PEGADyn: A Cluster-Based Energy Efficient Routing Protocol for Ad Hoc Networks

Because wireless sensor networks are limited energy environments that cannot be recharged, various routing protocols have been studied to maximize energy efficiency. One of the most energy-efficient routing protocols in this research area is PEGASIS (Power-Efficient Gathering in Sensor Information Systems), a hierarchical routing protocol of chain-based topology configuration. However, PEGASIS also has some considerable problems resulted in higher energy consumption such as (1) it does not consider the Base Station (BS) location; (2) it does not consider residual energy of Leader Nodes (LNs); (3) it needs an additional device such as Global Positioning System (GPS); and (4) its chain can become too long to keep energy efficiency. In this paper, we have suggested a new routing protocol to improve PEGASIS by getting rid of the above problems. Especially, we have used the concepts of relative distance, by which the suggested protocol does not need GPS and it allows BS to generate the location information table and construct the multi-chain topology. Furthermore, this multi-chain protocol has used the differential data transfer that aggregates only the changed values in order to reduce the amount of data transmission. Simulation results show that the suggested protocol can increase the network lifetime of WSNs compared to PEGASIS.

A protocol for position-responsive routing (PRRP) was developed dynamically to minimize the maximum distance between nodes and gateways/cluster heads, for maximum energy utilization of a deployed wireless sensor node. A tree routing technique was employed to display notable gains in key performance metrics. Network Simulator (NS3) software was utilized to evaluate and compare the effectiveness of the suggested technique using two selected conventional techniques: LEACH (Low Energy Adaptive Clustering Hierarchy) and PEGASIS (Power Efficient Gathering in Sensor Information System). The node energy efficiency of the proposed PRRP was obtained as 0.3881J, LEACH as 0.2249J and PEGASIS as 0.2755J. The total energy remaining after 100 second iteration process was evaluated as 19.4060J, 11.2490J and 13.7745J for PPRP, LEACH and PEGASIS respectively. The result obtained showed that PRRP achieved a 63% energy efficiency improvement over LEACH and 41% over PEGASIS, demonstrating superior energy conservation capabilities.

A wireless sensor network is a deployment of massive numbers of small, inexpensive, self powered devices that can sense, compute and communicate with other devices for the purpose of gathering local information to make global decisions about a physical environment. Wireless Sensor Networks are tightly constrained in terms of transmission power, onboard energy, processing capacity and storage, and thus require careful resource management. We mainly have LEACH(Low Energy Adaptive Clustering Hierarchy) and PEGASIS(Power Efficient Gathering in Sensor Information Systems) protocols. But LEACH doesn’t support distribution of cluster heads optimally and PEGASIS has the overhead of data delay. This proposed approach emphasizes on increasing network lifetime via efficient routing path ands , efficient energy consumption.

Traditional network data transmission (DT) has certain limitations in terms of processing, storage, and communication capabilities. Moreover, DT is easily affected by the network environment, which can reduce the real-time performance of DT. In severe cases, network transmission failures, DT interruptions, and other issues may even occur. As a new network, wireless sensor networks (WSN) have been widely used in military, industrial, agricultural, medical and other fields. In this paper, WSN was regarded as an important research method, and in-depth research was carried out around the real-time and energy consumption (for the convenience of the following text, the abbreviation for energy consumption is EC) of WSN DT. This paper focused on the issues of real-time performance, EC, and real-time transmission. It balanced EC and improved real-time performance through the low energy adaptive clustering hierarchy (LEACH) protocol and the power-efficient gathering in sensor information systems (PEGASIS) protocol. The experimental results showed that the real-time rates of LEACH under single reaction nodes were 45.5% and 48.6%, respectively. The lowest and highest real-time rates of PEGASIS were 86.2% and 89.5%, respectively. The real-time rate of PEGASIS was much higher than that of LEACH, proving that the proposed PEGASIS had high real-time performance and reduced DT delay.

The increasing complexity of Wireless Sensor Networks (WSNs) demand efficient techniques to fulfill the strict constraints imposed by the sensor nodes to achieve system performance. Interconnection between sensor nodes via wireless relays is another important requirement since one hop communication from source to base station may not be feasible due to two reasons; the distance between the sensor node and sink and poor communication link. While computing the path during data transmission, these sensor nodes consume major portions of energy. To conquer these issues, suitable routing techniques must be designed to intensify the network lifetime. Many researchers have discussed these issues in the current literature. LEACH and Power-Efficient GAthering in Sensor Information Systems (PEGASIS) is proven to be most efficient routing protocol provides a basis on top of which many routing protocols are proposed. This paper presents a chain-based routing protocol where the chain formation algorithm considers both distance and energy to select the neighbor node for formation of a chain. Further, sink mobility makes the protocol attractive and extends the wider applicability. Simulation results obtained from the protocol reveals that the superiority of our proposed system over the existing approaches in the literature.

