TY - GEN
T1 - Offloading Dependent Tasks in Mobile Edge Computing with Service Caching
AU - Zhao, Gongming
AU - Xu, Hongli
AU - Zhao, Yangming
AU - Qiao, Chunming
AU - Huang, Liusheng
N1 - Publisher Copyright:
© 2020 IEEE.
PY - 2020/7
Y1 - 2020/7
N2 - In Mobile Edge Computing (MEC), many tasks require specific service support for execution and in addition, have a dependent order of execution among the tasks. However, previous works often ignore the impact of having limited services cached at the edge nodes on (dependent) task offloading, thus may lead to an infeasible offloading decision or a longer completion time. To bridge the gap, this paper studies how to efficiently offload dependent tasks to edge nodes with limited (and predetermined) service caching. We formally define the problem of offloading dependent tasks with service caching (ODT-SC), and prove that there exists no algorithm with constant approximation for this hard problem. Then, we design an efficient convex programming based algorithm (CP) to solve this problem. Moreover, we study a special case with a homogeneous MEC and propose a favorite successor based algorithm (FS) to solve this special case with a competitive ratio of O(1). Extensive simulation results using Google data traces show that our proposed algorithms can significantly reduce applications' completion time by about 27-51% compared with other alternatives.
AB - In Mobile Edge Computing (MEC), many tasks require specific service support for execution and in addition, have a dependent order of execution among the tasks. However, previous works often ignore the impact of having limited services cached at the edge nodes on (dependent) task offloading, thus may lead to an infeasible offloading decision or a longer completion time. To bridge the gap, this paper studies how to efficiently offload dependent tasks to edge nodes with limited (and predetermined) service caching. We formally define the problem of offloading dependent tasks with service caching (ODT-SC), and prove that there exists no algorithm with constant approximation for this hard problem. Then, we design an efficient convex programming based algorithm (CP) to solve this problem. Moreover, we study a special case with a homogeneous MEC and propose a favorite successor based algorithm (FS) to solve this special case with a competitive ratio of O(1). Extensive simulation results using Google data traces show that our proposed algorithms can significantly reduce applications' completion time by about 27-51% compared with other alternatives.
KW - Approximation
KW - Dependency
KW - Mobile Edge Computing
KW - Service Caching
KW - Task Offloading
UR - https://www.scopus.com/pages/publications/85090272398
U2 - 10.1109/INFOCOM41043.2020.9155396
DO - 10.1109/INFOCOM41043.2020.9155396
M3 - Conference contribution
AN - SCOPUS:85090272398
T3 - Proceedings - IEEE INFOCOM
SP - 1997
EP - 2006
BT - INFOCOM 2020 - IEEE Conference on Computer Communications
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 38th IEEE Conference on Computer Communications, INFOCOM 2020
Y2 - 6 July 2020 through 9 July 2020
ER -