# GAFOR: Genetic Algorithm Based Fuzzy Optimized Re-Clustering in Wireless Sensor Networks
## 1 Introduction  
One of the critical issues in wireless sensor networks (WSNs) is the hot-spot problem [1]. It occurs due to the fact that the rate of energy consumption at the nodes around the base station (BS) and on critical paths is faster as compared to other nodes. The hot-spot problem results in network partition since intermediate nodes not only transmitting their information but also acting as a forwarder. A widespread placement of WSNs requires mitigating security threats. One of the prevalent threats is false report injection attacks by an adversary, resulting in energy drain of the nodes on the path. An example of the hot-spot problem is shown in Figure 1. The first event sensing node sends its event report to the next node on the path towards the BS. If the the second node senses an event, the node would send not only its report, but also act as a forwarder for the report it received from the first node. Consequently, the nodes closer to the BS and on critical paths experience more traffic and thus more energy consumption occurs at these nodes, resulting in a hot-spot problem that eventually creates partitions in the network. Furthermore, if these event reports are generated by an adversary, a significant amount of energy is wasted with the draining of batteries of the nodes en-route. In this paper, we therefore propose a genetic algorithm (GA) based fuzzy optimized re-clustering (GAFOR), where the end user is informed about nonexistent event by triggering an alarm so that an adversary cannot decode the complete message since event reports are transmitted via multiple paths. In that way, GAFOR can be more robust in mitigating the said attacks. In general, existing en-route filtering schemes [2; 3; 4; 5; 6] exhibit similar limitations: (1) underlying shortest fixed path routing, which is counter-intuitive from network lifetime perspective, (2) fixed security response for varying degree of attacks, and the (3) hot-spot problem. For example, the greedy perimeter-based stateless routing (GPSR) [7] is a shortest path routing that follows the fixed path routing approach. Several energy-efficient routing protocols [8; 9; 10] have been proposed in the past, but they do not focus on en-route filtering schemes. Energy consumption analysis of a few existing en-route filtering schemes is performed using the first order radio model [11; 12]. However, various assumptions about radio characteristics, such as amount of energy consumption in transmitters and receivers, could be biased towards different protocols. In order to address this issue, a commonly used radio model is used in GAFOR with an acceptable signal-to-noise ratio (i.e., \(E_{b}/N_{0}\)). Some of the major challenges hindering the widespread application of WSNs are security, network lifetime, and energy-efficiency. Efforts have been made to extend the network lifetime by improving underlying routing schemes [9]. To the best of our knowledge, our study is one of the first attempts to increase the network lifetime while preserving energy and security requirements of en-route filtering schemes. Generally, en-route filtering schemes use the shortest path routing such as GPSR which is designed for ad-hoc networks and does not perform well for WSNs. These limitations make it challenging to enhance network lifetime in en-routing filtering schemes and thus become an interesting problem. Therefore, the question arises as to whether it is possible to significantly improve network lifetime while maintaining energy and detection capacity. The aforesaid limitations-driven question thus motivates us to carry out this study. This study is important to lay out the foundation of an optimized re-clustering scheme to enhance network lifetime in en-route filtering scheme. For different network sizes (i.e., number of nodes) and attack ratios, GAFOR extends network lifetime from 2.29 to 3.64 fold on an average without perturbing the energy efficiency and security level compared to the existing schemes.