TY - GEN
T1 - CTOM
T2 - 2018 IEEE International Conference on Communications, ICC 2018
AU - Fan, Xiaochen
AU - He, Xiangjian
AU - Puthal, Deepak
AU - Chen, Shiping
AU - Xiang, Chaocan
AU - Nanda, Priyadarsi
AU - Rao, Xunpeng
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2018/7/27
Y1 - 2018/7/27
N2 - Mobile cloud computing has emerged as a pervasive paradigm to execute computing tasks for capacity- limited mobile devices. More specifically, at the network edge, the resource-rich and trusted cloudlet system is acting as a 'data center in a box' to support compute-intensive mobile applications. The mobile cloudlets can provide in-proximity services by executing the workloads for nearby devices. Nevertheless, load balancing in mobile cloudlet network is of great importance, as it has a huge impact on task response time. Existing methods for cloudlet load balancing basically rely on the strategic placement or user cooperation. However, the above solutions require the global task load information from the whole network, which is costly in both communication and computation. To achieve more efficient and low-cost load balancing, we propose 'CTOM', a Collaborative Task Offioading Mechanism for mobile cloudlet networks. Our solution is based on the balls-and-bins theory and can balance the task load only requiring limited information. Extensive simulations and evaluation based on mobility trace demonstrate that, our CTOM outperforms the conventional random and proportional allocation schemes by reducing the task gaps among mobile cloudlets by 65% and 55% respectively. Meanwhile, CTOM's performance is close to that of the greedy algorithm but with much lower computing complexity.
AB - Mobile cloud computing has emerged as a pervasive paradigm to execute computing tasks for capacity- limited mobile devices. More specifically, at the network edge, the resource-rich and trusted cloudlet system is acting as a 'data center in a box' to support compute-intensive mobile applications. The mobile cloudlets can provide in-proximity services by executing the workloads for nearby devices. Nevertheless, load balancing in mobile cloudlet network is of great importance, as it has a huge impact on task response time. Existing methods for cloudlet load balancing basically rely on the strategic placement or user cooperation. However, the above solutions require the global task load information from the whole network, which is costly in both communication and computation. To achieve more efficient and low-cost load balancing, we propose 'CTOM', a Collaborative Task Offioading Mechanism for mobile cloudlet networks. Our solution is based on the balls-and-bins theory and can balance the task load only requiring limited information. Extensive simulations and evaluation based on mobility trace demonstrate that, our CTOM outperforms the conventional random and proportional allocation schemes by reducing the task gaps among mobile cloudlets by 65% and 55% respectively. Meanwhile, CTOM's performance is close to that of the greedy algorithm but with much lower computing complexity.
KW - Load balancing
KW - Mobile cloudlet network
KW - Task allocation
UR - http://www.scopus.com/inward/record.url?scp=85051435582&partnerID=8YFLogxK
U2 - 10.1109/ICC.2018.8422114
DO - 10.1109/ICC.2018.8422114
M3 - Conference contribution
AN - SCOPUS:85051435582
SN - 9781538631805
T3 - IEEE International Conference on Communications
BT - 2018 IEEE International Conference on Communications, ICC 2018 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 20 May 2018 through 24 May 2018
ER -