Wireless Sensor Networks, referred to as WSNs, are made up of various types of sensor nodes. Recent developments in micro electro-mechanical technology have given rise to new integrated circuitry, microprocessor hardware and nano technology, wireless technology, and advanced networking routing protocols. Hospitals and health service facilities, the armed forces, and even residential customers represent a potential huge market for these devices. The problem is that existing sensor network nodes are incapable of providing the support needed to maximize usage of wireless technology. For this reason, there are many novel routing protocols for the wireless sensor networks proposed recently. One is Hierarchical or cluster-based routing. In this paper, we analyze three different types of hierarchical routing protocols: Low Energy Adaptive Clustering Hierarchy (LEACH), Power-Efficient Gathering in Sensor Information Systems (PEGASIS), and Virtual Grid Architecture (VGA). We tried to analyze the performance of these protocols, including the power consumption and overall network performance. We also compared the routing protocol together. This comparison reveals the important features that need to be taken into consideration while designing and evaluating new routing protocols for sensor networks. The simulation results, using same limited sensing range value, show that PEGASIS outperforms all other protocols while LEACH has better performance than VGA. Furthermore, the paper investigates the power consumption for all protocols. On the average, VGA has the worst power consumption when the sensing range is limited, while VGA is the best when the sensing range is increased. Using homogeneous nodes can greatly prolong sensor network’s life time. Also, The network lifetime increases as the number of clusters decreases

Energy equalizing routing for fast data gathering in wireless sensor networks

The area of Wireless Sensor Networks (WSNs) is one of the fast growing and emerging field in the scientific and engineering world.It is an ad-hoc network that consists of small nodes with sensing, computing and communicating wireless abilities.These sensor nodes are densely deployed in the sensor field environments.The environment can be an Information Technological framework, a physical world, or a biological system.The main objective of WSN is to sense the crucial information from the environment depending on the type of application for which it is deployed and send this information to its Base Station (BS) so that it can take corrective actions.These Sensor Nodes communicate with each other via various Routing Protocols.Protocols in WSNs are broadly classified as Flat, Hierarchical and Location Based routing protocols.This paper presentshierarchical routing protocol, Power Efficient Gathering in Sensor Information Systems (PEGASIS) and a comparative study on various versions of PEGASIS protocols.

The Comparative Study of three main energy efficient wireless sensor networks (WSNs) protocols are studied according to their working. The WSN protocols are Low Energy Adaptive Clustering Hierarchy (LEACH), Power-Efficient Gathering in Sensor Information System (PEGASIS) and Threshold Sensitive Energy Efficient Sensor Network (TEEN). These three protocols work on hierarchical structure to succeed their own functioning and improvement energy efficiency. Here include four quality of services (QOS) parameter performance namely “Average End to End Delay”, “Average Energy Consumption”, “Packet Delivery Ratio” and “Throughput” which are developed and compare to their QOS parameter performance. At the end of the analysis, design an overall study for these protocols with respect to their QOS parameter and further generalized the future scope of this study.

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.

