Fuzzy Logic Based Cluster Head Research Articles

A Fuzzy Logic Based Cluster Head Election Technique for Energy Consumption Reduction in Wireless Sensor Networks

Wireless sensor networks deploy sensor nodes to different areas for data collection. The small size of these sensor nodes allows limited energy storage capacity, and most applications of the networks do not support recharging the batteries once their energy is depleted. Research on energy efficiency in wireless sensor networks is thus an active area that seeks to minimize energy consumption so that the sensor nodes can live longer. Clustering, one of the energy consumption optimization techniques, is employed in this research. It splits the network into smaller groups for data collection and forwards the data to the base station via appointed cluster heads. A fuzzy-based cluster head election strategy is proposed here to improve energy efficiency in wireless sensor networks. The input parameters of the fuzzy inference system are chosen as the residual energy, the node centrality, and the mobility factor. The system generates an output of the chance of a node being selected as a cluster head based on the combination of the values of the given inputs. The simulation results show that the proposed model reduces the network’s overall energy consumption and extends the sensor nodes’ lifetime.

Type II Fuzzy Logic Based Cluster Head Selection for Wireless Sensor Network

Wireless Sensor Network (WSN) forms an essential part of IoT. It is embedded in the target environment to observe the physical parameters based on the type of application. Sensor nodes in WSN are constrained by different features such as memory, bandwidth, energy, and its processing capabilities. In WSN, data transmission process consumes the maximum amount of energy than sensing and processing of the sensors. So, diverse clustering and data aggregation techniques are designed to achieve excellent energy efficiency in WSN. In this view, the current research article presents a novel Type II Fuzzy Logic-based Cluster Head selection with Low Complexity Data Aggregation (T2FLCH-LCDA) technique for WSN. The presented model involves a two-stage process such as clustering and data aggregation. Initially, three input parameters such as residual energy, distance to Base Station (BS), and node centrality are used in T2FLCH technique for CH selection and cluster construction. Besides, the LCDA technique which follows Dictionary Based Encoding (DBE) process is used to perform the data aggregation at CHs. Finally, the aggregated data is transmitted to the BS where it achieves energy efficiency. The experimental validation of the T2FLCH-LCDA technique was executed under three different scenarios based on the position of BS. The experimental results revealed that the T2FLCH-LCDA technique achieved maximum energy efficiency, lifetime, Compression Ratio (CR), and power saving than the compared methods.

FLCH: Intuitionistic Fuzzy Logic based Cluster Head Selection in Wireless Sensor Networks

A large number of tiny sensor nodes are grouped together to form Wireless Sensor Network (WSN). In Industry and other areas using of sensors are increasing every day. Therefore, the energy utilization of sensor nodes becomes a vital problem due to non-rechargeable battery. To improve the vital resources, the energy efficient clustering models are to be improved. This paper presents a novel idea IFLCH: Intuitionistic Fuzzy Logic based Cluster Head Selection for WSNs for electing Cluster Head (CH) based on the energy efficiency parameters such as residual energy, distance between neighbors. The proposed scheme also elects Super CH (SCH) based on the above-mentioned parameters along with number of neighbors. The simulation results compared the proposed model with the existing schemes and it receives better performance by selecting efficient CH and SCH.

Fuzzy Logic Based Cluster Head Selection and Sensor Node Classification for Energy Efficient Wireless Sensor Network

Fuzzy Logic Based Cluster Head Selection and Sensor Node Classification for Energy Efficient Wireless Sensor Network

Distributed fuzzy logic based cluster head election scheme (DFLCHES) for prolonging the lifetime of the wireless sensor network

Wireless sensor networks (WSNs) is considered as the predominant technology due to their high suitability and adaptability that makes it possible to be deployed in wide range of applications like civil and military domain. But energy-constraint is the significant feature that needs to be addressed for sensor networks since energy drain of sensor nodes affects network lifetime, stability and co-operation of sensor nodes in the event of enforce reliable data dissemination. Cluster head election has to been performed periodically in order to handle energy balance for facilitating reliable packet delivery. Most of the cluster head election schemes of the literature elect a node as cluster head either randomly or by elucidating their stochastic probabilities. Hence a Distributed Fuzzy Logic based Cluster Head Election Scheme (DFLCHES) that discriminates and discards packets from the sensor nodes that has the least probability of being elected as cluster head is proposed. DFLCHES utilizes five significant parameters such as trust, energy, node density, hop count and centrality measure for quantifying the probability of cluster head election. This DFLCHES is run on each neighbor nodes of the cluster members to facilitate the action of discrimination. DFLCHES also balances the energy consumption of the cluster members during transmission as it discards packets from ineligible nodes. Further the action of cluster head election has to be optimized periodically for reducing and balancing energy consumption for prolonging the network lifetime. In DFLCHES, the process of optimizing cluster head depends on the incorporation of the concept of Genetic algorithms for enabling and ensuring reliable routing.

A Secure Cluster Based En-route FilteringScheme in Wireless Sensor Networks

Wireless Sensor Networking is one of the most prominent technology that is used in almost all real time applications. WSN is used in the estimat ion of temperature in Cyber Physical Network System(CPNS) where the sensor nodes are deployed in an unsecured environment. In this kind of environment the lifetime of the network , consumption of energy , re-election of cluster head plays an effective role . So, the network lifet ime with limited battery power becomes a problemat ic issue. By selecting the cluster head randomly among the nodes may leads to the issue of battery loss , false data injection attacks. In order to prevent this we make use of Fuzzy logic technique. In fuzzy logic based cluster head election the base station is responsible for the cluster head election because the base station is more powerful than the sensor nodes in terms of power of computing , unlimited supply and storage of power , and memory. So by selecting the most efficient node as the cluster head we can securely forward the data to the base station by using secure algorithms.