Dynamic service placement for mobile micro-clouds with predicted future costs

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Title: Dynamic service placement for mobile micro-clouds with predicted future costs
Authors: Wang, S
Urgaonkar, R
He, T
Chan, K
Zafer, M
Leung, KK
Item Type: Journal Article
Abstract: Mobile micro-clouds are promising for enabling performance-critical cloud applications. However, one challenge therein is the dynamics at the network edge. In this paper, we study how to place service instances to cope with these dynamics, where multiple users and service instances coexist in the system. Our goal is to find the optimal placement (configuration) of instances to minimize the average cost overtime, leveraging the ability of predicting future cost parameters with known accuracy. We first propose an offline algorithm that solves for the optimal configuration in a specific look-ahead time-window. Then, we propose an online approximation algorithm with polynomial time-complexity to find the placement in real-time whenever an instance arrives. We analytically show that the online algorithm is 0(1)-competitive for a broad family of cost functions. Afterwards, the impact of prediction errors is considered and a method for finding the optimal look-ahead window size is proposed, which minimizes an upper bound of the average actual cost. The effectiveness of the proposed approach is evaluated by simulations with both synthetic and real-world (San Francisco taxi) usermobility traces. The theoretical methodology used in this paper can potentially be applied to a larger class of dynamic resource allocation problems.
Issue Date: 1-Apr-2017
Date of Acceptance: 23-Aug-2016
URI: http://hdl.handle.net/10044/1/69229
DOI: https://dx.doi.org/10.1109/TPDS.2016.2604814
ISSN: 1045-9219
Publisher: Institute of Electrical and Electronics Engineers
Start Page: 1002
End Page: 1016
Journal / Book Title: IEEE Transactions on Parallel and Distributed Systems
Volume: 28
Issue: 4
Copyright Statement: © 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Sponsor/Funder: IBM United Kingdom Ltd
Funder's Grant Number: PO4603106973
Keywords: Science & Technology
Technology
Computer Science, Theory & Methods
Engineering, Electrical & Electronic
Computer Science
Engineering
Cloud computing
fog/edge computing
online approximation algorithm
optimization
resource allocation
wireless networks
MIGRATION
NETWORKS
0805 Distributed Computing
0803 Computer Software
Distributed Computing
Publication Status: Published
Online Publication Date: 2016-08-31
Appears in Collections:Faculty of Engineering
Computing
Electrical and Electronic Engineering



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