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A Unified Solution for Gateway and In-network Traffic Load Balancing in Multihop Data Collection Scenarios

机译:多跳数据收集方案中网关和网络内流量负载均衡的统一解决方案

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摘要

Data collection is a fundamental task of Wireless Sensor Networks (WSN) to support a variety of applications, such as remote monitoring, and emergency response, where collected information is relayed to an infrastructure network via packet gateways for processing and decision making. In large-scale monitoring scenarios, data packets need to be relayed over multi-hop paths to the gateways, and sensors are often randomly deployed, causing local node density differences. As a result, imbalance in data traffic load on the gateways is likely to occur. Furthermore, due to dynamic network conditions and differences in sensor data generation rates, congestion on some data paths is also often experienced. Numerous studies have focused on the problem of in-network traffic load balancing, while a few works have aimed at equalizing the loads on gateways. However, there is a potential trade-off between these two problems. In this paper, the dual objective of gateway and in-network load balancing is addressed and the RALB (Reactive and Adaptive Load Balancing) algorithm is presented. RALB is proposed as a generic solution for multihop networks and mesh topologies, especially in large-scale remote monitoring scenarios, to balance traffic loads.
机译:数据收集是无线传感器网络(WSN)的一项基本任务,用于支持各种应用程序,例如远程监视和紧急响应,其中收集的信息通过分组网关中继到基础结构网络以进行处理和决策。在大规模监视场景中,数据包需要通过多跳路径中继到网关,并且传感器通常是随机部署的,从而导致本地节点密度差异。结果,网关上数据流量负载的不平衡可能会发生。此外,由于动态网络条件和传感器数据生成速率的差异,某些数据路径上也经常出现拥塞。许多研究集中在网络内流量负载平衡的问题上,而一些工作旨在均衡网关上的负载。但是,这两个问题之间存在潜在的权衡。本文解决了网关和网络内负载平衡的双重目标,并提出了RALB(无功和自适应负载平衡)算法。 RALB被建议作为多跳网络和网状拓扑的通用解决方案,尤其是在大规模远程监视场景中,以平衡流量负载。

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