State-Aware Resource Allocation for Wireless Closed-Loop Control Based on Multi-Connectivity

Scheuvens, Lucas; Schulz, Philipp; Hößler, Tom; Franchi, Norman; Barreto, André Noll; Fettweis, Gerhard

doi:10.1109/globecom42002.2020.9348069

Cited by 4 publications

(2 citation statements)

References 16 publications

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“…The dynamic resource allocation of SARA can improve the control application's MTTF by orders of magnitude compared with the static multi-connectivity baseline, while simultaneously keeping the average channel consumption low, as we have previously shown in [60]. Tab.…”

Section: Resultsmentioning

confidence: 54%

“…However, in general it was observed that SARA schemes featuring a low number of channels in the first states and a large number of channels in high states (increasingly many parallel channels for increasing SUA) exhibit a good MTTF ↔ f τ ↔ l trade-off, making it decreasingly likely for packet losses to occur consecutively the longer the current number of consecutive packet losses is. This enables to significantly increase the MTTF while keeping l low [60].…”

Section: State-aware Resource Allocationmentioning

confidence: 99%

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State-Aware Resource Allocation for Wireless Closed-Loop Control Systems

Scheuvens

Hobler

Schulz

et al. 2021

IEEE Trans. Commun.

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Wireless closed-loop control is of major significance for future industrial manufacturing. However, control applications pose stringent quality of service requirements for reliable operation. Contrary to traditional ultra-reliable low-latency communications design goals such as low packet loss rates and low latency, research results in the domain of networked control systems (NCS) state that depending on the sampling period, control applications inherently tolerate a few consecutive packet losses. This translates into a better-suited metric to capture control application requirements and therefore a more conclusive design goal for wireless networks: ensuring a maximum age of information (AoI). With a Markov modeling approach, we propose to exploit the tolerance through a novel dynamic multiconnectivity scheme that we term state-aware resource allocation (SARA), which temporally negatively correlates packet losses, thus avoiding long packet loss sequences. Through statistical multiplexing, SARA enables a mean time to failure (MTTF) in the order of years while keeping the per-agent average channel usage close to one, also in a multi-agent setting with competition for resources. Compared with static dual-connectivity, the MTTF can be increased 100-fold whereas the number of required channels reduces by 40%. Our approach also statistically guarantees system-wide AoI distributions, which aid to ensure control performance.

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Section: Resultsmentioning

confidence: 54%

Section: State-aware Resource Allocationmentioning

confidence: 99%