Choosing optimal parameters for a distributed multi-constrained QoS routing

TL;DR

This paper investigates the challenges of distributed multi-constrained routing, proposing methods to select optimal composite metrics to maximize feasible path discovery, supported by theoretical analysis and extensive experiments.

Contribution

It introduces a novel approach for choosing optimal composite metrics in distributed routing to improve feasible path discovery under multiple constraints.

Findings

Impossible to guarantee distributed routing with multiple constraints in general.

Efficient methods to find convex combinations of metrics under certain assumptions.

Extensive experiments demonstrate the effectiveness of the proposed approach.

Abstract

We consider several basic questions on distributed routing in directed graphs with multiple additive costs, or metrics, and multiple constraints. Distributed routing in this sense is used in several protocols, such as IS-IS and OSPF. A practical approach to the multi-constraint routing problem is to, first, combine the metrics into a single `composite' metric, and then apply one-to-all shortest path algorithms, e.g. Dijkstra, in order to find shortest path trees. We show that, in general, even if a feasible path exists and is known for every source and destination pair, it is impossible to guarantee a distributed routing under several constraints. We also study the question of choosing the optimal `composite' metric. We show that under certain mathematical assumptions we can efficiently find a convex combination of several metrics that maximizes the number of discovered feasible paths. Sometimes it can be done analytically, and is in general possible using what we call a 'smart iterative approach'. We illustrate these findings by extensive experiments on several typical network topologies.