Improving the Energy Efficiency of Fog Computing-Based System for Selective Forwarding Detection in Mobile Wireless Sensor Networks Using Multipath Route

Abstract

Selective forwarding attacks in mobile wireless sensor networks are difficult to detect because they selectively delete packets. Such attacks are more dangerous than selective forwarding attacks in wireless sensor networks because it is difficult to detect a selective forwarding attack that occurs on sensor nodes with high mobility. In order to detect such attacks, a fog computing-based selective forwarding attack detection technique has been proposed. However, in the ad hoc on-demand distance vector (AODV) routing scheme using a single path, all packets are dropped until a selective forwarding attack is detected. In addition, energy consumption for path re-setting is significant because sensor nodes move frequently. To solve this problem, we propose a selective forwarding attack detection method using an ad hoc on-demand multipath distance vector (AOMDV) routing technique. The proposed scheme increases the packet transmission probability to the BS and increases the energy efficiency of the sensor network. Experiments with the proposed method show that the energy efficiency of the sensor network is improved by about 10%.