Constructing low-connectivity and full-coverage three dimensional sensor networks
IEEE Journal on Selected Areas in Communications - Special issue on simple wireless sensor networking solutions
Barrier coverage with sensors of limited mobility
Proceedings of the eleventh ACM international symposium on Mobile ad hoc networking and computing
Review: From wireless sensor networks towards cyber physical systems
Pervasive and Mobile Computing
Energy-efficient optical acquisition schemes in wireless sensor networks
Wireless Networks
International Journal of Information and Computer Security
Hi-index | 0.00 |
Although most of the studies on coverage and connectivity in wireless sensor networks (WSNs) considered two-dimensional (2D) settings, such networks can in reality be accurately modeled in a three-dimensional (3D) space. The concepts of continuum percolation theory best fit the problem of connectivity in WSNs to find out whether the network provides long-distance multihop communication. In this paper, we focus on percolation in coverage and connectivity in 3D WSNs. We say that the network exhibits a coverage percolation (respectively, connectivity percolation) when a giant covered region (respectively, giant connected component) almost surely spans the entire network for the first time. Because of the dependency between coverage and connectivity, the problem is not only a continuum percolation problem but also an integrated continuum percolation problem. Thus, we propose an integrated-concentric-sphere model to address coverage and connectivity in 3D WSNs in an integrated way. First, we compute the critical density \lambda_{c}^{\rm cov} above which coverage percolation in 3D WSNs will almost surely occur. Second, we compute the critical density \lambda_{c}^{con} above which connectivity percolation in 3D WSNs will almost surely occur. Third, we compute the critical density \lambda_{c}^{{\rm cov}{-}con} above which both coverage and connectivity percolation in 3D WSNs will almost surely occur. For each of these three problems, we also compute their corresponding critical network degree. Our results can be helpful in the design of energy-efficient topology control protocols for 3D WSNs in terms of coverage and connectivity.