InterJournal Complex Systems, 1823 Status: Accepted |
Manuscript Number: [1823] Submission Date: 2006 |
Obtaining Robust Wireless Sensor Networks through Self-Organization of Heterogenous Connectivity |
Subject(s): CX.6
Category:
Abstract:
Wireless sensor networks with randomly deployed nodes are becoming increasingly viable for several applications including environmental monitoring and battlefield awareness. With advances in miniaturization and wireless technology, networks with very large numbers of nodes will soon be possible. The nodes in these networks communicate wirelessly, with a node’s transmission power determining the range — or radius — over which it can be heard. So far, most models for wireless sensor networks have used homogeneous nodes, i.e., nodes with identical communication range. In an isotropic environment, these networks have symmetric connectivity, which makes them easier to analyze using percolation models. It is well-known that heterogeneous networks, where each node can customize its transmission radius, potentially provide many advantages, including longer lifetimes, lower congestion and greater robustness. However, devising algorithms for such reconfiguration has proved to be difficult. Scalability requires that any configuration process be completely distributed and use only local information, which presents the classic problem confronting all self-organized systems: How to obtain global optimality from local adaptation. In this paper, we present a heuristic for the self-organization of heterogeneous networks with the explicit goal of producing robust networks that minimize energy consumption. We consider a network model where each node can have one of two or three transmission radii. After deployment, nodes collect information on their spatial neighbors through localized communication and each node then makes an autonomous decision to choose one of the transmission radius values. The resulting networks are analyzed for robustness, congestion and average inverse shortest path length (AISPL), and are compared with homogeneous percolating networks. The results show that the heuristic is both effective and efficient: the self-organized networks significantly surpass the homogeneous networks on all measures while using less energy. From simulation results for networks with 200 to 1000 nodes, the following improvements in performance have been achieved: reduction in congestion by 8-12%, reduction in mean radius by 6-8% and an increase in average inverse short path length by 8-20%. Significantly, the networks remain robust even with as much as 35% random node failure while achieving the above improvements in performance. The networks obtained through the heuristic are also compared structurally with homogeneous networks to elucidate general attributes of robust networks.
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