Cloud and Fog based Integrated Environment for Load Balancing using Cuckoo Levy Distribution and Flower Pollination for Smart Homes

Reducing delay and latency in cloud computing environment is a challenging task for the research community. There are several smart cities in the world. These smart cities contain numerous Smart Communities (SCs), which have number of Smart Buildings (SBs) and Smart Homes (SHs). They require resources to process and store data in cloud. To overcome these challenges, another infrastructure fog computing environment is introduced, which plays an important role to enhance the efficiency of cloud. The Virtual Machines (VMs) are installed on fog server to whom consumers' requests are allocated. In this paper, the cloud and fog based integrated environment is proposed. To overcome the delay and latency issues of cloud and to enhance the performance of fog. When there are a large number of incoming requests on fog and cloud, load balancing is another major issue. This issue has also been resolved in this paper. The load balancing algorithm Cuckoo search with Levy Walk distribution (CLW) and Flower Pollination (FP) are proposed. The proposed algorithms are compared with existing Cuckoo Search (CS) and BAT algorithm. The comparative analysis of these proposed and existing techniques are performed on the basis of Closest Data Center (CDC), Optimize Response Time (ORT) and Reconfigure Dynamically with Load (RDL). The RT of DCs of cloud and clusters, Processing Time (PT) of fogs is also optimized on the basis of CLW and FP.