Optimal Energy-Efficient Regular Delivery of Packets in Cyber-Physical Systems

TL;DR

This paper develops energy-efficient scheduling policies for regular packet delivery in cyber-physical systems, balancing energy use and delivery regularity using Markov Decision Processes and Whittle Index policies, with proven asymptotic optimality.

Contribution

It introduces a novel approach combining MDP and restless bandit models to optimize packet delivery and energy efficiency, deriving Whittle indexes and proving asymptotic optimality.

Findings

Whittle Index policy is indexable and derived.

The policy is asymptotically optimal.

Extensive simulations validate the approach.

Abstract

In cyber-physical systems such as in-vehicle wireless sensor networks, a large number of sensor nodes continually generate measurements that should be received by other nodes such as actuators in a regular fashion. Meanwhile, energy-efficiency is also important in wireless sensor networks. Motivated by these, we develop scheduling policies which are energy efficient and simultaneously maintain "regular" deliveries of packets. A tradeoff parameter is introduced to balance these two conflicting objectives. We employ a Markov Decision Process (MDP) model where the state of each client is the time-since-last-delivery of its packet, and reduce it into an equivalent finite-state MDP problem. Although this equivalent problem can be solved by standard dynamic programming techniques, it suffers from a high-computational complexity. Thus we further pose the problem as a restless multi-armed bandit problem and employ the low-complexity Whittle Index policy. It is shown that this problem is indexable and the Whittle indexes are derived. Also, we prove the Whittle Index policy is asymptotically optimal and validate its optimality via extensive simulations.