Distributed Dynamic Packet Scheduling Framework for Handling Disturbances in Real-Time Wireless Networks

Abstract

Real-time wireless networks (RTWNs) are fundamental to many Internet-of-Things (IoT) applications. RTWNs typically apply time-division multiple access (TDMA)-based media access control mechanisms and often demand deterministic end-to-end packet delivery to meet the given quality of service (QoS) requirements. Packet scheduling in an RTWN thus plays a critical role for achieving the desired performance but is a challenging problem especially when the RTWN is large and must deal with multiple disturbances (i.e., unexpected events causing abrupt workload changes associated with certain sensing tasks) occurring concurrently. This paper introduces a novel distributed dynamic packet scheduling framework, D $^2$2-PaS. D $^2$2-PaS is capable of processing disturbances and minimizes the number of dropped packets while ensuring that all critical events due to disturbances are handled by their deadlines. As a distributed approach, D $^2$2-PaS constructs schedules locally at individual nodes, which significantly reduces the amount of schedule-related information to be broadcast by the gateway. As a dynamic approach, D $^2$2-PaS applies a lightweight packet dropping algorithm to determine on-line at the gateway which packets can be dropped in response to disturbances and disseminate this information to the network. D $^2$2-PaS has been implemented on a multi-hop RTWN testbed to validate its applicability on hardware and a popular RTWN stack. Both testbed measurements and extensive simulation results demonstrate the effectiveness of D $^2$2-PaS.