Lifetime Of Wireless Sensor Networks Research Articles

Multi Duty Cycle Scheduled Routing in Wireless Sensor Network-lifetime Maximization

Cluster-based protocols are best for applications that require reliability and a continuous functioning environment with a sustainable lifetime of WSN. The dynamic nature of the sensor node makes energy conservation a challenging issue. Sensor node scheduled based on sensing error for energy conservation compromise the accuracy of prediction. The high data accuracy achieved using a single duty cycle controller at each node with compromised throughput and increased routing overhead. Duty Cycle Controller managing a more number of control messages at the network level leads to control packet interference with data packet transmission, increasing packet drop and minimizing throughput. Also, the single-duty cycle controller at the network level leads to increased control overhead. The proposed multilevel cluster-based approach focuses on the appropriate cluster design, selection of cluster head, and sensor nodes scheduling based on sensing error. The proposed method applies a multi-duty cycle controller at each cluster level, and control messages handled are related to nodes in a cluster. Thus has less interference and packet drop leading to maximum throughput than existing methods. The simulation results demonstrated that the proposed method with sensor nodes scheduled at individual cluster levels using a multi-duty cycle controller exhibited improved network lifetime, throughput, and reduced energy consumption compared with the state-of-the-art techniques.

Investigation of energy efficient protocols based on stable clustering for enhancing lifetime in heterogeneous WSNs

There are certain challenges faced with wireless sensor networks (WSNs) performances, consumption can be seen amongst all these challenges as a serious area of research. Data from sensor nodes are transmitted by most WSN energy either among many nodes or to the base station (BS), and due this connection, several routing protocols were developed for supporting in data transmission in the WSNs. Extending network lifetime in an operational environment is the major objective of the wireless sensor network. Charging or exchanging sensor node batteries is almost impossible. Energy balancing and energy efficiency are significant research scopes as per designing of routing protocols aimed at self-organized WSNs. A heterogeneous WSN is one where every node has different amount of energy linked to it before it is deployed in a network. Therefore, different energy efficient routing protocols have been proposed which enables lesser consumption of energy, longer stability period which leads to the network lifetime increasing. In this study, the average energy of a WSN is computed after every logical round of operation for our protocol-HPEEA and compare it with two well-known heterogeneous protocols namely-SEP and CCS. At the end of the considered number of logical operations, MATLAB with simulation results confirm that HPEEA protocol have a reduction in the energy consumption compared to other protocols.

An Energy-Efficient Mobile Sink based Clustering using Simulated Annealing for Traversing

Abstract: Over recent decades, both scientific and commercial societies have been seeing the progress of wireless sensor networks (WSNs). Clustering is the most common form of growing WSN lifetime. The optimal number of cluster heads (CHs) & structure of clusters are the main problems in clustering techniques. The paper focuses on an efficient CH preference mechanism that rotates CH between nodes amid a greater energy level than others. Original energy, residual energy as well as the optimum value of CHs is assumed to be used by the algo for the choice of the next category of IoT-capable network cluster heads including ecosystem control, smart cities, or devices. The updated version of K-medium algo k-means++. Meanwhile, Simulated Annealing is implemented as the shortest path tree for mobile nodes which is constructed to establish the connection between the nodes for finding the shortest and secure path for data transmission hence resulting in faster data sending and receiving process. Keywords: WSN, CH selection, Residual energy (RE), Network Lifetime, Energy-efficient (EE)

ERP-DDA: Event Reporting Protocol Based on Distributed Data Aggregation for Wireless Sensor Networks

Wireless Sensor Networks (WSNs) have a wide range of applications in human life. Accordingly, WSNs have beenthoroughly considered in research community to improve their performance and address their challenges. Eventreporting in WSNs has always been a major challenge in terms of energy consumption. Event reporting requiressensing the event and sending a reporting packet from the sensor to the centralized base station (BS). However,sensor’s energy is limited and stored in a non-rechargeable battery. Therefore, several event-reporting (or datacollection) protocols have been proposed to improve energy consumption in WSNs, and consequently, to extendtheir lifetime. In this paper, we propose an efficient event reporting protocol for WSNs called Event ReportingProtocol Based on Distributed Data Aggregation (ERP-DDA). This protocol mainly aims at reporting any event byno more than one sensor node such that energy saving is satisfied in the whole network. To achieve this goal, ERPDDAis mainly based on the following features: it is a cluster-based protocol, it is a multi-hop routing protocol, itapplies distributed data aggregation, and it employs variable clustering and cluster head selection. Simulationsshow that ERP-DDA significantly extends the lifetime of WSNs compared with other related protocols.

