Design of Video Compression Approach in Grid Environment

Grid offers an optimal solution to problems requiring large storage requiring large storage and/or processing power. Grid provides direct access to computers, data, software and many other resources. Sharing between these resources is highly controlled and done with consensus of both resource providers and consumers. Video compression is a lengthy and compute intensive task, involving compression of video media from one format to another. Video compression refers t reducing the quantity of data used to represent digital video images, and it’s a combination of spatial image compression and temporal motion compensation. Video compression system maintains high picture quality while reducing its quantity by removing redundancies. In Grid computing the task is split up into smaller chunks and the resources of many computers in a network can be applied to a single problem at the same time independently. These factors make the distribution of video compression viable in Grid environment. This paper provides a discussion of design of video compression in Grid environment, Grid environment and its globus toolkit 4.0

Erasure Code Based Cloud Storage System

Cloud Computing is the technology that provides on demand services and resources like storage space, networks, programming language execution environment on the top of Internet pay per use model. Cloud computing is globalized concept and there are no borders within the Cloud. Because of attractive features of Cloud computing, many organizations are using Cloud storage for storing their critical information. The data can be stored remotely in the Cloud by user and can be accessed using thin clients as and when required. One of the major issue in Cloud today is data security. Storage of data in the Cloud can be risky because storage is done on Cloud service providers� servers which mean less control over the stored data. One of the major concern in Cloud is how do we grab all the benefits of Cloud while maintaining security controls over the data. In this paper reliable storage system is proposed which can be robust in case of errors or erasures in data to be stored. Proposed system provides reliable storage while maintaining the integrity of the data. The files are split into parts to get an extra layer of security

A Novel Technique for Storage in Cloud Data Centers

An Information Dispersal Algorithm takes a file F as a input and divide this file into n pieces that needs to be dispersed among n nodes such that any m pieces out of total n pieces will be sufficient to reconstruct the whole file F. The size of each piece is |F| / m. It must also ensure that the complete knowledge of any m-1 pieces is insufficient to reconstruct the complete file F. The ideas for accomplishing this have been given in many literatures in the past. This manuscript discusses the application of Information Dispersal Algorithms in Storage of files on cloud Data Centers instead of using previous schemes of replication

Score Based Budget Constraint Workflow Scheduling Algorithm for Cloud System

Cloud Computing is the technology that provides on demand services and resources like storage space, networks, programming language execution environment on the top of Internet using pay as you go model. The concept of Cloud Computing emerging as a latest model of service provisioning in distributed system encourage researchers to investigate its advantages and drawbacks in executing scientific applications involving workflows. Workflow scheduling is one of the major issues in Cloud environment that maps and allows the execution of inter-dependent tasks on different resources. It allocates desire resources to workflow tasks so that the execution can be completed to satisfy the QoS constraint defined by the users. At present, the workflow scheduling algorithms only focus on certain QoS parameters which are mainly execution cost and execution time during the allocation of virtual machines to workflow applications. Sometimes resources (virtual machines) are unreliable at data centers. These resources frequently results into failure when workflow applications are scheduled on these resources. The user workflow application may contain sensitive data that cannot tolerate failure of resources on which it is scheduled. In this paper the problem of workflow scheduling that is based on the concept of score is presented. A score based budget constraint workflow scheduling algorithms has been design and simulated. These algorithms reduce the execution time and failure rate of workflow applications within user specified budget

Score Based Budget Constraint Workflow Scheduling Algorithm for Cloud System

Cloud Computing is the technology that provides on demand services and resources like storage space, networks, programming language execution environment on the top of Internet using pay as you go model. The concept of Cloud Computing emerging as a latest model of service provisioning in distributed system encourage researchers to investigate its advantages and drawbacks in executing scientific applications involving workflows. Workflow scheduling is one of the major issues in Cloud environment that maps and allows the execution of inter-dependent tasks on different resources. It allocates desire resources to workflow tasks so that the execution can be completed to satisfy the QoS constraint defined by the users. At present, the workflow scheduling algorithms only focus on certain QoS parameters which are mainly execution cost and execution time during the allocation of virtual machines to workflow applications. Sometimes resources (virtual machines) are unreliable at data centers. These resources frequently results into failure when workflow applications are scheduled on these resources. The user workflow application may contain sensitive data that cannot tolerate failure of resources on which it is scheduled. In this paper the problem of workflow scheduling that is based on the concept of score is presented. A score based budget constraint workflow scheduling algorithms has been design and simulated. These algorithms reduce the execution time and failure rate of workflow applications within user specified budget

A Novel Technique for Storage in Cloud Data Centers

An Information Dispersal Algorithm takes a file F as a input and divide this file into n pieces that needs to be dispersed among n nodes such that any m pieces out of total n pieces will be sufficient to reconstruct the whole file F. The size of each piece is |F| / m. It must also ensure that the complete knowledge of any m-1 pieces is insufficient to reconstruct the complete file F. The ideas for accomplishing this have been given in many literatures in the past. This manuscript discusses the application of Information Dispersal Algorithms in Storage of files on cloud Data Centers instead of using previous schemes of replication

Erasure Code Based Cloud Storage System

Cloud Computing is the technology that provides on demand services and resources like storage space, networks, programming language execution environment on the top of Internet pay per use model. Cloud computing is globalized concept and there are no borders within the Cloud. Because of attractive features of Cloud computing, many organizations are using Cloud storage for storing their critical information. The data can be stored remotely in the Cloud by user and can be accessed using thin clients as and when required. One of the major issue in Cloud today is data security. Storage of data in the Cloud can be risky because storage is done on Cloud service providers’ servers which mean less control over the stored data. One of the major concern in Cloud is how do we grab all the benefits of Cloud while maintaining security controls over the data. In this paper reliable storage system is proposed which can be robust in case of errors or erasures in data to be stored. Proposed system provides reliable storage while maintaining the integrity of the data. The files are split into parts to get an extra layer of securit

Cost Effective Information Dispersal and Retrieval Framework for Cloud Storage

Cloud data storage applications widely demand security of data with minimum cost. Various cloud computing security threats supposed to be addressed in Cloud data service include Data Access Controllability, Data Confidentiality, and Data Integrity. In this paper, we propose a cost effective Information Dispersal and Retrieval framework for Cloud storage. Our proposed framework is different from existing approaches of replication. In our approach, multiple datacenters are considered as virtual independent disks for storing redundant data encoded with erasure codes and hence the proposed framework enables to retrieve user file even when failure of certain number of Cloud services occur . Besides security related benefits of our approach, the application provides user the cost-availability pattern of datacenters and allows cost effective storage on Cloud within user�s budget limit