Resumption of virtual machines after adaptive deduplication of virtual machine images in live migration

In cloud computing, load balancing, energy utilization are the critical problems solved by virtual machine (VM) migration. Live migration is the live movement of VMs from an overloaded/underloaded physical machine to a suitable one. During this process, transferring large disk image files take more time, hence more migration and down time. In the proposed adaptive deduplication, based on the image file size, the file undergoes both fixed, variable length deduplication processes. The significance of this paper is resumption of VMs with reunited deduplicated disk image files. The performance measured by calculating the percentage reduction of VM image size after deduplication, the time taken to migrate the deduplicated file and the time taken for each VM to resume after the migration. The results show that 83%, 89.76% reduction overall image size and migration time respectively. For a deduplication ratio of 92%, it takes an overall time of 3.52 minutes, 7% reduction in resumption time, compared with the time taken for the total QCOW2 files with original size. For VMDK files the resumption time reduced by a maximum 17% (7.63 mins) compared with that of for original files

A Model Approach to Cloud Implementation on Public Libraries with a focus on West Bengal, India

The purpose of this paper is to explore the possibility of introducing cloud architecture for public library system in areas where library automation is operational on a standalone server. It also proposes a cloud based model library management system to function on an affordable, robust architecture. The paper made an attempt to highlight the present status of library automation and networking among public libraries in West Bengal. It presents functional requirements for a SaaS based (Software as a Service) model. The simulation approach for the model architecture supports the possibility to connect all public libraries across different hierarchical tiers under the public library system of West Bengal. The proposed model will upscale workflow, reduce cost and duplication of work in terms of procurement, cataloguing, classification and creating an union catalogue/ OPAC with the provision of resource sharing. The current study is the first of its kind, proposing a SaaS cloud based model architecture for a huge public library network. It suggests ways to improve public library services and coordination across the network to visually present the holdings of the entire network to the user community via a cost effective infrastructure

Adaptive deduplication of virtual machine images using AKKA stream to accelerate live migration process in cloud environment

Abstract Cloud Computing is a paradigm which provides resources to users from its pool based on demand to satisfy their requirements. During this process, many servers are overloaded and underloaded in the cloud environment. Thus, power consumption and load balancing are the major problems and are resolved by live virtual machine (VM) migration. Load balancing is addressed by moving virtual machines from overloaded host to under loaded host and from under loaded host to any other host which is not overloaded called VM migration. If this process is done without power off (Live) the virtual machines then it is called live VM migration. By this process, the issue of power consumption by physical hosts is also resolved. Migrating virtual machines involves virtualized components like storage disks, memory, CPU and networking, the entire state of VM is captured as a collection of data files. These data files are virtual disk files, configuration files, and log files. The virtual disk files take larger memory and take more migration time and hence the downtime. These disk files include many zero pages, similar and redundant pages. Many techniques such as compression, deduplication is used reduce the size of VM disk image file. Compression techniques are not widely used, due to the disadvantage of compression ratio and decompression time. Many researchers hence used deduplication techniques for reducing the VM disk image file in the live migration process. The significance of the research work is to design an adaptive deduplication mechanism for reducing VM disk image file size by performing fixed length and variable length block-level deduplication processes. The Rabin-Karp rolling hash algorithm is used in variable length block-level deduplication. Akka stream is used for streaming the VM disk image files as it is the bulk volume of live data transfer. To reduce the time of the deduplication process, many researchers used multithreading and multi-core technologies. We use multithreading in Akka framework to run the deduplication process concurrently without OutofMemory errors. The experiment results show that we achieved a maximum of 83% overall reduction in image storage space and 89.76% reduction in total migration time are achieved by adaptive deduplication method. 3% improvement in deduplication rate when compared with the existing image management system. The results are significant because when we apply this in the storage of data centres, there are much space savings. The reduction in size is dependent on the dataset was taken and the applications running on the VM