Connectivity Restoration in Wireless Sensor Networks via Space Network Coding
AbstractThe problem of finding the number and optimal positions of relay nodes for restoring the network connectivity in partitioned Wireless Sensor Networks (WSNs) is Non-deterministic Polynomial-time hard (NP-hard) and thus heuristic methods are preferred to solve it. This paper proposes a novel polynomial time heuristic algorithm, namely, Relay Placement using Space Network Coding (RPSNC), to solve this problem, where Space Network Coding, also called Space Information Flow (SIF), is a new research paradigm that studies network coding in Euclidean space, in which extra relay nodes can be introduced to reduce the cost of communication. Unlike contemporary schemes that are often based on Minimum Spanning Tree (MST), Euclidean Steiner Minimal Tree (ESMT) or a combination of MST with ESMT, RPSNC is a new min-cost multicast space network coding approach that combines Delaunay triangulation and non-uniform partitioning techniques for generating a number of candidate relay nodes, and then linear programming is applied for choosing the optimal relay nodes and computing their connection links with terminals. Subsequently, an equilibrium method is used to refine the locations of the optimal relay nodes, by moving them to balanced positions. RPSNC can adapt to any density distribution of relay nodes and terminals, as well as any density distribution of terminals. The performance and complexity of RPSNC are analyzed and its performance is validated through simulation experiments. View Full-Text
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Uwitonze, A.; Huang, J.; Ye, Y.; Cheng, W. Connectivity Restoration in Wireless Sensor Networks via Space Network Coding. Sensors 2017, 17, 902.
Uwitonze A, Huang J, Ye Y, Cheng W. Connectivity Restoration in Wireless Sensor Networks via Space Network Coding. Sensors. 2017; 17(4):902.Chicago/Turabian Style
Uwitonze, Alfred; Huang, Jiaqing; Ye, Yuanqing; Cheng, Wenqing. 2017. "Connectivity Restoration in Wireless Sensor Networks via Space Network Coding." Sensors 17, no. 4: 902.