Task Scheduling and Resource Allocation Using a Heuristic Approach In Cloud Computing

Authors(2) :-K. Durailingam, Dr.V.S. Prakash

Cloud computing is needed by trendy technology. Task planning and resource allocation are vital aspects of cloud computing. This paper proposes a heuristic approach that mixes the changed analytic hierarchy method (MAHP), bandwidth aware divisible scheduling (BATS) + BAR optimization, longest expected processing time preemption (LEPT), and divide-and-conquer strategies to perform task planning and resource allocation. During this approach, every task is processed before its actual allocation to cloud resources using a MAHP process. The resources are allocated victimization the combined haywire + BAR optimization methodology, that considers the information measure and cargo of the cloud resources as constraints. Additionally, the planned system preempts resource intensive tasks exploitation LEPT preemption. The divide-and-conquer approach improves the planned system, as is established by experimentation through comparison with the existing bats and improved differential evolution algorithmic rule (IDEA) frameworks once turnaround and time interval square measure used as performance metrics.

Authors and Affiliations

K. Durailingam
Indian Arts and Science College, Kondam, Tiruvannamalai, Tamil Nadu, India
Dr.V.S. Prakash
Indian Arts and Science College, Kondam, Tiruvannamalai, Tamil Nadu, India

Cloud computing, Task planning, Heuristic, Resource management, Analytic hierarchy system, BATS, BAR

  1. Mezmaz M, Melab N, Kessaci Y, Lee YC, Talbi E-G, Zomaya AY, Tuyttens D (2011) A parallel bi-objective hybrid meta heuristic for energy-aware scheduling for cloud computing systems. J Parallel Distributed Computing 71(11):1497–1508
  2. Armbrust M, Fox A, Griffith R, Joseph AD, Katz R, Konwinski A, Lee G, Patterson D, Rabkin A, Stoica I et al (2010) A view of cloud computing. Commun ACM 53(4):50–58
  3. Tsai J-T, Fang J-C, Chou J-H (2013) Optimized task scheduling and resource allocation on cloud computing environment using improved differential evolution algorithm. ComputOper Res 40(12):3045–3055
  4. Cheng C, Li J, Wang Y (2015) An energy-saving task scheduling strategy based on vacation queuing theory in cloud computing. Tsinghua SciTechnol 20(1):28–39
  5. Ergu D, Kou G, Peng Y, Shi Y, Shi Y (2013) The analytic hierarchy process: task scheduling and resource allocation in cloud computing environment. The Journal of Supercomputing. 64(3):835-848
  6. Zhu X, Yang LT, Chen H, Wang J, Yin S, Liu X (2014) Real-time tasks oriented energy-aware scheduling in virtualized clouds. IEEE Transactions on Cloud Computing 2(2):168–180
  7. Handfield R, Walton SV, Sroufe R, Melnyk SA (2002) Applying environmental criteria to supplier assessment: a study in the application of the analytical hierarchy process. Eur J Oper Res 141(1):70–87
  8. Calheiros RN, Ranjan R, Beloglazov A, De Rose CA, Buyya R (2011) Cloudsim: a toolkit for modeling and simulation of cloud computing environments and evaluation of resource provisioning algorithms. Software: Practice and Experience
  9. Maguluri ST, Srikant R (2014) Scheduling jobs with unknown duration in clouds. IEEE/ACM Trans Netw (TON) 22(6):1938–
  10. Lin W, Liang C, Wang JZ, Buyya R (2014) Bandwidth-aware divisible task scheduling for cloud computing. Software: Practice and Experience 44(2):163–174
  11. Shamsollah G, Othman M (2012) Priority based job scheduling algorithm in cloud computing. Procedia Engineering 50:778–785
  12. Polverini M, Cianfrani A, Ren S, Vasilakos AV (2014) Thermal aware scheduling of batch jobs in geographically distributed data centers. IEEE Transactions on Cloud Computing 2(1):71–84
  13. Keshk AE, El-Sisi AB, Tawfeek MA (2014) Cloud task scheduling for load balancing based on intelligent strategy. Int J IntellSystAppl 6(5):25
  14. Rodriguez MA, Buyya R (2014) Deadline based resource provisioningand scheduling algorithm for scientific workows on clouds. IEEE Transactions on Cloud Computing 2(2):222–235
  15. Liu X, Zha Y, Yin Q, Peng Y, Qin L (2015) Scheduling parallel jobs with tentative runs and consolidation in the cloud. J SystSoftw 104:141–151

Publication Details

Published in : Volume 4 | Issue 3 | January-February 2018
Date of Publication : 2018-03-31
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 71-81
Manuscript Number : CSEIT184313
Publisher : Technoscience Academy

ISSN : 2456-3307

Cite This Article :

K. Durailingam, Dr.V.S. Prakash, "Task Scheduling and Resource Allocation Using a Heuristic Approach In Cloud Computing", International Journal of Scientific Research in Computer Science, Engineering and Information Technology (IJSRCSEIT), ISSN : 2456-3307, Volume 4, Issue 3, pp.71-81, January-February-2018.
Journal URL : http://ijsrcseit.com/CSEIT184313

Article Preview