End-to-End Reliability-aware Scheduling for Wireless Sensor Networks

TL;DR

This paper introduces SchedEx, a fast heuristic extension for reliability-aware scheduling in wireless sensor networks, providing guaranteed end-to-end reliability with significantly improved scalability over existing methods.

Contribution

SchedEx is a novel heuristic scheduling extension that guarantees user-defined reliability and outperforms existing Incrementer methods in speed and reliability distribution.

Findings

SchedEx is over ten times faster than the Incrementer.

SchedEx guarantees reliability more effectively under higher reliability demands.

SchedEx improves scheduling algorithm performance more evenly across different algorithms.

Abstract

Wireless Sensor Networks (WSN) are gaining popularity as a flexible and economical alternative to field-bus installations for monitoring and control applications. For mission-critical applications, communication networks must provide end-to-end reliability guarantees, posing substantial challenges for WSN. Reliability can be improved by redundancy, and is often addressed on the MAC layer by re-submission of lost packets, usually applying slotted scheduling. Recently, researchers have proposed a strategy to optimally improve the reliability of a given schedule by repeating the most rewarding slots in a schedule incrementally until a deadline. This Incrementer can be used with most scheduling algorithms but has scalability issues which narrows its usability to offline calculations of schedules, for networks that are rather static. In this paper, we introduce SchedEx, a generic heuristic scheduling algorithm extension which guarantees a user-defined end-to-end reliability. SchedEx produces competitive schedules to the existing approach, and it does that consistently more than an order of magnitude faster. The harsher the end-to-end reliability demand of the network, the better SchedEx performs compared to the Incrementer. We further show that SchedEx has a more evenly distributed improvement impact on the scheduling algorithms, whereas the Incrementer favors schedules created by certain scheduling algorithms.