Battery-operated Sensor Nodes Research Articles

A Novel Hybridized Cluster-Based Geographical Opportunistic Routing Protocol for Effective Data Routing in Underwater Wireless Sensor Networks

Underwater wireless sensor nodes comprise hundreds to thousands of battery-operated sensor nodes with limited bandwidth. These networks are employed to transmit the data with enhanced quality of service (QoS). However, efficient data routing is the most challenging obstacle in many underwater applications. To solve the issues in underwater sensor nodes, the hybridized cluster-based geographical opportunistic routing protocol with distance vector establishment has been proposed to transmit the data efficiently. Primarily, the proposed methodology finds out the shortest path with minimal hop count whereas the void node can be updated with infinite hop count. Thereafter, the sleep/wake scheduling and waiting mechanism and periodic beaconing algorithm are incorporated into the proposed model to attain a higher packet delivery ratio with minimal energy consumption. This proper scheduling and optimal cluster routing enhance the continuous data transmission in underwater applications. The simulation result reveals that the proposed method achieves better energy efficiency and higher network lifetime when compared with the existing clustering methods.

Performance Analysis of Sink Mobility Models for Wireless Sensor Networks: A Comparative Study

Wireless sensor networks (WSNs), deployed in the area of interest to gather data unattended, comprise numerous tiny, ponderous, and battery-operated sensor nodes (SNs). Numerous research publications presented strategies for extending the lifespan and performance of wireless sensor networks because SNs lifetime depends on limited battery life. One strategy for enhancing the performance of wireless sensor networks is to deploy an energy-rich sink capable of mobility to gather data sensed by stationary SNs. Therefore, several mobility models (MMs) were suggested. The primary objective of this investigation is to compare the effectiveness of wireless sensor networks using two MMs for mobile sinks (MSs): Kohonen’s self-organizing map-based model and the genetic algorithm-based model, in order to find the most suitable conditions under which each one of them can be used. As a result, network performance is investigated using the NS-2 simulator under various scenarios and MS speeds. Additionally, throughput, packet delivery ratio (PDR), and end-to-end (E2E) delay are the metrics used to analyze performance. Finally, messages are forwarded from their sources to the MS using the AODV routing protocol. The results show that the Kohonen-based model is suitable for small networks with moderate speeds of the mobile sink. On the other hand, the genetic algorithm-based model is suitable to be used with medium-sized networks with low speeds of the mobile sink.

Design of improved deer hunting optimization enabled multihop routing protocol for wireless sensor networks

A wireless sensor network (WSN) encompasses a huge set of sensor nodes employed to collect data and transmit it to a base station (BS). Due to its compact, inexpensive, and scalable nature of sensors, WSN finds its applicability in diverse real-time applications. The battery-operated sensor nodes necessitate the design of a multi-hop routing protocol for the effective utilization of available energy in the network. Routing can be considered an optimization problem and can be solved by the design of bioinspired algorithms. This study introduces an improved deer hunting optimization-enabled multihop routing (IDHO-MHR) protocol for WSN. The major intention of the IDHO-MHR approach is to optimally find the routes to the destination in WSN. The IDHO algorithm is initially derived by the incorporation of the Nelder Mead (NM) concept into the traditional DHO algorithm. In addition, the IDHO-MHR technique primarily derives a fitness function with the inclusion of two major variables, namely residual energy (RE) and distance. The nodes with higher RE and minimum distance have the probability of becoming optimal routes from the networks. The performance validation of the IDHO-MHR approach is performed, and the outcomes are inspected in various aspects. The experimental outcomes reported the supremacy of the IDHO-MHR protocol over the other recent approaches.

