# A Game-Theoretic Framework for Resource Sharing in Clouds

**Authors:** Faheem Zafari, Kin K. Leung, Don Towsley, Prithwish Basu, and, Ananthram Swami

arXiv: 1904.00820 · 2019-05-30

## TL;DR

This paper introduces a cooperative game-theoretic framework for resource sharing among cloud providers, optimizing allocations to improve overall utility and satisfaction while considering diverse objectives.

## Contribution

It models resource sharing as a convex NTU cooperative game and proposes an efficient algorithm for Pareto optimal allocations within the core.

## Key findings

- Improves user satisfaction in simulations.
- Guarantees Pareto optimality of resource allocations.
- Models resource sharing as a convex NTU cooperative game.

## Abstract

Providing resources to different users or applications is fundamental to cloud computing. This is a challenging problem as a cloud service provider may have insufficient resources to satisfy all user requests. Furthermore, allocating available resources optimally to different applications is also challenging. Resource sharing among different cloud service providers can improve resource availability and resource utilization as certain cloud service providers may have free resources available that can be ``rented'' by other service providers. However, different cloud service providers can have different objectives or \emph{utilities}. Therefore, there is a need for a framework that can share and allocate resources in an efficient and effective way, while taking into account the objectives of various service providers that results in a \emph{multi-objective optimization} problem. In this paper, we present a \emph{Cooperative Game Theory} (CGT) based framework for resource sharing and allocation among different service providers with varying objectives that form a coalition. We show that the resource sharing problem can be modeled as an $N-$player \emph{canonical} cooperative game with \emph{non-transferable utility} (NTU) and prove that the game is convex for monotonic non-decreasing utilities. We propose an $\mathcal{O}({N})$ algorithm that provides an allocation from the \emph{core}, hence guaranteeing \emph{Pareto optimality}. We evaluate the performance of our proposed resource sharing framework in a number of simulation settings and show that our proposed framework improves user satisfaction and utility of service providers.

## Full text

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## Figures

6 figures with captions in the complete paper: https://tomesphere.com/paper/1904.00820/full.md

## References

18 references — full list in the complete paper: https://tomesphere.com/paper/1904.00820/full.md

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Source: https://tomesphere.com/paper/1904.00820