A novel energy-efficient resource allocation algorithm based on immune clonal optimization for green cloud computing

Cloud computing is a style of computing in which dynamically scalable and other virtualized resources are provided as a service over the Internet. The energy consumption and makespan associated with the resources allocated should be taken into account. This paper proposes an improved clonal selection algorithm based on time cost and energy consumption models in cloud computing environment. We have analyzed the performance of our approach using the CloudSim toolkit. The experimental results show that our approach has immense potential as it offers significant improvement in the aspects of response time and makespan, demonstrates high potential for the improvement in energy efficiency of the data center, and can effectively meet the service level agreement requested by the users.Comment: arXiv admin note: text overlap with arXiv:1006.0308 by other author

An improved resource allocation scheme for WiMAX using channel information

In recent years, tremendous progress has been made in wireless communication systems to provide wireless coverage to end users at different data rates. WiMAX technology provides wireless broadband access over an extended coverage area in both fixed and mobility environments. Most of the existing resource allocation schemes allocate resources based on respective service class of the incoming users’ requests. However, due to variation in channel conditions, user mobility and diverse resource requirements QoS based resource allocation either results in over or under utilization of allocated resources. Therefore, resource allocation is a challenging task in WiMAX. This research proposes an improved resource management mechanism that performs resource allocation by taking into consideration not only the user service class but also the respective channel status. Based on these two parameters, this research aims to achieve improved resource allocation in terms of resource utilization, fairness and network throughput. First, a Channel Based Resource Allocation scheme is introduced where priority in resource allocation is given to users’ requests with relatively higher service classes and better channel status. To maintain fairness in resource allocation process, a Fair Resource Allocation Based Service mechanism is developed where priority is given to users’ requests having less additional resources demand. Finally, to improve throughput of the network, a Channel Based Throughput Improvement approach is proposed which dynamically selects a threshold level of channel gain based on individual channel gain of users. During resource allocation process, users above the threshold level are selected for resource allocation such that priority is given to users with high channel gain. Different simulation scenario results reveal an overall improved resource utilization from 87% to 91% and the throughput improves up to 15% when compared to existing schemes. In conclusion the performance of resource utilization is improved if channel status is considered as an input parameter