Published Paper Details:

The usage of smartphone made possible for many real-time applications such as mobile crowdsourcing, by which the task owner can crowdsource the data from the smartphone users. There are many challenging problems such as data aggregation, data analysis and data collection faced by the resource constrained requester, when the data volume is extremely large i.e., Big Data (BD). The process of filtering redundant data and preprocessing raw data from the Big Data Analysis (BDA) by using set operations such as union, complementation and intersection. The most promising way for solving the BDA issues is the cloud-assisted approaches in terms of limited number of resources like computation and storage resources. If the privacy of the smartphone user's sensing data and identity are preserved well, the users will be ready to participate in the untrusted cloud. But due to the security issues faced by the cloud, the smartphone users are not willing to share their private data with the task owner. This review paper evaluates the researches done on the BDA and also auditing the major issues face by several techniques. The researchers can give the better solution for the current problems faced by using this procedure in the BDA