Dynamic Service Placement for Mobile Micro-Clouds with Predicted Future Costs
TLDR
In this paper, the authors propose an offline algorithm that solves for the optimal configuration in a specific look-ahead time-window, and an online approximation algorithm with polynomial time-complexity to find the placement in real-time whenever an instance arrives.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 over time, 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 $O(1)$ -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) user-mobility traces. The theoretical methodology used in this paper can potentially be applied to a larger class of dynamic resource allocation problems.read more
Citations
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References
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Book
Convex Optimization
Stephen Boyd,Lieven Vandenberghe +1 more
TL;DR: In this article, the focus is on recognizing convex optimization problems and then finding the most appropriate technique for solving them, and a comprehensive introduction to the subject is given. But the focus of this book is not on the optimization problem itself, but on the problem of finding the appropriate technique to solve it.
Proceedings ArticleDOI
Friendship and mobility: user movement in location-based social networks
TL;DR: A model of human mobility that combines periodic short range movements with travel due to the social network structure is developed and it is shown that this model reliably predicts the locations and dynamics of future human movement and gives an order of magnitude better performance.
Book
Online Computation and Competitive Analysis
Allan Borodin,Ran El-Yaniv +1 more
TL;DR: This book discusses competitive analysis and decision making under uncertainty in the context of the k-server problem, which involves randomized algorithms in order to solve the problem of paging.
Book
Combinatorial Optimization: Theory and Algorithms
Bernhard Korte,Jens Vygen +1 more
TL;DR: This fourth edition of this comprehensive textbook on combinatorial optimization is again significantly extended, most notably with new material on linear programming, the network simplex algorithm, and the max-cut problem.
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