Migration Management in Sensor-Cloud Networks

Computer and Knowledge Engineering

مقاله 1، دوره 1، شماره 2، اسفند 2018، صفحه 1-12   

نوع مقاله: Internet of Thing (IoT)-Yaghmaee

شناسه دیجیتال (DOI): 10.22067/cke.v1i2.57729

نویسندگان

Seyed Amin Hosseini Seno^* ؛ Farahnaz Farazestanian

Ferdowsi University of Mashhad

چکیده

Placement of virtual sensors in servers of cloud environment is one of the most important issues in resource management of sensor-cloud networks. Virtual sensors allocate resources of cloud servers to themselves, run different applications and use equivalent physical sensors. Selecting an appropriate method for placement of virtual sensors on cloud servers has a significant impact on resource management and energy consumption. Also, because of the real-time requirements of sensor-cloud networks, traffic-aware placement is necessary to minimize delay in a network and respond to user requests in the shortest possible time. A new method for traffic-aware placement and migration of virtual sensors in sensor-cloud networks is proposed using the unique characteristics of sensor-cloud networks such as grouping virtual sensors and sharing them among different applications. This approach tries to meet the needs of users and the quality of service expected by the applications. Also, the resources of cloud servers are managed properly in this approach. The results of simulation show an optimization in energy consumption and also a reduction in traffic costs and reduction in service level agreement violation.

کلیدواژه‌ها

Sensor-cloud networks؛ virtual sensors؛ resource management؛ Migration؛ Energy Consumption؛ traffic

مراجع

[1]A. Alamri, W. S. Ansari, M. M. Hassan, M. S. Hossain, A. Alelaiwi, and M. A. Hossain, "A Survey on Sensor-Cloud: Architecture, Applications, and Approaches", International Journal of Distributed Sensor Networks, vol. 2013, p. 18, Art. no. 917923, 2013.

[2]M. Körner, A. Stanik, O. Kao, M. Wallschläger, and S. Becker, "The ASCETiC Testbed - An Energy Efficient Cloud Computing Environment", in Testbeds and Research Infrastructures for the Development of Networks and Communities: 11th International Conference, TRIDENTCOM 2016, Hangzhou, China, June 14-15, 2016, Revised Selected Papers, S. Guo, G. Wei, Y. Xiang, X. Lin, and P. Lorenz, Eds. Cham: Springer International Publishing, pp. 93-102, 2016.

[3]Piraghaj, S. Fotuhi, A. V. Dastjerdi, R. N. Calheiros, and R. Buyya, A Survey and Taxonomy of Energy Efficient Resource Management Techniques in Platform as a Service Cloud. Handbook of Research on End-to-End Cloud Computing Architecture Design, 2016.

[4]S. Kabadayi, A. Pridgen, and C. Julien, "Virtual sensors: Abstracting data from physical sensors", in In Proceedings of the International Symposium on on World of Wireless, Mobile and Multimedia Networks, Buffalo-Niagara Falls, NY, 2006.

[5]S. Bose, N. Mukherjee, and S. Mistry, "Environment Monitoring in Smart Cities Using Virtual Sensors", in 2016 IEEE 4th International Conference on Future Internet of Things and Cloud (FiCloud), pp. 399-404, 2016.

[6]M. Yuriyama and T. Kushida, "Sensor-Cloud Infrastructure - Physical Sensor Management with Virtualized Sensors on Cloud Computing", presented at the 13th International Conference on Network-Based Information Systems, Takayama, 2010.

[7]A. Beloglazov, J. Abawajy, and R. Buyya, "Energy-aware resource allocation heuristics for efficient management of data centers for cloud computing", Future Generation Computer Systems, vol. 28, no. 5, pp. 755-768, 2012.

[8]D. Huang, D. Yang, H. Zhang, and L. Wu, "Energy-aware virtual machine placement in data centers", presented at the Global Communications Conference (GLOBECOM), Anaheim, CA, 2012.

[9]F. Song, D. Huang, H. zhou, and I. You, "application-aware virtual machine placement in data centers", presented at the Sixth International Conference on Innovative Mobile and Internet Services in Ubiquitous Computing (IMIS), 2012.

