TY - JOUR
T1 - Cloudlets Activation Scheme for Scalable Mobile Edge Computing with Transmission Power Control and Virtual Machine Migration
AU - Rodrigues, Tiago Gama
AU - Suto, Katsuya
AU - Nishiyama, Hiroki
AU - Kato, Nei
AU - Temma, Katsuhiro
N1 - Publisher Copyright:
© 2012 IEEE.
PY - 2018/9/1
Y1 - 2018/9/1
N2 - Mobile devices have several restrictions due to design choices that guarantee their mobility. A way of surpassing such limitations is to utilize cloud servers called cloudlets on the edge of the network through Mobile Edge Computing. However, as the number of clients and devices grows, the service must also increase its scalability in order to guarantee a latency limit and quality threshold. This can be achieved by deploying and activating more cloudlets, but this solution is expensive due to the cost of the physical servers. The best choice is to optimize the resources of the cloudlets through an intelligent choice of configuration that lowers delay and raises scalability. Thus, in this paper we propose an algorithm that utilizes Virtual Machine Migration and Transmission Power Control, together with a mathematical model of delay in Mobile Edge Computing and a heuristic algorithm called Particle Swarm Optimization, to balance the workload between cloudlets and consequently maximize cost-effectiveness. Our proposal is the first to consider simultaneously communication, computation, and migration in our assumed scale and, due to that, manages to outperform other conventional methods in terms of number of serviced users.
AB - Mobile devices have several restrictions due to design choices that guarantee their mobility. A way of surpassing such limitations is to utilize cloud servers called cloudlets on the edge of the network through Mobile Edge Computing. However, as the number of clients and devices grows, the service must also increase its scalability in order to guarantee a latency limit and quality threshold. This can be achieved by deploying and activating more cloudlets, but this solution is expensive due to the cost of the physical servers. The best choice is to optimize the resources of the cloudlets through an intelligent choice of configuration that lowers delay and raises scalability. Thus, in this paper we propose an algorithm that utilizes Virtual Machine Migration and Transmission Power Control, together with a mathematical model of delay in Mobile Edge Computing and a heuristic algorithm called Particle Swarm Optimization, to balance the workload between cloudlets and consequently maximize cost-effectiveness. Our proposal is the first to consider simultaneously communication, computation, and migration in our assumed scale and, due to that, manages to outperform other conventional methods in terms of number of serviced users.
KW - cloudlet
KW - Mobile edge computing
KW - particle swarm optimization
KW - resource management
KW - scalability
KW - transmission power control
KW - virtualization
UR - http://www.scopus.com/inward/record.url?scp=85044304738&partnerID=8YFLogxK
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U2 - 10.1109/TC.2018.2818144
DO - 10.1109/TC.2018.2818144
M3 - Article
AN - SCOPUS:85044304738
SN - 0018-9340
VL - 67
SP - 1287
EP - 1300
JO - IEEE Transactions on Computers
JF - IEEE Transactions on Computers
IS - 9
M1 - 8322166
ER -