Network lifetime improvement using routing algorithm with sleep mode in wireless sensor network

Wireless sensor networks (WSN) play a key role in enabling wireless communication technology among several nodes to remotely communicate and exchange information. WSN consists of tiny sensor nodes equipped with battery, scattered in an area to gather information around an environment and send to data collection node known as sink or base station (BS). WSN have been widely used in various applications like agriculture, fire detection, health care and military and has become imperative necessity for future revolutionary area like UAV (unmanned aerial vehicles), IoT (Internet of things) and smart cities which employs large scale sensor nodes. However sensor nodes are limited to battery, memory, low computational power, resource and bandwidth. Continues sensing of events, makes node to drain its battery faster and goes dead fast. For resource constrained WSN, hierarchical cluster based approaches are considered as energy efficient and improves network performance for large scale WSN. Minimizing energy consumption and extending network lifetime are major challenging issues of WSN, clustering methods with optimized routing have offered solution to optimize energy utilization. To balance energy consumption and improve network lifetime many existing hierarchical clustering approaches have been proposed, however existing method does not consider rotation of cluster head (CH) and considers cluster head selection based on residual energy and distance parameter. In this paper we propose an improved energy efficient cluster tree (IEECT) based routing to improve energy efficiency of hierarchical cluster. IEECT considers modification of existing LEACH (Low energy adaptive clustering hierarchy) protocol to improved energy efficient LEACH by considering energy parameters like residual node energy and average network energy. IEECT accounts optimal number of cluster head (CH) and selection of CH is done using threshold value among sensor nodes. Proposed IEECT combines tree based routing and data aggregation scheme to maintain desirable quality of service. Simulation experiments are carried out by using network simulator. Performance of IEECT is evaluated in terms of PDR, delay, energy consumption, network lifetime and overhead.

Recent developments in wireless sensor networks (WSNs) have led to significant advances in energy-efficient routing protocols through the integration of deep learning and bio-inspired optimization algorithms. WSNs face critical challenges due to limited battery capacity, computational constraints, and dynamic network topology. This review article provides a comprehensive comparative analysis of state-of-the-art approaches for energy optimization in WSNs, focusing on clustering and routing protocols. We examine three major publications that propose hybrid frameworks combining deep learning architectures (CapsNet, ResNet-50) with metaheuristic optimization algorithms (ETSA, SOPSO, ACO). The analysis categorizes these protocols based on network architecture, energy models, optimization strategies, and performance metrics. We compare their effectiveness in extending network lifetime, reducing energy consumption, improving packet delivery ratio, and minimizing transmission delay. The comparative study demonstrates that hybrid deep learning-swarm intelligence approaches achieve 18-38% improvement in network lifetime, <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mathbf{1 2} \boldsymbol{-} \mathbf{1 4 \%}$</tex> reduction in energy consumption, and <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mathbf{1 5} \boldsymbol{-} \mathbf{2 4 \%}$</tex> lower delay compared to traditional protocols. This article serves as a comprehensive reference for researchers and practitioners working on nextgeneration energy-efficient WSN deployments.

The sensor network performs gathering, monitoring, and tracking of objects in the given area. The sensor nodes are normally distributed randomly in the network area for collecting the information. The major issues in Wireless Sensor Networks (WSN) are coverage, energy, and limited resources. Sensor Nodes’ (SN) performance depends on so many parameters but normally depends on Residual Energy (RE) and Distance from the base station. The Cluster Head (CH) cooperatively communicates with Base Station (BS) via routing protocols. The proposed Energy Efficient Multilevel Region Based (EEMRB) protocol performs the task by partitioning the entire network area into multiple levels and sub-levels. The sub-levels are partitioned to perform clusters to communicate the sensor via CH (s) using single/multi-hop communication to BS. The proposed protocol is compared with the Stable Election Protocol and shows improvement in network lifetime. Based on the proposed protocol data set, a Multivariate Polynomial Regression (MPR) Model is proposed to predict network lifetime. The model uses packet size and node density as network design parameters. The simulation results show that the size of the packet and network area play a major role in network lifetime. Therefore, the lifetime of the predicted model and EEMRB protocol are close to each other. This prediction model is suitable for the prediction of any network area's lifetime.

Wide usage of wireless sensor network (WSN) is the reason for development of many routing protocols. Recent advances in WSN observe the increased interest in the potential use in applications like Military, Environmental, Health, Vehicular, Mechanical stress levels on attached objects, disaster management etc. Wireless sensor networks are callously restricted by storage capacity, energy and computing power. So it is essential to design an energy efficient aware protocol in order to augment the network lifetime. WSN also has the influencing features to perform remote communication, it is also shrouded with various loopholes in its precise operation, where majority of the communication issues are raised from deployment of existing standards of routing protocols and algorithm. Sensors are expected to be remotely deployed in unnoticed environments. Routing as one key technologies of wireless sensor network has now become very important research work because the applications of WSN is everywhere, it is impractical that there is a routing protocol suitable for all applications. In this paper, a review on routing protocol in WSNs is carried out which are classified as data-centric, hierarchical and location based depending on the network structure. Then some of the multipath routing protocols which are widely used in WSNs like Multipath Multispeed Protocol (MMSPEED), Braided Multipath Routing Protocol, Energy-Aware Routing to improve network performance are also discussed. Massive research work has already been carried out in past to introduce some of the effective routing protocols to enable robust communication system in WSN. Advantages and disadvantages of each routing algorithm are discussed thereafter. This paper also discusses the critical open issues that are yet to be solved. This paper compares and summarizes the performances of routing protocols.

