Essay Example on Cloud computing is a widely used technology Today

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Abstract Cloud computing is a widely used technology today It works by accessing a network to a resource pool which can be quickly provided and released with less management constraints or service provider interaction The aim of our work is to find out the shortest path between each physical machines and transfer the virtual machines from overloaded physical machines inorder to avoid overloading We are using Dijkstra s algorithm to find out the shortest distance Followed by this process we calculate the cpu load And we transfer the virtual machines to the nearest physical machine with the minimum load Introduction Cloud computing is a model for enabling pervasive suitable on demand network access to a shared pool of composite computing resources e g networks servers storage applications and services that can be rapidly provisioned and released with minimal management effort or service provider interaction The essential characteristics of cloud computing includes on demand self service resource pooling rapid elasticity measured service 



Various services provided by the cloud architecture are Software as a Service SaaS Platform as a Service PaaS Infrastructure as a Service IaaS The deployment models of cloud incorporate public cloud private cloud community cloud and hybrid cloud Literature Review The present system works based on a double threshold based dynamic load balancing approach Threshold calculation is based on the host utilization The main objective of our system is to reduce the number of migrations If the upper threshold is greater than the load on host all VMs running on that host get moved to the other host If the upper threshold is less than load on host then host is overloaded Therefore some VM should be migrated During migration VM is suspended for a few times which will decrease the performance of the system An effective load balancing approach should minimize the number of migration Existing system A Double threshold based dynamic load balancing approach where threshold is calculated based on host utilization If Load on host upper threshold vm running on that host are moved to other host server consolidation If Load on host upper threshold host is overloaded therefore some vm has to be migrated When the load on host below above threshold vm migration strategy is used ie technique of transfer of vm from one host to another host During the migration vm is suspended for few times will decrease the performance of the system Effective load balancing approach should minimize the number of migration Proposed System We propose a system which consists of a particular load limit 



When the load increases the downtime also increases In order to decrease the down time we transfer the VM to the nearest physical machines which contain comparatively less load than our host machine The advantage while comparing to existing system is that we can increase the speed of transmission and decrease the downtime by calculating the smallest distance Load balancing Load balancing is the process of distributing workloads and computing resources across one or more servers This ensures maximum throughput in minimum response time The workload is separated among two or more servers hard drives network interfaces or other computing resources enabling better resource utilization and system response time Thus for a high traffic website effective use of load balancing can ensure business continuity The common objectives of using load balancers are To maintain system firmness To improve system performance To protect against system failures Advantages of Cloud Load Balancing a High Performing applications b Increased scalability c Ability to handle sudden traffic spikes d Business continuity with complete flexibility Load balancing challenges a Provide services automatically Cloud resources are capable to allocate and release resources automatically as per the user's needs The threat here is about the allocation and releasing of resources as the system performance should be kept unchanged b Stored Data Management Cloud computing consists of large amount of data but to distribute these data across the cloud is a big threat c Virtual Machine Migration


Virtualization helps to create a virtual device or resource that can be a server storage device any network or an operating system to unload a physical machine that is currently heavily loaded The challenge here is to dynamically distribute load from that overloaded physical machine to some other by moving virtual machine to limit bottlenecks of computing system which provides cloud d Usage of small data centers Small data centers may be more beneficial cheaper and less energy consuming than large data centers Load balancing will become a problem in this case that ensure a maximum response time with an optimal distribution of resources e Spatial Distribution of the Cloud Nodes Some algorithms are designed to be efficient only for closely located nodes which are comparatively small Here the challenge is to design a load balancing algorithm that can work for spatially distributed nodes Different algorithms used in cloud load balancing in live VM The Routing and Bandwidth Allocation RBA algorithm Dynamic Resource Allocation Algorithm Remote Page fault Filter RPFF Geometric programming model and online multi VM live migration algorithm Hierarchy Token Bucket Algorithm Multiple VMs migration scheduling Algorithm Existing techniques 1 Dynamic Round Robin algorithm It consists of two rules which helps to consolidate the virtual machines 2 Hybrid algorithm It is a combination of Dynamic Round Robin and First Fit It uses virtual machines incoming rate for scheduling the virtual machines 3 Power Aware Load balancing PALB Algorithm It maintains the state of all computing nodes and based on utilizing percentage it decides the number of computing nodes that should be operated 4 Equally Spread Active Execution ESCE algorithm The random selection based distributed problem in round robin Selection depends on least load 5 Join Idle Queue It first checks for the idle processors at each dispatcher Then assigns jobs to those processors to reduce average queue length of jobs at each processor


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