Skip to content
2000
Volume 18, Issue 2
  • ISSN: 2352-0965
  • E-ISSN: 2352-0973

Abstract

The goal of the distributed computing paradigm known as “cloud computing,” which necessitates a large number of resources and demands, is to share the resources as services delivered over the internet. Task scheduling is a very significant stage in today's cloud computing. While lowering the makespan and cost, the task scheduling method must schedule the tasks to the virtual machines. Various academics have proposed many scheduling methods for organizing work in cloud computing environments. Scheduling has been considered the most important for cloud computing since it might directly impact a system's performance, including the efficiency of resource utilization and running costs. This paper has compared all the already used algorithms that work on different parameters. We have tried to give better solutions for resource allocation and resource scheduling. In this study, various swarm optimization, evolutionary, physical, evolving, and fusion meta-heuristic scheduling methods are categorized according to the environment of the scheduling problem, the main scheduling goal, the task-resource mapping pattern, and the scheduling constraint. More specifically, the fundamental concepts of cloud task scheduling are addressed without difficulty.

© 2025 Bentham Science Publishers
Loading

Article metrics loading...

/content/journals/raeeng/10.2174/0123520965255860231012020315
2023-10-20
2025-07-26

  • From This Site

    /content/journals/raeeng/10.2174/0123520965255860231012020315
    dcterms_title,dcterms_subject,pub_keyword
    -contentType:Contributor -contentType:Concept -contentType:Institution
    10
    5
Loading full text...

Full text loading...

