Energy Efficient Routing Research Articles

An Energy-Efficient Learning Automata and Cluster-Based Routing Algorithm for Wireless Sensor Networks

Wireless sensor networks (WSNs), which may be used for a broad variety of applications, have recently emerged as a prominent data collection paradigm. The fundamental concerns in wireless sensor networks are the efficient use of energy and the reliable delivery of data, both of which are largely determined by the rate at which packets are dropped. When developing an energy-efficient routing protocol, one of the most important steps is selecting a node to act as a successor node in a routing path. The application of learning automata theory to guide the routing decisions made by the sensors in a WSN has recently been the subject of research in the field of WSNs, where it has been shown to have several advantages. In this paper, a learning automata-based PSO relay selection scheme for energyefficient relay selection and reliable data delivery is proposed. The network is clustered using the LEACH protocol. The random number in the traditional LEACH protocol will be stabilized with the sensor node energy level for CH stability. Every sensor node in the network estimates the best possible routes to the sink node using the PSO algorithm. Instead of retransmissions, here we introduce learning automata for successor node selection during packet loss. The proposed learning automata calculate the next node’s selection probability in a routing path using multi-objective parameters like communication cost, residual energy, distance from BS, buffer size, and previous selection probability. Performance evaluation clearly showed that the proposed approach decreases energy usage, transmission delays, and data transfers while extending network lifetime. According to the experimental results, the proposed scheme can improve energy efficiency by 21.68%, delay by 31%, PDR by 87%, routing overhead by 0.5%, and throughput by 18.76% as compared to existing techniques like O-LEACH (Optimized Low Energy Adaptive Clustering Hierarchy Protocol) and EEPC (enhanced energy proficient clustering).

A social relationship-based energy efficient routing scheme for Opportunistic Internet of Things

Opportunistic Internet of Things (OppIoT) combines Opportunistic Networks and the Internet of Things to provide opportunistic communication between IoT devices and human-created communities in order to improve network connectivity, reliability, and longevity. This is significant because it introduces a new approach to connect and communicate smart devices in situations where there is no end-to-end connectivity. Due to the non-stable existence of connectivity between nodes, building a scalable, flexible, interoperable, and energy efficient routing protocol is a difficult issue. This study presents a new routing protocol for the Opportunistic Internet of Things called Social relationship based Energy Efficient Routing (SEER), which bases routing decisions on the forwarding feasibility degree, residual energy, and buffer capacity of nodes. SEER surpasses EBR and EDR in terms of delivery probability, hop count, and overhead ratio, according to simulation results utilizing the Opportunistic Network Environment (The ONE) simulator.

Proposed energy efficient clustering and routing for wireless sensor network

Wireless sensor network (WSN) is considered a growing research field that includes numerous sensor nodes used to gather, process, and broadcast information. Energy efficiency is considered one of the challenging tasks in the WSN. The clustering and routing are considered capable approaches to solve the issues of energy efficiency and enhance the network’s lifetime. In this research, the multi-objective-energy based black widow optimization algorithm (M-EBWOA) is proposed to perform the cluster-based routing over the WSN. The M-EBWOA-based optimal cluster head discovery is used to assure an energy-aware routing over the WSN. The main goal of this M-EBWOA is to minimize the energy consumed by the nodes while improving the data delivery of the WSN. The performance of the M-EBWOA is analyzed as alive and dead nodes, dissipated energy, packets sent to base station, and life expectancy. The existing research such as low-energy adaptive clustering hierarchy (LEACH), hybrid grey wolf optimizer-based sunflower optimization (HGWSFO), genetic algorithm-particle swarm optimization (GA-PSO), and energy-centric multi-objective Salp Swarm algorithm (ECMOSSA) are used to evaluate the efficiency of M-EBWOA. The alive nodes of the M-EBWOA are 100 for 2,500 rounds, which is higher than the LEACH, HGWSFO, GA-PSO, and ECMOSSA.

