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首页> 外文期刊>Iranian Journal of Science and Technology, Transactions of Electrical Engineering >Determination of the Multicast Optimal Route for Mobile Sinks in a Specified Deadline Using Network Coding and Tabu Search Algorithm in Wireless Sensor Networks
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Determination of the Multicast Optimal Route for Mobile Sinks in a Specified Deadline Using Network Coding and Tabu Search Algorithm in Wireless Sensor Networks

机译:使用网络编码和无线传感器网络中的网络编码和禁忌搜索算法在指定截止日期中的多播最佳路径的确定

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The purpose of this paper is to determine a multicast optimal route (OR) at a specific deadline for mobile sinks (MSs) using network coding (NC) in wireless sensor networks (WSNs). For this purpose, we first show that the solution of the problem of OR of MSs (ORM) is NP-hard; then to solve this problem, we propose several convex optimization models based, on the mixed integer linear model (MILP). In these models, NC and support vector regression (SVR) methods are used, and the difference of the models is based on their objective function, which includes maximizing the fit value, minimizing the total energy consumption of the active sensor nodes (ASNs), minimizing the energy consumption of the entire network, and maximizingthe remaining energy of ASNs. These models cannot be solved in polynomial time because they have several parameters and WSNs resources are limited. For this purpose, we propose an algorithm based on the tabu search (TS) algorithm. In the simulation section, we compare the proposed algorithm and optimization models with the famous traveling salesman problem (TSP). The results show the superiority of the proposed models and algorithm based on the deadline, the number of ASNs in energy consumption and network lifetime and calculation time. Each model based on its objective function improves energy consumption by 23% and network lifetime by 16%. The reason for this excellence is the use of NC in models. However, the calculation time in the models is 8% more than the proposed and TSP algorithms.
机译:本文的目的是在无线传感器网络(WSN)中使用网络编码(NC)确定移动宿(MSS)的特定截止日期的多播最佳路线(或)。为此目的,我们首先表明MSS(ORM)问题的解决方案是NP-HARD;然后解决这个问题,我们提出了几种基于凸的优化模型,在混合整数线性模型(MILP)上。在这些模型中,使用NC和支持向量回归(SVR)方法,并且模型的差异基于它们的目标函数,其包括最大化拟合值,最小化有源传感器节点(ASN)的总能量消耗,最小化整个网络的能量消耗,并最大化ASN的剩余能量。这些模型不能在多项式时间中解决,因为它们具有若干参数,并且WSNS资源有限。为此,我们提出了一种基于禁忌搜索(TS)算法的算法。在仿真部分中,我们将提议的算法和优化模型与着名的旅行推销员问题(TSP)进行比较。结果显示了基于截止日期的提出模型和算法的优越性,能耗和网络寿命和计算时间中的ASN的数量。根据其目标函数的每个模型将能耗提高23%,网络寿命增加了16%。卓越的原因是在模型中使用NC。但是,模型中的计算时间比提议和TSP算法更高为8%。

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