The Internet of Things (IoT) has introduced transformative capabilities for ecological monitoring through the acquisition of real-time sensor-based data. In this context, the Internet of Trees (IoTr) has emerged as a promising domain for monitoring trees in forest ecosystems. However, the existing literature lacks species-specific, energy-efficient, and scalable frameworks capable of supporting proactive tree health surveillance and disease detection. Current research focuses on using IoTr for tree monitoring, but primarily covers basic soil moisture, with limited integration of disease-relevant parameters and species classification. This research addresses the existing research gap by proposing IoT-Based Tree Routing for Energy-Efficient Systems (I-TREES), a novel context-aware framework for real-time monitoring of tree health, with a specific focus on ash dieback and oak decline in the United Kingdom (UK). This research first evaluates three long-range communication protocols: Narrowband IoT (NB-IoT), Long Range Wide Area Network (LoRaWAN), and Sigfox, using MATLAB simulations to compare energy efficiency, Packet Delivery Ratio (PDR), Packet Loss Ratio (PLR), delay, latency, and throughput across two node densities (100 and 300 nodes). Based on the comparative evaluation, NB-IoT was selected as the optimal protocol, and the I-TREES framework is designed and simulated in Network Simulator 3 (NS-3) using a large-scale network of 700 IoT nodes to assess its performance in forest health monitoring. The comparative benchmark against six established routing protocols Low-Energy Adaptive Clustering Hierarchy (LEACH), Power-Efficient Gathering in Sensor Information Systems (PEGASIS), Hierarchical Clustering Algorithm (HCA), Heuristic Clustering and Scheduling Algorithm (H-CSA), Event-Driven Spatio-Temporal Optimisation (ESTO), and K-Means. The results showed that I-TREES consistently outperformed in terms of scalability, throughput, latency, and energy efficiency. In the final phase, a Proof of-Concept (PoC) approach is adopted to assess the feasibility of disease classification under limited real-world data conditions. A multimodal PoC dataset was constructed by integrating IoT sensor readings with custom labelled image data of ash and oak trees. Machine Learning (ML) models, including Random Forest (RF), Convolutional Neural Networks (CNN), Long Short-Term Memory (LSTM), and hybrid (CNN-RF, CNN-LSTM) architectures, are trained for disease detection. The RF-based multimodal model, in particular, offered strong interpretability and demonstrated consistently high performance in accuracy, precision, recall, and F1 score, supporting its suitability for real world deployment. The findings verified the effectiveness of the framework as an energy efficient and scalable approach for the detection of tree diseases. The proposed I-TREES framework presents a reliable and intelligent forest health surveillance framework for tree disease detection, suitable for real-world forest applications to manage diseases sustainably and support policy-making decisions for ecological resilience in the UK and similar environments.

Wireless Sensor Network are deployed in areas where human intervention is impossible like habitat monitoring, landslide and forest fire detection etc. Fundamental issues involved in Wireless sensor networks are expanding the network lifetime and reducing energy consumption because the nodes are battery operated. To overcome these challenges, innumerous techniques were established in past few years using techniques such as network protocols, in network data fusion algorithms, energy aware routing and locating optimal sink location. This paper concentrates on energy effective unequal clustering algorithm and inter-cluster routing which equalizes the energy utilization of the network using least distance multiple hop technique and improves the network lifetime. MATLAB based simulation results have shown that the proposed method is giving higher network life and decreased energy consumption by the network. A comparison has been made between the proposed and the existing algorithm such as Low Energy Adaptive Clustering Hierarchy (LEACH), Power Efficient Gathering In Sensor Information Systems (PEGASIS) and Delay Aware Data Collection Network Structure (DADCNS) to prove the efficiency of this hybrid algorithm.

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

A large number of spatially dispersed nodes on the wireless network create Wireless Sensor Networks (WSNs) to collect and analyze the physical data from the environment. The issues that affected the network and had an impact on network energy consumption were cluster head random selection, working node redundancy, and cluster head transmission path construction. Consequently, this energy constraint also has an impact on the network lifetime and energy-efficient routing. Therefore, the primary goals of this research are to decrease energy consumption and lengthen the network’s lifespan. So, using improved optimization algorithms, this paper presents a dynamic cluster head-based energy-efficient routing system. The Improved Coyote Optimization Algorithm (ICOA), in this case, consists of three phases setup, transmission, and measurement phase. The Improved Jaya Optimization Algorithm with Levy Flight (IJO-LF) then determines the route between the BS and the CH. It selects the most effective course based on the distance, node degree, and remaining energy. The proposed approach is compared with traditional methods and the routing protocols Power-Efficient Gathering in Sensor Information Systems (PEGASIS) and Threshold sensitive Energy Efficient Sensor Network protocol (TEEN) during implementation on the MATLAB platform. Performance indicators for the suggested methodology are evaluated based on data packets collected by the BS, energy usage, alive nodes, and dead nodes. The outputs of the suggested methodology performed better than the conventional plans.

Wireless sensor network is an emerging technology capable of having low-cost and low-power and battery-powered sensor node. At this point the protocol concentric clustered power-efficient gathering in sensor information systems and clustered general self organized tree based energy-balance routing protocol energy efficient protocol are used to increase the energy and to extend network lifetime. For these achievement of clustering techniques, optimization technique particle swarm optimization is used for data transmission through base station. If the base station is inaccessible region from the cluster-head, energy consumption will be augmented and it can shrink the lifetime of wireless sensor network. To conquer these, multi-hop gateway node is implemented with both protocol to achieve maximum lifetime and energy efficiency of wireless sensor network. To improve the quality-of-service (QoS) placing more number of gateways is required. So we propose a new algorithm nearer optimal algorithm which recursively computes least possible adequate dominating sets, at the time constantly preserving QoS requirements across iterations. In this paper comparison is done in terms of throughput, packets delivery ratio and number of nodes alive.