References

  1. KeivaniA. TapamoJ-R. Task scheduling in cloud computing: A review.2019 International Conference on Advances in Big Data, Computing and Data Communication Systems (icABCD)Winterton, South Africa, 05-06 Aug, 2019, pp. 1-610.1109/ICABCD.2019.8851045
     [Google Scholar]
  2. ArunaraniA. ManjulaD. SugumaranV. Task scheduling techniques in cloud computing: A literature survey.Future Gener. Comput. Syst.20199140741510.1016/j.future.2018.09.014
     [Google Scholar]
  3. IbrahimM. NabiS. BazA. NaveedN. AlhakamiH. Towards a task and resource aware task scheduling in Cloud Computing: An experimental comparative evaluation.Int. J. Net. Distributed Comput.20208313113810.2991/ijndc.k.200515.003
     [Google Scholar]
  4. BacaninN. BezdanT. TubaE. StrumbergerI. TubaM. ZivkovicM. Task scheduling in cloud computing environment by grey wolf optimizer.27th Telecommunications Forum (TELFOR)Belgrade, Serbia, 26-27 Nov, 201910.1109/TELFOR48224.2019.8971223
     [Google Scholar]
  5. LiuY. WangL. WangX.V. XuX. ZhangL. Scheduling in cloud manufacturing: State-of-the-art and research challenges.Int. J. Prod. Res.20195715-164854487910.1080/00207543.2018.1449978
     [Google Scholar]
  6. KarmakarK. DasR.K. KhatuaS. Resource scheduling of workflow tasks in cloud environment.IEEE International Conference on Advanced Networks and Telecommunications Systems (ANTS), Goa, India, 16-19 Dec, 2019, pp. 1-610.1109/ANTS47819.2019.9118150
     [Google Scholar]
  7. KashikolaeiS.M.G. HosseinabadiA.A.R. SaemiB. SharehM.B. SangaiahA.K. BianG-B. An enhancement of task scheduling in cloud computing based on imperialist competitive algorithm and firefly algorithm.J. Supercomput.20207686302632910.1007/s11227‑019‑02816‑7
     [Google Scholar]
  8. ChenX. ChengL. LiuC. LiuQ. LiuJ. MaoY. MurphyJ. A WOA-based optimization approach for task scheduling in cloud computing systems.IEEE Syst. J.20201433117312810.1109/JSYST.2019.2960088
     [Google Scholar]
  9. AgarwalM. SrivastavaG.M.S. A genetic algorithm inspired task scheduling in cloud computing.International Conference on Computing, Communication and Automation (ICCCA), Greater Noida, India, 29-30 April, 201710.1109/CCAA.2016.7813746
     [Google Scholar]
  10. ZuoL. ShuL. DongS. ChenY. YanL. A multi-objective hybrid cloud resource scheduling method based on deadline and cost constraints.IEEE Access20175220672208010.1109/ACCESS.2016.2633288
     [Google Scholar]
  11. ZhuW. ZhuangY. ZhangL. A three-dimensional virtual resource scheduling method for energy saving in cloud computing.Future Gener. Comput. Syst.201769667410.1016/j.future.2016.10.034
     [Google Scholar]
  12. SinghS. ChanaI. A survey on resource scheduling in cloud computing: Issues and challenges.J. Grid Comput.201614221726410.1007/s10723‑015‑9359‑2
     [Google Scholar]
  13. JenaR.K. Energy efficient task scheduling in cloud environment.Energy Procedia.201714122222710.1016/j.egypro.2017.11.096
     [Google Scholar]
  14. MellekY. KayaA. Multi objective task scheduling algorithm based on SLA and processing time suitable for cloud environment.Comput. Commun.20201514
     [Google Scholar]
  15. VelliangiriS. KarthikeyanP. Arul XavierV.M. BaswarajD. Hybrid electro search with genetic algorithm for task scheduling in cloud computing.Ain Shams Eng. J.202112163163910.1016/j.asej.2020.07.003
     [Google Scholar]
  16. AgarwalM. SrivastavaG.M.S. Genetic algorithm-enabled Particle Swarm Optimization (PSOGA)-based task scheduling in cloud computing environment.Int. J. Inf. Technol. Decis. Mak20181741237126710.1142/S0219622018500244
     [Google Scholar]
  17. YanM. FengG. ZhouJ. SunY. LiangY.C. Intelligent resource scheduling for 5G radio access network slicing.IEEE Trans. Vehicular Technol.20196887691770310.1109/TVT.2019.2922668
     [Google Scholar]
  18. SaeediS. KhorsandR. Ghandi BidgoliS. RamezanpourM. Improved many-objective particle swarm optimization algorithm for scientific workflow scheduling in cloud computing.Comput. Ind. Eng.2020147July10664910.1016/j.cie.2020.106649
     [Google Scholar]
  19. GuoS. XiaoB. YangY. YangY. Energy-efficient dynamic offloading and resource scheduling in mobile cloud computing.IEEE INFOCOM 2016 - The 35th Annual IEEE International Conference on Computer Communications, San Francisco, CA, USA, 10-14 April, 201610.1109/INFOCOM.2016.7524497
     [Google Scholar]
  20. MehtaH. PrasadV.K. Efficient resource scheduling in cloud computing.Int. J. Adv. Res. Comput. Sci.20178
     [Google Scholar]
  21. SinghS. ChanaI. EARTH: Energy-aware autonomic resource scheduling in cloud computing.J. Intell. Fuzzy Syst.20163031581160010.3233/IFS‑151866
     [Google Scholar]
  22. WangX. WangK. WuS. DiS. JinH. YangK. OuS. Dynamic resource scheduling in mobile edge cloud with cloud radio access network.IEEE Trans. Parallel Distrib. Syst.201829112429244510.1109/TPDS.2018.2832124