Improved-Equalized Cluster Head Election Routing Protocol for Wireless Sensor Networks

Throughout the use of the small battery-operated sensor nodes encourage us to develop an energy-efficient routing protocol for wireless sensor networks (WSNs). The development of an energy-efficient routing protocol is a mainly adopted technique to enhance the lifetime of WSN. Many routing protocols are available, but the issue is still alive. Clustering is one of the most important techniques in the existing routing protocols. In the clustering-based model, the important thing is the selection of the cluster heads. In this paper, we have proposed a scheme that uses the bubble sort algorithm for cluster head selection by considering the remaining energy and the distance of the nodes in each cluster. Initially, the bubble sort algorithm chose the two nodes with the maximum remaining energy in the cluster and chose a cluster head with a small distance. The proposed scheme performs hierarchal routing and direct routing with some energy thresholds. The simulation will be performed in MATLAB to justify its performance and results and compared with the ECHERP model to justify its performance. Moreover, the simulations will be performed in two scenarios, gateway-based and without gateway to achieve more energy-efficient results.

Model-based design for self-sustainable sensor nodes

Long-term and maintenance-free operation is a critical feature for large-scale deployed battery-operated sensor nodes. Energy harvesting (EH) is the most promising technology to overcome the energy bottleneck of today’s sensors and to enable the vision of perpetual operation. However, relying on fluctuating environmental energy requires an application-specific analysis of the energy statistics combined with an in-depth characterization of circuits and algorithms, making design and verification complex. This article presents a model-based design (MBD) approach for EH-enabled devices accounting for the dynamic behavior of components in the power generation, conversion, storage, and discharge paths. The extension of existing compact models combined with data-driven statistical modeling of harvesting circuits allows accurate offline analysis, verification, and validation. The presented approach facilitates application-specific optimization during the development phase and reliable long-term evaluation combined with environmental datasets. Experimental results demonstrate the accuracy and flexibility of this approach: the model verification of a solar-powered wireless sensor node shows a determination coefficient (R2) of 0.992, resulting in an energy error of only -1.57% between measurement and simulation. Compared to state-of-practice methods, the MBD approach attains a reduction of the estimated state-of-charge error of up to 10.2% in a real-world scenario. MBD offers non-trivial insights on critical design choices: the analysis of the storage element selection reveals a 2–3 times too high self-discharge per capacity ratio for supercapacitors and a peak current constrain for lithium-ion polymer batteries.

Diverse Congestion Control Schemes for Wireless Sensor Networks

Wireless Sensor Networks (WSNs) comprised of battery operated sensor nodes that collect data from their neighbor nodes and transmit the aggregated information to the sink node or the Base Station (BS). This may result in congestion near the BS and leads to a bottleneck situation in the network. In this paper, an extensive study of earlier reported diverse congestion techniques explicitly diverse Algorithm based - and Layer based-congestion techniques is carried out. Accordingly, a recommendation is drawn based upon their performance comparison. Furthermore, a demonstration is carried out for contemporary earlier reported strategies such as Pro-AODV, CC-AODV, EDAPR, ED-AODV and PCC-AODV by evaluating delay, packet delivery ratio (PDR) and packet loss ratio (PLR). Accordingly, a recommended congestion strategy is suggested depending upon the comparison of the demonstrated schemes.

Energy-efficient virtual infrastructure based geo-nested routing protocol for wireless sensor networks

The wireless sensor networks (WSN) are comprised of hundreds to thousands of compact and battery-operated sensor nodes. The deployed sensor nodes are widely used to sense the physical changes in the environment,which collect, aggregate, and transmit the information as data packets or static sink or monitoring station. Thedata transmission is very challenging under some extreme environments and applications. The efficient way of datatransmission is achieved by designing an energy-efficient routing protocol. The position of the sink nodes is broadcasted periodically to all other sensor nodes to forward the sensed data to the monitoring system or sink. The frequentbroadcasting of the sink position of the sink will lead to the consumption of more energy and collision in networks. Inorder to overcome these issues, the new energy-efficient virtual infrastructure based routing protocol has been proposed inthis paper. This proposed energy-efficient geo-nested routing protocol with a modified virtual multiring structure is usedto update and forward the sensed information. The proposed algorithm comprises of two phases: routing establishmentusing virtual infrastructure and data forwarding. During the first phase, the geo-nested virtual infrastructure constructedto form a closed-loop structure to identify the effective router nodes to route the data. This stage will minimize thenumber of hops based on depth threshold values. In the second phase of the algorithm, the links are formed during thelast stages are changed dynamically based on the sink mobility and energy levels. This will achieve the energy balanceand significantly improves the network lifetime of wireless sensor networks. The simulated results of the proposed routingalgorithm show that the energy consumption, impact of sink mobility, and end to end delay metrics are comparativelybetter than the existing routing protocol algorithms.

