Reliable Transmission Scheme Against Security Attacks in Wireless Sensor Networks

There are many existing clustering protocols that aim at making the sensor network stay functioning longer out of which Low-Energy Adaptive Clustering Hierarchy (LEACH) and Threshold-based LEACH (T-LEACH) protocols. T-LEACH protocol takes advantage of LEACH main deficiency, which is about having high control overhead. In other words, T-LEACH proposes that cluster heads do not have to turn over every round but rather every batch of rounds. Nodes will keep serving as cluster heads as long as their energy is higher than a threshold energy. This article imposes upon major drawbacks of T-LEACH and proposes a Modified Threshold-based Cluster Head Replacement (MT-CHR). In MT-CHR, a new probability of being a cluster head, for any node in any round, has been proposed which agrees fairly with the assumptions introduced in LEACH protocol.

Wireless sensor networks (WSN) are a yield of advancement in information technology and the requirement of large-scale communication infrastructures. Routing of data via selected paths is a critical task in WSN as process need to be carried on under resource constraint situations. This route identification problem can be better handled by employing appropriate heuristic bio-inspired computational intelligence optimization method. The most frequently applied routing is hierarchical routing algorithm is Low Energy Adaptive Clustering Hierarchy (LEACH) algorithm which has limitations in identifying energy efficient inter and intra route communication, identification of number of cluster head (CH), an eminent node to communicate to CH and Base Station (BS), selection of CH, and computing residual energy level, etc. Hence, researchers are focusing on boosting the capability of LEACH clustering algorithm by applying heuristic bio-inspired computational intelligence optimization methods. The proposed work is an attempt in this direction through applying heuristic bio-inspired Grey Wolf Optimization algorithm (GWO) for improving the performance of LEACH algorithm. In this paper, focus is given to increase the overall network time by adapting two modifications to conventional algorithms (i) selection of vice cluster head (VCH) in addition to CH (VCH node will replace the CH when CH when CH node goes down due to unexpected reasons as sensor node work under critical and uninterruptable environments and (ii) selection of intra and inter relay nodes (intra relay node will enhance the life span during CH data gathering and inter relay node will further enhance the life span of CH by acting as a mediator between CH an BS). The Spyder-py3 tool is used to simulate the proposed algorithms, LEACH Binary Grey Wolf search based Optimization (LEACH-BGWO) and LEACH Discrete Grey Wolf search based Optimization (LEACH-DGWO) protocols. The proposed work is compared with cluster based LEACH algorithm, chain based power-efficient gathering in sensor information systems (PEGASIS) algorithm, bio-inspired GWO and Genetic Algorithm data Aggregation (GADA) LEACH protocols. The results prove that both proposed algorithms outperformed other conventional algorithms in terms of prolonged network lifespan and increased throughput. Among proposed algorithms LEACH-BGWO outperformed LEACH-DGWO

Wireless Sensor Networks (WSNs) is the vast area and developing very speedily now-a-days. This paper gives some of the major applications and critical limitations of WSNs like power and lifespan, communication bandwidth, memory size. Sensor nodes are working by node energy so the energy consumption is the essential issue in WSN. Routing in WSN consumes more energy than any other phase. Various routing techniques in WSNs are discussed and different routing protocols are illustrated. Low Energy Adaptive Clustering Hierarchy (LEACH) is one of the popular and feasible hierarchical clustering routing protocols in WSN. Working of LEACH is explained in brief. Furthermore, the descendants of LEACH e.g. LEACH-C (Centralized LEACH), LEACH-B (Balanced LEACH), LEACH-F, Multihop LEACH, MS-LEACH (Multihop and Single hop LEACH), MH-LEACH etc. are discussed in terms of the energy utilization. By analyzing the variants of LEACH, it is observed that the energy requirement in the cluster set up phase or data transmission phase is minimized to minimize the total energy consumption of the WSN. To elect the proper cluster head node, centralized approach is followed. Afterwards, data transmission will use the multihop communication technique. This will help to save some energy when base station is located far away from the cluster head node. Proposed protocol aims to decrease the energy overhead of the sensor nodes. The new approach is proposed entitled PV-LEACH which will save the energy consumption in cluster setup phase and also in data transmission phase of the conventional LEACH protocol. So, this will enhance the performance ratio in terms of energy consumption and life time of the sensor nodes.