     [Google Scholar]
  23. BirjeM. ChallagidadP. TapaleM. T. GoudarR. H. Security issues and countermeasures in cloud computing.International Conference on Data Engineering and Communication System2015
     [Google Scholar]
  24. RashidZ.N. ZebariS.R.M. SharifK.H. JacksiK. Distributed cloud computing and distributed parallel computing: A review.International Conference on Advanced Science and Engineering (ICOASE), Duhok, Iraq, 09-11 Oct, 201810.1109/ICOASE.2018.8548937
     [Google Scholar]
  25. PraveenS.P. RaoK.T. JanakiramaiahB. Effective allocation of resources and task scheduling in cloud environment using social group optimization.Arab. J. Sci. Eng.20184384265427210.1007/s13369‑017‑2926‑z
     [Google Scholar]
  26. ZhanZ.H. LiuX.F. GongY.J. ZhangJ. ChungH.S.H. LiY. Cloud computing resource scheduling and a survey of its evolutionary approaches.ACM Comput. Surv.201547413310.1145/2788397
     [Google Scholar]
  27. JiangF. WangK. DongL. PanC. XuW. YangK. Deep-learning-based joint resource scheduling algorithms for hybrid mec networks.IEEE Internet Things J.2020776252626510.1109/JIOT.2019.2954503
     [Google Scholar]
  28. ChengD. ZhouX. LamaP. WuJ. JiangC. Cross-platform resource scheduling for spark and MapReduce on YARN.IEEE Trans. Comput.20176681341135310.1109/TC.2017.2669964
     [Google Scholar]
  29. PriyaV. Sathiya KumarC. KannanR. Resource scheduling algorithm with load balancing for cloud service provisioning.Appl. Soft Comput.20197641642410.1016/j.asoc.2018.12.021
     [Google Scholar]
  30. SinghS. ChanaI. QRSF: QoS-aware resource scheduling framework in cloud computing.J. Supercomput.201571124129210.1007/s11227‑014‑1295‑6
     [Google Scholar]
  31. LiQ. GuoY. Optimization of resource scheduling in cloud computing.12th International Symposium on Symbolic and Numeric Algorithms for Scientific ComputingTimisoara, Romania, 23-26 Sep, 201010.1109/SYNASC.2010.8
     [Google Scholar]
  32. StrumbergerI. BacaninN. TubaM. TubaE. Resource scheduling in cloud computing based on a hybridized whale optimization algorithm.Appl. Sci.2019922489310.3390/app9224893
     [Google Scholar]
  33. LuoQ. HuS. LiC. LiG. ShiW. Resource scheduling in edge computing: A survey.IEEE Commun. Surv. Tutor.20212342131216510.1109/COMST.2021.3106401
     [Google Scholar]
  34. RakroukiM.A. AlharbeN. QoS-aware algorithm based on task flow scheduling in cloud computing environment.Sensors2022227263210.3390/s2207263235408246
     [Google Scholar]
  35. GillS.S. BuyyaR. ChanaI. SinghM. AbrahamA. BULLET: Particle swarm optimization based scheduling technique for provisioned cloud resources.J. Netw. Syst. Manage.201826236140010.1007/s10922‑017‑9419‑y
     [Google Scholar]
  36. KumarM. SharmaS.C. PSO-based novel resource scheduling technique to improve QoS parameters in cloud computing.Neural Comput. Appl.20203216121031212610.1007/s00521‑019‑04266‑x
     [Google Scholar]
  37. BezdanT. ZivkovicM. BacaninN. StrumbergerI. TubaE. TubaM. Multi-objective task scheduling in cloud computing environment by hybridized bat algorithm.J. Intell. Fuzzy Syst.202142141142310.3233/JIFS‑219200
     [Google Scholar]
  38. AbazariF. AnalouiM. TakabiH. FuS. MOWS: Multi-objective workflow scheduling in cloud computing based on heuristic algorithm.Simul. Model Pract. Theory20199311913210.1016/j.simpat.2018.10.004
     [Google Scholar]
  39. LinW. XuS. HeL. LiJ. Multi-resource scheduling and power simulation for cloud computing.Inf. Sci.2017397-39816818610.1016/j.ins.2017.02.054
     [Google Scholar]
  40. IsmayilovG. TopcuogluH.R. Neural network based multi-objective evolutionary algorithm for dynamic workflow scheduling in cloud computing.Future Gener. Comput. Syst.202010230732210.1016/j.future.2019.08.012
     [Google Scholar]
  41. DubeyK. KumarM. SharmaS.C. Modified HEFT algorithm for task scheduling in cloud environment.Procedia Comput. Sci.201812572573210.1016/j.procs.2017.12.093
     [Google Scholar]
  42. LiG. LiuY. WuJ. LinD. ZhaoS. Methods of resource scheduling based on optimized fuzzy clustering in fog computing.Sensors2019199212210.3390/s1909212231071923
     [Google Scholar]
  43. SunY. LinF. XuH. Multi-objective optimization of resource scheduling in fog computing using an improved NSGA-II.Wirel. Pers. Commun.201810221369138510.1007/s11277‑017‑5200‑5
     [Google Scholar]
  44. HuangX. LiC. ChenH. AnD. Task scheduling in cloud computing using particle swarm optimization with time varying inertia weight strategies.Cluster Comput.20202321137114710.1007/s10586‑019‑02983‑5
     [Google Scholar]
  45. ChenX. LongD. Task scheduling of cloud computing using integrated particle swarm algorithm and ant colony algorithm.Cluster Comput.201922S22761276910.1007/s10586‑017‑1479‑y
     [Google Scholar]
  46. KongW. LeiY. MaJ. Virtual machine resource scheduling algorithm for cloud computing based on auction mechanism.Optik2016127125099510410.1016/j.ijleo.2016.02.061
