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  A Service Level Agreement Effective Optimal Cloud Based Road Traffic Management System  
  Authors : Md. Rafeeq; Dr C.Sunil Kumar; Dr. N. Subhash Chandra; Dr Arunavaranasi
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With the fabulous growth of population and the increasing road traffic, the demand for optimized traffic data collection and management framework is also demanding. The collection of traffic data using various sensors and other capture devices are been addressed in multiple researches deploying the mechanism using geodetically static sensor agents. However to avoid the congestion, the parallel research works has proposed frameworks based on cloud based data centers. Thought, those approaches does not propose any technique to decrease the cost and improve the service level agreements to match with the existing industry and research demands. Thus, this paper proposes a cloud based automatized framework for VM (VM) migration to increase the Service Level Agreement (SLA). Without negotiating the cost for storage and energy. The major attainment of this work is to minimize the SLA violation compared to existing VM migration methods for load balancing (LB). The extensive practical demonstrations of virtualization and migration advantages are also carried out in this work. With the extensive experimental setup the work provides the comparative analysis of simulations for popular existing methods and the proposed framework. ?


Published In : IJCSN Journal Volume 6, Issue 5

Date of Publication : October2017

Pages : 580-587

Figures :02

Tables : 10


Md. Rafeeq : is working as an Associate Professor in Department of Computer Science and Engineering at CMR Technical Campus, Hyderabad. He completed B. Tech, M. Tech in Computer science and engineering and Pursuing PhD (CSE) in Cloud Computing at JNTHU Hyd. He is having 12 years of teaching experience. He has 15 research publications at International/National Journals and Conferences

Dr. C. Sunil Kumar : did his B.E in Computer Science and Engineering from University of Madras, Vellore, India, in 1998, M. Tech in Computer Science and Engineering from SRM university, Chennai, India, in 2005 and PhD (CSE) from JNTUH in 2012. Currently, he is Professor in IT, SNIST, Hyderabad, India. He has 58 research publications at International / National Journals and Conferences. Research interests are Distributed Databases, Data warehousing and Data Mining.

Dr. N. Subhash Chandra : Professor in CSE, CVRCE. He is actively engaged in research work, six scholars are pursuing their doctoral work under his supervision. He has got more than 35- research publications to his credit including in prestigious international/ national journals. He has been on the panel of Referees for many prestigious international & national conferences. He was conferred with the prestigious Ideal Teacher and Best Teacher awards. He has been honored with Best paper award in the Map world forum, 2007.

Dr. Aruna Varanasi : did her M. Tech in Computer Science and Engineering from Andhra University, Visakhapatnam in the year 2003, PhD in C.S.E, JNTU Hyderabad, awarded in the year 2014. Currently, she is working as Professor and head in the Department of Computer Science and Engineering (CSE), Sreenidhi Institute of Science and Technology (SNIST), Hyderabad, India. She was awarded “Suman Sharma” by Institute of Engineers (India), Calcutta for securing highest marks among women in India in AMIE course. She award as best faculty from Accenture and SNIST. She has 35 research publications at international/ National journals and conferences.


optimal migration, SLA improvement, VM, image formats, cost, performance, evaluation matrix

LB can be achieved through VM migration. However the existing migration techniques constraints to improve the SLA and often compromise to a higher scale on the other performance evaluation factors. This work, demonstrates the optimal three phase VM migration technique with up to 70% improvement to retain SLA compared to the other VM migration technique. The work also elaborates on the VM image operability most suitable for migration and determines the best format. However the proposed technique is independent of the VM image format and demonstrates the same improvement.


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