Hard-Real-Time Routing in Probabilistic Graphs to Minimize Expected Delay

Document Type

Conference Proceeding

Publication Date

12-1-2020

Abstract

This work studies the hard-real-time routing problem in graphs: one needs to travel from a given vertex to another within a hard deadline. For each edge in the network, the worst-case delay that may be encountered across that edge is bounded. As far as this given bound is trustworthy at a very high level of assurance, it must be guaranteed that one will meet the specified deadline. The actual delays across edges are uncertain and the goal is to minimize the total expected delay while meeting the deadline. We propose a comprehensive solution to this problem. Specifically, if the precise a priori estimates of the delay probability distributions are available, we develop an optimal table-driven algorithm that identifies the route with the minimum expected delay. If those estimates are not precise (i.e., unknown or dynamic), we develop an efficient Q-Learning approach that leverages the table-driven algorithm to track the true distributions rapidly, while ensuring to meet the specified hard deadline. The proposed solution suggests a promising direction towards incorporating probabilistic information and learning-based approaches into safety-critical systems without compromising safety guarantees, when it is not feasible to establish the trustworthiness of the probabilistic information at the high assurance levels required for verification purposes.

Identifier

85101977776 (Scopus)

ISBN

[9781728183244]

Publication Title

Proceedings Real Time Systems Symposium

External Full Text Location

https://doi.org/10.1109/RTSS49844.2020.00017

ISSN

10528725

First Page

63

Last Page

75

Volume

2020-December

Grant

1850851

Fund Ref

National Science Foundation

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