A study of overheads and accuracy for efficient monitoring of wireless mesh networks.

Graduate Group in Computer Science, University of California Davis, Davis, CA 95616, United States
Pervasive and Mobile Computing 01/2010; 6:93-111. DOI: 10.1016/j.pmcj.2009.07.011
Source: DBLP

ABSTRACT IEEE 802.11-based wireless mesh networks are being increasingly deployed in enterprize and municipal settings. A lot of work has been done on developing measurement-based schemes for resource provisioning and fault management in these networks. The above goals require an efficient monitoring infrastructure to be deployed, which can provide the maximum amount of information regarding the network status, while utilizing the least possible amount of network resources. However, network monitoring involves overheads, which can adversely impact performance from the perspective of the end user. The impact of monitoring overheads on data traffic has been overlooked in most of the previous works. It remains unclear as to how parameters such as number of monitoring agents, or frequency of reporting monitoring data, among others, impact the performance of a wireless network. In this work, we first evaluate the impact of monitoring overheads on data traffic, and show that even small amounts of overhead can cause a large degradation in the network performance. We then explore several different techniques for reducing monitoring overheads, while maintaining the objective (resource provisioning, fault management, and others) that needs to be achieved. Via extensive simulations and experiments, we validate the efficiency of our proposed approaches in reducing overheads, their impact on the quality of data collected from the network, and the impact they have on the performance of the applications using the collected data. Based on results, we conclude that it is feasible to make the current monitoring techniques more efficient by reducing the communication overheads involved while still achieving the desired application-layer objectives.

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    ABSTRACT: In large scale deployments of Wireless Mesh Networks (WMNs), access to the Internet is ensured by multiple gateways spread over the network. In such environments that rely on heterogeneous backhaul technologies offering different and time-varying bandwidth, delay or jitter characteristics, monitoring the end-to-end performances on the diversity of paths Internet flows can be forwarded on is challenging: the end-to-end measurement strategy must capture the diversity of backhaul connections, as well as multi-hop behavior within the mesh, and it must scale with the number of gateways, nodes and flows. In this paper we propose and evaluate the scalability of two measurement strategies for the monitoring of end-to-end paths. We establish closed form formulas for the overhead incurred by these measurement strategies, and compare their efficiency against greedy measurements in grid topologies. We conclude that one can reach linear increase in the number of probing nodes in place of an exponential growth for greedy end-to-end measurements. We extend these results to also show that this strategy takes advantage of dense topologies.
    Proceedings of the 8h ACM symposium on QoS and security for wireless and mobile networks; 10/2012


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