Zone Head Selection Algorithm Based on Fuzzy Logic for Wireless Sensor Networks

Clustering extends energy resources, improves scalability and preserves communication bandwidth of the network. Clustering is either categorized as static and dynamic or as equal and unequal. Hot-spots issue needs a high overhead and is prone to connectivity problems in the wireless sensor network and this can be only possible because of unequal clustering. In this paper a zone divisional method based on fuzzy logic has been proposed. This method uses a fuzzy logic to form clusters and allot nodes to them for the reduction of energy consumption, and extends the age of the sensor network. The simulation and results section shows that the outperformance of the proposed algorithm, where the (EAUCF) energy-aware unequal clustering fuzzy, (LEACH) lowenergy adaptive clustering hierarchy, (EAMMH) energy-aware multi-hop multi-path hierarchical, and (TTDFP) two-tier distributed fuzzy logic-based protocol for efficient data aggregation in multi-hop wireless sensor networks algorithms. The proposed algorithm has better results in terms of energy consumption minimization, load balancing, and prolongation of the network lifetime.

A Study on Multi-Hop Routing Scheme for Wireless Sensor Networks

Wireless sensor networks (WSN) play an important role in IoT (Internet of Things) as an interconnecting infrastructure. Working with a limited energy source, the vital challenge for WSN is to prolong the network lifetime as an important performance metric. Furthermore, the limitations of regular transmission technologies create localized network areas of a multi-hop fashion form that adds more constraints to enhance the network performance. Hence, the clustering strategies initially have solved these problems and received the attention of many studies, an approach using unequal clustering strategy has yielded some positive results since consumed energy gaps are avoided in regions near base stations. However, the routing strategy among cluster heads in multi-hop wireless networks is still a big challenge because of its inefficiency in energy consumption aspects. Therefore, in this paper, we propose a novel method that combining an unequal clustering problem and a simple multi-hop routing to prolong network life. The numerical results show that the proposed solution is more effective than other models in recent studies

Unequal Clustering Multipath Routing Algorithm for Wireless Sensor Network based on Clustering and Ant Colony

To improve the energy efficiency of the wireless sensor network (WSN), and extend the network life. This paper proposes an improved unequal clustering multipath routing algorithm (UCMRA). The algorithm improves the formula of cluster head selection probability and competition radius, and considers the energy factor, node density, optimal number of cluster heads, etc. Experimental results show that, compared with the traditional algorithm, UCMRA has more stable cluster head distribution, less energy consumption and longer network lifetime.

Fuzzy Logic Based Zone Head Selection Algorithm for Wireless Sensor Networks

Hot-spots are a problem that comes in the cluster-based routing protocol that employs multi-hop communication due to this problem the energy among the sensor nodes is not balanced. The hot-spots issue requires high overhead and is prone to connectivity issues in the sensor network this can be only possible because of unequal clustering. In this method, we have to act on all the nodes of the sensor network for communication. This process consumes high system energy if the numbers of nodes are very high. To offer guaranteed connectivity, decrease high usage and complexity, a fuzzy logic-based zone divisional method has been proposed in this paper. Use fuzzy logic to create clusters and assign nodes to them to decrease the consumption of energy and the age of the network prolongation. The simulation and results section shows the outperformance of the proposed protocol, where the (LEACH) low-energy adaptive clustering hierarchy, (EAUCF) energy-aware unequal clustering fuzzy,(EAMMH) energy-aware multi-hop multi-path hierarchical, and (TTDFP) two-tier distributed fuzzy logic-based protocol for efficient data aggregation in multi-hop wireless sensor networks algorithms. The proposed algorithm has better results in terms of energy consumption minimization, and prolongation of the network lifetime.

Improved Unequal-Clustering and Routing Protocol

We propose improved unequal-clustering and routing protocol (IUCR) protocol to solve both of these problems jointly. IUCR provide fixed area clustering derived from transmission range of network nodes. This clustering also develops strong network backbone that provides fail-over-proof routing. Efficient routing path is achieved by finding minimal hop-count with availability of alternate routing path.

Improved Unequal-Clustering and Routing Protocol

We propose improved unequal-clustering and routing protocol (IUCR) protocol to solve both of these problems jointly. IUCR provide fixed area clustering derived from transmission range of network nodes. This clustering also develops strong network backbone that provides fail-over-proof routing. Efficient routing path is achieved by finding minimal hop-count with availability of alternate routing path.

System Lifetime and Performance Improvement in Wireless Sensor Networks by having Improved Energy Distributed Unequal Clustering Protocol

Wireless Sensor Network (WSN) is becoming a very important area of research in today’s world and contributes a lot in the field of technology. Reducing energy consumption and improving the network lifetime is the key factor to be considered.Clustering provides an effective way for prolonging the lifetime of a wireless sensor network. Current clustering algorithms usually utilize two techniques, selecting cluster heads with more residual energy and rotating cluster heads periodically, to distribute the energy consumption among nodes in each cluster and extend the network lifetime. Also, it comprises various sensor nodes to detect different parameters. Among those non-replaceable batteries plays a greater part. Hence the system with such networks is essential that the sensor nodes consume as little energy as possible.To address the problem, we propose anovel model namely enhanced energy distributed unequal clustering which is mainly utilized for tackling energy consumption issues in multi-hop remote sensor systems. In the proposed method with an area of base station and energy are given significance as clustering parameters. Because of these parameters, diverse nodes are assigned. Here, another methodology has been proposed to enhance the working of EDUC, by electing cluster heads considering several nodes in the neighborhood. The incorporation of the area data for calculation of the opposition radii gives better adjusting of energy in correlation with the current methodology. The technique utilized is of holding similar bunches for a couple of rounds and is successful in decreasing the clustering overhead. The execution of the proposed convention has been assessed under three distinct scenarios and contrasted and existing conventions through reenactments. The outcomes demonstrate that the proposed plan beats the current conventions regarding system lifetime and performances in all the scenarios in terms of delay, energy consumption, packet loss ratio, and packet received ratio.