Congestion Avoidance Based on Lightweight Buffer Management in Sensor Networks

Abstract

A wireless sensor network is constrained by computation capability, memory space, communication bandwidth, and above all, energy supply. When a critical event triggers a surge of data generated by the sensors, congestion may occur as data packets converge toward a sink. Congestion causes energy waste, throughput reduction, and information loss. However, the important problem of congestion avoidance in sensor networks is largely open. This paper proposes a congestion-avoidance scheme based on lightweight buffer management. We describe simple yet effective approaches that prevent data packets from overflowing the buffer space of the intermediate sensors. These approaches automatically adapt the sensors' forwarding rates to nearly optimal without causing congestion. We discuss how to implement buffer-based congestion avoidance with different MAC protocols. In particular, for CSMA with implicit ACK, our 1=k-buffer solution prevents hidden terminals from causing congestion. We demonstrate how to maintain nearoptimal throughput with a small buffer at each sensor and how to achieve congestion-free load balancing when there are multiple routing paths toward multiple sinks.

Take one for the team: On the time efficiency of application-level buffer-aided data relaying in edge cloud communication

“…Following the principles of Design of Experiments (DOE) [30], we repeated the FIFS health monitoring experiment multiple times (five times in specific) for 50 made-up individuals, and then calculated average values of latency indicators. According to the experimental results, there is no waiting latency between the data processing and report uploading in the individual prediagnosis tasks [6] , as illustrated in Figure 6. In terms of "waiting", there are merely queuing delays for the later tasks due to the FIFS nature.…”

“…Benefiting from the increased network utilization, correspondingly, large-size data transmissions will be more energy efficient [45]. An opposite use case is to use managed buffering to avoid network congestion and improve transmission reliability when many source nodes attempt to send data simultaneously [5,6]. In addition, buffering data and lowering transmission frequency have been advocated to decrease the power usage and maximize the lifetime of source nodes [13,26].…”

Congestion avoidance in multi sink wireless sensor networks using NS2

“…The paper [7] provides buffer-based congestion avoidance. That is, any sensor node sends packet to another sensor node only when that node has buffer space to hold the data.…”

Energy-Efficient and Traffic-Dispersive Event Contour Tracking in Multi-sink Wireless Sensor Networks

“…Because the sink node is a unique and common end point of data flow for sensors, the region near the sink node has a high possibility to get congested. There are several transport control protocols designed for WSNs for congestion control and end-to-end reliability [11,12,13]. However, these traditional congestion control schemes have weaknesses such as heavy control overhead and/or ineligible latency.…”

“…The momentarily heavy traffic could cause the congestion problem, especially around the sink node. Some congestion control or congestion avoidance schemes [11,12,13] should be adopted to solve the problem. However, these schemes have the weaknesses of heavy control overheads and/or unnegligible data reporting delay.…”