Networking and Communication Engineering

A. Rajalakshmi ¹, D. Vijayakumar ¹, K. G. Srinivasagan ¹

Affiliations
1 Department of Computer Science and Engineering-PG, National Engineering College, Kovilpatti, Tamilnadu, IN

Abstract

Cloud computing platform is getting more and more attentions as a new trend of data management. Data replication has been widely used to speed up data access in cloud. Replica selection and placement are the major issues in replication. In this paper we propose an approach for dynamic data replication in cloud. A replica management system allows users to create, register and manage replicas and update the replicas if the original datasets are modified. The proposed work concentrates on designing an algorithm for suitable optimal replica selection and placement to increase availability of data in the cloud. The method consists of two main phases file application and replication operation. The first phase contains the replica location and creation by using catalog and index. In second phase is used to find whether there is enough space in the destination to store the requested file or not. Replication aims to increase availability of resources, minimum access cost, shared bandwidth consumption and delay time by replicating data. The proposed systems developed under the Eucalyptus cloud environment. The results of proposed replica selection algorithm achieve better accessibility compared with other methods.

Keywords

Hash Key, Replication, Optimal Selection, Eucalyptus, Hybrid Cloud, Catalog, Virtual Synchrony, State Transition.

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G. Suryadevi ¹, D. Vijayakumar ¹, R. Sabari Muthu Kumar ²

Affiliations
1 Department of Computer Science and Engineering, National Engineering College, Kovilpatti, Tamilnadu, IN
2 Department of Computer Science and Engineering-PG, National Engineering College, Kovilpatti, Tamilnadu, IN

Abstract

In recent years cloud computing is one of the emerging research area that encompasses virtualization, networking, storage, software and on-demand web services. Clients, distributed servers and datacenters are the fundamental components of cloud infrastructure. The number of users in cloud computing is growing in an exponential rate at every day. Large number of user requests tries to allocate the resources for many applications which lead to high load on cloud server. To reducing the heavy load on server, the virtual machines are allocated for resources based on priority. In this paper the distributed dynamic priority based algorithm is used for balancing the load on instances effectively and to improve the system consistency, minimum response time and increase the throughput. Allocating the resources on virtual machines based on priority achieves the better response time and processing time. Load balancing ensures all instances in a node in the networks do the equal amount of work at any instant of time. Priority based resource provision to improve the utilization of resources and reducing response time of cloud services.

Keywords

Cloud Computing, Resource Allocation, Priority Based Scheduling, Load Balancing.

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S. Anjanadevi ¹, D. Vijayakumar ²

Affiliations
1 Department of Computer Science and Engineering, National Engineering College, Kovilpatti, Tamilnadu, IN
2 Department of Computer Science and Engineering-PG, National Engineering College, Kovilpatti, Tamilnadu, IN

Abstract

Cloud computing is an emerging, computing model wherein the tasks are allocated to software, combination of connections, and services accessed over a network. This connections and network of servers is collectively known as the cloud. In place of operating their own data centers, users might rent computing power and storage capacity from a service provider and pays only for what they use. Cloud storage is delivering the data storage as service. If the data is stored in cloud, it must provide the data access and heterogeneity. With the advances in cloud computing it allows storing of large number of images and data throughout the world. This paper proposes the indexing and metadata management which helps to access the distributed data with reduced latency. The metadata management can be enhanced for large scale file system applications. When designing the metadata, the storage location of the metadata and attributes is important for the efficient retrieval of the data. Indexes are used to quickly locate data without having to search over every location in storage. Based on these two models, the data can be easily fetched and the search time was reduced to retrieve the appropriate data.

Keywords

Metadata, Cloud Storage, Index, Google File System, Hadoop Distributed File System.

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