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Topology-Aware Energy Efficient Task Assignment for Collaborative In-Network Processing in Distributed Sensor Systems

机译:分布式传感器系统中协作内部网络的节能任务任务分配

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In the emerging networked sensor systems, collaborative in-network processing provides a viable solution to overcome the limited energy and resource constraints of one single node. In this novel computing paradigm, it is very critical to perform task assignment. In this paper, we formally model TETA, an energy efficient topology-aware real time task assignment problem in wireless sensor networks, and prove its NP-completeness.We also propose an ant-based meta-heuristic algorithm to solve the TETA problem.We implement our algorithm and conduct experiments based on a simulation environment. The experimental results show that our approach can archive significant energy saving and improve the system lifetime effectively as well.
机译:在新兴网络传感器系统中,协作内部处理提供了一种可行的解决方案,以克服一个单个节点的有限能量和资源约束。在这种新颖的计算范例中,执行任务分配非常重要。在本文中,我们正式模型TETA,无线传感器网络中的节能拓扑知识的实时任务分配问题,并证明了其NP完整性。我们还提出了一种基于蚂蚁的元启发式算法来解决TETA问题.WE基于仿真环境实现我们的算法和进行实验。实验结果表明,我们的方法可以归档显着的节能和有效地改善系统寿命。

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