Wireless sensor networks (WSNs) consist of a large number of small, low data rate and inexpensive nodes that communicate in order to sense or control a physical phenomenon. The major difference between the WSN and the traditional wireless network is that sensors are very sensitive to energy consumption. Moreover, the performance of the sensor network applications highly depends on the lifetime of the network and we expect the lifetime of several months to several years. Thus, energy saving is crucial in designing long-lived wireless sensor networks. Many researchers have focused on developing energy efficient cluster based protocols for WSNs, but there has not been much research on event driven WSNs and, their focus is on continuous driven networks. In this paper, we propose a modified algorithm of Low Energy Adaptive Clustering Hierarchy (LEACH) protocol which is a well known energy efficient clustering algorithm for WSNs. Our modified protocol called “Adaptive and Energy Efficient Clustering Algorithm for Event-Driven Application in Wireless Sensor Networks (AEEC)” is aimed at prolonging the lifetime of a sensor network by balancing energy usage of the nodes. AEEC makes the nodes with more residual energy have more chances to be selected as cluster head. Also, we use elector nodes which take the responsibility of collecting energy information of the nearest sensor nodes and selecting the cluster head. We compared the performance of our AEEC algorithm with the LEACH protocol using simulations .

The requirement for operation with low energy consumption is one of the major constraints that guide the de- sign of routing protocol in Wireless Sensor Networks (WSN) because each node is powered by a limited and generally an irreplaceable source of energy. In this context, we would like to propose a new protocol which respects the energy constraints, nodes' life duration and packets reception. This work is based on the protocol LEACH-C (Low Energy Adaptive Clustering Hierarchy) which uses a centralized architecture to select clus- ter-heads while involving the base station and the sensors' local information. It addresses the isolation problem of remote nodes that fail to communicate their information (coordinates and residual energies) to the base station. This results in an ineffi- cient group formation that leads to a huge loss of data and there- fore the network loses its performance. For this, we propose a solution that takes into account the remote nodes during the formation of groups. This new protocol, called LEACH-CKM, uses the K-means classification method to group the nodes and Minimum Transmission Energy routing protocol (MTE) to route information from remote nodes. Keywords—WSN; Routing Protocol; Energy Optimization; Clustering.

Wireless Sensor Network (WSN) is a self-configured network of light-weight nodes, that are used in many applications by sending their data through this network to a Base Station (BS), which in turn, delivers the data to its final destination. In WSN, the sensor node’s energy is usually limited, and thus, the overall power consumption of the network is a real challenge. Numerous methods have been proposed to overcome this challenge by improving the overall power consumption and thus, prolonging the lifetime of the network. Low Energy Adaptive Clustering Hierarchy (LEACH) protocol has been considered as a leading routing protocol in WSN, due to its low power consumption resultant from its cluster-based behavior. However, for dense networks, LEACH suffers from large burden over cluster head (CH), which might result in packet loss due to the induced congestion in the CH. In this paper, an improved algorithm based on LEACH is proposed to maximize the lifetime of WSN, by using another node to relieve CH’s burden. The routing path selection process is refined through selecting a new node that has the highest residual energy in each cluster to be an alternative gateway for the cluster head. Then, the routing path will be decided based on distance. This modified algorithm outperforms the original LEACH by 4.35% increase in the residual energy, which prolongs the network lifetime. However, there is a slight increase in the overhead ratio.

