Abstract-Wireless sensor-actuator networks are gaining ground as the communication infrastructure for process monitoring and control. Industrial applications demand a high degree of reliability and real-time guarantees in communication. Because wireless communication is susceptible to transmission failures in industrial environments, industrial wireless standards such as WirelessHART adopt reliable graph routing to handle transmission failures through retransmissions and route diversity. While these mechanisms are critical for reliable communication, they introduce substantial challenges in analyzing the schedulability of real-time flows. This paper presents the first worst-case endto-end delay analysis for periodic real-time flows under reliable graph routing. The proposed analysis can be used to quickly assess the schedulability of real-time flows with stringent requirements on both reliability and latency. We have evaluated our schedulability analysis against experimental results on a wireless testbed of 69 nodes as well as simulations. Both experimental results and simulations show that our delay bounds are safe and enable effective schedulability tests under reliable graph routing.
Abstract-Industry is adopting Wireless Sensor-Actuator Networks (WSANs) as the communication infrastructure for process control applications. To meet the stringent real-time performance requirements of control systems, there is a critical need for fast end-to-end delay analysis for real-time flows that can be used for online admission control. This paper presents a new endto-end delay analysis for periodic flows whose transmissions are scheduled based on the Earliest Deadline First (EDF) policy. Our analysis comprises novel techniques to bound the communication delays caused by channel contention and transmission conflicts in a WSAN. Furthermore, we propose a technique to reduce the pessimism in admission control by iteratively tightening the delay bounds for flows with short deadlines. Experiments on a WSAN testbed and simulations demonstrate the effectiveness of our analysis for online admission control of real-time flows.
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