A Comprehensive Review on Energy Balancing and Routing in Wireless Sensor Networks

Wireless Sensor Networks (WSNs) play a vital role in various applications ranging from environmental monitoring to industrial automation. One of the key challenges in WSNs is the limited energy resources of sensor nodes, which necessitates the development of energy-efficient routing and clustering protocols to prolong network lifetime and ensure reliable data transmission. This literature review provides an extensive overview of recent research efforts in energy-efficient routing and clustering techniques for WSNs. The review covers a wide range of algorithms, including optimization-based, machine learning-based, hybrid, and protocol-based approaches. Additionally, it discusses the challenges faced in designing energy-efficient WSNs, identifies research gaps, outlines objectives, proposes future research directions, and concludes with insights into the current state and future prospects of energy-efficient WSNs

Tetra Optimization Based Hybrid Parameters for OFDM Modulated Wireless Sensor Network

Orthogonal frequency-division multiplexing [OFDM] is an information transfer technique in which a single data flow is divided between several closely spaced narrowband subchannel frequency range rather than a single Wideband channel frequency. The information is sent to the relay node there is a delay and some data is lost in the relay node is the major issue in the existing system. To overcome these challenges, The objective of this study is to minimize the overall energy consumption and to maximize the network lifetime. In this paper, a novel Five Input Hybrid Optimization Relay Node Selection and Energy Efficient Routing (FIHORNSEER) technique has been proposed for choosing the best relay based on noises. Ant Lion Optimization (ALO) is initially utilized to select the relay node's elite position. Secondly, the Crow Search Optimization (CSO) Algorithm is used for the phenomenon of position and memory of each relay. Finally, the Memetic Algorithm (MA) was generated by integrating the Ant Lion and Crow search optimization algorithm for the best relay node selection. The proposed framework is compared with previous techniques like FRNSEER, LMMSE, and HABO-OFDM Methods in terms of performance analysis, such as average utility, Energy Consumption, and Network Life Time. The result shows that the proposed FIHORNSEER improves the energy consumption better than 22.01%, 16.4%, and 12.2% FRNSEER, LMMSE, and HABO-OFDM, respectively.

Balancing Security and Energy-Efficiency in Vehicular Ad-Hoc Sensor Networks Using EHDSORP

Automobile networks have been the focus of growing amounts of research from scholarly community and organization as a method to improve traffic safety and provide drivers and passengers with real-time data. Beyond that, however, what is driving the expansion of VANETs is the need for a safe and secure network in moving vehicles. Ad hoc vehicular networks are made up of intelligent, on-the-road cars that can exchange data with one other and with permanent roadside infrastructure. In order to provide an energy-efficient and secure routing for ad-hoc sensor networks, a balancing security-based energy-aware routing leveraging the hybrid Fuzzy logic technique with dove swarm optimization-based routing (HFLDSOR) protocol is proposed in this study. The sensor nodes in this balancing security-based energy-aware routing are first set up in the ad hoc network. The clustering is carried out using an estimate of the distance between each node, and the cluster head (CH) is chosen using a fuzzy logic method. After the selection of the CH, the distance between each node, the quantity of energy left, and the number of neighbours for each node are evaluated as fuzzy logic criterion. In order to choose the best routing route for secured communication, the trustworthy nodes are forwarded. Balancing security-based hybrid vehicles that use less energy The optimum paths to the target are chosen using fuzzy logic method with dove swarm optimization-based routing (SE- HFLDSOR) protocol approach based on the parameters such as distance delay and energy objective function. Consequently, the SE- HFLDSOR protocol was used for safe and energy-efficient routing. The suggested model outperforms the comparable current procedures, according to the assessment performed using the MATLAB simulation tool. Hence, the SE- HFLDSOR protocol was appropriate for real-time applications.

