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An Optimal Cloud Based Road Traffic Management System with Novel VM Machine Migration Technique

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An Optimal Cloud Based Road Traffic Management System with Novel VM Machine Migration Technique An Optimal Cloud Based Road Traffic Management System with Novel VM Machine Migration Technique Md. Rafeeq1, C. Sunil Kumar2, and N. Subhash Chandra3 1 CMR Technical Campus, Kandlakoya, medchal, hyd-501401, TS, India 2 SNIST, Yamnampet, Ghatkesar, Hyd 501301, TS-India 3 HITS, Keesara, Bogaram, Rangareddy - 501301, TS-India Email: {rafeeqmail, ccharupalli, subhashchandra.n.cse}@gmail.com Abstract—With the tremendous growth of population and the geodetically distributed servers [2], [3]. Multiple parallel increasing road traffic, the demand for optimized traffic data researches are been carried out to demonstrate the benefits collection and management framework is also increasing. The of load balancing on cloud based data centers as handling collection of traffic data using multiple sensors and other the high unexpected traffic generally referred to Cyber capture devices are been addressed in multiple researches Spikes. Making the application scalable based on demand deploying the mechanism using geodetically static sensor agents. Nevertheless to avoid the congestion, the parallel without degrading the performance, increases the research works has proposed frameworks based on cloud based reliability at the cost of VM migration. data centers. Thought, those approaches does not propose any However the recent researches constraint to achieve technique to reduce the cost and improve the service level the optimal SLA violation during VM Migration. Thus agreements to match with the current industry and research this work demonstrates A Service Level Agreement demands. Thus, this work proposes a cloud based automatized Effective Optimal Virtual Machine Migration Technique framework for virtual machine migration to increase the SLA for Load Balancing on Cloud Data Centers using without compromising the cost for storage and energy. The proposed three phase optimal virtual machine migration major achievement of this work is to minimize the SLA technique. violation compared to existing virtual machine migration techniques for load balancing. The extensive practical demonstrations of virtualization and migration benefits are also II. VIRTUALIZATION BENEFITS FOR CLOUD DATA carried out in this work. With the extensive experimental setup CENTERS the work furnishes the comparative analysis of simulations for This work also highlights the benefits of virtual popular existing techniques and the proposed framework. machine migrations and also evaluates the parameters influencing the performance and productivity [3]. Index Terms—Three phase optimal migration, SLA improvement, VM image formats, cost comparison, A. Open Access Control performance evaluation matrix TABLE I: PARAMETERS FOR OPEN ACCESS CONTROL [3] Access Permissions Parameter I. INTRODUCTION Parameter Name Virtual Machine Type Traditional Migration Load Balancing Techniques on cloud computing is the CPU Type Not Allowed Allowed generic framework based process where the generated Processing Allocation Allowed Allowed workloads are distributed over multiple data center resources. The load balancing techniques brings the Priority Allowed Allowed advantage of lower response time [1]. However the cost Memory Size Allowed Allowed of replication of resources is also to be taken care as an Buffer Not Allowed Allowed additional cost. The cloud data center based load Not Allowed, Access IDE Bus Allowed, Logical balancing is distinguished from the domain name service Physical Storage based load balancing. Capture Mode Not Allowed Allowed The domain name service load balancers deploys the Allowed, Library Group Allowed, Logical hardware and software components to balance load for Physical the hardware resources, whereas the cloud based load IP Address Allowed Allowed balancing techniques deploys the software algorithms or MAC Address Not Allowed Allowed protocols to distribute the load over multiple data center Network Partially Internal Network Allowed nodes. Also it is to be understood that, the cloud based Allowed load balancing techniques allows the customers to use the global or geodetically distributed services based on The Virtual Machines come with a reduced abstraction in the system level and allows the provider, Manuscript received December 25, 2016; revised May 23, 2017. customer and researchers to access more properties of doi:10.12720/jcm.11.5. the system. The access to computing environment data, The Virtual Machines are hosted by all service system level codes, hardware utilization statistics, traces providers with similar configurations but with added of the active application, failing and down timing advantages. Hence adopting to