Nowadays, cloud computing becomes emerging technology, where any kind of data can be shared. Software and resources can be offered based on the requirement of customers. Effective resource allocation is a challengeable task in a Cloud environment. Cloud resource providers have sufficient resources which should be efficiently allocated. Otherwise, a problem will occur in underutilization devices. The main difficulty is to identify an appropriate cloud resource provider for each cloud user who could sell various resources in minimum possible cost according to their requirements and simultaneously find suitable cloud user for a cloud service provider who values his resources at the most. To overcome the above issues, Efficient Resource Utilization Auction Method is designed to solve resource allocation issues by using dynamic cost model and effective resource utilization for cost resources. The method offers one type of safe auction process between resource provider and user to grow their business mutually in win-win condition. Where, cloud user looks to get actual requirement with an affordable cost; simultaneously cloud resource provider also looks to generate good revenue and meaningful profit. The method fascinates the cloud resource provider to decide the resource allocation for the submitted virtual machine (VM) to the physical machine (PMs). The proposed method works based on a dynamic economic auction model. Based on the experimental evaluation, proposed Efficient Resource Utilization Auction Method improves the 18% resource utilization (RU), and reduces 20 seconds task completion time (TCT) compare than conventional methodologies.

The resource management in 3G systems with multi-nodes environment is a demanding task to provide flexible and higher bandwidth services. To cope multi-nodes environment heterogeneity, there is a need of intelligent RNC (Radio Network Controller) at BS (Base Station), which cooperates to adapt and retrieve information to manage the resources intelligently and reliably in a consistent manner. Knowledge sharing for radio resource management, at cell level is a novel approach presented in this paper. The proposed architecture has induced the global effect through local information sharing to make reliable and consistent decisions. It provides efficient solutions for symmetric scenarios at different locations without replication of knowledge base. Our inference engine adapts the closest information retrieved from the knowledge repository efficiently through distant indexed values technique. Consequently, an Autonomous and Sociable RNC accepts, rejects or buffers a connection request to mange resources to meet QoS requirement as defined in Service Level Agreement (SLA).

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