A Network Traffic Aware Tuning Algorithm in Wireless Sensor Networks

Wireless sensor networks (WSNs) are being widely deployed in many areas such as smart homes and Internet of Things. A main concern in WSNs is energy conservation because battery operated sensor nodes are expected to run for a long period of time without human intervention. The backoff mechanism implemented in the WSNs communication protocol is a key element to ensure energy efficient communication between sensor nodes. Many previous backoff schemes perform well in light or medium loaded networks. However, on a heavily loaded network, performance degrades significantly. Also, most of the proposed schemes in the literature are based on the assumption that the number of nodes is given. In this paper, we propose an adaptive scheme that estimates the number of competing nodes in wireless sensor networks by using the collision probability and adapts the backoff window parameters accordingly, such that higher throughput and energy efficiency are obtained. The numerical results show that the proposed scheme could achieve much higher throughput and energy efficiency than the standard and previous methods for almost all the different competing number of nodes.

Particle Swarm Optimization-Based Data Aggregation in Wireless Sensor Network

Wireless sensor networks have battery-operated sensor nodes, which need to be conserved to have prolonged network lifetime. The amount of power consumed for routing sensed data from the sensor node to the sink node is large. Thus, in order to optimize the energy usage in sensor network efficient data aggregation techniques are needed. Particle swarm optimization (PSO) is a speculative and evolutionary computing technique based on swarm intelligence for solving optimization problems in sensor network such as nodes deployment, node scheduling, data clustering, and aggregation. The paper proposes a PSO-based sensor network aggregation protocol (PSO-SNAP) with K-means to provide initial centroid. The PSO has been used to find the optimal aggregated value having minimum quantization error. The output of the K-means algorithm is used as an initial centroid in PSO. Apart from K-means, K-medoid and simple average has also been used to provide initial seed to the PSO algorithm and results of all three approaches are compared.

Quasi Oppositional Glowworm Swarm Optimization Algorithm for Energy Efficient Clustering in Wireless Sensor Networks

Wireless sensor network (WSN) becomes popular due to its applicability in distinct application areas like healthcare, military, search and rescue operations, etc. In WSN, the sensor nodes undergo deployment in massive number which operates autonomously in harsh environment. Because of limited resources and battery operated sensor nodes, energy efficiency is considered as a main design issue. To achieve, clustering is one of the effective technique which organizes the set of nodes into clusters and cluster head (CH) selection takes place. This paper presents a new Quasi Oppositional Glowworm Swarm Optimization (QOGSO) algorithm for energy efficient clustering in WSN. The proposed QOGSO algorithm is intended to elect the CHs among the sensor nodes using a set of parameters namely residual energy, communication cost, link quality, node degree and node marginality. The QOGSO algorithm incorporates quasi oppositional based learning (QOBL) concept to improvise the convergence rate of GSO technique. The QOGSO algorithm effectively selects the CHs and organizes clusters for minimized energy dissipation and maximum network lifetime. The performance of the QOGSO algorithm has been evaluated and the results are assessed interms of distinct evaluation parameters.

