Abstract
This paper focuses on an integrated workload scheduling and pre-fetching model in a multimedia mobile cloud computing environment to enhance the performance of response time and reduce the cost to process multimedia data. The response time and cost optimization problems are presented along with the computation resources such as virtual machines (VMs) allocation, workload conservation, queueing stability constraints, and to overcome the total response time and cost, a heuristic approach of workload scheduling method is proposed. The integrated workload scheduling at pre-fetcher and cloud are considered to study the effects of various parameters such as VM’s processing speed, pre-fetcher’s utilization, the user requests arrival rate. The performance analysis results reveal that the cost and transmission speed are directly relevant factors, meaning that, once the rate of data transmission is increasing, the cost is also increasing and vice versa. Hence, the time and cost efficient workload scheduling is essential to satisfy both delay and cost in pre-fetcher enabled multimedia cloud systems.
Highlights
Multimedia communication over the cellular network with minimum latency become critical with the ever increasing number of cellular users along with multimedia data traffic
This paper investigates the performance of response time and cost in the integrated workload scheduling and pre-fetching model in mobile cloud computing environment to process multimedia data requests
Similar to the above concepts, we proposed the pre-fetcher enabled multimedia mobile cloud computing model, shown in Fig.1, where the pre-fetcher is located in close proximity to the users and contains high speed Virtual Machine (VM) and storage servers
Summary
Multimedia communication over the cellular network with minimum latency become critical with the ever increasing number of cellular users along with multimedia data traffic. This paper investigates the performance of response time and cost in the integrated workload scheduling and pre-fetching model in mobile cloud computing environment to process multimedia data requests. We propose a heuristic based workload scheduling method which utilizes both cloud and pre-fetcher to distribute workload to minimize the total response service time and cost.
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