Constructing Schedules for Time-Critical Data Delivery in Wireless Sensor Networks

Abstract

BraunschweigWireless sensor networks for industrial process monitoring and control require highly reliable and timely data delivery. To match performance requirements specialised schedule based medium access control (MAC) protocols are employed. In order to construct an efficient system it is necessary to find a schedule that can support the given application requirements in terms of data delivery latency and reliability. Furthermore, additional requirements such as transmission power may have to be taken into account when constructing the schedule. In this paper we show how such schedule can be constructed. We describe methods and tools to collect the data necessary as input for schedule calculation. Moreover, due to the high complexity of schedule calculation, we also introduce a heuristic. We evaluate the proposed methods in a real-world process automation and control application deployed in an oil refinery and further present a long-term experiment in an office environment. Additionally, we discuss a framework for schedule life-cycle management.

Real-Time Scheduling for Event-Triggered and Time-Triggered Flows in Industrial Wireless Sensor-Actuator Networks

“…The work in [7] proves that the scheduling problem of WSANs is NP-hard, and then derives a strong necessary condition for schedulability. After that, to improve the realtime performance of WSANs, many centralized scheduling algorithms are proposed, such as assigning fixed priorities [8], [9], assigning segmented slots [10], eliminating bottleneck [11], and addressing spatial re-use [12]. However, these centralized algorithms assign communication resources only to time-triggered packets.…”

Orchestra

“…As a benchmark, we implement a simple offline scheduler inspired by the work of Pöttner et al [28]. The scheduler takes PRR measurements for every link as input, computes their routing metric -it uses squared ETX, as in Orchestra, to favor good links -and uses Dijkstra to compute the shortest path from each node to the sink.…”

“…The schedule is injected into the network and continuously updated throughout the lifetime of the network [18]. In static networks with predictable traffic patterns, commercial TSCH-like networks such as WirelessHART or SmartMesh IP [36] offer very high reliability (published results include 99.999% on a 49 node industrial deployment [8], 99.95% on a 15-node testbed [28]), and a decade of battery lifetime [39]. Note that the centralized scheduling algorithms are not part of the standards and much attention has been given to scheduling theory in the context of TSCH networks [27,30,31,44].…”

“…With end-to-end reliability, losses trigger costly re-transmissions which often come in burst and result in jittery performance. At the other end of the spectrum, deterministic networks running TDMA and scheduled traffic can achieve 2 or 3 orders of magnitude fewer losses (i.e., up to one loss per 10.000 packets or more) [8,2,37,12,28]. We investigate how to achieve such high level of reliability in non-deterministic scenarios.…”

Implementation and Experimentation of Industrial Wireless Sensor-Actuator Network Protocols

“…Munir et al [10] designed a scheduling algorithm that produces latency bounds of the real-time periodic streams and accounts for both link bursts and interference. Pottner et al [11] designed a scheduling algorithm to meet application requirements in terms of data delivery latency, reliability, and transmission power. While valuable insights can be drawn from the aforementioned effort, the novelty of our work lies in its focus on key aspects of the WirelessHART standard such as graph routing that was not studied in earlier work.…”