Adaptive-atom whale optimization algorithm using autonomous mobile ad hoc network for energy-efficient multipath routing

Mobile ad hoc network (MANET) consists of a group of self-operated mobile nodes that form a network without considering predefined infrastructure. In the network, each node poses less energy due to battery-operated sensor nodes. Numerous methods are devised for routing, but each method suffered from the energy constraint. This paper proposes an energy-efficient multipath routing protocol for exploiting different routes between source and destination to mitigate energy constraints. The key idea is to determine the optimal path from a set of paths available between the source and the target node. To improve the security in routing protocol, the factors, like energy, trust, and mobility are considered as major components. Here, the trust is modeled by considering trust factors, like average encounter rate (AER), successful cooperation frequency (SCF), direct trust, integrity factor, and forwarding rate factor. Moreover, secure routing is performed between the nodes using the proposed Adaptive-Atom Whale Optimization algorithm (Adaptive-AWOA). The proposed Adaptive-AWOA) is designed by incorporating the Adaptive concept in the Atom Whale Optimization algorithm (AWOA). The fitness function is newly modeled considering mobility, energy, and trust factors. The proposed Adaptive-AWOA outperformed the other methods with a minimal end-to-end delay of 0.009, maximal throughput of 85.802% and maximal packet delivery ratio (PDR) of 97.391%, respectively.

A novel energy-efficient data aggregation protocol for cognitive radio based wireless multimedia networks

In recent days, wireless multimedia cognitive radio networks (WMCRN) become a hot research topic due to its wide range of delay intolerant and time-critical applications. However, the increasing requirement of multimedia applications by cognitive radio networks (CRN) poses several design issues like energy efficiency, interferences, computational speed and memory. Due to the battery operated sensor nodes in WMCRN, it is very difficult to upload all multimedia information to the user in remote areas. Therefore, it is highly needed to design an energy-efficient data aggregation technique to minimize the data traffic and lengthen the network lifetime. But the conventional data aggregation schemes are not adaptable to the requirements of WMCRN due to the handling of massive sized multimedia data. In this view, this paper presents a new energy efficient Link Selection with Data Aggregation (EELSDA) Protocol for WMCRN. The proposed EELSDA model makes use of data aggregation factor in the link selection process of the graph routing technique. The proposed EELSDA model increases the possibility of data fusion at the intermittent routing nodes and minimizes the amount of data transmission in the network. The proposed EELSDA model utilizes link quality, communication energy and transmission frequency to select the optimal set of links. Consequently, reliability links to parent nodes with maximum remaining energy will be chosen for ensuring the success ratio for data transmission and total energy balancing of the network. Moreover, the relation among the transmission frequencies of the child as well as parent nodes represents the significant packet delay for data fusion in the specific parent node. A series of simulation results are carried out to ensure the effective performance of the EELSDA protocol over the compared methods in a significant way. The maximum network lifetime has been attained by the EELSDA model than all other models under diverse number of nodes. For sample, under the presence of 350 nodes, the EELSDA approach has obtained maximum lifetime of 2240 while the SPEED, MMSPEED, RAP and SAP technologies have resulted in lower lifetime of 1400, 1690, 1790 and 2100 correspondingly.

Secure and energy aware multi-hop routing protocol in WSN using Taylor-based hybrid optimization algorithm

The advancements of Wireless sensor network (WSN) in large number of applications made it common. However, the energy is a major challenge in the WSN environment as the battery-operated sensor nodes in the network consumes huge amount of energy during transmission. This work addresses the energy issue and provides an energy efficient multi-hop routing in WSN named Taylor based Cat Salp Swarm Algorithm (Taylor C-SSA) by modifying C-SSA with Taylor series. This method undergoes two stages for attaining multi-hop routing, which includes selection of cluster head (CH), and transmission of data. Initially, the energy-efficient cluster heads are selected using the Low Energy Adaptive Clustering Hierarchy (LEACH) protocol for effective data transmission, the sensor nodes sends data over the CH, which transmits the data to the base station through the selected optimal hop. The optimal hop selection is done using the proposed Taylor C-SSA. Moreover, the security aware multi-hop routing is performed by introducing trust model that involves indirect trust, integrity factor, direct trust, and data forwarding rate. The proposed Taylor C-SSA algorithm shows best performance in terms of energy, number of alive nodes, delay, and throughput values of 0.129, 42, 0.291, and 0.1, respectively.

