Title :
Job Scheduling for Cloud Computing Integrated with Wireless Sensor Network
Author :
Chunsheng Zhu ; Xiuhua Li ; Leung, Victor C. M. ; Xiping Hu ; Yang, Laurence T.
Author_Institution :
Dept. of Electr. & Comput. Eng., Univ. of British Columbia, Vancouver, BC, Canada
Abstract :
The powerful data storage and data processing abilities of cloud computing (CC) and the ubiquitous data gathering capability of wireless sensor network (WSN) complement each other in CC-WSN integration, which is attracting growing interest from both academia and industry. However, job scheduling for CC integrated with WSN is a critical and unexplored topic. To fill this gap, this paper first analyzes the characteristics of job scheduling with respect to CC-WSN integration and then studies two traditional and popular job scheduling algorithms (i.e., Min-Min and Max-Min). Further, two novel job scheduling algorithms, namely priority-based two phase Min-Min (PTMM) and priority-based two phase Max-Min (PTAM), are proposed for CC integrated with WSN. Extensive experimental results show that PTMM and PTAM achieve shorter expected completion time than Min-Min and Max-Min, for CC integrated with WSN.
Keywords :
cloud computing; minimax techniques; scheduling; ubiquitous computing; wireless sensor networks; CC-WSN integration; PTAM algorithms; PTMM algorithms; cloud computing; data processing; data storage; expected completion time; expected execution time; job scheduling algorithms; priority-based two phase max-min algorithms; priority-based two phase min-min algorithms; ubiquitous data gathering capability; wireless sensor network; Job shop scheduling; Memory; Scheduling algorithms; Temperature sensors; Wireless sensor networks; Cloud computing; Max-Min; Min-Min; expected execution time; job scheduling; priority; wireless sensor network;
Conference_Titel :
Cloud Computing Technology and Science (CloudCom), 2014 IEEE 6th International Conference on
Conference_Location :
Singapore
DOI :
10.1109/CloudCom.2014.106