Computer Science ›› 2018, Vol. 45 ›› Issue (8): 100-104.doi: 10.11896/j.issn.1002-137X.2018.08.018

• Network & Communication • Previous Articles     Next Articles

Time-aware Minimum Area Task Scheduling Algorithm Based on Backfilling Algorithm

YUAN Jia-xin, CHEN Jian-xin, XIAO Jun, WU Dao-liang   

  1. Key Lab of Broadband Wireless Communication & Sensor Network Technology,Ministry of Education, Nanjing University of Posts & Telecommunications,Nanjing 210003,China
  • Received:2017-06-19 Online:2018-08-29 Published:2018-08-29

Abstract: In the cloud computing,the task scheduling algorithm directly affects the performance of cloud computing system,so a good cloud computing scheduling task algorithm can not only reduce the pressure of cloud computing data center,deal with user’s large amount of data requests faster and better,but also allow users to obtain better user expe-rience.The existing backfilling algorithm considers single index,and its backfilling performance is poor,resulting in longer final completion time and longer task delay.In order to get rid of these limitations,an MRA algorithm based on backfilling algorithm was proposed.On this basis,the backfilling operation was performed on the basis of the relationship between the number of processor cores for task applications and the task execution time.In the backfilling operation,the virtual machine load distribution was also considered to achieve a certain load balancing.Experimental results show that the MRA algorithm has excellent performance in the maximum task completion time,task queue wait delay and load distribution of virtual machine.

Key words: Cloud computing, Task scheduling, Cloudsim, Infrastructure as a service, QoS

CLC Number: 

  • TP393
[1]ELHADY G F,TAWFEEK M A.A comparative study intoswarm intelligence algorithms for dynamic tasks scheduling in cloud computing[C]∥IEEE Seventh International Conference on Intelligent Computing and Information Systems.IEEE,2015:362-369.
[2]MITTAL S,KATAL A.An optimized task scheduling algo-rithm in cloud computing[C]∥IEEE Sixth International Confe-rence on Advanced Computing.IEEE,2016:197-202.
[3]NOROOZOLIAEE M,HAMDAOUI B,GUIZANI M,et al.Online multi-resource scheduling for minimum task completion time in cloud servers[C]∥Computer Communications Workshops.IEEE,2014:375-379.
[4]WADHONKAR A,THENG D.A survey on different scheduling algorithms in cloud computing[C]∥International Confe-rence on Advances in Electrical,Electronics,Information,Communication and Bio-Informatics.IEEE,2016:665-669.
[5]LI J,FENG L,FANG S.An Greedy-Based Job Scheduling Algorithm in Cloud Computing[J].Journal of Software,2014,9(4):921-925.
[6]LIU S,QUAN G,REN S.On-Line Scheduling of Real-TimeServices for Cloud Computing[C]∥World Congress on Ser-vices.IEEE Computer Society.2010:459-464.
[7]GERSOVITZ M.SLA-based Optimization of Power and Migration Cost in Cloud Computing[C]∥IEEE/ACM International Symposium on Cluster,Cloud and Grid Computing.IEEE,2012:172-179.
[8]PATEL S J,BHOI U R.Improved Priority Based Job Scheduling Algorithm in Cloud Computing Using Iterative Method[C]∥International Conference on Advances in Computing & Communications.2014:199-202.
[9]BEGHDADBEY K,BENHAMMADI F,BENAISSA R.Balan-cing heuristic for independent task scheduling in cloud computing[C]∥International Symposium on Programming and Systems.IEEE,2015:1-6.
[10]SURESH A,VIJAYAKARTHICK P.Improving scheduling of backfill algorithms using balanced spiral method for cloudme-tascheduler[C]∥2011 International Conference on Recent Trends in Information Technology (ICRTIT).IEEE,2011:624-627.
[11]VRATT SINGH L S,AHMED J,KHAN A.An Algorithm to Optimize the Traditional Backfill Algorithm Using Priority of Jobs for Task Scheduling Problems in Cloud Computing[J].International Journal of Computer Science & Information Technology,2014,5(2):1671-1674.
[12]LIU S,REN K,DENG K,et al.A task backfill based scientific workflow scheduling strategy on cloud platform[C]∥Sixth International Conference on Information Science and Technology.2016:105-110.
[1] YAO Juan, XING Bin, ZENG Jun, WEN Jun-hao. Survey on Cloud Manufacturing Service Composition [J]. Computer Science, 2021, 48(7): 245-255.
[2] WANG Zheng, JIANG Chun-mao. Cloud Task Scheduling Algorithm Based on Three-way Decisions [J]. Computer Science, 2021, 48(6A): 420-426.
[3] PAN Rui-jie, WANG Gao-cai, HUANG Heng-yi. Attribute Access Control Based on Dynamic User Trust in Cloud Computing [J]. Computer Science, 2021, 48(5): 313-319.
[4] CHEN Yu-ping, LIU Bo, LIN Wei-wei, CHENG Hui-wen. Survey of Cloud-edge Collaboration [J]. Computer Science, 2021, 48(3): 259-268.
[5] JIANG Hui-min, JIANG Zhe-yuan. Reference Model and Development Methodology for Enterprise Cloud Service Architecture [J]. Computer Science, 2021, 48(2): 13-22.
[6] LU Yi-fan, CAO Rui-hao, WANG Jun-li, YAN Chun-gang. Method of Encapsulating Procuratorate Affair Services Based on Microservices [J]. Computer Science, 2021, 48(2): 33-40.
[7] WANG Wen-juan, DU Xue-hui, REN Zhi-yu, SHAN Di-bin. Reconstruction of Cloud Platform Attack Scenario Based on Causal Knowledge and Temporal- Spatial Correlation [J]. Computer Science, 2021, 48(2): 317-323.
[8] WANG Qin, WEI Li-fei, LIU Ji-hai, ZHANG Lei. Private Set Intersection Protocols Among Multi-party with Cloud Server Aided [J]. Computer Science, 2021, 48(10): 301-307.
[9] CAI Ling-feng, WEI Xiang-lin, XING Chang-you, ZOU Xia, ZHANG Guo-min. Failure-resilient DAG Task Rescheduling in Edge Computing [J]. Computer Science, 2021, 48(10): 334-342.
[10] ZHNAG Kai-qi, TU Zhi-ying, CHU Dian-hui, LI Chun-shan. Survey on Service Resource Availability Forecast Based on Queuing Theory [J]. Computer Science, 2021, 48(1): 26-33.
[11] LEI Yang, JIANG Ying. Anomaly Judgment of Directly Associated Nodes Under Cloud Computing Environment [J]. Computer Science, 2021, 48(1): 295-300.
[12] XU Yun-qi, HUANG He, JIN Zhong. Application Research on Container Technology in Scientific Computing [J]. Computer Science, 2021, 48(1): 319-325.
[13] LI Yan, SHEN De-rong, NIE Tie-zheng, KOU Yue. Multi-keyword Semantic Search Scheme for Encrypted Cloud Data [J]. Computer Science, 2020, 47(9): 318-323.
[14] ZHANG Long-xin, ZHOU Li-qian, WEN Hong, XIAO Man-sheng, DENG Xiao-jun. Energy Efficient Scheduling Algorithm of Workflows with Cost Constraint in Heterogeneous Cloud Computing Systems [J]. Computer Science, 2020, 47(8): 112-118.
[15] MA Xiao-xiao and HUANG Yan. Publicly Traceable Accountable Ciphertext Policy Attribute Based Encryption Scheme Supporting Large Universe [J]. Computer Science, 2020, 47(6A): 420-423.
Full text



