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Novel probabilistic resource migration algorithm for cross-cloud live migration of virtual machines in public cloud

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Abstract

In cloud computing environment, cross-cloud live migration of virtual machines (VMs) is a major concern in these days. Cloud computing provides the users with huge, versatile and on-demand access to a bulk of customizable and configurable registered physical devices or things. It helps organizations or enterprises to share data efficiently by privately owned cloud or by the third-party servers. This type of sharing of bulky data through cloud is more efficient and reliable. In an enterprise environment, one of the essential capabilities of cloud infrastructure is VM migration. VM live migration basically involves the transference of instances that includes the operating system, runtime memory pages and active CPU states from source hub to the destination hub. In this paper, we have discussed on resource allocation algorithm which performs better in utilization of CPU, time and memory. Our proposed algorithm deals with the effective utilization of unoccupied memory, and we have also measured VM memory stack flow of total memory for cloud computing architecture.

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References

  1. Abderrahim W, Choukair Z (2017) The three-dimensional model for dependability integration in cloud computing. Ann Telecommun 72(5–6):371–384

    Article  Google Scholar 

  2. Adhikary T, Das AK, Razzaque MA, Almogren A, Alrubaian M, Hassan MM (2016) Quality of service aware reliable task scheduling in vehicular cloud computing. Mob Netw Appl 21(3):482–493

    Article  Google Scholar 

  3. Agarwal A, Raina S (2012) Live migration of virtual machines in cloud. Int J Sci Res Publ 2(6):45–52

    Google Scholar 

  4. Alkhanak EN, Lee SP, Khan SUR (2015) Cost-aware challenges for workflow scheduling approaches in cloud computing environments: taxonomy and opportunities. Future Gener Comput Syst 50:3–21

    Article  Google Scholar 

  5. Almutairi A, Sarfraz MI, Ghafoor A (2018) Risk-aware management of virtual resources in access controlled service-oriented cloud datacenters. IEEE Trans Cloud Comput 6(1):168–181

    Article  Google Scholar 

  6. Babukarthik RG, Raju R, Dhavachelvan P (2012) Energy-aware scheduling using hybrid algorithm for cloud computing. In: 2012 Third International Conference on Computing Communication & Networking Technologies (ICCCNT). IEEE, pp 1–6

  7. Breitgand D, Kutiel G, Raz D (2011) Cost-aware live migration of services in the cloud. In: Hot-ICE’11 Proceedings of the 11th USENIX Conference on Hot Topics in Management of Internet, cloud, and Enterprise Networks and Services, p 3

  8. Callau-Zori M, Samoila L, Orgerie AC, Pierre G (2017) An experiment-driven energy consumption model for virtual machine management systems. Sustain Comput Inform Syst 18:163–174

    Google Scholar 

  9. Chen X, Zhang J, Li J, Li X (2013) Resource virtualization methodology for on-demand allocation in cloud computing systems. SOCA 7(2):77–100

    Article  Google Scholar 

  10. Dave A, Patel B, Bhatt G (2016) Load balancing in cloud computing using optimization techniques: a study. In: International Conference on Communication and Electronics Systems (ICCES). IEEE, pp 1–6

  11. Doss S, Nayyar A, Suseendran G, Tanwar S, Khanna A, Son LH, Thong PH (2018) APD-JFAD: accurate prevention and detection of jelly fish attack in MANET. IEEE Access 6:56954–56965

    Article  Google Scholar 

  12. Fukai T, Shinagawa T, Kato K (2018) Live migration in bare-metal clouds. IEEE Trans Cloud Comput. https://doi.org/10.1109/TCC.2018.2848981

    Article  Google Scholar 

  13. Gai K, Qiu M, Zhao H (2016) Cost-aware multimedia data allocation for heterogeneous memory using genetic algorithm in cloud computing. IEEE Trans Cloud Comput. https://doi.org/10.1109/TCC.2016.2594172

    Article  Google Scholar 

  14. Giap CN, Son LH, Chiclana F (2018) Dynamic structural neural network. J Intell Fuzzy Syst 34:2479–2490

    Article  Google Scholar 

  15. Hai DT, Son H, Vinh LT (2017) Novel fuzzy clustering scheme for 3D wireless sensor networks. Appl Soft Comput 54:141–149

    Article  Google Scholar 

  16. Hemanth DJ, Anitha J, Son LH (2018) Brain signal based human emotion analysis by circular back propagation and Deep Kohonen neural networks. Comput Electr Eng 68:170–180

