# Resource Allocation in One-dimensional Distributed Service Networks

## TL;DR

This paper analyzes resource allocation policies in one-dimensional networks, introducing new algorithms and mappings to queuing systems to optimize assignment efficiency and fairness.

## Contribution

It proposes the Move to Right policy, compares it with Gale-Shapley, and maps unidirectional policies to queuing models, providing new analytical results and efficient algorithms.

## Key findings

- MTR policy is fairer than UGS while maintaining similar request distance.
- Unidirectional policies can be mapped to bulk service queues for analysis.
- New algorithms for bidirectional resource assignment outperform existing methods.

## 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 these policies are optimal among all unidirectional policies, we show that they are equivalent with respect to the expected distance traveled by a request (request distance), although 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 queuing systems, thus allowing the application of a plethora of queuing 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. Finally, numerical evaluation of performance of unidirectional and bidirectional allocation schemes yields design guidelines beneficial for resource placement.