# Resource Management in Cloud Networking Using Economic Analysis and   Pricing Models: A Survey

**Authors:** Nguyen Cong Luong, Ping Wang, Dusit Niyato, Wen Yonggang, and Zhu Han

arXiv: 1701.01963 · 2017-01-10

## TL;DR

This survey reviews how economic and pricing models are applied to resource management in cloud networking, focusing on adaptive algorithms, incentive mechanisms, and future challenges.

## Contribution

It provides a comprehensive overview of economic and pricing strategies used for resource management in cloud networking and edge computing.

## Key findings

- Economic models improve resource allocation efficiency
- Pricing strategies enhance fairness and user satisfaction
- Identifies open challenges and future research directions

## Abstract

This paper presents a comprehensive literature review on applications of economic and pricing models for resource management in cloud networking. To achieve sustainable profit advantage, cost reduction, and flexibility in provisioning of cloud resources, resource management in cloud networking requires adaptive and robust designs to address many issues, e.g., resource allocation, bandwidth reservation, request allocation, and workload allocation. Economic and pricing models have received a lot of attention as they can lead to desirable performance in terms of social welfare, fairness, truthfulness, profit, user satisfaction, and resource utilization. This paper reviews applications of the economic and pricing models to develop adaptive algorithms and protocols for resource management in cloud networking. Besides, we survey a variety of incentive mechanisms using the pricing strategies in sharing resources in edge computing. In addition, we consider using pricing models in cloud-based Software Defined Wireless Networking (cloud-based SDWN). Finally, we highlight important challenges, open issues and future research directions of applying economic and pricing models to cloud networking

## Full text

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## Figures

26 figures with captions in the complete paper: https://tomesphere.com/paper/1701.01963/full.md

## References

309 references — full list in the complete paper: https://tomesphere.com/paper/1701.01963/full.md

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Source: https://tomesphere.com/paper/1701.01963