IDCT: Intelligent Data Collection Technique for IoT-Enabled Heterogeneous Wireless Sensor Networks in Smart Environments

Wireless Sensor Networks (WSNs) lend themselves to a wide variety of applications in our daily lives, such as environmental monitoring, safety, health-care, animal monitoring, etc. However, one of the key issues in WSN is energy constraints. This makes energy-conservation one of the major keys to the efficient functioning and lifetime of WSN. In this paper, given a network of nodes with heterogeneous energy, our goal is to determine energy-aware disjoint dominating sets (DSs) that work as data collection nodes in each round, to improve overall WSN lifetime. In order to accomplish this goal, we propose an intelligent data collection technique with two phases, the collector nodes selection, and the data gathering path formation and collection phases. In the collector nodes selection phase, an energy-aware algorithm based on swarm intelligence is proposed to construct disjoint dominating sets that work as collector nodes in each round. In the data gathering path formation and collection phase, data gathering path is determined for achieving maximal data collection efficiency and reduced energy consumption. The efficiency of our proposed technique is proved mathematically and through simulations.

An Energy-Efficient Routing Protocol for 3D Wireless Sensor Networks

Energy optimization is a key problem of the energy-limited wireless sensor network (WSN), which is usually deployed in the three-dimensional space. In order to alleviate this problem, this paper studies the energy-efficient routing protocol for 3D WSN. The less sensor nodes work simultaneously, the more energy is saved. To minimize energy consumption on the premise of satisfying the full coverage of discrete points of interest (DPOI), finding the least and optimal node set for routing is an important problem. Through studying this problem, we propose an algorithm employing the improved genetic algorithm to find the minimum set of sensor nodes which can ensure the full coverage of DPOI. On the basis of the optimal node set, we propose a new adaptive clustering routing optimizing energy consumption, which includes three parts. The first one is selecting the cluster head according to the residual energy of the sensor node and the distance from the base station. The second one is setting the intra-cluster communication mode by considering the angle of node space. The last one is deciding inter-cluster communication mode by combining single-hop and multi-hop. To fully utilize the energy of the network, we design a node wake-up scheme to wake up the sleep node to replace the sensor nodes which runs out of energy. This policy also can make our proposed protocol suitable for the rechargeable WSN. In addition, we also consider the additional energy consumption of retransmission caused by the unreliable wireless channel. Simulation results show that our proposed scheme is obviously superior to other existing schemes in prolonging the WSN lifetime.

Analysis of the multi-objective cluster head selection problem in WSNs

The target of wireless sensor networks is to gather data regarding certain phenomena. This is why they are meant to last as long as possible. An efficient strategy to extend the wireless sensor network lifetime is to organize sensors hierarchically into clusters and, for each cluster, select one of the sensors as the cluster head. The task of the cluster head is to collect data from the cluster members and retransmit it to the base station across the network. By means of cluster organization, the process of acquiring data is enhanced and, consequently, the lifetime of the network is increased. Nevertheless, in addition to data collection and transmission, every cluster head performs additional tasks. Thus, they spend their energy quicker than the cluster members. This is the reason why cluster head selection is a multi-objective optimization problem. In this paper, we consider the three objectives, distance, delay, and residual energy, and apply three multi-objective evolutionary algorithms, specifically NSGA-II, SMS-EMOA, and MOEA/D, for studying the problem by means of solving several instances. We analyze the conflict between the objectives, present a proper multi-objective performance comparison of the algorithms, and investigate the efficiency of the found solutions regarding network energy consumption.

