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PER-NODE POWER MINIMAL MULTICAST TREES WHICH MAXIMIZE THE TIME-TO-FIRST-FAILURE IN ENERGY CONSTRAINED STATIC WIRELESS NETWORKS: A 2-STEP HEURISTIC APPROACH

机译:每个节点功率最小多播树,最大限度地提高了能量受限静态无线网络中的第一失败:2步启发式方法

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We consider the problem of jointly maximizing the time-to-first-failure (TTFF), defined as the time till the first node in the network runs out of battery energy, and minimizing the total power in energy constrained static wireless networks. It is shown in [6] that simply optimizing the TTFF criterion may not provide the ideally optimum solution. Besides maximizing the TTFF, the ideally optimum solution guarantees that the lifetimes of all nodes are at least as high as in other trees which provide the same TTFF. A composite objective function involving the TTFF and the sum of the transmitter powers is therefore proposed in [6], along with a discussion of an optimal solution methodology using mixed integer linear programming. In this paper, we discuss a 2-step heuristic procedure for the joint optimization problem. The first step is a greedy iterative algorithm which provides an optimal solution, but with respect to the TTFF criterion only. The second step is a tree-improvement technique which is used to refine the TTFF-optimal tree such that the total transmitter power is minimized, without affecting the optimal TTFF. Recent work has shown that the power consumed in the receiver circuitry can be almost comparable to the transmit power, especially in short-range networks. Our algorithms are therefore designed to take into account both the transmitter side and receiver side power expenditures. Simulation results are presented to validate the performance of the algorithm.
机译:我们考虑联合最大化最初发生故障(TTFF)的问题,定义为网络中的第一节内部的时间,并最大限度地减少能量受限静态无线网络中的总功率。它如[6]所示,简单地优化TTFF标准可能无法提供理想的最佳解决方案。除了最大化TTFF之外,理想的最佳解决方案还保证所有节点的寿命至少与提供相同TTFF的其他树木一样高。因此,在[6]中提出了一种涉及TTFF的复合目标函数和发射器功率之和,以及使用混合整数线性编程的最佳解决方法的讨论。在本文中,我们讨论了联合优化问题的2步启发式程序。第一步是一种贪婪的迭代算法,它提供了最佳解决方案,而是仅提供了TTFF标准。第二步骤是一种树改善技术,用于改进TTFF - 最佳树,使得总发射机功率最小化,而不会影响最佳TTFF。最近的工作表明,接收器电路中消耗的功率可以与发射功率几乎相当,尤其是在短程网络中。因此,我们的算法设计用于考虑发射器侧和接收器侧功率支出。提出了仿真结果以验证算法的性能。

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