Resource Allocation in One-dimensional Distributed Service Networks with Applications

TL;DR

This paper studies resource allocation policies in one-dimensional networks, introducing new algorithms and analytical models that improve fairness and efficiency, with applications to queueing systems and resource placement strategies.

Contribution

It proposes the Move to Right policy, maps unidirectional policies to queueing models, and develops efficient algorithms for bidirectional and two-dimensional assignment problems.

Findings

MTR policy is fairer than UGS while minimizing request distance.

Unidirectional policies can be analyzed using queueing theory, yielding closed-form results.

Heuristic algorithms for 2D scenarios perform within a constant factor of optimal.

Abstract

We consider assignment policies that allocate resources to users, where both resources and users are located on a one-dimensional line. First, we consider unidirectional assignment policies that allocate resources only to users located to their left. We propose the Move to Right (MTR) policy, which scans from left to right assigning nearest rightmost available resource to a user, and contrast it to the Unidirectional Gale-Shapley (UGS) matching policy. While both policies among all unidirectional policies, minimize the expected distance traveled by a request (request distance), MTR is fairer. Moreover, we show that when user and resource locations are modeled by statistical point processes, and resources are allowed to satisfy more than one user, the spatial system under unidirectional policies can be mapped into bulk service queueing systems, thus allowing the application of many queueing theory results that yield closed form expressions. As we consider a case where different resources can satisfy different numbers of users, we also generate new results for bulk service queues. We also consider bidirectional policies where there are no directional restrictions on resource allocation and develop an algorithm for computing the optimal assignment which is more efficient than known algorithms in the literature when there are more resources than users. Numerical evaluation of performance of unidirectional and bidirectional allocation schemes yields design guidelines beneficial for resource placement. \np{Finally, we present a heuristic algorithm, which leverages the optimal dynamic programming scheme for one-dimensional inputs to obtain approximate solutions to the optimal assignment problem for the two-dimensional scenario and empirically yields request distances within a constant factor of the optimal solution.