Rethinking LEO Constellations Routing with the Unsplittable Multi-Commodity Flows Problem

Abstract

This study investigates the performance of an innovative routing protocol inspired by the Unsplittable Multi-Commodity Flow (UMCF) problem. LEO routing schemes are often based on Shortest Path (SP) algorithms, the Floyd-Warshall algorithm is usually chosen to compute these network paths within the constellation and their end-toend latency. Instead of considering latency as a criterion, we seek to optimize the overall amount of IP traffic crossing the constellation. This criterion can be optimized by considering the Unsplittable Multi Commodity Flow problem associated with the system. To solve this problem, we use a heuristic algorithm based on randomized rounding that was shown to return solutions of good quality of the Unsplittable Multi Commodity Flow problem in the optimization literature. Using network simulation over Telesat constellation, we show this proposal significantly reduces the overall congestion level compared to the standard SP routing schemes.

Rethinking LEO Mega-Constellation Routing to Provide Fast Internet Access Services

“…In recent years, various routing algorithms based on LEO large-scale constellations, have been proposed [ 12 , 13 , 14 , 15 ]. In [ 12 ], Lai et al measured large amounts of real-time communications (RTC) session data and found two critical causes of high latency in the current cloud-based wide-area RTC architecture: (i) additional latency introduced by underlying cross-domain protocols and suboptimal paths; (ii) insufficient cloud server deployments can also cause additional latency.…”

“…Compared with shortest path routing and backup dependent multi-path routing, RMPR transmits multiple copies over multiple independent shortest paths, in an optimal ratio, to ensure the reliability and timeliness of data. Grislain et al were more interested in improving system throughput than reducing transmission latency, and proposed an innovative routing protocol in [ 15 ]. This protocol solves the indivisible multi-commodity flow problem in satellite networks, by a randomized rounding based heuristic algorithm, and optimizes the total amount of traffic across the constellation.…”