Abstract: Reprogramming (i.e.code dissemination) is one of the key technologies to enable software update in wireless sensor networks.Traditional code dissemination protocols are evaluated for performance comparisons by simulations and testbed experiments.Recently,the analytical model was proposed to characterize software update and evaluate performance of state-of-the-art code dissemination protocols because the analytical model is both lightweight and accurate for performance evaluation in large scale networks.However,the analytical model depends on estimation of network-wide link quality.The methods used to calculate network-wide link quality in previous analytical models ignore local characteristics in software update,thus the calculated network-wide link qualities are not scalable in different topologies of networks and are not accurate enough.By this observation,a novel method with local characteristics for estimation of network-wide link quality was proposed,which takes the averaged expectation of link qualities of neighborhood nodes from any node as local link quality for that node.Therefore,the proposed method an reflect network-wide software update accurately.When taking the estimated network-wide link quality of this proposed method as input for the analytical model to predict the performance of reprogramming,i.e.completion time of software update,the analytical results match that of testbed experiments with high accuracy.The prediction error of the analytical results is below 5% in linearand grid networks.Therefore,the proposed method is robust and adaptive in both linear and grid networks,compared with existing methods for estimating network-wide link quality.

Key words: Wireless sensor networks,Network link quality,Local characteristics,Software update,Reprogramming