Restricted battery life is a crucial constraint in wireless sensor networks (WSNs). Many routing protocols have been proposed to reduce the energy consumption by extending the network lifetime. So, a new design of energy efficient routing using clustering is proposed where we use heterogeneous nodes for data transmission through the optimal path between cluster heads (CHs) and the base station (BS). This paper discusses the algorithm called Advanced-Multi-hop Low Energy Adaptive Clustering Hierarchy (LEACH) protocol with heterogeneous nodes. Multi-hop LEACH protocol changes the mode of communication to prolong the network lifetime from single hop to multi-hop between the CH and BS by reducing energy consumption. The paper tries to evaluate the performance of the network in terms of lifetime and stability by introducing the concept of optimum number of clusters and also considers the optimum number of hops in the network with heterogeneous nodes. This paper also provides the algorithm for the avoidance of the overlapping of the clusters and collisions in the network. For the evaluation and comparison of the performance of advanced single-hop and multi-hop energy efficient LEACH protocols with heterogeneous nodes, MATLAB simulations are carried out. Results show that advanced-multi-hop LEACH protocol outperforms the advanced single-hop LEACH protocol regarding energy efficiency, stability and network lifetime.

Due to the limitation of power and memory size for WSN (wireless sensor networks), the routing protocol of wireless sensor networks must maintain small routing information and reduce the power consumption as much as possible. LEACH (low-energy adaptive clustering hierarchy) protocol and PEGASIS (power-efficient gathering in sensor information systems) protocol are analyzed firstly in this paper. Use for reference of the ideas used in both of the two protocols of reducing power dissipation, a three-layered routing protocol for WSN based on LEACH (TL-LEACH) is given. Then, this improved LEACH protocol is simulated and the simulation results show that TL-LEACH protocol is with greatly improved WSN lifetime than LEACH protocol.

This paper proposed a EELP (Energy Efficient LEACH Protocol) routing protocol based on LEACH. LEACH (Low Energy Adaptive Clustering Hierarchy) is seminal work in the area of clustering-based protocol, proposed by W.B. Heinzelman. In EELP, all nodes are organized sequentially in the rooms of the apartments of a multi-story building. In this protocol, cluster head (CH) selection is determined as the highest energy by the base station. Simulation results demonstrated that our protocol is more energy-efficient than the LEACH protocol.

The emergence of wireless sensor network (WSN) makes the communication between people and things more extensive, and provides a new way for people to obtain information and more accurate real‐time communication. However, the regional distance in WSN is still a big problem. This method can not only optimize the cluster structure, but also reduce the number of member nodes in the cluster, the cluster head receiving energy, and reduce the data transmission distance between nodes. At the same time, the number of packets received by the base station increases, so that more sensing information can be obtained. The simulation results showed that compared with the smart Ethernet protection (SEP) protocol and the low energy adaptive clustering hierarchy (LEACH) protocol, the number of first node deaths (FND) of the grey wolf optimizer (GWO) algorithm was 153 and 233 times different from those of the SEP and LEACH protocols respectively at 100m*100m. In the case of 200m*200m, compared with that of SEP and LEACH, the number of FND of GWO was 152 and 200 times different. Finally, in the case of 300m*300m, compared with that of SEP and LEACH, the number of FND of GWO was 142 and 158 times different. The GWO algorithm has a higher node ARE ratio in a wider region. In the same 1000 rounds, the node ARE of GWO was 61%, while the node ARE of SEP and LEACH protocols were 7% and 3%, respectively. From the above results, it can be found that the GWO algorithm has been greatly improved in terms of network energy efficiency, network lifetime, etc., and can still work normally under larger scale monitoring. The innovation of this article lies in the localization problem of fixed node mobile sensor networks, proposing a mobile sensor network localization method based on mobile error nodes. This can optimize the distance between nodes and improve the positioning accuracy of the algorithm in both distributed and centralized situations. This article is protected by copyright. All rights reserved.

Wireless Sensor Network (WSN) is the deployed randomly and on the far places to sense information. The security, quality of service and energy consumption is the major issues of WSN. To minimize the consumption of higher amount of energy in these networks, clustering is applied. The Low-Energy Adaptive Clustering Hierarchy (LEACH) protocol is used for the cluster head selection in the network. The cluster head is selected based on the energy consumption and distance to base station. A node is selected as Cluster Head (CH) if it has the highest amount of energy and the least distance from base station. In this research work, genetic algorithm is applied with the LEACH protocol for the cluster head selection. The proposed work is implemented in Matlab. The results of existing LEACH protocol is compared with proposed LEACH protocol in terms of certain parameters. The comparative analysis and achieved outcomes show that the proposed approach performs well in terms of energy consumption as it consumes lesser amount of energy.

