Volume 35, Issue 4
Collaborative Resource Allocation over a Hybrid Cloud Center and Edge Server Network

Houfeng Huang, Qing Ling, Wei Shi & Jinlin Wang

J. Comp. Math., 35 (2017), pp. 423-438.

Published online: 2017-08

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  • Abstract

This paper considers the collaborative resource allocation problem over a hybrid cloud center and edge server network, an emerging infrastructure for efficient Internet services. The cloud center acts as a pool of inexhaustible computation and storage powers. The edge servers often have limited computation and storage powers but are able to provide quick responses to service requests from end users. Upon receiving service requests, edge servers assign them to themselves, their neighboring edge servers, as well as the cloud center, aiming at minimizing the overall network cost.
This paper first establishes an optimization model for this problem. Second, in light of the separable structure of the optimization model, we utilize the alternating direction method of multipliers (ADMM) to develop a fully collaborative resource allocation algorithm. The edge servers and the cloud center autonomously collaborate to compute their local optimization variables and prices of network resources, and reach an optimal solution. Numerical experiments demonstrate the effectiveness of the hybrid network infrastructure as well as the proposed algorithm.

  • Keywords

Network resource allocation, Distributed network optimization, Cloud center, edge server.

  • AMS Subject Headings

90C25, 90C30.

  • Copyright

COPYRIGHT: © Global Science Press

  • Email address

hhoufeng@mail.ustc.edu.cn (Houfeng Huang)

qingling@mail.ustc.edu.cn (Qing Ling)

wilburs@illinois.edu (Wei Shi)

wangjl@dsp.ac.cn (Jinlin Wang)

  • BibTex
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@Article{JCM-35-423, author = {Huang , Houfeng and Ling , Qing and Shi , Wei and Wang , Jinlin }, title = {Collaborative Resource Allocation over a Hybrid Cloud Center and Edge Server Network}, journal = {Journal of Computational Mathematics}, year = {2017}, volume = {35}, number = {4}, pages = {423--438}, abstract = {

This paper considers the collaborative resource allocation problem over a hybrid cloud center and edge server network, an emerging infrastructure for efficient Internet services. The cloud center acts as a pool of inexhaustible computation and storage powers. The edge servers often have limited computation and storage powers but are able to provide quick responses to service requests from end users. Upon receiving service requests, edge servers assign them to themselves, their neighboring edge servers, as well as the cloud center, aiming at minimizing the overall network cost.
This paper first establishes an optimization model for this problem. Second, in light of the separable structure of the optimization model, we utilize the alternating direction method of multipliers (ADMM) to develop a fully collaborative resource allocation algorithm. The edge servers and the cloud center autonomously collaborate to compute their local optimization variables and prices of network resources, and reach an optimal solution. Numerical experiments demonstrate the effectiveness of the hybrid network infrastructure as well as the proposed algorithm.

}, issn = {1991-7139}, doi = {https://doi.org/10.4208/jcm.1608-m2016-0561}, url = {http://global-sci.org/intro/article_detail/jcm/10024.html} }
TY - JOUR T1 - Collaborative Resource Allocation over a Hybrid Cloud Center and Edge Server Network AU - Huang , Houfeng AU - Ling , Qing AU - Shi , Wei AU - Wang , Jinlin JO - Journal of Computational Mathematics VL - 4 SP - 423 EP - 438 PY - 2017 DA - 2017/08 SN - 35 DO - http://doi.org/10.4208/jcm.1608-m2016-0561 UR - https://global-sci.org/intro/article_detail/jcm/10024.html KW - Network resource allocation, Distributed network optimization, Cloud center, edge server. AB -

This paper considers the collaborative resource allocation problem over a hybrid cloud center and edge server network, an emerging infrastructure for efficient Internet services. The cloud center acts as a pool of inexhaustible computation and storage powers. The edge servers often have limited computation and storage powers but are able to provide quick responses to service requests from end users. Upon receiving service requests, edge servers assign them to themselves, their neighboring edge servers, as well as the cloud center, aiming at minimizing the overall network cost.
This paper first establishes an optimization model for this problem. Second, in light of the separable structure of the optimization model, we utilize the alternating direction method of multipliers (ADMM) to develop a fully collaborative resource allocation algorithm. The edge servers and the cloud center autonomously collaborate to compute their local optimization variables and prices of network resources, and reach an optimal solution. Numerical experiments demonstrate the effectiveness of the hybrid network infrastructure as well as the proposed algorithm.

Houfeng Huang, Qing Ling, Wei Shi & Jinlin Wang. (2019). Collaborative Resource Allocation over a Hybrid Cloud Center and Edge Server Network. Journal of Computational Mathematics. 35 (4). 423-438. doi:10.4208/jcm.1608-m2016-0561
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