Abstract
Connectivity is a fundamental issue in research on wireless sensor networks. However, unreliable and asymmetric links have a great impact on the global quality of connectivity (QoC). By assuming the deployment of nodes a homogeneous Poisson point process and eliminating the border effect, this paper derives an explicit expression of node non-isolation probability as the upper bound of one-connectivity, based on an analytical link model which incorporates important parameters such as path loss exponent, shadowing variance of channel, modulation, encoding method etc. The derivation has built a bridge over the local link property and the global network connectivity, which makes it clear to see how various parameter impact the QoC. Numerical results obtained further confirm the analysis and can be used as reference for practical design and simulation of wireless ad hoc and sensor networks. Besides, we find giant component size a good relaxed measure of connectivity in some applications that do not require full connectivity.
Highlights
Introduction and MotivationConsiderable studies have discussed the issues such as the capacity [1] and multi-hop routing [2,3,4]in wireless ad hoc and sensor networks, among which connectivity is a fundamental property to be preserved and provides design reference for upper-layer protocols
We have presented an analytical procedure of calculating the node non-isolation probability based on a generalized radio link model in wireless sensor networks
The non-isolation probability is the upper bound of one-connectivity probability
Summary
Considerable studies have discussed the issues such as the capacity [1] and multi-hop routing [2,3,4]. In wireless ad hoc and sensor networks, among which connectivity is a fundamental property to be preserved and provides design reference for upper-layer protocols. The real low-power wireless links are unreliable and asymmetric, suffering from severe propagation impairments such as path loss, multi-path fading and shadowing, which have great impact on the global QoC. Important to our work is the contribution in [9], studying the node isolation probability, from which, under the assumption of dense networks, an approximation of one-connectivity probability can be obtained.
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