    Article  Google Scholar 

  17. Hemanth DJ, Anitha J, Son LH, Mittal M (2018) Diabetic retinopathy diagnosis from retinal images using modified Hopfield neural network. J Med Syst 42(12):247

    Article  Google Scholar 

  18. Hemanth J, Anitha J, Naaji A, Geman O, Popescu D, Son LH (2018) A Modified deep convolutional neural network for abnormal brain image classification. IEEE Access 7(1):4275–4283

    Google Scholar 

  19. Hirofuchi T, Lebre A, Pouilloux L (2018) SimGrid VM: virtual machine support for a simulation framework of distributed systems. IEEE Trans Cloud Comput 6(1):221–234

    Article  Google Scholar 

  20. Jung G, Gnanasambandam N, Mukherjee T (2012) Synchronous parallel processing of big-data analytics services to optimize performance in federated clouds. In: 2012 IEEE 5th International Conference Cloud Computing (CLOUD). IEEE, pp 811–818

  21. Kapil D, Pilli E, Joshi R (2013) Live virtual machine migration techniques: survey and research challenges. In: 2013 3rd IEEE International Advance Computing Conference (IACC), p p 78–83

  22. Kapoor R, Gupta R, Kumar R, Son LH, Jha S (2019) New scheme for underwater acoustically wireless transmission using direct sequence code division multiple access in MIMO systems. Wirel Netw. https://doi.org/10.1007/s11276-018-1750-z

    Article  Google Scholar 

  23. Kapoor R, Gupta R, Son LH, Jha S, Kumar R (2018) Boosting performance of power quality event identification with KL divergence measure and standard deviation. Measurement 126:134–142

    Article  Google Scholar 

  24. Kapoor R, Gupta R, Son LH, Jha S, Kumar R (2018) Detection of power quality event using histogram of oriented gradients and support vector machine. Measurement 120:52–75

    Article  Google Scholar 

  25. Lin W, Liang C, Wang JZ, Buyya R (2014) Bandwidth-aware divisible task scheduling for cloud computing. Softw Pract Exp 44(2):163–174

    Article  Google Scholar 

  26. Liu H, Abraham A, Snášel V, McLoone S (2012) Swarm scheduling approaches for work-flow applications with security constraints in distributed data-intensive computing environments. Inf Sci 192:228–243

    Article  Google Scholar 

  27. Long HV, Ali M, Khan M, Tu DN (2019) A novel approach for fuzzy clustering based on neutrosophic association matrix. Comput Ind Eng. https://doi.org/10.1016/j.cie.2018.11.007

    Article  Google Scholar 

  28. Malekloo MH, Kara N, El Barachi M (2018) An energy efficient and SLA compliant approach for resource allocation and consolidation in cloud computing environments. Sustain Comput Inform Syst 17:9–24

    Google Scholar 

  29. Malik V, Barde C (2015) Live migration of virtual machines in cloud environment using prediction of CPU usage. Int J Comput Appl 117(23):124–131

    Google Scholar 

  30. Mishra SK, Puthal D, Sahoo B, Jayaraman PP, Jun S, Zomaya AY, Ranjan R (2018) Energy-efficient VM-placement in cloud data center. Sustain Comput Inform Syst 20:48–55

    Google Scholar 

  31. Osanaiye O, Chen S, Yan Z, Lu R, Choo K, Dlodlo M (2017) From cloud to fog computing: a review and a conceptual live VM migration framework. IEEE Access 5:8284–8300

    Article  Google Scholar 

  32. Panda SK, Jana PK (2015) Efficient task scheduling algorithms for heterogeneous multi-cloud environment. J Supercomput 71(4):1505–1533

    Article  Google Scholar 

  33. Phan LT, Zhang Z, Zheng Q, Loo BT, Lee I (2011) An empirical analysis of scheduling techniques for real-time cloud-based data processing. In: 2011 IEEE International Conference on Service-Oriented Computing and Applications (SOCA). IEEE, pp 1–8

  34. Phuong PTM, Thong PH, Son LH (2018) Theoretical analysis of picture fuzzy clustering: convergence and property. J Comput Sci Cybern 34(1):17–32

    Article  Google Scholar 

  35. Robinson YH, Julie EG, Saravanan K, Kumar R, Son LH (2019) FD-AOMDV: fault-tolerant disjoint ad-hoc on-demand multipath distance vector routing algorithm in mobile ad-hoc networks. J Ambient Intell Humaniz Comput. https://doi.org/10.1007/s12652-018-1126-3

    Article  Google Scholar 

  36. Sampaio AM, Barbosa JG (2013) Optimizing energy-efficiency in high-available scientific cloud environments. In: 2013 Third International Conference on Cloud and Green Computing (CGC). IEEE, pp 76–83

