Distributed and Dynamic Service Placement in Pervasive Edge Computing Networks

The explosive growth of mobile devices promotes the prosperity of novel mobile applications, which can be realized by service offloading with the assistance of edge computing servers. However, due to limited computation and storage capabilities of a single server, long service latency hinders the co...

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Published inIEEE transactions on parallel and distributed systems Vol. 32; no. 6; pp. 1277 - 1292
Main Authors Ning, Zhaolong, Dong, Peiran, Wang, Xiaojie, Wang, Shupeng, Hu, Xiping, Guo, Song, Qiu, Tie, Hu, Bin, Kwok, Ricky Y. K.
Format Journal Article
LanguageEnglish
Published New York IEEE 01.06.2021
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects
Algorithms
Applications programs
Approximation
Approximation algorithms
distributed Markov approximation
Edge computing
Electronic devices
Heuristic algorithms
Lyapunov optimization
Markov processes
Mathematical analysis
Mobile computing
Networks
Optimization
Performance evaluation
Pervasive edge computing
Placement
Quality of service
Servers
service migration
Task analysis
Online AccessGet full text

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Abstract The explosive growth of mobile devices promotes the prosperity of novel mobile applications, which can be realized by service offloading with the assistance of edge computing servers. However, due to limited computation and storage capabilities of a single server, long service latency hinders the continuous development of service offloading in mobile networks. By supporting multi-server cooperation, Pervasive Edge Computing (PEC) is promising to enable service migration in highly dynamic mobile networks. With the objective of maximizing the system utility, we formulate the optimization problem by jointly considering the constraints of server storage capability and service execution latency. To enable dynamic service placement, we first utilize Lyapunov optimization method to decompose the long-term optimization problem into a series of instant optimization problems. Then, a sample average approximation-based stochastic algorithm is proposed to approximate the future expected system utility. Afterwards, a distributed Markov approximation algorithm is utilized to determine the service placement configurations. Through theoretical analysis, the time complexity of our proposed algorithm is linear to the number of users, and the backlog queue of PEC servers is stable. Performance evaluations are conducted based on both synthetic and real trace-driven scenarios, with numerical results demonstrating the effectiveness of our proposed algorithm from various aspects.
AbstractList The explosive growth of mobile devices promotes the prosperity of novel mobile applications, which can be realized by service offloading with the assistance of edge computing servers. However, due to limited computation and storage capabilities of a single server, long service latency hinders the continuous development of service offloading in mobile networks. By supporting multi-server cooperation, Pervasive Edge Computing (PEC) is promising to enable service migration in highly dynamic mobile networks. With the objective of maximizing the system utility, we formulate the optimization problem by jointly considering the constraints of server storage capability and service execution latency. To enable dynamic service placement, we first utilize Lyapunov optimization method to decompose the long-term optimization problem into a series of instant optimization problems. Then, a sample average approximation-based stochastic algorithm is proposed to approximate the future expected system utility. Afterwards, a distributed Markov approximation algorithm is utilized to determine the service placement configurations. Through theoretical analysis, the time complexity of our proposed algorithm is linear to the number of users, and the backlog queue of PEC servers is stable. Performance evaluations are conducted based on both synthetic and real trace-driven scenarios, with numerical results demonstrating the effectiveness of our proposed algorithm from various aspects.
Author Dong, Peiran
Wang, Shupeng
Hu, Xiping
Hu, Bin
Kwok, Ricky Y. K.
Wang, Xiaojie
Guo, Song
Ning, Zhaolong
Qiu, Tie
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Snippet The explosive growth of mobile devices promotes the prosperity of novel mobile applications, which can be realized by service offloading with the assistance of...
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SubjectTerms Algorithms
Applications programs
Approximation
Approximation algorithms
distributed Markov approximation
Edge computing
Electronic devices
Heuristic algorithms
Lyapunov optimization
Markov processes
Mathematical analysis
Mobile computing
Networks
Optimization
Performance evaluation
Pervasive edge computing
Placement
Quality of service
Servers
service migration
Task analysis
Title Distributed and Dynamic Service Placement in Pervasive Edge Computing Networks
URI https://ieeexplore.ieee.org/document/9301260
https://www.proquest.com/docview/2478150805
Volume 32
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