CR-NBEER: Cooperative-Relay Neighboring-Based Energy Efficient Routing Protocol for Marine Underwater Sensor Networks

This paper proposes a Cooperative-Relay Neighboring-Based Energy-Efficient Routing (CR-NBEER) protocol with advanced relay optimization for MUSN. The utilization of the relay nodes, among all other sensor nodes, makes it possible to achieve node-to-node deployment. The proposed method focuses only on cooperation and relay optimization schemes. Both schemes have previously been implemented, and thus the proposed method represents the extended version of the Neighboring-Based Energy-Efficient Routing (NBEER) protocol. Path loss, end-to-end delay, packet delivery ratio, and energy consumption parameters were considered as part of the performance evaluation. The average performance was revealed based on simulations, where the overall average EED of Co-UWSN was measured to be 35.5 ms, CEER was measured to be 26.7 ms, NBEER was measured to be 27.6 ms, and CR-NBEER was measured to be 19.3 ms. Similarly, the overall EC of Co-UWSN was measured to be 10.759 j, CEER was measured to be 8.694 j, NBEER was measured to be 8.309 j, and CR-NBEER was measured to be 7.644 j. The overall average PDR of Co-UWSN was calculated to be 79.227%, CEER was calculated to be 66.73.464%, NBEER was calculated to be 85.82%, and CR-NBEER was calculated to be 94.831%. The overall average PL of Co-UWSN was calculated at 137.5 dB, CEER was calculated at 230 dB, NBEER was calculated at 173.8 dB, and CR-NBEER was calculated at 79.9 dB. Based on the simulations and evaluations, it was observed that the cooperation and relay optimization scheme outperformed previous schemes.

Energy Efficient Routing Protocols for Mobile Robots: A Review

Many vital applications benefit from mobile multi-robot teams, including search and rescue, environmental monitoring, military, unmanned space exploration, hazard detection and analysis. Communication between robots is important for group coordination and information sharing in mobile multi-robot teams. Because many mobile robot applications involve scenarios where communication infrastructure is destroyed or unavailable, mobile robot teams must regularly connect with one another through ADHOC networking. In such situations, low over-head and energy efficient routing systems for sending information are essential. The most difficult task is to provide a unified foundation for robot communication. The framework of Mobile Robots is described in this paper, as well as a review and analysis of several research papers on Energy Efficient Routing in Robotic Wireless sensor networks (RWSN).

Privacy preservation in wireless sensor network using energy efficient multipath routing for healthcare data

Every day, WSNs (Wireless Sensor Networks) based healthcare systems is witnessing improvement in providing advice to the health condition and living habits of people. Healthcare applications based on WSNs face crucial problems of security and are vulnerable to assaults. In this study, a privacy-preserving method using the multipath routing and principles of secret keys are suggested for healthcare applications based on WSNs. Multiple paths to the sink will be computed using ECSO (Enhanced Cuckoo Search Optimization). The proposed algorithm utilizes distance and also the traffic rate of paths in the form of a parameter for discovering the optimum paths utilizing ECSO. Among these chosen paths, just one ideal path is chosen based on node energy using BO (Butterfly Optimization) that helps in decreasing the energy demands of the network. Encrypted data will be sent to the sink using the selected path. It is found from the results that the secret key merged with multipath routing is helpful in achieving security of privacy in healthcare systems based on WSNs. The results of simulation performance metrics are throughput, End to End delay, PDR, Energy Consumption, encryption time.

A novel routing protocol for underwater wireless sensor networks based on shifted energy efficiency and priority

Underwater Wireless Sensor Networks (UWSNs) are among the most promising research areas these days due to their unique characteristics and diverse underwater applications. Though a number of routing protocols have been designed and implemented for UWSNs over the past few years, the researchers face several challenges, e.g., low speed of propagation, small bandwidth, limited battery power, etc., while designing routing protocols for communication in UWSNs. Acoustic sensor nodes are equipped with batteries with limited power and it is quite costly to replace or recharge them. The network will not survive for the desired period of time if the power of node batteries is not efficiently used. To effectively resolve this issue, this paper proposes a Shifted Energy Efficiency and Priority (SHEEP) routing protocol for UWSNs. The proposed protocol aims to enhance the efficiency of the state-of-the-art Energy Balanced Efficient and Reliable Routing (EBER2) protocol for UWSNs. SHEEP is built upon the depth and energy of the current forwarding node, the depth of the expected next forwarding node, and the average energy difference among the expected forwarders. Simulation results demonstrate that SHEEP improves the energy efficiency and packet delivery ratio in comparison to EBER2 by 7.4% and 13% respectively.

