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Psdot 18 performance analysis of cloud computing

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ZTech Proje
ZTech Proje

FINAL YEAR IEEE PROJECTS, EMBEDDED SYSTEMS PROJECTS, ENGINEERING PROJECTS, MCA PROJECTS, ROBOTICS PROJECTS, ARM PIC BASED PROJECTS, MICRO CONTROLLER PROJECTS Z Technologies, Chennai

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PERFORMANCE ANALYSIS OF CLOUD COMPUTING SERVICES FOR MANY-TASKS SCIENTIFIC COMPUTING OBJECTIVE: The main role of this system as to analysis the performance of each and every cloud and assign multiple tasks to highly performance cloud. PROBLEM STATEMENT: Recently, cloud computing has found its way into the provision of web services. Information, as well as software is permanently stored in Internet servers and probably cached temporarily on the user side. The main issue is to get optimal service pricing for a cloud cluster. There are two major challenges when trying to define an optimal pricing scheme in the cloud cluster. The first is to define a simplified enough model of the price demand dependency, to achieve a feasible pricing solution, but not oversimplified model that is not representative. For example, a static pricing scheme cannot be optimal if the demand for services has deterministic seasonal fluctuations. The second challenge is to define a pricing scheme that is adaptable to (i) modeling errors, (ii) time-dependent model changes, and (iii) stochastic behavior of the application.
ABSTRACT: The leading trend for service infrastructures in the IT domain is called cloud computing, a style of computing that allows users to access information services. Cloud providers trade their services on cloud resources for money. The quality of services that the users receive depends on the utilization of the resources. The operation cost of used resources is amortized through user payments. Cloud resources can be anything, from infrastructure (CPU, memory, bandwidth, network), to platforms and applications deployed on the infrastructure. Cloud applications that offer data management services are emerging. Such clouds support caching of data in order to provide quality query services. The users can query the cloud data, paying the price for the infrastructure they use. Cloud management necessitates an economy that manages the service of multiple users in an efficient, but also, resource economic way that allows for cloud profit. Naturally, the maximization of cloud profit given some guarantees for user satisfaction presumes an appropriate price-demand model that enables optimal pricing of query services. Optimal pricing is achieved based on a dynamic pricing scheme that adapts to time changes. This project proposes a novel price-demand model designed for a cloud cluster and a dynamic pricing scheme for queries executed in the cloud cluster.
EXISTING SYSTEM: Recently, cloud computing has found its way into the provision of web services. Information, as well as software is permanently stored in Internet servers and probably cached temporarily on the user side. The main issue is to get optimal service pricing for a cloud cluster. There are two major challenges when trying to define an optimal pricing scheme in the cloud cluster. The first is to define a simplified enough model of the price demand dependency, to achieve a feasible pricing solution, but not oversimplified model that is not representative. For example, a static pricing scheme cannot be optimal if the demand for services has deterministic seasonal fluctuations. DISADVANTAGES:  Modeling Errors  Time-dependent model changes  Stochastic behavior of the application PROPOSED STATEMENT: We propose a multi-cloud service for an e-shopping application that achieves optimal pricing for the products available in different cloud services (like Amazon, eBay, etc) in a clustered environment. This work proposes a novel pricing scheme designed for a cloud cluster that offers inter-querying services and aims at the maximization of the cloud profit. We define an appropriate price-
demand model and we formulate the optimal pricing problem. The proposed solution allows long-term profit maximization, and dynamic calibration to the actual behavior of the cloud application. The cloud services are interconnected using AJAX Cloud Platform. ADVANTAGES:  High Performance  Privacy Data Sharing  Fast Access  Reduce Time ALGORITHM USED: 1. A-Priori Algorithm 2. Priority Scheduling 3. COCOMO II
ARCHITECTURE DIAGRAM: CLOUD USER DIVITIONS CLOUD DETAILS ABOUT USER ACCESS SYSTEM DETAILS ABOUT COST DETAILS SYSTEM REQUIREMENTS: Software Requirements: – Platform - Windows 2000 and Above – Front End - C#.NET – Web Application - ASP.NET – Web Server - IIS 6.0 – Back End - SQL Server
Hardware Requirements: – Intel Pentium IV – 256/512 MB RAM – 1 GB Free disk space or greater – 1 GB on Boot Drive – 1 Network Interface Card (NIC) APPLICATIONS: 1. Organizations 2. Colleges 3. Banks