[1] . [J]. Computer Science, 2018, 1(1): 1 .
[2] LEI Li-hui and WANG Jing. Parallelization of LTL Model Checking Based on Possibility Measure[J]. Computer Science, 2018, 45(4): 71 -75 .
[3] SUN Qi, JIN Yan, HE Kun and XU Ling-xuan. Hybrid Evolutionary Algorithm for Solving Mixed Capacitated General Routing Problem[J]. Computer Science, 2018, 45(4): 76 -82 .
[4] ZHANG Jia-nan and XIAO Ming-yu. Approximation Algorithm for Weighted Mixed Domination Problem[J]. Computer Science, 2018, 45(4): 83 -88 .
[5] WU Jian-hui, HUANG Zhong-xiang, LI Wu, WU Jian-hui, PENG Xin and ZHANG Sheng. Robustness Optimization of Sequence Decision in Urban Road Construction[J]. Computer Science, 2018, 45(4): 89 -93 .
[6] SHI Wen-jun, WU Ji-gang and LUO Yu-chun. Fast and Efficient Scheduling Algorithms for Mobile Cloud Offloading[J]. Computer Science, 2018, 45(4): 94 -99 .
[7] ZHOU Yan-ping and YE Qiao-lin. L1-norm Distance Based Least Squares Twin Support Vector Machine[J]. Computer Science, 2018, 45(4): 100 -105 .
[8] LIU Bo-yi, TANG Xiang-yan and CHENG Jie-ren. Recognition Method for Corn Borer Based on Templates Matching in Muliple Growth Periods[J]. Computer Science, 2018, 45(4): 106 -111 .
[9] GENG Hai-jun, SHI Xin-gang, WANG Zhi-liang, YIN Xia and YIN Shao-ping. Energy-efficient Intra-domain Routing Algorithm Based on Directed Acyclic Graph[J]. Computer Science, 2018, 45(4): 112 -116 .
[10] CUI Qiong, LI Jian-hua, WANG Hong and NAN Ming-li. Resilience Analysis Model of Networked Command Information System Based on Node Repairability[J]. Computer Science, 2018, 45(4): 117 -121 .