Secure cross-layer routing protocol with authentication key management scheme for manets

MANET (Mobile ad-hoc networks) is typically a no-infrastructure multi-hop network where every node interacts with other network nodes either indirectly or directly via intermediate nodes. A lot of research is being undertaken to save the energy of mobile nodes at different levels. Power-relevant issues can have an effect on every layer of the stack, making the traditional layered approach ineffective. In this work, cross layered routing protocol based on PSO (Particle swarm optimization) with adapted contention window technique is proposed. To form consistent and energy efficient routing paths, PSO algorithm uses Traffic index, Average energy load, data success rate & trust value parameters that are computed from network layer. After establishing routing paths, network's contentions are measured MAC layers for communications and contention with measured contentions and average energy loads. The trust of nodes is computed using the following constraints: group trust-provided by neighbour nodes & quality trust-computed by node QoS. Dual authentications with EnDA (enhanced dual authentication) using key management strategies for enhanced data security and integrity. ECC (Elliptical curve cryptography) and Diffie-Hellman key exchanges with bilinear maps improve security of communications. The suggested protocol when measured in terms of energy usage and secure key agreements during network's transmissions, showed satisfactory performances.

A Systematic Review Paper on Energy-Efficient Routing Protocols in Internet of Things

The Internet of Things (IoT) has witnessed remarkable growth, leading to the emergence of numerous applications and services. However, energy efficiency remains a critical concern in IoT networks due to the resource-constrained nature of many IoT devices. Energy-efficient routing protocols play a pivotal role in mitigating this challenge, optimizing energy consumption, and extending the operational lifetime of IoT deployments. This survey paper aims to provide a holistic understanding of the state-of-the-art approaches, their characteristics, strengths, limitations, and performance metrics. The survey encompasses a wide range of energy-efficient routing protocols proposed in the literature, including traditional routing protocols adapted for IoT scenarios and protocols specifically tailored for energy optimization. We discuss the impact of different network characteristics on the performance of energy-efficient routing protocols, such as network size, node density, mobility, and heterogeneity. Through this systematic survey, we aim to provide researchers, engineers, and practitioners with a comprehensive overview of energy-efficient routing protocols for IoT networks. The survey findings can serve as a valuable reference for protocol selection, performance evaluation, and the development of novel energy-efficient routing strategies in future IoT deployments.

A Cluster-Based Energy-Efficient Secure Optimal Path-Routing Protocol for Wireless Body-Area Sensor Networks.

Recently, research into Wireless Body-Area Sensor Networks (WBASN) or Wireless Body-Area Networks (WBAN) has gained much importance in medical applications, and now plays a significant role in patient monitoring. Among the various operations, routing is still recognized as a resource-intensive activity. As a result, designing an energy-efficient routing system for WBAN is critical. The existing routing algorithms focus more on energy efficiency than security. However, security attacks will lead to more energy consumption, which will reduce overall network performance. To handle the issues of reliability, energy efficiency, and security in WBAN, a new cluster-based secure routing protocol called the Secure Optimal Path-Routing (SOPR) protocol has been proposed in this paper. This proposed algorithm provides security by identifying and avoiding black-hole attacks on one side, and by sending data packets in encrypted form on the other side to strengthen communication security in WBANs. The main advantages of implementing the proposed protocol include improved overall network performance by increasing the packet-delivery ratio and reducing attack-detection overheads, detection time, energy consumption, and delay.

