TY - GEN
T1 - Joint Collaborative Task Offloading for Cost-Efficient Applications in Edge Computing
AU - Ma, Chaochen
AU - Qin, Zhida
AU - Gan, Xiaoying
AU - Fu, Luoyi
N1 - Publisher Copyright:
© 2020, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.
PY - 2020
Y1 - 2020
N2 - Edge computing is a new network model providing low-latency service with low bandwidth cost for the users by nearby edge servers. Due to the limited computational capacity of edge servers and devices, some edge servers need to offload some tasks to other servers in the edge network. Although offloading task to other edge servers may improve the service quality, the offloading process will be charged by the operator. In this paper, the goal is to determine the task offloading decisions of all the edge servers in the network. A model is designed with different types of cost in edge computing, where the overall cost of the system reflects the performance of the network. We formulate a cost minimization problem which is NP-hard. To solve the NP-hard problem, we propose a Joint Collaborative Task Offloading algorithm by adopting the optimization process in nearby edge servers. In our algorithm, an edge server can only offload its tasks to other edge servers within a neighborhood range. Based on the real-world data set, an adequate range is determined for the edge computing network. In cases of different density of tasks, the evaluations demonstrate that our algorithm has a good performance in term of overall cost, which outperforms an algorithm without considering the influence of neighborhood range.
AB - Edge computing is a new network model providing low-latency service with low bandwidth cost for the users by nearby edge servers. Due to the limited computational capacity of edge servers and devices, some edge servers need to offload some tasks to other servers in the edge network. Although offloading task to other edge servers may improve the service quality, the offloading process will be charged by the operator. In this paper, the goal is to determine the task offloading decisions of all the edge servers in the network. A model is designed with different types of cost in edge computing, where the overall cost of the system reflects the performance of the network. We formulate a cost minimization problem which is NP-hard. To solve the NP-hard problem, we propose a Joint Collaborative Task Offloading algorithm by adopting the optimization process in nearby edge servers. In our algorithm, an edge server can only offload its tasks to other edge servers within a neighborhood range. Based on the real-world data set, an adequate range is determined for the edge computing network. In cases of different density of tasks, the evaluations demonstrate that our algorithm has a good performance in term of overall cost, which outperforms an algorithm without considering the influence of neighborhood range.
KW - Cost-efficiency
KW - Edge computing
KW - Quality of service
KW - Task offloading
UR - http://www.scopus.com/inward/record.url?scp=85082129600&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-41114-5_7
DO - 10.1007/978-3-030-41114-5_7
M3 - Conference contribution
AN - SCOPUS:85082129600
SN - 9783030411138
T3 - Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST
SP - 77
EP - 90
BT - Communications and Networking - 14th EAI International Conference, ChinaCom 2019, Proceedings
A2 - Gao, Honghao
A2 - Feng, Zhiyong
A2 - Yu, Jun
A2 - Wu, Jun
PB - Springer
T2 - 14th EAI International Conference on Communications and Networking in China, ChinaCom 2019
Y2 - 29 November 2019 through 1 December 2019
ER -