Context Aware Data Center Allocation

The method to find a proper data center is based on six contextual parameters: 1) Geographical distance network delay) between a consumer and data centers, 2) Workload of each data center 3)Power usage effectiveness 4)Network monitoring 5)Facility monitoring 6)Allocation delay time. The proposed model can successfully allocate the decanter based on above mentioned parameters. Objective or Aim: To allocate each consumer request to an appropriate data center among the distributed data centers based on the location Of consumer and the location of data centers.

Scope: Using the proposed model can expect fast allocation time, but also future response time. The proposed model can successfully allocate the data center tit minimum distance between user and data center, workload, power usage effectiveness, network traffic, allocation delay, good facility. Problem Statement: Mapped/Reducer Provider computing service providers deliver their resources to consumers as a service, for example, software, platform and Infrastructure. Those services are based on the demands of the consumers, and the provider offers the services to consumers through brutalized resources.

The resources of the providers are usually hosted by a data center. Since the location of consumer is different in geographically, a service provider should have strutted data centers throughout the world to deliver its services. Therefore, to find an appropriate data center for a consumer request is very much necessary. Existing System: Dynamic resource allocation problem is one of the most challenging problems in the resource management problems. In [7] authors have explained the algorithm for negotiation protocol for resource provisioning in detail. In authors have made a comparison of many resource allocation strategies.

In [9] authors propose a model and a utility function for location- aware dynamic resource allocation. A comprehensive comparison of resource allocation policies is covered in [10]. In [1 1], authors propose an adaptive resource allocation algorithm for the Mapped/Reducer Provider system with predictable tasks in which algorithms adjust the resource allocation adaptively based on the updates of the actual task counterinsurgency Allocation [1 2] is a subject that has been addressed in many computing areas, such as operating systems, grid computing, and data center management.

For example, developers can have network requirements, such as bandwidth and delay, and computational requirements, such as CAP], memory and storage. The RA should deal with these unpredictable requests in an elastic and transparent way. This elasticity should allow the dynamic use of physical resources, thus avoiding both under-provisioning and over provisioning of resources. Proposed System: In this project, we propose a Context aware data center allocation model which allocates the consumer’s request to an appropriate data center. Here, we assume the VIM run on the providers data centers infinitely after they are successfully allocated.

Also, the VIM allocated in only one data center. Context aware data center allocation is designed to demonstrate the data enter allocation. In this model we have consumer and Mapped/Reducer Provider service provider, and coordinator agent. Coordinator agent works on behalf of each consumer and Mapped/Reducer Provider service provider. System Architecture: Working Principle: In this project, we assume the VIM run on the provider’s data centers infinitely after they are successfully allocated. Also, the VIM allocated in only one data center. That means a VIM has not allocated a VIM in multiple data centers to support the consumer requests.

For this reason, the workload of each data center has not depends on its resource availability, but the allocated Vim’s specification (number of Cups) in the data center. Context aware data center allocation is designed to demonstrate the data center allocation. In this model we have consumer and Mapped/Reducer Provider service provider, and coordinator agent. Coordinator agent works on behalf of each consumer and Mapped/Reducer Provider service provider. In this model, a Mapped/Reducer Provider service provider consists of several data centers that are geographically distributed.

Likewise, there are consumers that are geographically distributed, or else they may be moving entities. The intent aware data center allocation model consists of different kind of agents; 1) User Agent, 2) Coordinator Agent, and 3) Monitoring Agent. In this agents; 1) User Agent, 2) Coordinator Agent, and 3) Monitoring Agent User Agent: A user agent sends a demand to the coordinator agent by sending an allocation request message on behalf of a consumer. Request message format is as follows: Request (allocation_ARQ_size, Location details of user).

The user agent waits to receive an allocation result message from the coordinator agent. Coordinator Agent: A coordinator agent is responsible to coordinate resource allocations for geographically disturbed data centers and consumer. The coordinator agent finds an appropriate data center for a consumer request. When the coordinator agent receives an allocation request, the agent evaluate each data center to allocate the consumer request based on the location of consumer, workload on data center, Power usage, Facility monitoring, Network monitoring, and allocation delay latency of data centers.

Functional Requirements The functional requirements for a system describe what the system should do. These requirements depend on the type of software being developed, the expected users of the software and the general approach taken by the organization when writing requirements. When expressed as user requirements, the requirements are usually described in a fairly abstract way. However, functional system requirements describe the System function in detail, its inputs and outputs, exceptions, and so on.

Functional requirements are as follows: The proposed system should allocate each consumer request to an appropriate data center among the distributed data centers The proposed model can expect fast allocation time, and also future response time. Non-Functional Requirement Non-functional requirements, as the name suggests, are requirements that are not directly concerned with the specific functions delivered by the system. They may relate to emergent system properties such as reliability, response time and store occupancy.

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