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Energy efficiency and network lifetime maximization in wireless sensor networks using improved ant colony optimization

机译:无线传感器网络中的能效和网络寿命最大化,使用改进的蚁群优化

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Improving network lifetime is the fundamental challenge of wireless sensor networks. One possible solution consists in making use of mobile sinks. Sink mobility along a constrained path can improve the energy efficiency in wireless sensor networks. However, due to the path constraint, a mobile sink with constant speed has limited communication time to collect data from the sensor nodes deployed randomly. This poses significant challenges in jointly improving the amount of data collected and reducing the energy consumption. This paper proposes a data collection scheme, called the Maximum Amount Shortest Path (MASP), to address this issue that increases network throughput as well as conserves energy by optimizing the assignment of sensor nodes. MASP is formulated as an integer linear programming problem and then solved with the help of improved ant colony optimization. The residual energy of each node is calculated and the optimal path is selected by considering the shortest path, residual energy, channel noise, and delay. This approach is validated through simulation experiments using NS2
机译:提高网络寿命是无线传感器网络的根本挑战。一个可能的解决方案包括使用移动水槽。沿着约束路径的汇流量可以提高无线传感器网络中的能量效率。然而,由于路径约束,具有恒定速度的移动接收器具有有限的通信时间来从随机部署的传感器节点收集数据。这在共同改善收集的数据量并降低能量消耗方面存在重大挑战。本文提出了一种数据收集方案,称为最大数量最短路径(MASP),以解决增加网络吞吐量的问题,并通过优化传感器节点的分配来解决能量。 MASP被制定为整数线性编程问题,然后在改进的蚁群优化的帮助下解决。计算每个节点的剩余能量,通过考虑最短路径,剩余能量,信道噪声和延迟来选择最佳路径。通过使用NS2的模拟实验验证这种方法

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