Optimized mobile cloud resource discovery architecture based on dynamic cognitive and intelligent technique

In current world, the Mobile Cloud Computing (MCC) will undergo a dramatic upgrade with integrating of mobile cloud resources in small regions to provide a better MCC service. This paper considers the MCC resource availability problem in integrated mobile cloud environment to optimization resources availability with a better effectiveness, accuracy, reliable, low latency and low complexity. The DCICRD architecture is proposed in this paper optimizes the resource discover process with better resource availability. The proposed DCICRD architecture runs various operations such Resource demand prediction to find the required level of resources, Cloudlet Resource Discovery process which discovers resources based on the requirement predicted using two states expand and shrink. The expand state is used to discover resources on-demand in resource scarcity situation and the shrink state is called when abundant resource available to the required level.  Further, Resource reliability check is performed to identify the reliable resource with energy level and signal strength above the threshold level. Finally, Local Resource Information Management Table is used to store the local resource provider information and Central Resource Information Management Table is used to store all local resource information for handover of resource provider. The implementation and evaluation is conducted by comparing the HARD architecture. The comparison result shows that proposed DCICRD architecture is better than HARD architecture by optimizing the resource discovery process and produce reliable resources on demand as per the required level with a better effectiveness using expand and shrink state, accuracy by making resource available for required level, reliable by sending message for frequent checking of Resource with required energy level and signal strength, low latency by making resource available locally and reduce complexity by performing only on-demand resource discovery operation after initial startup. Thus, the proposed DCICRD architecture is better when compared to HARD architecture.