Cloud computing is another pattern rising concept in IT industry with immense inevilability of framework furthermore, resources. Cloud computing is build up by conglomerating two terms in the area of innovation. Initial is Cloud and second is computing. Cloud comprises of heterogeneous assets. It is a work of immense framework with no significance with name "Cloud". Load Balancing is a vital part of distributed computing scenario. Productive load adjustment plan guarantees effective asset usage by provisioning of assets to cloud client's onrequest premise in pay-as-you-use. Load Balancing may indeed, even help organizing clients by applying proper planning criteria. This paper presents a review on load balancing methods in cloud computing with its various techniques. The objective of this paper is to study the various existing load balancing techniques on various parameters utilized to compare the current techniques with each other.
Cloud computing is the recent advancement in the technology of distributed computing that works on the basis of pay as you use model. It comprises of virtual machines that provides both storage and computational facility. The main aim of cloud computing is to offer access to remotely distributed resources to its users. Scheduling of tasks plays a vital role in the efficient working of cloud computing. Sometimes situation comes where multiple tasks with same priority arrives so a good scheduler is one which handles the situation appropriately with proper load balancing. There are various scheduling algorithms proposed in the past. Most of the scheduling algorithms neglect the concept of load balancing. Load balancing in cloud computing is also as much important as task scheduling. As cloud environment consists of virtual machine, it should take care that no virtual machine remains idle and also no virtual machine is under heavy load of the tasks. So, it is important to balance the load equally among the virtual machines to solve the issue of under loading and over loading of virtual machines. In this paper, a credit based scheduling algorithm with load balancing (CBSA_LB) is proposed that balances the load along with the scheduling of tasks. The results are evaluated on the basis of six parameters: processing time, processing cost, response time, makespan time, Throughput and Execution Time. Experimental results show that the proposed technique outperforms the existing techniques (EMOSA and CBSA). .
The latest advancements in the manufacturing industry due to ICT (Information and Communication Technologies) has promoted the wave of Industry 4.0 in today's world. This has transformed the traditional mass-production model into the mass customization model. The vision of Industry 4.0 is to make machines that have the capability of self-learning and self-awareness for improving the planning, performance, operations, and maintenance of manufacturing units. This paper analyses the fundamental technologies behind the success of I4.0, namely Cloud computing and big data analysis, in great detail. The Cloud is the heart of Industry 4.0. It is the primary enabler of innovative, more efficient, and practical strategies in business processes by using artificial intelligence, intelligent sensors, and robotics. It has additionally examined numerous applications where this concept is being used along with various issues and challenges.
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