A Primal-Dual Algorithmic Aspect of Link Scheduling in Dynamic Wireless Networks

In this paper, we consider a primal-dual algorithmic aspect of the link scheduling problem in dynamic wireless networks, where the channel characteristics are dramatically time-varying that could render state-of-the-art link scheduling mechanisms computational expensive to fit network dynamics. Building upon the optimality condition of treating interference as noise, we formulate link scheduling as a maximum weighted clique problem on a coexisting graph, which can be transformed into a minimum weighted vertex coloring problem (MWVCP) through the primal-dual technique. With an adversarial perturbation modeling of network dynamics with edge insertion/deletion, we propose dynamic graph algorithms to solve the MWVCP for chordal graph classes with theoretical guarantees on algorithmic feasibility, optimality, and updating complexity. It is expected the resulting link scheduling mechanism could shed light on robust, scalable, and certifiable system designs in dynamic wireless networks from the algorithmic perspective.