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Psdot 18 performance analysis of cloud computing

  • 1. PERFORMANCE ANALYSIS OF CLOUD COMPUTING SERVICES FOR MANY-TASKS SCIENTIFIC COMPUTING OBJECTIVE: The main role of this system as to analysis the performance of each and every cloud and assign multiple tasks to highly performance cloud. PROBLEM STATEMENT: Recently, cloud computing has found its way into the provision of web services. Information, as well as software is permanently stored in Internet servers and probably cached temporarily on the user side. The main issue is to get optimal service pricing for a cloud cluster. There are two major challenges when trying to define an optimal pricing scheme in the cloud cluster. The first is to define a simplified enough model of the price demand dependency, to achieve a feasible pricing solution, but not oversimplified model that is not representative. For example, a static pricing scheme cannot be optimal if the demand for services has deterministic seasonal fluctuations. The second challenge is to define a pricing scheme that is adaptable to (i) modeling errors, (ii) time-dependent model changes, and (iii) stochastic behavior of the application.
  • 2. ABSTRACT: The leading trend for service infrastructures in the IT domain is called cloud computing, a style of computing that allows users to access information services. Cloud providers trade their services on cloud resources for money. The quality of services that the users receive depends on the utilization of the resources. The operation cost of used resources is amortized through user payments. Cloud resources can be anything, from infrastructure (CPU, memory, bandwidth, network), to platforms and applications deployed on the infrastructure. Cloud applications that offer data management services are emerging. Such clouds support caching of data in order to provide quality query services. The users can query the cloud data, paying the price for the infrastructure they use. Cloud management necessitates an economy that manages the service of multiple users in an efficient, but also, resource economic way that allows for cloud profit. Naturally, the maximization of cloud profit given some guarantees for user satisfaction presumes an appropriate price-demand model that enables optimal pricing of query services. Optimal pricing is achieved based on a dynamic pricing scheme that adapts to time changes. This project proposes a novel price-demand model designed for a cloud cluster and a dynamic pricing scheme for queries executed in the cloud cluster.
  • 3. EXISTING SYSTEM: Recently, cloud computing has found its way into the provision of web services. Information, as well as software is permanently stored in Internet servers and probably cached temporarily on the user side. The main issue is to get optimal service pricing for a cloud cluster. There are two major challenges when trying to define an optimal pricing scheme in the cloud cluster. The first is to define a simplified enough model of the price demand dependency, to achieve a feasible pricing solution, but not oversimplified model that is not representative. For example, a static pricing scheme cannot be optimal if the demand for services has deterministic seasonal fluctuations. DISADVANTAGES:  Modeling Errors  Time-dependent model changes  Stochastic behavior of the application PROPOSED STATEMENT: We propose a multi-cloud service for an e-shopping application that achieves optimal pricing for the products available in different cloud services (like Amazon, eBay, etc) in a clustered environment. This work proposes a novel pricing scheme designed for a cloud cluster that offers inter-querying services and aims at the maximization of the cloud profit. We define an appropriate price-
  • 4. demand model and we formulate the optimal pricing problem. The proposed solution allows long-term profit maximization, and dynamic calibration to the actual behavior of the cloud application. The cloud services are interconnected using AJAX Cloud Platform. ADVANTAGES:  High Performance  Privacy Data Sharing  Fast Access  Reduce Time ALGORITHM USED: 1. A-Priori Algorithm 2. Priority Scheduling 3. COCOMO II
  • 5. ARCHITECTURE DIAGRAM: CLOUD USER DIVITIONS CLOUD DETAILS ABOUT USER ACCESS SYSTEM DETAILS ABOUT COST DETAILS SYSTEM REQUIREMENTS: Software Requirements: – Platform - Windows 2000 and Above – Front End - C#.NET – Web Application - ASP.NET – Web Server - IIS 6.0 – Back End - SQL Server
  • 6. Hardware Requirements: – Intel Pentium IV – 256/512 MB RAM – 1 GB Free disk space or greater – 1 GB on Boot Drive – 1 Network Interface Card (NIC) APPLICATIONS: 1. Organizations 2. Colleges 3. Banks