Spreading the load in a tree type routing structure
|Title:||Spreading the load in a tree type routing structure||Authors:||Delaney, Declan T.
O'Hare, G. M. P. (Greg M. P.)
|Permanent link:||http://hdl.handle.net/10197/7209||Date:||2-Aug-2013||Abstract:||Many routing protocols have advanced the Wire- less Sensor Network (WSN) paradigm with each new method offering unique ways to maximise Quality of Service (QoS) while minimising energy cost to the network. Tree routing is a well examined method with a proven record in offering a high level of service with trees constructed to fulfil a particular routing objective defined by a chosen metric. The tree structure can be maintained with low overall network overhead but exhibits a weakness with regard to load balancing. Without effective load balancing particular nodes in the network may be subject to excessive network load, leading to uneven energy consumption in the network. This in turn can lead to an unwanted scenario of premature node failure. Neighbourhood metrics is presented in this paper as a means to preserve network objectives while achieving improved load distribution in a tree type routing structure. Neighbourhood metrics offer a framework for expand- ing on currently used metrics to include information on the quality of a nodes neighbourhood in addition to the current forwarding route. Neighbourhood metrics is compared to the current state of the art in the form of the Routing Protocol for Low Power and Lossy Networks (RPL) implementation using the direct Expected Transmissions (ETX) metric. Neighbourhood metrics exhibits improved load distribution in a number of open public testbeds.||Funding Details:||Science Foundation Ireland||Type of material:||Conference Publication||Publisher:||IEEE||Copyright (published version):||2013 IEEE||Keywords:||WSN;Routing;Load balancing;Metric||DOI:||10.1109/ICCCN.2013.6614196||Language:||en||Status of Item:||Peer reviewed||Conference Details:||2013 22nd International Conference on Computer Communications and Networks (ICCCN), Nassau, Bahamas, 30 July - 2 August, 2013|
|Appears in Collections:||CLARITY Research Collection|
Computer Science Research Collection
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