International Journal of Computer and Applications

/pdf/a-break-in-the-clouds-towards-a-cloud-definition-svovsw1r5a.pdf

A Break in the Clouds: Towards a Cloud Definition

Text categorization-assignment of natural language texts to one or more predefined categories based on their content-is an important component in many information organization and management tasks.Different automatic learning algorithms for text categori-zation have different classification accuracy.Very accurate text classifiers can be learned automatically from training examples.

Inductive learning algorithms and representations for text categorization

A comprehensive survey for scheduling techniques in cloud computing

Load balancing mechanisms and techniques in the cloud environments

https://cyberleninka.org/article/n/468779.pdf

A review of metaheuristic scheduling techniques in cloud computing

In a large-scale cloud computing environment the cloud data centers and end users are geographically distributed across the globe. The biggest challenge for cloud data centers is how to handle and service the millions of requests that are arriving very frequently from end users efficiently and correctly. In cloud computing, load balancing is required to distribute the dynamic workload evenly across all the nodes. Load balancing helps to achieve a high user satisfaction and resource utilization ratio by ensuring an efficient and fair allocation of every computing resource. Proper load balancing aids in minimizing resource consumption, implementing fail-over, enabling scalability, avoiding bottlenecks and over-provisioning etc. In this paper, we propose “Central Load Balancer” a load balancing algorithm to balance the load among virtual machines in cloud data center. Results show that our algorithm can achieve better load balancing in a large-scale cloud computing environment as compared to previous load balancing algorithms.

A novel approach for load balancing in cloud data center

Cloud computing is a provider of dynamic services which offers readily elastic on demand computing resources as per the customer's request in economical way. As there are a lot of requests fabricated by cloud users which are processed by the accessible resources, there exists a need for better and effective scheduling mechanism for efficient allocation of resources. In this paper, a genetic algorithm based scheduling approach is proposed in which initial population is generated with advance version of Max Min by which we can get more optimize results, in terms of make span. The performance of the proposed Modified Genetic Algorithm (MGA) and existing algorithms have been evaluated against the sample data. Experimental results show that proposed algorithm exhibits acceptable performance and outperforms the existing algorithms.

Scheduling of Independent Tasks in Cloud Computing Using Modified Genetic Algorithm

Optimal component selection based on cohesion & coupling for component based software system under build-or-buy scheme

Virtualization technology is currently becoming increasingly popular and valuable in cloud computing environments due to the benefits of server consolidation, live migration, and resource isolation. Live virtual machine migration is the process of moving virtual machine from one physical host to other without disturbing the users. Effective migration of virtual machine requires the movement of storage, memory, process states and network connectivity. Live migration of virtual machines has been a powerful tool to facilitate system maintenance, load balancing, fault tolerance, and powersaving, especially in clusters or data centers. During the process of migration, services are running in the virtual machines, hence it requires minimum total migration time, down time in order to avoid service degradation. This paper introduced discussion of various techniques for effective live virtual machine migration to reduce both downtime and total migration time. This paper also present the various scenarios, where the live migration of virtual machines can takes place.

/pdf/comparative-study-of-live-virtual-machine-migration-3wvhu5pr3s.pdf

Mala Kalra

Papers

A review of metaheuristic scheduling techniques in cloud computing

A novel approach for load balancing in cloud data center

Scheduling of Independent Tasks in Cloud Computing Using Modified Genetic Algorithm

Optimal component selection based on cohesion & coupling for component based software system under build-or-buy scheme

Comparative Study of Live Virtual Machine Migration Techniques in Cloud