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Providing a resource scheduling algorithm based on recommender system in order for development of cloud computing


Elnaz Mazaheri, Sasan Berehlia


Vol. 17  No. 11  pp. 215-225


Cloud computing has caused a new revolution in computer science. This computing includes key technologies such as services, virtualization, and data centers. Data centers include locations where computer and computing facilities are located. These centers are responsible for providing energy, maintenance, and air conditioning for computing devices. Data centers face new challenges, including dynamic distribution of virtual management and resource sharing. The infrastructure resources of cloud computing can be widely distributed in different phases according to the needs of different users. Efficient planning strategy and algorithms should be used tailored to the needs of different businesses and in order to meet business goals. The key goal in cloud data centers is to improve system performance and service quality. Consequently, with the increasing expansion of data centers, the scale of energy consumption has seriously become a major problem. Also, energy consumption greatly affects cost and surrounding environment. Therefore, in order to develop scheduling of cloud resources, recommender system can be used in order to improve cloud computing. Using the recommender system, the considered service can be recommended to the user according to his needs so this system can provide the customer with the right resource. In this paper, firstly the types of scheduling and resource scheduling algorithms are examined. Then, recommender system is considered in this paper as a key solution. Finally, the recommended resource scheduling algorithm based on recommender system has been provided. The results show that the impact of the recommender system on resource scheduling has improved economic scheduling parameters and flexibility and has caused cost reduction and profit increasing.


Cloud computing, resource scheduling, resource scheduling algorithm, recommender system