Energy-Efficient Cooperative Routing in Wireless Sensor Networks: A Mixed-Integer Optimization Framework and Explicit Solution

• Published in: IEEE transactions on communications 2013-08, Vol.61 (8), p.3424-3437
• Main Authors: Habibi, J., Ghrayeb, A., Aghdam, A. G.
• Format: Article
• Language: English
• Subjects: Applied sciences; Broadcasting; Broadcasting. Videocommunications. Audiovisual; Computer networks; cooperative routing; Detection, estimation, filtering, equalization, prediction; energy efficiency; Exact sciences and technology; explicit solution; Information, signal and communications theory; Lead; Mathematical analysis; Mathematical models; Miscellaneous; mixed-integer optimization; multi-parametric programming; Optimization; Relay; relay selection; Relays; Remote sensors; Routing; Routing (telecommunications); Services and terminals of telecommunications; Signal and communications theory; Signal to noise ratio; Signal, noise; Studies; Systems, networks and services of telecommunications; Telecommunications; Telecommunications and information theory; Telemetry. Remote supervision. Telewarning. Remote control; Transmission and modulation (techniques and equipments); Wireless networks; Wireless sensor networks
• ISSN: 0090-6778; 1558-0857
• DOI: 10.1109/TCOMM.2013.070213.120570

This paper presents an optimization framework for a wireless sensor network whereby, in a given route, the optimal relay selection and power allocation are performed subject to signal-to-noise ratio constraints. The proposed approach determines whether a direct transmission is preferred for a given configuration of nodes, or a cooperative transmission. In the latter case, for each node, data transmission to the destination node is performed in two consecutive phases: broadcasting and relaying. The proposed strategy provides the best set of relays, the optimal broadcasting power and the optimal power values for the cooperative transmission phase. Once the minimum-energy transmission policy is obtained, the optimal routes from every node to a sink node are built-up using cooperative transmission blocks. We also present a low-complexity implementation approach of the proposed framework and provide an explicit solution to the optimization problem at hand by invoking the theory of multi-parametric programming. This technique provides the optimal solution as a function of measurable parameters in an off-line manner, and hence the on-line computational tasks are reduced to finding the parameters and evaluating simple functions. The proposed efficient approach has many potential applications in real-world problems and, to the best of the authors' knowledge, it has not been applied to communication problems before. Simulations are presented to demonstrate the efficacy of the approach.