Computing Time-varying Network Reliability using Binary Decision Diagrams

2025-04-02

AI Summary

Computing reliability in time-varying networks (e.g., space networks, vehicular ad hoc networks, UAV networks)—specifically, the probability that a strictly time-respecting path (journey) exists from source to destination with all links operational—has traditionally relied on explicit enumeration of all journeys and inclusion–exclusion or disjoint products, resulting in exponential complexity. Method: This paper introduces Binary Decision Diagrams (BDDs) to this problem for the first time, enabling compact encoding of journey structures and efficient probabilistic inference without explicit journey enumeration. Contribution/Results: We present the first exact, scalable algorithm for time-respecting reliability computation under temporal graph models. Experimental evaluation demonstrates speedups of up to four orders of magnitude over state-of-the-art methods, enabling real-time reliability assessment on large-scale, sparse temporal networks.

Technology Category

• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Reasoning under Uncertainty: Relational Probabilistic Models
• Knowledge Representation and Reasoning: Computational Complexity of Reasoning

Application Category

• Graph Algorithms and Modeling for the Web: Algorithms and analysis for heterogeneous, signed, attributed, multi-relational, temporal, higher-order, and annotated Web-related graphs
• Web Mining and Content Analysis: Web data provenance, reliability, and authenticity
• Responsible Web: Human-perceived consequences of algorithmic deployment on the web

Abstract

Computing the reliability of a time-varying network, taking into account its dynamic nature, is crucial for networks that change over time, such as space networks, vehicular ad-hoc networks, and drone networks. These networks are modeled using temporal graphs, in which each edge is labeled with a time indicating its existence at a specific point in time. The time-varying network reliability is defined as the probability that a data packet from the source vertex can reach the terminal vertex, following links with increasing time labels (i.e., a journey), while taking into account the possibility of network link failures. Currently, the existing method for calculating this reliability involves explicitly enumerating all possible journeys between the source and terminal vertices and then calculating the reliability using the sum of disjoint products method. However, this method has high computational complexity. In contrast, there is an efficient algorithm that uses binary decision diagrams (BDDs) to evaluate the reliability of a network whose topology does not change over time. This paper presents an efficient exact algorithm that utilizes BDDs for computing the time-varying network reliability. Experimental results show that the proposed method runs faster than the existing method up to four orders of magnitude.

Problem

• Computing reliability of dynamic networks efficiently
• Reducing high complexity in journey enumeration methods
• Applying BDDs to time-varying network reliability analysis

Innovation

• Uses Binary Decision Diagrams (BDDs)
• Computes time-varying network reliability
• Improves speed by four orders