     [Google Scholar]
  47. LiX. WanJ. DaiH.N. ImranM. XiaM. CelestiA. A hybrid computing solution and resource scheduling strategy for edge computing in smart manufacturing.IEEE Trans. Industr. Inform.20191574225423410.1109/TII.2019.2899679
     [Google Scholar]
  48. VijayasekaranG. DuraipandianM. An efficient clustering and deep learning based resource scheduling for edge computing to integrate cloud-IoT.Wirel. Pers. Commun.202212432029204410.1007/s11277‑021‑09442‑8
     [Google Scholar]
  49. Arul XavierV.M. AnnaduraiS. Chaotic social spider algorithm for load balance aware task scheduling in cloud computing.Cluster Comput.201922S128729710.1007/s10586‑018‑1823‑x
     [Google Scholar]
  50. YuH. Evaluation of cloud computing resource scheduling based on improved optimization algorithm.Complex Intell. Sys.2021741817182210.1007/s40747‑020‑00163‑2
     [Google Scholar]
  51. ZhouG. TianW. BuyyaR. Deep reinforcement learning-based methods for resource scheduling in cloud computing: A review and future directions.arxiv2021202104086
     [Google Scholar]
  52. KhallouliW. HuangJ. Cluster resource scheduling in cloud computing: Literature review and research challenges.J. Supercomput.20227856898694310.1007/s11227‑021‑04138‑z
     [Google Scholar]
  53. DeS. An efficient technique of resource scheduling in cloud using graph coloring algorithm.Glob. Transit. Proc.20223116917610.1016/j.gltp.2022.03.005
     [Google Scholar]
  54. AronR. AbrahamA. Resource scheduling methods for cloud computing environment: The role of meta-heuristics and artificial intelligence.Eng. Appl. Artif. Intell.2022116August10534510.1016/j.engappai.2022.105345
     [Google Scholar]
  55. RahimikhanghahA. TajkeyM. RezazadehB. RahmaniA.M. Resource scheduling methods in cloud and fog computing environments: A systematic literature review.Cluster Comput.202225291194510.1007/s10586‑021‑03467‑1
     [Google Scholar]
  56. RashidifarR. BouzaryH. ChenF.F. Resource scheduling in cloud-based manufacturing system: A comprehensive survey.Int. J. Adv. Manuf. Technol.202212211-124201421910.1007/s00170‑022‑09873‑y
     [Google Scholar]
  57. YadavC. YadavV. KumarJ. Secure and reliable data sharing scheme using attribute-based encryption with weighted attribute-based encryption in cloud environment.Int. J. Elec. Elec. Res.202193485610.37391/IJEER.090305
     [Google Scholar]
  58. YadavV. KundraP. VermaD. Role of iot and big data support in healthcare.Adv. Intell. Sys. Comput.2021108644545510.1007/978‑981‑15‑1275‑9_36
     [Google Scholar]
  59. LuY. SunN. An effective task scheduling algorithm based on dynamic energy management and efficient resource utilization in green cloud computing environment.Cluster Comput.201922S151352010.1007/s10586‑017‑1272‑y
     [Google Scholar]
  60. ElsherbinyS. EldaydamonyE. AlrahmawyM. ReyadA.E. An extended intelligent water drops algorithm for workflow scheduling in cloud computing environment.Egyptian Inform. J.2018191335510.1016/j.eij.2017.07.001
     [Google Scholar]
  61. WangY. TaoX. ZhaoF. TianB. Vera Venkata SaiA.M. SLA-aware resource scheduling algorithm for cloud storage.EURASIP J. Wirel. Commun. Netw.202020201610.1186/s13638‑019‑1604‑0
     [Google Scholar]
  62. ShukriS.E. Al-SayyedR. HudaibA. MirjaliliS. Enhanced multi-verse optimizer for task scheduling in cloud computing environments.Expert Syst. Appl.202116811423010.1016/j.eswa.2020.114230
     [Google Scholar]
  63. GuptaS. IyerS. AgarwalG. ManoharanP. AlgarniA.D. AldehimG. RaahemifarK. Efficient prioritization and processor selection schemes for HEFT algorithm: A makespan optimizer for task scheduling in cloud environment.Electronics20221116255710.3390/electronics11162557
     [Google Scholar]
  64. Abd ElazizM. AttiyaI. An improved Henry gas solubility optimization algorithm for task scheduling in cloud computing.Artif Intell. Rev.2021543599363710.1007/s10462‑020‑09933‑3
     [Google Scholar]
  65. RahulM. YadavV. A survey on state-of-the-art of cloud computing, its challenges and solutions.Recent Trends in Communication and Electronic.CRC Press2021
     [Google Scholar]
/content/journals/raeeng/10.2174/0123520965255860231012020315
Loading
An Evolutionary Review on Resource Scheduling Algorithms Used for Cloud Computing with IoT Network
Recent Advances in Electrical & Electronic Engineering 18, 119 (2025); https://doi.org/10.2174/0123520965255860231012020315
/content/journals/raeeng/10.2174/0123520965255860231012020315
/content/journals/raeeng/10.2174/0123520965255860231012020315
Loading

Data & Media loading...


  • Article Type:     Review Article
Keyword(s): Cloud computing; IoT; resource; scheduling; virtual machine; virtual machine (VM)

Most Cited Most Cited RSS feed

This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error
Please enter a valid_number test