Secure Hash Authentication And Cryptography Based Geographical Routing (SHAC-GR) For Wireless Sensor Networks

The expeditious growth in manufacturing anvils industries has lead towards the development of tiny devices. This growth has motivated to develop small and battery-operated sensor nodes that are widely adopted for establishing the reliable wireless communication. The wireless sensor based communication is generally divided into hierarchal and geographical deployment. Hierarchical system based approaches are widely studied in this field, limited work is present in the field of geographical WSN. In this work, we focus on the geographical WSN. Generally, these networks suffer from energy efficiency and security related issues. Hence, in this work we preset a combined approach to address these challenges. In order to mitigate the energy sparsity issue, we develop geographical routing scheme which selects the neighboring node based on residual energy of the node and distance from the sink node i.e. the maximum residual energy node from the neighboring node which is having less distance from the sink node is selected as next-hop. Due to this approach, the path computation and other network parameters computation is not required hence it reduces the power consumption. Further, we address the security issues where we present Hash modeling to secure the location, Key Exchange model for authentication by using ECDH approach , later we present ECIS based encapsulation method for data security and finally, a trust model based security system is developed. The trust computation of node helps to the routing whether to select the node for next hop or not. This multistage security approach is called as Secure Hash, Authentication and Cryptography based geographical routing (SHAC-GR) protocol. The proposed approach is simulated using MATLAB simulation tool and the performance of proposed approach is compared with existing technique that shows that the proposed approach improves the network performance in terms of network lifetime, energy and packet delivery rate.

Efficient Power Allocation based on CHESS-PC for Energy-efficient Public Safety Networks

The Public Safety Network (PSN) and public safety communications are being improved with the adoption of various sensor network (SN) technologies. A PSN is similar to an SN that contains battery-operated sensor nodes and to emergency first responders (EFRs) where the power consumption issue has always been around. Power consumption in an SN is a crucial factor that energy efficiency of the network relies upon. Proper management of power consumption makes the network efficient. The efficiency of various SNs has been greatly enhanced by utilizing clustering techniques. Besides clustering, the selection of an efficient cluster head (CH) increases the efficiency of the network even more. To show the constructive impact of cluster division on the efficiency of a PSN, we propose an algorithm using cluster division based on a cluster head selection scheme with power control (CHESS-PC). We cluster the network and select an efficient CH for each cluster using CHESS-PC. Then, we divide each cluster into cluster-center and clusteredge regions. Finally, we improve the power control technique and incorporate it in our proposed algorithm. The improved power control is used to control transmission power for every EFR and CH in the network. The results from implementing the proposed algorithm show a noteworthy reduction in power consumption in the network. And the algorithm provides an efficiency improvement of 38.07%, 29.39%, and 11.23% compared to a direct-communication scheme, a conventional clustering-based scheme, and the original CHESS-PC, respectively.

Energy-Aware Adaptive Weighted Grid Clustering Algorithm for Renewable Wireless Sensor Networks

Wireless sensor networks (WSNs), built from many battery-operated sensor nodes are distributed in the environment for monitoring and data acquisition. Subsequent to the deployment of sensor nodes, the most challenging and daunting task is to enhance the energy resources for the lifetime performance of the entire WSN. In this study, we have attempted an approach based on the shortest path algorithm and grid clustering to save and renew power in a way that minimizes energy consumption and prolongs the overall network lifetime of WSNs. Initially, a wireless portable charging device (WPCD) is assumed which periodically travels on our proposed routing path among the nodes of the WSN to decrease their charge cycle time and recharge them with the help of wireless power transfer (WPT). Further, a scheduling scheme is proposed which creates clusters of WSNs. These clusters elect a cluster head among them based on the residual energy, buffer size, and distance of the head from each node of the cluster. The cluster head performs all data routing duties for all its member nodes to conserve the energy supposed to be consumed by member nodes. Furthermore, we compare our technique with the available literature by simulation, and the results showed a significant increase in the vacation time of the nodes of WSNs.

