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HireSome II:Towards Privacy Aware Cross Cloud Service Composition for Big Data Applications
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HireSome - II:Towards Privacy-Aware Cross-Cloud Service Composition for Big Data Applications

Category : Cloud Computing


Sub Category : DOTNET


Project Code : ITDCC05


Project Abstract

HIRESOME-II: TOWARDS PRIVACY-AWARE CROSS-CLOUD SERVICE COMPOSITION FOR BIG DATA APPLICATIONS

ABSTRACT

In this paper, the Cloud computing promises a scalable infrastructure for processing big data applications such as medical data analysis. The complexity of potential compositions of cloud services calls for new composition and aggregation methods, especially when some private clouds refuse to disclose all details of their service transaction records due to business privacy concerns in cross-cloud scenarios. Cross-cloud service composition provides a concrete approach capable for large-scale big data processing. The authority of cross-clouds and on-line service compositions will become mistrust, if a cloud fails to deliver its services according to its promised quality. In view of these challenges, we propose a privacy-aware cross-cloud service composition method, named HireSome-II (History record-based Service optimization method) based on its previous basic version HireSome-I. In our method, to enhance the credibility of a composition plan, the evaluation of a service is promoted by some of its QoS history records, rather than its advertised QoS values. Besides, the k-means algorithm is introduced into our method as a data filtering tool to select representative history records. HireSome-II can protect cloud privacy, as a cloud is not required to make public all its transaction records. It significantly reduces the time complexity of developing a cross-cloud service composition plan as only representative ones are recruited, which is demanded for big data processing.

 

 

 

 

 

 

 

EXISTING SYSTEM

PROPOSED SYSTEM

EXISTING CONCEPT:-

In the existing system Current service optimization approaches often assume that the quality delivered by service providers does not change over time. However, this assumption is often spoilt by the dynamic network environment. Therefore, a service provider may fail to deliver their services with promised quality.

It often causes some fluctuations in service performance, and the evaluation of a service will be suspicion, if the evaluation is scored by the QoS values promised in advance.

PROPOSED CONCEPT:-

In the proposed system aims at enhancing the credibility of service composition. HireSome-I is incapable of dealing with the privacy issue in cross-cloud service composition. Compared to HireSome-I, HireSome-II greatly speed up the process of selecting an optimal service composition plan, and protect the privacy of a cloud service for cross-cloud service composition.

 

EXISTING TECHNIQUE:-

Global analysis QoS of Cloud-Service

PROPOSED TECHNIQUE:-

History Record-Based Service Composition Evaluation

TECHNIQUE DEFNITION:-

Quality of Service (QoS) a choice is required to determine which services for the expected optimal service composition.

TECHNIQUE DEFNITION:-

History record-based Service optimization method named HireSome-II is presented in this paper for privacy-aware cross-cloud service composition for big data applications.

DRAWBACKS:-

the higher its value is, the lower quality it owns

(e.g., execution time and execution price).

ADVANTAGES:-

The time cost as indicated is the average time cost for producing an optimal composition plan.

 
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