  37. Saravanan K, Anusuya E, Kumar R, Son LH (2018) Real-time water quality monitoring using Internet of Things in SCADA. Environ Monit Assess 190(9):556

    Article  Google Scholar 

  38. Saravanan K, Aswini S, Kumar R, Son LH (2019) How to prevent maritime border collision for fisheries? A design of real-time automatic identification system. Earth Sci Inf. https://doi.org/10.1007/s12145-018-0371-5

    Article  Google Scholar 

  39. Satpathy A, Addya SK, Turuk AK, Majhi B, Sahoo G (2017) Crow search based virtual machine placement strategy in cloud data centers with live migration. Comput Electr Eng. https://doi.org/10.1016/j.compeleceng.2017.12.032

    Article  Google Scholar 

  40. Seo D, Jeon YB, Lee SH, Lee KH (2016) Cloud computing for ubiquitous computing on M2 M and IoT environment mobile application. Clust Comput 19(2):1001–1013

    Article  Google Scholar 

  41. Sharma P, Lee S, Guo T, Irwin D, Shenoy P (2018) Managing risk in a derivative IaaS cloud. IEEE Trans Parallel Distrib Syst 29(8):1750–1765

    Article  Google Scholar 

  42. Singh K, Singh K, Son LH, Aziz A (2018) Congestion control in wireless sensor networks by hybrid multi-objective optimization algorithm. Comput Netw 138:90–107

    Article  Google Scholar 

  43. Singh N, Son LH, Chiclana F, Jean-Pierre M (2019) A new fusion of salp swarm with sine cosine for optimization of non-linear functions. Engineering with Computers. https://doi.org/10.1007/s00366-018-00696-8

    Article  Google Scholar 

  44. Singh RM, Paul S, Kumar A (2014) Task scheduling in cloud computing. Int J Comput Sci Inf Technol: IJCSIT 5(6):7940–7944

    Google Scholar 

  45. Sofia AS, Ganesh Kumar P (2018) Multi-objective task scheduling to minimize energy consumption and makespan of cloud computing using NSGA-II. J Netw Syst Manage 26(2):463–485

    Article  Google Scholar 

  46. Son LH (2015) A novel kernel fuzzy clustering algorithm for geo-demographic analysis. Inf Sci Inform Comput Sci Intell Syst Appl Int J 317(C):202–223

    Google Scholar 

  47. Son LH (2016) Generalized picture distance measure and applications to picture fuzzy clustering. Appl Soft Comput 46(C):284–295

    Article  Google Scholar 

  48. Son LH, Hai PV (2016) A novel multiple fuzzy clustering method based on internal clustering validation measures with gradient descent. Int J Fuzzy Syst 18(5):894–903

    Article  MathSciNet  Google Scholar 

  49. Son LH, Jha S, Kumar R, Chatterjee JM, Khari M (2019) Collaborative handshaking approaches between internet of computing and internet of things towards a smart world: a review from 2009–2017. Telecommun Syst. https://doi.org/10.1007/s11235-018-0481-x

    Article  Google Scholar 

  50. Son LH, Tien ND (2017) Tune up fuzzy C-means for big data: some novel hybrid clustering algorithms based on initial selection and incremental clustering. Int J Fuzzy Syst 19(5):1585–1602

    Article  MathSciNet  Google Scholar 

  51. Son LH, Tuan TM (2016) A cooperative semi-supervised fuzzy clustering framework for dental X-ray image segmentation. Expert Syst Appl 46:380–393

    Article  Google Scholar 

  52. Son LH, Fujita H (2019) Neural-fuzzy with representative sets for prediction of student performance. Appl Intell 49(1):172–187

    Article  Google Scholar 

  53. Son LH, Thong PH (2017) Some novel hybrid forecast methods based on picture fuzzy clustering for weather nowcasting from satellite image sequences. Appl Intell 46(1):1–15

    Article  Google Scholar 

  54. Son LH, Tuan TM (2017) Dental segmentation from X-ray images using semi-supervised fuzzy clustering with spatial constraints. Eng Appl Artif Intell 59:186–195

    Article  Google Scholar 

  55. Stavrinides GL, Karatza HD (2015) A cost-effective and qos-aware approach to scheduling real-time workflow applications in paas and saas clouds. In: 2015 3rd International Conference on Future Internet of Things and Cloud (FiCloud). IEEE, pp 231–239

