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WARP: On-the-fly Program Synthesis for Agile, Real-time, and Reliable Wireless Networks
Conference proceeding   Open access

WARP: On-the-fly Program Synthesis for Agile, Real-time, and Reliable Wireless Networks

Ryan Brummet, Md Kowsar Hossain, Octav Chipara, Ted Herman and Steve Goddard
IPSN'21: PROCEEDINGS OF THE 20TH ACM/IEEE CONFERENCE ON INFORMATION PROCESSING IN SENSOR NETWORKS, pp.254-267
IPSN '21: The 20th International Conference on Information Processing in Sensor Networks (05/18/2021–05/21/2021)
01/01/2021
DOI: 10.1145/3412382.3458270
Appears in  UI Libraries Support Open Access
url
https://doi.org/10.1145/3412382.3458270View
Published (Version of record) Open Access

Abstract

Emerging Industrial Internet-of-Things systems require wireless solutions to connect sensors, actuators, and controllers as part of high data rate feedback-control loops over real-time flows. A key challenge is to provide predictable performance and agility in response to fluctuations in link quality, variable workloads, and topology changes. We propose WARP to address this challenge. WARP uses programs to specify a network's behavior and includes a synthesis procedure to automatically generate such programs from a high-level specification of the system's workload and topology. WARP has three unique features: (1) WARP uses a domain-specific language to specify stateful programs that include conditional statements to control when a flow's packets are transmitted. The execution paths of programs depend on the pattern of packet losses observed at run-time, thereby enabling WARP to readily adapt to packet losses due to short-term variations in link quality. (2) Our synthesis technique uses heuristics to improve network performance by considering multiple packet loss patterns and associated execution paths when determining the transmissions performed by nodes. Furthermore, the generated programs ensure that the likelihood of a flow delivering its packets by its deadline exceeds a user-specified threshold. (3) WARP can adapt toworkload and topology changes without explicitly reconstructing a network's program based on the observation that nodes can independently synthesize the same program when they share the same workload and topology information. Simulations show that WARP improves network throughput for data collection, dissemination, and mixed workloads on two realistic topologies. Testbed experiments show that WARP reduces the time to add new flows by 5 times over a state-of-the-art centralized control plane and guarantees the real-time and reliability of all flows.
 Computer Science Engineering Technology Telecommunications Computer Science, Information Systems Engineering, Electrical & Electronic Science & Technology UIOWA OA Agreement

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