An Efficient and Dynamic Data Placement, Data Mining and Knowledge Discovery Using Surrogate Object in Mobile Cloud Paradigm

Abstract

Advancement in wireless and mobile communication with ubiquity of devices in cloud has the potential in storing incredible volumes of knowledge provided by data in the mobile devices. Knowledge provided by high volume of data stored in virtually infinite computing infrastructure, namely, the mobile cloud has become very essential in many day to day applications. However, mobile cloud faces many challenges such as dependency on continuous network connections, data placement problems, limitation and issues in data mining and knowledge discovery with multiple service providers. In this paper a novel data placement and knowledge discovery technique, SD2-Kd (Surrogate object based Dynamic Data placement and Knowledge discovery) is proposed, which interacts two or more service providers for the purpose of load balancing and data placement in cloud replication for fast and easy access. The proposed model provides a real-time data placement from different service providers using surrogate object in the mobile support station and an exact copy updated with the database and mining server in synchronized and unsynchronized manner. The model also allows mobile devices to participate seamlessly in mining process and act on behalf of mobile device and permit to cache the location based frequent datasets and retrieve the knowledge from those datasets which in turn provides better response time and minimizes the overall network traffic incurred due to mobility and database server failover. It handles the data placement and mining process at the object level. An extensive simulation of the D2S-Kd technique has been done and it shows that the proposed technique improves the response times, achieves better bandwidth utilization, provides support for disconnection and increases the success rate of mining progressively more than the existing techniques.