  56. Tam NT, Hai DT, Son LH, Vinh LT (2018) Improving lifetime and network connections of 3D wireless sensor networks based on fuzzy clustering and particle swarm optimization. Wireless Netw 24(5):1477–1490

    Article  Google Scholar 

  57. Thong PH, Son LH (2016) Picture fuzzy clustering: a new computational intelligence method. Soft Comput 20(9):3549–3562

    Article  MATH  Google Scholar 

  58. Thong PH, Son LH (2016) A novel automatic picture fuzzy clustering method based on particle swarm optimization and picture composite cardinality. Knowl-Based Syst 109:48–60

    Article  Google Scholar 

  59. Thong PH, Son LH (2016) Picture fuzzy clustering for complex data. Eng Appl Artif Intell 56:121–130

    Article  Google Scholar 

  60. Tsai JT, Fang JC, Chou JH (2013) Optimized task scheduling and resource allocation on cloud computing environment using improved differential evolution algorithm. Comput Oper Res 40(12):3045–3055

    Article  MATH  Google Scholar 

  61. Tsakalozos K, Verroios V, Roussopoulos M, Delis A (2017) Live VM migration under time-constrains in share-nothing IaaS-clouds. IEEE Trans Parallel Distrib Syst 28(8):2285–2298

    Article  Google Scholar 

  62. Tuan TM, Ngan TT, Son LH (2016) A novel semi-supervised fuzzy clustering method based on interactive fuzzy satisficing for dental X-ray image segmentation. Appl Intell 45(2):402–428

    Article  Google Scholar 

  63. Wang L, Gelenbe E (2018) Adaptive dispatching of tasks in the cloud. IEEE Trans Cloud Comput 6(1):33–45

    Article  Google Scholar 

  64. Xavier VA, Annadurai S (2018) Chaotic social spider algorithm for load balance aware task scheduling in cloud computing. Clust Comput. https://doi.org/10.1007/s10586-018-1823-x

    Article  Google Scholar 

  65. Xiong et al (2017) Layered virtual machine migration algorithm for network resource balancing in cloud computing. Front Comput Sci 8(2):187–198

    Google Scholar 

  66. Ye K, Jiang X, Huang D, Chen J, Wang B (2011) Live migration of multiple virtual machines with resource reservation in cloud computing environments. In: 2011 IEEE 4th International Conference on Cloud Computing, pp 48–53

  67. Zhang F, Liu G, Fu X, Yahyapour R (2018) A survey on virtual machine migration: challenges, techniques, and open issues. IEEE Commun Surv Tutor 20(2):1206–1243

    Article  Google Scholar 

  68. Zuo L, Shu L, Dong S, Chen Y, Yan L (2017) A multi-objective hybrid cloud resource scheduling method based on deadline and cost constraints. IEEE Access 5:22067–22080

    Article  Google Scholar 

  69. Zuo L, Shu L, Dong S, Zhu C, Zhou Z (2017) Dynamically weighted load evaluation method based on self-adaptive threshold in cloud computing. Mob Netw Appl 22(1):4–18

    Article  Google Scholar 

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Author information

Authors and Affiliations

  1. Department of Computer Science and Engineering, JIS College, Kalyani, India

    Souvik Pal

  2. Department of Computer Science and Engineering, LNCT College, Jabalpur, MP, India

    Raghvendra Kumar

  3. Institute of Research and Development, Duy Tan University, Da Nang, 550000, Vietnam

    Le Hoang Son

  4. VNU Information Technology Institute, Vietnam National University, Hanoi, Vietnam

    Le Hoang Son

  5. Department of Computer Science and Engineering, Anna University Regional Campus, Tirunelveli, India

    Krishnan Saravanan

  6. Department of Operations Research, Faculty of Computers and Informatics, Zagazig University, Zagazig, Sharqiyah, Egypt

    Mohamed Abdel-Basset

  7. University of California, Davis, USA

    Gunasekaran Manogaran

  8. Division of Data Science, Ton Duc Thang University, Ho Chi Minh City, 700000, Vietnam

    Pham Huy Thong

  9. Faculty of Information Technology, Ton Duc Thang University, Ho Chi Minh City, 700000, Vietnam

    Pham Huy Thong

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  1. Souvik Pal
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  2. Raghvendra Kumar
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  3. Le Hoang Son
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  4. Krishnan Saravanan
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  7. Pham Huy Thong
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Pal, S., Kumar, R., Son, L.H. et al. Novel probabilistic resource migration algorithm for cross-cloud live migration of virtual machines in public cloud. J Supercomput 75, 5848–5865 (2019). https://doi.org/10.1007/s11227-019-02874-x

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