QDVGDD: Query-Driven Virtual Grid based Data Dissemination for wireless sensor networks using single mobile sink

In wireless sensor networks, efficient resource management is a major concern for the battery operated sensor nodes. Data collection using mobile sink(s) is considered as a good strategy to prolong network lifetime and improve network coverage. Most of the existing mobile sink based data collection schemes operate in event driven or periodic sensing modes. There are several application environments, which dictate query driven data collection using a mobile sink e.g., a mobile sink might require reinforced data reporting from one particular network segment compared to others. In this regard, the existing query driven data collection schemes either impose too many constraints on network operation or poorly perform when delivering the requested data to a mobile sink with variable speed. In this paper we propose Query-Driven Virtual Grid based Data Dissemination (QDVGDD) scheme that aims to improve data delivery performance to a mobile sink. The proposed scheme makes use of a virtual infrastructure thereby causing minimal network control overheads while delivering the requested data with high quality of service to the mobile sink. We carried out extensive simulation works in NS-2.35 to evaluate the performance of our QDVGDD at different sink’s speeds and network sizes. Simulation results reveal improved performance of QDVGDD in terms of data delivery latency, data delivery ratio, average energy consumption, and estimated network traffic as compared to other state-of-the-art.

WSN Lifetime and Reliability Analysis From the Death Criterion Perspective

Wireless Sensor Networks (WSNs) are widely used in numerous critical applications, and require the network to have a prolonged lifetime and high tolerance to failures. However, the battery-operated sensor nodes used in WSNs cause the network to be resource-constrained. On the one hand, there is a continuous urge to efficiently exploit the WSN energy, and hence, prolong the network lifetime. On the other hand, WSN node failures are not only attributed to battery drain. Node failures can be caused by hardware or software malfunctioning. In this article, the authors assess the impact of the death criterion on the network lifetime and reliability. It is related how the data from the different sensors are aggregated to the death criterion. Additionally, the impact of the number of sensing cycles per network master on the network lifetime and energy efficiency for the different considered death criteria. The effect of the network master selection process on the energy efficiency is also examined. Finally, the impact of the death criterion on the reliability of the WSN is evaluated.

Modeling and performance analysis for a receiver-initiated MAC protocol in wireless sensor networks

Energy efficiency is a very important requirement in designing a MAC protocol for wireless sensor networks using battery-operated sensor nodes. We proposed a new energy-efficient MAC protocol, RIX-MAC, based on asynchronous duty cycling and receiver-initiated scheme. In this article, we analyze the performance such as throughput, delay, and energy consumption of RIX-MAC with modeling and simulation. For mathematical analysis, we first use the Markov chain model and determine the transmission and state probabilities and set the equations to solve throughput and delay. We also calculate the energy consumption by separating a cycle period into TX and RX durations. Our analysis results are validated by comparing with the simulation results obtained by NS-2.

Object Tracking in Wireless Sensor Networks: Challenges and Solutions

Wireless Sensor Networks (WSNs) are small, inexpensive and battery-operated sensor nodes that are deployed over a geographical area. WSNs are used in many applications such border patrolling, military intrusion detection, wildlife animal monitoring, surveillance of natural disasters and healthcare systems. Mobile object tracking is a vital task in all these applications. The goal of this work is to highlight the most important challenges in the field of object tracking and provide a survey of the WSN architectural design and implementation approaches for tackling this problem. To that end, we analyze how each approach responds to each challenge and where it falls short. This analysis should provide researchers with a state-of-the-art review and inspire them to propose novel solutions.