Maximum Utility-Aware Capacity Partitioning in Cooperative Computing - Inria - Institut national de recherche en sciences et technologies du numérique Access content directly
Journal Articles IEEE Communications Letters Year : 2021

Maximum Utility-Aware Capacity Partitioning in Cooperative Computing

Nitin Singha
Sanket Kalamkar

Abstract

In many networks, a user has to allocate the link capacity between upload and download. When such networks are used for cooperative computing, the user needs to maintain the division of upload and download capacities at an optimal value to receive the maximum utility. To determine this optimal value, we model upload-download partitioning as a resource maximization game. We show that a Nash equilibrium (NE) obtained for this game is socially optimal. Thus this NE acts as an upper bound on capacity partitioning and serves as a benchmark to analyze the efficiency and performance of various capacity partitioning algorithms. Specifically, using this upper bound and simulations, we examine the performance of different partitioning algorithms while considering the dynamics of resource requests.

Dates and versions

hal-03550073 , version 1 (31-01-2022)

Identifiers

Cite

Nitin Singha, Sanket Kalamkar, Yatindra Nath Singh. Maximum Utility-Aware Capacity Partitioning in Cooperative Computing. IEEE Communications Letters, 2021, 25 (10), pp.3360-3364. ⟨10.1109/LCOMM.2021.3097045⟩. ⟨hal-03550073⟩
27 View
0 Download

Altmetric

Share

Gmail Mastodon Facebook X LinkedIn More