Tremendous traffic demands for ubiquitous access and emerging multimedia applications significantly increase the energy consumption of battery-powered mobile devices. This trend leads to that energy efficiency (EE) becomes an essential aspect of mobile ad hoc networks (MANETs). In this paper, we explore EE optimization as measured in bits per Joule for MANETs based on the cross-layer design paradigm. We model this problem as a nonconvex mixed integer nonlinear programming (MINLP) formulation by jointly considering routing, traffic scheduling, and power control. Because the nonconvex MINLP problem is NP-hard in general, it is exceedingly difficult to globally optimize this problem. We, therefore, devise a customized branch and bound (BB) algorithm to efficiently solve this globally optimal problem. The novelties of our proposed BB algorithm include upper and lower bounding schemes and branching rule that are designed using the characteristics of the nonconvex MINLP problem. We demonstrate the efficiency of our proposed BB algorithm by offering numerical comparisons with a reference algorithm that uses the relaxation manners proposed in -. Numerical results show that our proposed BB algorithm scheme, respectively, decreases the optimality gap 81.98% and increases the best feasible solution 32.79% compared with the reference algorithm. Furthermore, our results not only provide insights into the design of EE maximization algorithms for MANETs by employing cooperations between different layers but also serve as performance benchmarks for distributed protocols developed for real-world applications.
All Science Journal Classification (ASJC) codes
- Computer Science(all)
- Materials Science(all)