Wireless sensor networks (WSNs) are composed of many low cost, low power devices with sensing, local processing and wireless communication capabilities. Recent advances in wireless networks have led to many new protocols specifically designed for WSNs where energy awareness is an essential consideration. Most of the attention, however, has been given to the routing protocols since they might differ depending on the application and network architecture. Minimizing energy dissipation and maximizing network lifetime are important issues in the design of routing protocols for WSNs. In this paper, the low-energy adaptive clustering hierarchy (LEACH) routing protocol is considered and improved. We propose a clustering routing protocol named intra-balanced LEACH (IBLEACH), which extends LEACH protocol by balancing the energy consumption in the network. The simulation results show that IBLEACH outperforms LEACH and the existing improvements of LEACH in terms of network lifetime and energy consumption minimization.

Clustered routing protocols in wireless sensor networks (WSN) provide significant advantages in energy saving and data preprocessing. However, the communication greatly depends on cluster heads, which leads to severe security problems. In order to solve this problem, a clustered routing protocol with distributed intrusion detection for WSN (WSN_DID) is proposed in this paper. In WSN_DID all nodes are organized to identify intruding cluster heads in a distributed way by predistributed random keys. The experiments demonstrate that compared with classic cluster-based routing protocol in WSN, energy dissipation in WSN_DID is rather less and the toleration of intrusion is elevated.

This paper presents a level based clustering routing scheme to solve these problems. There are many routing protocols for Wireless Sensor Network in the literature, while this paper studies the Low Energy Adaptive Clustering Hierarchy (LEACH) protocol, which is a well referred protocol for WSN, and put forward its methodology. Every node can have a level number according to their hops to the Base Station. Then the level information is used to select Cluster Head (CH) and Second Cluster Head (SCH). Like LEACH, this paper also divided into rounds to setup clusters and transmit data. But it has different two kinds of cluster heads and in each round CH do the different things. When CH is selected, it will pick out a SCH from its cluster and the SCH can substitute the CH when CH work for a stable period. This methodology improves the choice method of cluster head and the communication mode from CH to the Base Station. Keywords-Wireless Sensor Networks; Level Based Routing; Clustering Hierarchy; Energy efficient

The convergence of the Internet of Things (IoT) and Artificial Intelligence (AI) is significantly transforming the landscape of future networking. The Internet of Things (IoT) is a technological paradigm that encompasses embedded systems, wireless sensors, and automation, facilitating the integration of various applications ranging from smart homes to wearable devices. In addition, the advent of artificial intelligence (AI) amplifies this influence by providing data-driven analytics, optimising processes, and presenting novel opportunities for growth. Nevertheless, the widespread adoption of devices within Internet of Things (IoT) networks gives rise to apprehensions regarding increased energy consumption. In order to ensure the longevity of network operations, it is imperative to employ energy-efficient protocols for sensor nodes that possess limited power resources. One example of a protocol that demonstrates this concept is the Low Energy Adaptive Clustering Hierarchy (LEACH) protocol. This protocol effectively divides networks into clusters and dynamically adjusts the cluster heads to optimise the transmission of data to the base stations. Our study enhances the LEACH protocol by incorporating digital twin simulation, thereby enhancing the efficiency of IoT systems. Virtual network models and AI analytics are employed to assess energy consumption and performance. Cache nodes play a crucial role within this framework as they collect data from cluster heads in order to transmit it to the base station. By leveraging artificial intelligence (AI) and simulation techniques, we are able to improve the energy efficiency and reliability of the Internet of Things (IoT) systems. The findings indicate a significant reduction of 83% in non-functioning nodes and a notable increase of 1.66 times in energy levels of nodes compared to conventional approaches. This study highlights a potential direction for energy-efficient, AI-enhanced Internet of Things (IoT) networking through the utilisation of the Low-Energy Adaptive Clustering Hierarchy (LEACH) protocol.