Wireless Sensor Networks (WSNs) have led to tremendous growth in the development of sensor technology and offer numerous applications, such as wildlife monitoring, environment, healthcare, military surveillance and security systems. In terms of performance, the evolutions of WSN routing protocols play a vital role in extending the lifetime of networking operations. Due to the limited resources of power in sensor nodes, the design and implementation of an energy-efficient routing protocol comprise a key challenge for researchers. Before, in the case of a static sink, nodes at farther areas from the sink transmit their sensed data at a longer transmission range and die early, while nearby nodes face lesser transmission costs and stay alive for a longer period. This unbalanced energy distribution creates energy holes in ares far from the sink in WSNs. Mobility-based sink routing protocols are proposed to minimize the sub-optimal energy consumption in WSNs, as the sink mobility covers the sensor field, which alleviates the overall load-balancing among sensor nodes. In order to overcome the energy hole issue while prolonging the network lifetime, it is important to determine the optimal mobility pattern. In this regard, we propose the Spiral Mobility based on Optimized Clustering (SMOC) routing protocol and the Multiple sink-based SMOC (M-SMOC) routing protocol for large-scale WSNs. Performance evaluations of the proposed protocols are compared with various existing routing protocols based on static sink, random mobility and grid mobility. Different numbers of performance parameters are considered for evaluation, such as network lifetime, network stability, packet drop ratio, packet delivery ratio, end-to-end delay, average energy consumption, network connection time and the impact of different heterogeneity levels. Experimental results show the benefits of the spiral mobility pattern and how it improves the network lifetime and stability period over the existing state-of-the-art routing protocols.

Energy efficient multipath ant colony based routing algorithm for mobile ad hoc networks

This work proposes an approach for improving energy-efficiency and thus increasing network lifetime in wireless sensor network (WSN) using a logical energy tree (LET). In our scheme, LET is constructed using the remaining available energy in each node. Two routing algorithms are framed based on LET: one with centralized sink node called LETCSN and the other with centralized sink node and secondary sink nodes called LETSSN. sensor nodes are deployed in some fixed patterns. A mathematical model is devised to understand the effect of node deployment pattern on improving network lifetime. Both proposed routing algorithms are evaluated with seven different deployment patterns, simulated in ns-2 and are compared with the existing classic algorithms based on the number of data packets, throughput, network lifetime, and data packet's average network lifetime product. Our evaluation and simulation results show that LETSSN maximizes the network lifetime for all node-deployment patterns taken into consideration.

Due to the limited resources of sensor nodes, an energyefficient routing algorithm of Wireless Sensor Networks is considered as one of the most important issues in improving network lifetime. To resolve this issue, several routing algorithms have been suggested, but the published studies have mainly focused on minimizing distances between sensor nodes or the number of hops. These researches have also assumed that all the sensor nodes participate in the sensing task. In this paper, we propose a new cluster head selection algorithm focusing on both the density of sensor nodes and sensing-awareness that has not been considered yet in other existing researches on cluster-based routing scheme. In the real sensor network environment, only a part of sensor nodes participates in data reporting, so consideration of sensing-awareness in a routing algorithm will have effect on network efficiency. Moreover, the density of sensor nodes that has resulted from geographical location of sensor nodes can be an important factor in cluster head selection. The simulation results show that the proposed algorithm, by considering these 2 factors simultaneously, reduces energy consumption and enhances network lifetime.

One of the major challenge in Wireless Sensor Networks (WSN’s) deployment is efficient energy consumption. Critical distance, proper routing algorithm and error control coding techniques can be used for energy optimization. As WSN contains a large number of power constrained sensors, the sensed data from the environment should be transmitted in a cooperative way to the base station (BS). The pattern of the clustering structure can extend the sensor network life time, reduce the total consumed energy and regulate the data transmission. Clustering concept combines group of sensors which are located in the same communication range. Some of the routing protocol like, SEED, LEACH, SEP, Z-SEP etc., suffers from idle listening problem, which cannot cope with an environment with sensor nodes. It leads to energy wastage across the network. To manage energy efficiency and traffic heterogeneity issues, a new routing protocol called enhanced energy efficient sleep awake aware intelligent sensor network (EEESAA) is proposed. Here, one sensor in each group will be in active mode whereas other sensors entered in sleep mode. Based on the nodes energy, sleep and awake node pairs will be altered. In the proposed method, one slot is allotted for group of pairs. The proposed approach is evaluated and compared against LEACH, SEP and Z-SEP protocols. Simulation results show that EEESAA protocol performs better than LEACH, SEP, Z-SEP in terms of cluster head selection, throughput, number of alive &amp; dead nodes and network lifetime.

