷搜索法的网络寿命。
