An efficient framework for processing big data in internet of things enabled cloud environments

Internet of Things (IoT) is a platform which connects the objects through the Internet. The IoT devices have limited processing capabilities. This makes the processing and analyzing huge amount of data as a challenging task in IoT environment. Due to this disadvantage of IoT devices, it cannot be used in many useful applications where they are mostly required. Hence, a technique which helps in overcoming this disadvantage is mostly desired. One of the desired technologies is the cloud computing. The cloud computing has rich set of resources, and it is efficient in processing and analyzing data irrespective of its type and quantity. The services of the cloud will be provided by a cloud service provider (CSP). Selecting an appropriate cloud service provider is a major issue in an integrated environment of IoT and Cloud. Therefore, the focus of this paper is on cloud collaboration with IoT environment with suitable CSPs. A multi-objective genetic algorithm to find the optimized solution is proposed in this paper. The Non-dominated Sorting Genetic Algorithm 2 (NSGAII) and Strength Pareto Evolutionary Algorithm 2 (SPEA2) are used to analyze the performance of the proposed algorithm. The Profit Information (PI) to the individual and Trust Relationship (TR) value are considered as the objectives for selecting the CSPs. The results demonstrated that the proposed Multi-objective Genetic Algorithm (MGA) algorithm along with NSGAII performs more efficiently than MGA algorithm with SPEA2.