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A Comprehensive Cross-Layer Framework for Optimization of Correlated Data Gathering in Wireless Sensor Networks

机译：用于优化无线传感器网络中相关数据收集的综合跨层框架

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Wireless Sensor Networks are energy-constrained and thereby require energy-efficient protocols to maximize the network lifetime. Since many sensors have closely-related readings, correlated data gathering has emerged as an efficient approach for achieving energy conservation. Hence, the objective of this work is to study the existing literature on correlated data gathering in WSN and propose an improvement. Many existing approaches are based on traditional layered architecture which optimizes some layers' functions independently. This strict layered approach results in unnecessary overhead in the context of resource-scarce sensor networks. Therefore, we focus on adaptive cross-layer design that jointly optimizes the activities of various layers. Existing cross-layer solutions optimize the activities of Routing and MAC layers only. RMC is an energy-aware cross-layer protocol that considers the clustering activity in addition to Routing and MAC layer functions for joint optimization. This research work studies the performance of RMC protocol in terms of energy consumption and network lifetime. We have proposed an enhancement to the basic RMC protocol named Enhanced-RMC (E-RMC) and show that it improves the network lifetime significantly. A thorough simulative study is carried out using Avrora simulator on TinyOS platform.
机译：无线传感器网络是能量约束的，从而需要节能协议来最大化网络寿命。由于许多传感器具有密切相关的读数，因此相关的数据收集成为实现节能的有效方法。因此，这项工作的目标是研究在WSN中的相关数据收集的现有文献，并提出改进。许多现有方法基于传统的分层体系结构，独立优化一些层次的功能。这种严格的分层方法在资源稀缺传感器网络的上下文中产生了不必要的开销。因此，我们专注于自适应跨层设计，共同优化各层的活动。现有的横梁解决方案仅优化路由和MAC层的活动。 RMC是一种能量感知交叉层协议，但除了用于联合优化的路由和MAC层函数之外，还考虑群集活动。本研究工作研究了RMC协议在能耗和网络寿命方面的表现。我们提出了对名为增强型RMC（E-RMC）的基本RMC协议的增强，并显示它显着提高了网络寿命。在Tinyos平台上使用Avrora Simulator进行了一种彻底的模拟研究。

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