Paper Info
Title
Maximizing Mobiles Energy Saving Through Tasks Optimal Offloading Placement in two-tier Cloud.
Abstract
In this paper, we focus on tasks offloading over two tiered mobile cloud computing environment. We consider several users with energy constrained tasks that can be offloaded over cloudlets or on a remote cloud with differentiated system and network resources capacities. We investigate offloading policy that decides which tasks should be offloaded and determine the offloading location on the cloudlets or on the cloud. The objective is to minimize the total energy consumed by the users. We formulate this problem as a Non-Linear Binary Integer Programming. Since the centralized optimal solution is NP-hard, we propose a distributed linear relaxation heuristic based on Lagrangian decomposition approach. To solve the subproblems, we also propose a greedy heuristic that computes the best cloudlet selection and bandwidth allocation following tasks' energy consumption. We compared our proposal against existing approaches under different system parameters (e.g. CPU resources), variable number of users and for six applications, each having specific traffic pattern, resource demands and time constraints. Numerical results show that our proposal outperforms existing approaches. We also analyze the performance of our proposal for each application.
Year
DOI
Venue
2018
10.1145/3242102.3242133
MSWIM '18: 21st ACM Int'l Conference on Modelling, Analysis and Simulation of Wireless and Mobile Systems Montreal QC Canada October, 2018
Field
DocType
ISBN
Mobile cloud computing,Heuristic,Cloudlet,Bandwidth allocation,Computer science,Computer network,Computation offloading,Greedy algorithm,Mobile edge computing,Distributed computing,Cloud computing
Conference
978-1-4503-5960-3
Citations 
PageRank 
References 
1
0.35
13
Authors
3
Name
Order
Citations
PageRank
Houssemeddine Mazouzi110.35
Nadjib Achir213122.92
Khaled Boussetta319327.71