Communication system design for wireless networked control systems (WNCSs) requires strict timing, reliability and lifetime guarantees despite limited battery resources and the non-idealities introduced by wireless networking such as delays. In this paper, we introduce radio frequency (RF) energy harvesting paradigm into WNCS framework for the first time in the literature. We study the optimal power control, energy harvesting and scheduling problem with the objective of providing maximum level of adaptivity under periodicity, delay and reliability requirements. We show that the power allocation problem is separable from the scheduling problem at optimality and provide the exact expression for optimal power control. The scheduling problem is then formulated as a mixed integer linear programming (MILP) problem and proven to be NP-Hard. For the scheduling, we propose polynomial-time heuristic algorithms motivated by the analogy between scheduling sensor nodes with energy harvesting requirements over time units and jobs with sequence dependent setup times on identical machines. We prove the theoretical worst-case bound for the performance of these heuristics. We show via extensive simulations that the proposed algorithms perform close-to-optimal and significantly better than Earliest Deadline First (EDF) algorithm in terms of adaptivity, delay, reliability and average runtime.

The dramatic growth of machine-to-machine (M2M) communication in cellular networks brings the challenge of satisfying the quality of service (QoS) requirements of a large number of M2M devices with limited radio resources. In this paper, we propose an optimization framework for the semi-persistent scheduling of M2M transmissions based on the exploitation of their periodicity with the goal of reducing the overhead of the signaling required for connection initiation and scheduling. The goal of the optimization problem is to minimize the number of frequency bands used by the M2M devices to allow fair resource allocation of newly joining M2M and human-to-human communications. The constraints of the problem are delay and periodicity requirements of the M2M devices. We first prove that the optimization problem is NP-hard and then propose a polynomial-time heuristic algorithm employing a fixed priority assignment according to the QoS characteristics of the devices. We show that this heuristic algorithm provides an asymptotic approximation ratio of 2.33 to the optimal solution for the case where the delay tolerances of the devices are equal to their periods. Through extensive simulations, we demonstrate that the proposed algorithm performs better than the existing algorithms in terms of frequency band usage and schedulability.