Virtual Machine component configurations and the guest operating computing is the best choice to avoid the lack of support system configuration parameters and the ability to and facility availability (Table IV). control them independently helps to understand the E. Optimal Manageability of Updates performance perimeters (Table I). Application on Virtual Machines hosted on cloud is B. Optimal Hardware Control always liable for automatic and regular updates from the Virtual Machines come with a flexibility to change or service provider without any extra cost. However in the alter the operating system and hardware components other side, hosting the traditional system demands the seamlessly. After the initial cost for setting up a virtual cost and time implications for updates environment, the users are free to modify the computing F. Optimal Migration Cost Control system including the operating system, libraries, tools and other supporting patches without investing the full Due to the tremendous competition in the cloud time needed for computing system change or upgrade service provider space, the drop of price for each (Table II). virtualization component used in the virtual machine configuration is dropping with an increasing speed. TABLE II: REDUCED HARDWARE UPGRADE CONSTRAINTS [4] Hence rather than up-gradation cost for traditional Parameter Parameter Name Accessibility systems, the cloud based virtual machines are very much Type Traditional Virtual cost effective (Table V). Machine Migration TABLE V: REDUCTION OF COST FOR VIRTUAL MACHINE MIGRATION / Version Available Available HOSTING (APPROX. COST) [5] Operating No Continuous System Interoperability Available Server Type Availability Amazon Microsoft Google IBM Patch Available Available Cloud Azure Cloud App Bluemix Patch Available Available Development Engine Cloud No Continuous Environment Device Driver Available Cloud Availability 2013 $0.64 $0.70 $0.63 $0.61 Version Control Available Available 2014 $0.48 $0.45 $0.49 $0.47 Configuration Configuration Delay Very High Low 2015 $0.35 $0.39 $0.31 $0.30 $0.28 $0.26 $0.29 C. Optimal Replication Control 2016 $0.26 The replication of the Virtual Machines using the Cost Compatibility is projected in this work (Fig. 1) snapshot feature allows the users to take timely and on demand backups of the virtual machine images. Thus the backups help to quickly reproduce the same computing environment without investing the complete setup time (Table III). TABLE III: REDUCED REPLICATION DURATION [4] Parameter Type Replication Time Traditional Virtual Machine Migration Windows Server 50 to 90 Mins Just in Time MAC Servers 40 to 60 Mins Just in Time Linux Servers 30 to 40 Mins Just in Time D. Service Provider Support for Virtual Machine Fig. 1. Cost for virtual machine migration/hosting [5]. Migration Henceforth it is been demonstrated that the virtual TABLE IV: SERVICE PROVIDER SUPPORT FOR MIGRATION [5] machine migration and hosting are been advocated by all Server Amazon Microsoft Google IBM Private Hosted major service providers. Type Cloud Azure App Bluemix Cloud Cloud Engine Cloud Cloud III. PROPOSED OPTIMAL MIGRATION FRAMEWORK Windows YES YES YES YES NO This work deploys a cost evaluation function to Server determine the most suitable virtual machine to be MAC YES YES YES YES NO migrated considering the least SLA violation. Servers The framework for optimal migration is presented Linux YES YES YES YES NO here (Fig. 2). Servers Fig. 2. Optimal framework virtual machine migration [6] The proposed framework is classified into three major n (1) algorithm components as VM identification, VM PhyCPUCapacity VM() i CPUCapacity migration and Cost Function. Algorithms for all three i1 phases are been discussed here: n (2) A. Virtual Machine Identification PhyMemoryCapacity VM() i MemoryCapacity The first phase of the algorithm analyses the highest i1 loaded node and migrates the virtual machine to the n available less loaded node. After identifying the source PhyIOCapacity VM() i IOCapacity (3) and destination, the algorithm identifies the virtual i1 machine to be migrated [6]. The outcome of this n algorithm is to obtain optimal load balanced condition Phy VM() i (4) for the data center after virtual machine migration. The NetworkCapacity NetworkCapacity i1 detail of the algorithm is explained here: Step-1.1. Calculate the load on each node in the data center ()PhyCPUCapacity Phy MemoryCapacity Phy IOCapacity Phy NetworkCapacity (5) Step-1.2. In the second step, the algorithm identifies MAX VM() i Source (9) the highest and lowest loaded node in the data center MIN VM() i Destination (10) Ifi j, then MAX i (6) MAX Step-1.4. After the calculation of the new load, the Elsej i, then MAX j source and destination nodes must obtain the optimal If , then load condition, where the loads are nearly equally i j MIN i balanced [6]. MIN (7) Elsej
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