HEEDAR: A Hybrid Energy Efficient Data Aggregation and Redundancy Removal Approach for Fog Enabled Internet of Things

Abstract

In modern technologies, Internet of Things (IoT) has grown as a novel communication technology.  Because of the limited hardware, operational capability and small sizes, IoT suffers several challenges.  Sensors and WSN are the building blocks of IoT. Since sensor nodes are driven by batteries, it is very difficult to run the critical operations that consume more power.  Therefore, it is required to eradicate redundant data before transmitting to the base station.  Aggregation is one of the prominent practices in the removal of duplicate data and enhance the energy efficiency; this practice is very much needed in order to extend the lifetime Networks. IoT equipped with fog computing has recently got substantial attention, due to the deployment of fog devices at the network edge.  It can enhance the quality of services in addition to low latency and location awareness in IoT applications.  Secured, authenticated data aggregation becomes an important fog computing services in IoT.  In this paper, we propose a hybrid, energy-efficient and reliable, data aggregation scheme enhanced with fog computing services. Experimental results prove that the proposed scheme is more efficient than the existing methods in terms of aggregation rates, network control overhead, power consumption and packet delivery ratio.

Keywords - Cloud Computing, Data aggregation, Fog Computing, Internet of Thing (IoT), Routing