A Novel Approach on Efficient Data Transfer in Multimedia Communication Network

In the Wireless sensor networks, the main crucial part as we observe based on literature analysis managing Real-time data, load balancing, security of data, managing data, and also transmitting large (multimedia data) from source to destination using WMSN. Using the proposed system work on energy efficiency and robustness of the system and based on result analysis achieve the better result as compared to the existing system.
 Introduction: The growth of wireless sensor networks during the past ten years has altered how data is gathered and retrieved from different areas. With the expansion of communication infrastructure, the requirement and use of Multimedia Wireless Sensor Networks is becoming more widespread on these days. These networks confront a number of difficulties in ensuring user data is secure, trustworthy, and private, just like any other WMSNs.
 Objectives: This paper works on multimedia data transmission in WMSN and for that works on 3-bit LSB Embedding for transmitting large-size data with min energy consumption rate as compared to other methods like AES, ECC, etc.
 Methods: 3-bit LSB Embedding will be done which provides secrecy of the data and then we will implement the Energy Efficient routing to the embedded multimedia data for WMSN .
 Results: The shortest path optimization, using energy efficient routing protocol, by sensor nodes to transfer multimedia-data from source-node to destination-node achieved in WMSN. The average energy consumption and throughput of 400 multimedia sensor nodes transferring large amount multimedia-data transfer from source-to-destination WMSN. Existing work shows that it has high energy consumption and low throughput as compare to the proposed work.
 Conclusions: In this paper, work on energy-efficient real time multimedia data trans receive using Wireless sensor network use 3-bit LSB data embedding in multimedia data transmission in a wireless sensor network for compress data. Based 3-bit LSB data embedding for digital audio, image, video, and 3D media. Given the tremendous developments in digital media communications ranging from conventional digital audio to immersive media, LSB data hiding plays an important role in providing high capacity and maintaining imperceptibility by considering mechanisms of the HAS and HVS. This paper uses a hybrid approach for secure data as well as compressing it using a 3-bit LSB embedding approach as well as for making energy optimization using a trust mechanism for set initial threshold values of parameters like min energy required, transmission power, location, transmission power, etc. in the transmission side source node and another surrounding node will be selected based on a parameter that we reserve than apply 3-bit LSB embedding on data and on the receiver and apply same de-embedding after selecting receiver node. And for establishing communication select the most appropriate and optimized path based on energy and location-based estimation. With the proposed structure we achieve significantly improve in results as achieve more throughput and less energy consumption as compared to the existing system.

Performance Analysis of Centroid-based Routing Protocol in Wireless Sensor Networks

In this paper, a clustering-based energy-efficient routing protocol is designed to overcome the hotspot problem in Wireless Sensor networks (WSNs). We have divided the sensor nodes into several clusters, each cluster having a Cluster Head (CH) or a leader node and also implemented a centroid-based mobile sink. The sink moves to a location called “Energy Dependent Centroid Point” where the CHs need minimal energy to transmit data to the sink. We have defined this “Centroid Point” by an equation where the residual energies of CHs are used as a “weight factor” on a normal centroid equation. We have simulated the proposed algorithm and analyzed the results by varying the values of the energy weight factor in the centroid equation up to certain limits (α = 0, 1, 2, and 3). The simulation results are compared with WSN’s existing routing protocols having a mobile sink and a static sink. The comparison results show that our proposed centroid model with α = 0, where the mobile sink moves independent of the residual energies of CHs gives better performances in terms of network lifetime, energy loss, and total data packet transmission.

Energy efficient fuzzy logic prediction-based opportunistic routing protocol (EEFLPOR) for wireless sensor networks

Energy efficient fuzzy logic prediction-based opportunistic routing protocol (EEFLPOR) for wireless sensor networks

Energy Efficient Region based Source Distributed Routing Algorithm for Sink Mobility in Underwater Sensor Network