Wireless sensor network consists of large number of sensor nodes which is used to capture environmental conditions, process and transfer it to base station.These sensor nodes are sensitive to energy consumption and gets exhausted on working.So we need to emphasize on reducing energy dissipation of sensor nodes in order to improve network lifetime.Various routing protocols are developed to enhance network scalability and stability.The cluster based routing is an efficient way of reducing energy dissipation by limiting data transmission from nodes to base station.For this purpose we proposed a new routing method which improves the life span of network, its data transmitting capability with low energy consumption.It is an improvised version of LEACH protocol which conserves energy by load balancing .Multi hop routing is proposed for the transmission of data.Reduction of energy consumption is achieved with the help of TDMA scheduling.Time division multiple access (TDMA)-based MAC can potentially reduce the delay and provide real-time guarantees as well as save power by eliminating collisions.To keep network alive we had added a random node on replacement of dyeing node.The performance evaluation of protocol is based on simulation test performed in network simulator 2 (NS2) to prove the effectiveness of this proposed method in terms of network lifetime and energy efficiency.

Wireless Sensor Network (WSN) is an emerging wireless communication networks to provide potential secure optimized data routing between source and destination. Presently the performance analysis of the Wireless Sensor Network routing technique and security protocols is the major research issues. A major issue in wireless sensor network (WSN) is the energy constraint in a node and its limited computing resources, which may pose an operational hazard or limitations on the network lifetime. Therefore, analyses of innovative secure routing techniques are required to utilize the resources of WSN to improve the life time of network in WSN. To design & develop any innovative wireless sensor network routing and security protocol, the network characteristics & its design issues are important consideration. The proposed spherical Grid Routing Protocol (SGRP) is designed and developed to enhance Quality of service to improve WSN performance using NS2 simulator compare to compared to modified LEACH techniques. The packet transmitted, packet received, average energy, throughput and packet delivery ratio are the main common performance measures that are used for performance analysis of proposed SGRP protocols.

Clustering protocol for data gathering is one of the effective ways to solve the energy hole problem in wireless sensor networks. However, most of the existing clustering protocols focus on the network model with uniform node distribution. They cannot effectively apply to the real network where the sensor nodes are randomly non-uniformly deployed. In this paper, we propose an energy-balanced clustering routing protocol (EBCRP) based on task separation. In this scheme, the network is firstly divided into clusters by using global information. And each of them has the same number of sensor nodes in order to balance the energy consumption of intra-cluster. In succession, task separation, the tasks of traditional single cluster head are separated and achieved by two cluster heads respectively, is proposed to reduce the traffic burden for single cluster head. Then, we explore an energy-efficient and reliable inter-cluster routing algorithm, which considers comprehensively three factors: residual energy, distance and available buffer space of nodes. Simulation results and performance evaluation of EBCRP show significant improvement in network lifetime and energy balance.

In this article, we consider a stochastic model of wireless sensor networks (WSNs) in which each sensor node randomly and alternatively stays in an active mode or a sleep mode. The active mode consists of two phases, called the full-active phase and the semi-active phase. When a referenced sensor node is in the full-active phase of the active mode, it may sense data packets, transmit the sensed packets, receive packets, and relay the received packets. However, when the phase of the sensor node switches from the full active phase to the semi-active phase, it is only able to transmit/relay data. When the referenced sensor node is in a sleep mode, it does not interact with the external world. In this article, first, we develop a stochastic model for the sensor node of a WSN, and then we derive an explicit expression of the stationary distribution of the number of data packets in the sensor node. Furthermore, we figure out some important performance measures, including the sensor node’s energy consumption for transmission, the energy consumption of the sensor operations, and the average energy consumption of the sensor node in a cycle of active and sleep modes. Also, a numerical analysis is provided to validate the proposed model and the results obtained. The novel aspects of our research are the development of a stochastic model for WSN with active and sleep features and the development of important analytical formulae for evaluating the energy consumption of a WSN. These results are expected to be useful as significant contributions to the fundamental theory of the design of various WSNs with active and sleep mode considerations.

QoSNET: An integrated QoS network for routing protocols in large scale wireless sensor networks

Reducing energy consumption has been a recent focus of wireless sensor network as it directly affects network lifetime. Geographical adaptive fidelity (GAF) is one of the well-known topology management multihop location-based routing protocols. Its main objective is to turn-off unnecessary sensor nodes while maintaining uninterrupted connectivity between communicating sensors. It is proved to be able to extend the lifetime of self-configuring systems by exploiting redundancy to conserve energy while maintaining application fidelity. Traditional GAF introduces unreachable corners; also the symmetric property is at stake thus providing with less network utility. In this paper, we propose a fuzzy logic based geographic routing protocol named FGAF-HEX to achieve higher energy optimization. Further, we use a GAF based Honeycomb Architecture to replace the traditional square grid with the hexagonal virtual grid. Simulation and analysis results show significant improvement in proposed work over traditional GAF in terms of various parameters, i.e., network lifetime and network connectivity. Results show that FGAF-HEX provides a substantial improvement in terms of various metrics as compared to traditional GAF.