Data Transmission Cost Evaluation of MLFFA-A Novel Multi-Level Federated Filter Architecture

摘要

Data Fusion is an analytical technique of combining huge quantity of data coming from different independent subsystems where the complete data set may not be available with each subsystem and that can be applied for the security of various applications. In this paper, we analyzed different data fusion filter architectures available in the literature and compared the Transmission Cost with our Multi-level Federated architecture to improve the filtration of each signaling sensor for a reference sensor (RS) within its fusion domain. It is done by sending the individual sensor data through multiple levels of local filters (LF) each time sensor carries the data for fusion. This process reduces both Rate of Data Loss and eases the load on Master Fusion Filter (MFF).