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Top1. Introduction
The Authors (Foster, 2008; Chandio, 2013) discuss in their previous work that Cloud environment is a fast, large-scale, emerging, distributed computing model for accessing on-demand, anywhere any time, pay per usage services with web applications over the internet. Users demand is raising fast day by day for cloud computing in these days because of its pay per usage and usage anywhere, anytime properties. Cloud is also used to solve complex business, engineering and scientific problems with cloud resources. There are several cloud service providers available to provide cloud services to the users or consumers. Due to increasing users demand, load is also increasing in cloud computing system so balancing the load is a major challenging issue in cloud in these days. Load balancing means distributing the all workload across multiple cloud resources so all the cloud resources works properly and it reduces the cost of the resource management system and also improve the availability of the resources to the cloud users. There are several other major challenges in cloud computing as configuration, deployment and management of cloud required software including the job schedulers, system software and end-consumer applications. There are numerous advantages of cloud computing for business and scientific computing. Cloud system reduces the total cost of cloud service provider (Dillon et al., 2010) by allowing dynamic scaling of computing resources which is depend on present workload. Cloud system can also significantly give less time to solve the problem with quick resource provision or deprovision, and skip the long process of making a new cluster or group on-premises and avoid large queue waiting time with sharing computing facilities.
Cloud computing is a rapid advances technology from the past twelve years have enabled a broad spectrum of Cloud computing services. Cloud computing services are made available to consumers on demand by the use of networks from the cloud data centers which are operated or controlled by the brokers (service providers). Cloud services are dynamically balance the needs of its consumers and there is no need for a consumer to provision or deprovision its own cloud resources to manage the service. Some examples of public Cloud services are Alibaba Cloud, Google Cloud, Amazon Web Services (AWS), Microsoft Azure, IBM Cloud etc. several organizations or IT business have constructed their own private Clouds or established hybrid Clouds to provide several cloud services to their customers. Cloud system is playing a very important role in these days because of pandemic Covid-19, most of the IT employees or other business employees are working at home with this cloud computing technology and this cloud computing technology gives the good performance. Although one important key issue of cloud computing is cloud performance because number of users are high. Data centers play a vital role in reducing cloud costs and improving cloud performance. The service broker/service provider controls the traffic routing between cloud users and cloud data centers using a variety of service broker methods, and service broker is playing an important role in determining the best cloud data center in a cloud environment. Cloud Data centers are designed by the cloud architects in cloud system as cloud service networks and the Cloud consumers can access as well as deploy the applications anywhere any time on reasonable cost in the world, according to their requirements. Scheduling is also an important term in cloud system to map or assign a task/job to a particular Virtual machine, so the resource utilization can increase. A proficient task scheduling method enhances the overall cloud system performance and also helps cloud broker to provide the good quality of services (QoS) (Ardagna et al., 2014). In this paper a novel dynamic job scheduling approach to improve the execution time has been proposed.