Data integration into cloud with efficient offloading of data from multiple nodes

Increase in Data traffic is a major challenge in the current business perspective, Distributed data collection from heterogeneous environments is a source of data traffic. Collecting the data from the distributed nodes and storing it to a centralized repository for analytical purpose is the main functionality of any business process management. The interface nodes which collect data from user might be Ad-hoc as well as some kind of Storage Area Network. Data integration from these nodes happen into Data nodes which are specialized for collecting the data. Then the Data nodes transmit the data into Communication nodes which in turn receives the data and transmit it to the centralized storage like cloud. The most important issue of the above depicted business data integration model is that there will be a huge energy loss and very less efficiency when data node or communication node tries to transmit data when the bandwidth is less, the distance between the nodes is quiet high or the network topology becomes incompetent due to network faults. The paper proposes a novel algorithm approach to perform offloading of data that is to transmit the data to the adjacent data node or communication node when the bandwidth, energy or efficiency is affected. The Offloading algorithm dynamically performs offloading of data based on the criterion like remaining energy, distance, and bandwidth and network topology. Fixing the offloading criteria and performing offloading of data improves the efficiency of the business data processing and integration.