# GAFOR: Genetic Algorithm Based Fuzzy Optimized Re-Clustering in Wireless Sensor Networks
## 3 Literature Review  
Micro-electro-mechanical systems (MEMS) advancements [13] have triggered mushroom growth of WSNs. WSNs have witnessed widespread application due to their low cost, small size, wireless capability, and higher density characteristics. Network partitioning, a consequent of the hot-spot problem [1], is a critical challenge in extending network lifetime. En-route filtering schemes [2; 3; 4; 5; 6] save energy by filtering false reports as early as possible. En-route filtering schemes, such as dynamic en-route filtering (DEF) [2] and commutative cipher-based en-route filtering (CCEF) [3], offer improved security at the expense of network lifetime. DEF employs the hill-climbing method for key distribution in order to early detect false report(s). All nodes contain secret keys and a seed authentication key which are loaded from a global key pool randomly. Authentication keys are broadcasted by the \(CH\) to nodes on the path encrypted with secret keys before reports forwarding, which will be used for validation. The event reports that are not approved by each en-route nodes are dropped. DEF makes use of several keys with a key chain method, which renders it less useful for large-size WSNs. On the other hand, CCEF employs early detection of false reports to save energy. A secret key association can be established within the nodes and the (\(BS\)) for a complete session. Every node en-route contains its own witness. It is noteworthy that the symmetric key among the en-route sensor nodes is not shared, resulting in stronger security protection in comparison with existing symmetric key sharing schemes. In order to resist the attacks, the security response in CCEF relies on probabilistic method \(p=1/\alpha h\). The detection probability is fixed response, since system parameters \(\alpha\) and hop count \(h\) on a path are constant. In contrast, GAFOR uses dynamic security response. Based on attack intensity, this is dynamically carried out by selecting a path from multiple paths (i.e., with a varying number of verification nodes). Novel statistical en-route filtering (SEF) [4] first countered the en-route filtering issue and calculated the number of compromised nodes. This en-route filtering scheme forms the basis of later schemes. However, energy is saved using early filtering of false reports. Network lifetime extension using underlying routing is not catered to in the design. Figure 3: Shortest path routing. Given no more than \(t\) compromised nodes, the interleaved hop-by-hop authentication scheme (IHA) [5] successfully detect false data reports. It determined hops count upper bound that a false report may travel before being detected and dropped in the presence of \(t\) conspiring nodes. Similar to CCEF, IHA underlying routing is also based on shortest path routing and faced similar issues. The authors [6] presented a bandwidth-efficient cooperative authentication (BECAN) method for filtering injected fabricated report attacks. Furthermore, during filtering, it utilized a cooperative neighbor router (CNR)-based approach that not only achieves high filtering capacity but high reliability as well. GPSR [7] forwards packets using a greedy approach by selecting a node from the candidate nodes that is closest to the destination. While making forwarding decisions, only distance is considered while residual energy of the nodes in the routing process is ignored, which is an important criterion. Several works on routing [8; 9; 10] present energy-efficient and lightweight routing protocols. The work [11; 12] presented radio transmission models. In this work, we used a first order radio model for energy consumption and comparison in the WSNs. Research works [14; 15; 16; 17] present various attack types and their counter measures in en-route filtering schemes. Some interesting works exist for improving network lifetime [18; 19; 20; 21; 22; 23; 24] and energy efficiency [25; 26; 27; 28; 29].