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Top1. Introduction
At no other time in human history have so many people had access to powerful computing resources. Cloud computing has been the enabling technology for shifting mass-scale computation and storage requirements from individually owned clients towards an on-demand and utility-styled alternative that provides many services. However, the cost of maintaining data centers, keeping the environmental ramifications of data centers in check, and providing affordable computation alternatives to users still needs to be addressed in a wholesome manner cloud computing is an economic model for big corporate as it eliminates the need for an initial investment in capital or infrastructure cost. Apart from cost reduction, other advantages such as scalability, elasticity, agility, multi-tenancy, etc. Due to the surge in demand for using utility computing systems like public cloud resources, many trade-offs between price and performance have emerged. The design of a mechanism that efficiently prices perishable cloud resources in line with a provider’s profit maximization goal remains an open research challenge, however, it has four essential elements, namely buyers, sellers, intermediaries, and interaction mechanisms.
Figure 1.
Sales of Cloud computing services with the help of market brokers
The paper is designed in four major parts in which the first part of the paper gives a simple introduction of computing. In the second part of the paper, we are going to discuss the background and related work done in the field of our research. The third section of the paper clarifies the mathematical model. The fourth part of the research paper describes the simulation and results with the performance of our model to the available models. Finally, summarizes the dissertation with its brief discussion of results and highlights some of the future directions for carrying out the research. And the last part shows the conclusion and future scope of the system. The main aim of this research work is to provide the services according to the reservation-based system by which the total cost of providing and taking the services should be less and more efficient. The risk may increase if the end users become late.
Top2. Background
A lot of research is going on computing to formulate and define the clusters, peers, web, grids, IoT, fog, and cloud. The idea that computers (and hence computing) can be provided as a utility, like electricity or telephony, dates back to the late 1970s. Technological advancements over the next three decades or so in the IC fabrication industry, multi-core processor architectures, and networked computing infrastructures gradually brought this grand vision closer to reality. These trends have enabled a vibrant IT industry that has shifted computing paradigms from traditional web-based computing to subsequent datacenter-based utility computing, grid, and cloud computing, infusing numerous attributes and capabilities, like scalability, access ubiquity, and the autonomy of deployment, and so on. The idea of having a market-oriented cloud dates back almost a decade. There are some challenging issues in a small-scale voluntary cloud. 1) Fluctuation: the uncertainty of sharing time results in a high fault rate of each working node, which brings large fluctuation to the computing ability of the voluntary cloud. Usually, this fluctuation makes the computing ability of the system hardly estimated. Especially, when the system accepts a series of tasks that are filled with almost all the nodes and some exceptions happen on some nodes at the same time, many of these tasks cannot be completed on time. 2) Under-capacity: indeed, some fluctuations do not bring a big problem to some large cloud providers where the resource pool is big enough. But, in a small-scale voluntary cloud, the insufficient resources cannot resist drastic fluctuations. 3) Low-benefit: if a task needs n nodes to complete, the system should prepare a resource pool.