The residual nodes energy consumption is a primary factor to extend the lifespan of network. Utilizing a sensor node's very low-powerbattery in Underwater Wireless Sensor Networks (UWSNs) is still a difficult task. To increase the network lifespan, this paper proposes an Energy Efficient Region based Source Distributed Routing Algorithm for Sink Mobility in Underwater Sensor Network (EERSDRA-GCOP-UWSN). The proposed work consists of three Phases that are initialization phase, Routing Phase and Data transmission. For initialization phase, sinks and the sensor nodes are initialized. For Routing phase, Energy EERSDRA with sink mobility is employed to identify the region of sensor nodes. For data transmission phase, Geographic and Cooperative Opportunistic Protocol is proposed to select the best relay node on the basis of depth fitness factor. The proposed EERSDRA-GCOP-UWSN is evaluated with the performance metrics. Then performance of the EERSDRA-GCOP-UWSN proposed method provides 18.409%, 13.843% and 23.768% high Network lifetime, 27.744%, 24.881% and 19.703% low energy consumption, 17.346%, 20.852% and 26.347% high throughput and 16.385%, 20.416% and 22.907% high PDR when compared to the existing methods such as, Energy-efficient regional based cooperative routing protocol with sink mobility for UWSN (EERCRP-UWSN), a safe energy efficient and cooperative routing protocol for UWSN (SEECRP-UWSN), geo-opportunistic routing protocols for improving the residual energy range (EEGORP-UWSN) methods respectively. Finally, the performance of the proposed method achieves better result while compared to the existing methods.

Enhanced energy efficient sleep awake aware intelligent sensor network routing protocol for wireless sensor network

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 & dead nodes and network lifetime.

MLRS-RL: An Energy-Efficient Multilevel Routing Strategy Based on Reinforcement Learning in Multimodal UWSNs

In recent years, Multimodal Underwater Wireless Sensor Networks (M-UWSNs) have attracted widespread concern in academia. Due to the complex underwater communication environment and the increasing marine applications, it is a crucial issue for M-UWSNs to design an energy efficient routing strategy that can satisfy multiple transmission latency requirements of different marine applications. Reinforcement learning (RL) approaches with distributed dynamic optimization ability provide a prospective way to solve the aforementioned problem. Therefore, we propose an improved RL framework and then design an energy efficient multi-level routing strategy (MLRS-RL) based on this framework for multiple transmission latency requirements. In MLRS-RL, a method of model knowledge collection based on the time backoff principle is proposed to preliminarily learn the network environment information before network operates. The convergence speed of the RL framework can be accelerated by utilizing the model knowledge. Then, underwater nodes use the improved RL model to calculate the transmission rewards that data packets with different transmission latency requirements are sent to different candidate relay nodes. Finally, a cooperative transmission strategy using multiple relay nodes is designed to further improve the reliability of data transmission. We verify the effectiveness of the MLRS-RL strategy in terms of packet delivery ratio, transmission latency, energy efficiency, network lifetime, and delivery quantity.

Comparison of the new version of DEEC protocol to extend WSN lifetime

Wireless sensor networks (WSNs) are used in many different fields. One of the most recent and rapidly expanding applications is the Internet of Things (IoT), which enables the connectivity of numerous objects or devices over the Internet. However, WSNs have a bigger concern about battery power than mobile ad hoc networks, which shortens the network's lifetime. As a result, extensive research has been done on lowering WSNs' energy usage. Designing a hierarchical clustering algorithm is one of many methods for lowering the energy consumption of WSNs. Given the restricted hardware capabilities of the sensor nodes, modeling and building energy-efficient routing solutions to enhance the overall network lifetime has emerged as one of the most crucial approaches in wireless sensor networks. Cluster-based heterogeneous routing protocols, a typical feature of routing technology, have demonstrated efficacy in managing topology, energy consumption, data collection or fusion, dependability, or stability in distributed sensor networks. The existing Distributed Energy-Efficient Clustering (DEEC) clustering protocol is changed in this study by switching the power level between the nodes and adding a threshold limit for cluster head selection. The number of packets sent to a base station increases by 843% when comparing the proposed improved DEEC protocol to the existing DEEC protocol, increasing the number of living nodes to more than 10,000 rounds, or over 30,000 rounds, which can be used to extend the WSN lifetime. The suggested algorithm outperforms alternative energy-efficient protocols in terms of stability period and network lifetime under various scenarios of area, energy, and node density.