[10]C. Clark et al., "Live migration of virtual machines", in Proceedings of the 2nd conference on Symposium on Networked Systems Design & Implementation, vol. 2, pp. 273-286: USENIX Association, 2005.

[11]U. Deshpande and K. Keahey, "Traffic-sensitive Live Migration of Virtual Machines", Future Generation Computer Systems, 2016.

[12]P. Barham et al., "Xen and the Art of Virtualization", ACM SIGOPS Operating Systems Review, vol. 37, no. 5, pp. 164-177, 2003.

[13]V. Shrivastava, P. Zerfos, K. W. Lee, H. Jamjoom, Y. H. Liu, and S. Banerjee, "Application-aware virtual machine migration in data centers", in INFOCOM, Shanghai, 2011.

[14]T. Chen, X. Gao, and G. Chen, "Optimized Virtual Machine Placement with Traffic-Aware Balancing in Data Center Networks", Scientific Programming, 2016.

[15]D. S. Dias and M. K. Costa, "Online traffic-aware virtual machine placement in data center networks", presented at the Global Information Infrastructure and Networking Symposium (GIIS), Choroni, 2012.

[16]J. Liu, J. Guo, and D. Ma, "Traffic Aware Virtual Machine Packing in Cloud Data Centers", in 2016 IEEE 2nd International Conference on Big Data Security on Cloud (BigDataSecurity), IEEE International Conference on High Performance and Smart Computing (HPSC), and IEEE International Conference on Intelligent Data and Security (IDS), pp. 256-261, 2016.

[17]H. T. Vu and S. Hwang, "A Traffic and Power-aware Algorithm for Virtual Machine Placement in Cloud Data Center", International Journal of Grid & Distributed Computing, vol. 7, no. 1, pp. Pages 21-32, 2014.

[18]A. Beloglazov and R. Buyya, "Optimal online deterministic algorithms and adaptive heuristics for energy and performance efficient dynamic consolidation of virtual machines in Cloud data centers", Concurrency and Computation: Practice and Experience, vol. 24, no. 13, pp. 1397-1420, 2012.

[19] M. F. H. Bhuiyan and C. Wang, "Energy-Efficient Virtual Machine Management in Heterogeneous Environment: Challenges, Approaches and Opportunities", presented at the International Conference on Systems, Man, and Cybernetics (SMC), Manchester, 2013.

[20] M. Sharifi, H. Salimi, and M. Najafzadeh, "Power-efficient distributed scheduling of virtual machines using workload-aware consolidation techniques", The Journal of Supercomputing, vol. 61, no. 1, pp. 46-66, 2012.

[21] X. Liu and L. Fan, "Priority-aware Gray-box Placement of Virtual Machines in Cloud Platforms", presented at the arXiv preprint arXiv:1307.6622, 2013.

[22] S. Madria, V. Kumar, and R. Dalvi, "Sensor cloud: A cloud of virtual sensors", Software, IEEE, vol. 31, no. 2, pp. 70-77, 2014.

[23] S. K. Madria, "Sensor Cloud: A Cloud of Sensor Networks", 2016 IEEE International Conference on Cloud Engineering Workshop (IC2EW), 2016.

[24] R. Calheiros, R. Ranjan, A. Beloglazov, C. Rose, and R. Buyya, "CloudSim: a toolkit for modeling and simulation of Cloud computing environments and evaluation of resource provisioning algorithms", Software: Practice and Experience, vol. 41, no. 1, pp. 23–50, 2011.

[25] "Cisco Data Center Infrastructure 2.5 Design Guide", May 2008.

[26] A. Gupta and N. Mukherjee, "Implementation of virtual sensors for building a sensor-cloud environment", in 2016 8th International Conference on Communication Systems and Networks (COMSNETS), pp. 1-8, 2016.

[27] R. Buyya, A. Beloglazov, and J. H. Abawajy, "Energy-Efficient Management of Data Center Resources for Cloud Computing: A Vision, Architectural Elements, and Open Challenges", CoRR, vol. abs/1006.0308, 2010.

[28] H. Goudarzi and M. Pedram, "Hierarchical SLA-Driven Resource Management for Peak Power-Aware and Energy-Efficient Operation of a Cloud Datacenter", IEEE Transactions on Cloud Computing, vol. 4, no. 2, pp. 222-236, 2016.