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Distributed Approach to the Holistic Resource Management of a Mobile Cloud Network

Tärneberg, William LU ; Papadopoulos Vittorio, Alessandro ; Mehta, Amardeep; Tordsson, Johan and Kihl, Maria LU (2017) 1st IEEE International Conference on Fog and Edge Computing (ICFEC’2017) In International Conference of Fog and Edge Computing
Abstract
The Mobile Cloud Network is an emerging cost and capacity heterogeneous distributed cloud topological paradigm that aims to remedy the application performance constraints imposed by centralised cloud infrastructures. A centralised cloud infrastructure and the adjoining Telecom network will struggle to accommodate the exploding amount of traffic generated by forthcoming highly interactive applications. Cost effectively managing a Mobile Cloud Network computing infrastructure while meeting individual application’s performance goals is non- trivial and is at the core of our contribution. Due to the scale of a Mobile Cloud Network, a centralised approach is infeasible. Therefore, in this paper a distributed algorithm that addresses these... (More)
The Mobile Cloud Network is an emerging cost and capacity heterogeneous distributed cloud topological paradigm that aims to remedy the application performance constraints imposed by centralised cloud infrastructures. A centralised cloud infrastructure and the adjoining Telecom network will struggle to accommodate the exploding amount of traffic generated by forthcoming highly interactive applications. Cost effectively managing a Mobile Cloud Network computing infrastructure while meeting individual application’s performance goals is non- trivial and is at the core of our contribution. Due to the scale of a Mobile Cloud Network, a centralised approach is infeasible. Therefore, in this paper a distributed algorithm that addresses these challenges is presented. The presented approach works towards meeting individual application’s performance objectives, constricting system-wide operational cost, and mitigating re- source usage skewness. The presented distributed algorithm does so by iteratively and independently acting on the objectives of each component with a common heuristic objective function. Sys- tematic evaluations reveal that the presented algorithm quickly converges and performs near optimal in terms of system-wide operational cost and application performance, and significantly outperforms similar na ̈ıve and random methods. (Less)
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author
organization
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type
Chapter in Book/Report/Conference proceeding
publication status
in press
subject
keywords
Fog Computing, Cloud computing, telecommunication, distributed algorithm
in
International Conference of Fog and Edge Computing
publisher
IEEE--Institute of Electrical and Electronics Engineers Inc.
conference name
1st IEEE International Conference on Fog and Edge Computing (ICFEC’2017)
language
English
LU publication?
yes
id
1a996931-7ebd-4cbb-b3d7-cfdc75ba2c14
date added to LUP
2017-04-13 15:17:28
date last changed
2017-06-13 10:22:47
@inproceedings{1a996931-7ebd-4cbb-b3d7-cfdc75ba2c14,
  abstract     = {The Mobile Cloud Network is an emerging cost and capacity heterogeneous distributed cloud topological paradigm that aims to remedy the application performance constraints imposed by centralised cloud infrastructures. A centralised cloud infrastructure and the adjoining Telecom network will struggle to accommodate the exploding amount of traffic generated by forthcoming highly interactive applications. Cost effectively managing a Mobile Cloud Network computing infrastructure while meeting individual application’s performance goals is non- trivial and is at the core of our contribution. Due to the scale of a Mobile Cloud Network, a centralised approach is infeasible. Therefore, in this paper a distributed algorithm that addresses these challenges is presented. The presented approach works towards meeting individual application’s performance objectives, constricting system-wide operational cost, and mitigating re- source usage skewness. The presented distributed algorithm does so by iteratively and independently acting on the objectives of each component with a common heuristic objective function. Sys- tematic evaluations reveal that the presented algorithm quickly converges and performs near optimal in terms of system-wide operational cost and application performance, and significantly outperforms similar na ̈ıve and random methods.},
  author       = {Tärneberg, William and Papadopoulos Vittorio, Alessandro  and Mehta, Amardeep and Tordsson, Johan  and Kihl, Maria},
  booktitle    = {International Conference of Fog and Edge Computing},
  keyword      = {Fog Computing,Cloud computing,telecommunication,distributed algorithm},
  language     = {eng},
  publisher    = {IEEE--Institute of Electrical and Electronics Engineers Inc.},
  title        = {Distributed Approach to the Holistic Resource Management of a Mobile Cloud Network},
  year         = {2017},
}