RETRACTED ARTICLE: System Lifetime and Performance Improvement in Wireless Sensor Networks by Having Improved Energy Distributed Unequal Clustering Protocol

RETRACTED ARTICLE: System Lifetime and Performance Improvement in Wireless Sensor Networks by Having Improved Energy Distributed Unequal Clustering Protocol

A survey on the characterization parameters and lifetime improvement techniques of wireless sensor network

Abstract Emerging technologies, such as the Internet of things (IoT), machine learning (ML) and machine-to-machine networks encourage deployment of large-scale wireless sensor networks (WSNs). The major problem in WSN is the limited energy of node batteries. Therefore, the efficient use of node energy for data sensing, processing and communication operations is important to maintain a fully operational network for longest period of time. Literature presents a wide range of lifetime maximization techniques for WSN such as resource allocation algorithm, clustering and routing, sleep–wake scheduling, energy harvesting, MIMO technique, Distributed source coding, genetic algorithm and sink mobility. These techniques effectively lessen the energy consumption and enhance the lifetime of the entire wireless sensor network in various applications. Besides energy consumption, the characterization parameters such as coverage and connectivity, communication and modulation schemes, operational environment, network parameters, node parameters and service parameters also have great impact on WSN performance. This paper presents a comprehensive survey of state-of-the-art research works that improves the performance of WSN by optimizing various network characterization parameters and lifetime maximization techniques. These results highlight the key issues which affects WSN performance and provide a roadmap for WSN designers for effective implementation of novel WSN strategies.

Improved LEACH protocol for increasing the lifetime of WSNs

<p>Recently, wireless sensor network (WSN) is taking a high place in several applications: military, industry, and environment. The importance of WSNs in current applications makes the WSNs the most developed technology at the research level and especially in the field of communication and computing. However, WSN’s performance deals with a number of challenges. Energy consumption is the most considerable for many researchers because nodes use energy to collect, treat, and send data, but they have restricted energy. For this reason, numerous efficient energy routing protocols have been developed to save the consumption of power. Low energy adaptive clustering hierarchy (LEACH) is considered as the most attractive one in WSNs. In the present document, we evaluate the LEACH approach effectiveness in the cluster-head (CH) choosing and in data transmission, then we propose an enhanced protocol. The proposed algorithm aims to improve energy consumption and prolong the lifetime of WSN through selecting CHs depending on the remaining power, balancing the number of nodes in clusters, determining abandoned nodes in order to send their data to the sink. Then CHs choose the optimal path to achieve the sink. Simulation results exhibit that the enhanced method can decrease the consumption of energy and prolong the life-cycle of the network.</p>

Increasing life-time of wireless sensor network using energy-efficient and fault tolerance algorithms

Energy-efficiency ofwireless sensor networks (WSN) becomes an essential issue in the research area. This is because of the energy constraints in WSN that depend on a battery, which is difficult to replace or recharge; therefore, multiple clustering algorithms were proposed to achieve efficiency in using the available energy as much as possible. This paper proposed energy-efficient and fault-tolerance algorithms that enhance thelow energy adaptive clustering hierarchy (LEACH) protocol by three algorithms. The first focuses on selecting the best cluster head and the second focuses on minimizing the required nodes within the same cluster. Simultaneously, the third fault tolerance algorithm uses software engineering techniques like sleep schedules to increase network lifetime as much as possible. The testing results of the proposed algorithms prove the claim of enhancing the lifetime of WSN. In order to check improvement of lifetime of WSN we have compered the results of the proposed algorithms with standered algorthim. The results show prove the claim of enhancing the life-time of WSN, where the total lifetime of WSN rise from about 550 rounds to reach 4100 when utilized self-checking process and rised up to 5200 after enhance minimum distans.

Joint Deployment Strategy of Battery-Free Sensor Networks with Coverage Guarantee

The energy limitation of wireless sensors limits the lifetime of the traditional wireless sensor networks. The <b>Battery-Free Sensor Network (BF-WSN)</b> is a new network architecture proposed in recent years to address the limitation of wireless sensor networks. In a BF-WSN, the battery-free node can harvest energy from the ambient environment, and thus the lifetime of a BF-WSN is unlimited in terms of energy. The coverage quality is an important measurement of BF-WSNs. Considering the specific features of BF-WSNs, we propose a new deployment concept for BF-WSNs, named <i>Joint Deployment</i>. It aims to determine the locations and working schedules of sensor nodes to maximize network coverage quality. Based on the joint deployment concept, we propose a new deployment problem of battery-free sensor nodes. We prove that this problem is at least NP-Hard. We also analyze the upper bound of this problem. Furthermore, we propose an approximated algorithm to solve this problem and analyze the time complexity and the ratio bound of the algorithm. Extensive simulations are carried out to examine the performance of the proposed algorithm. The simulation results show that the algorithm is efficient and effective.

Feature-Selection and Mutual-Clustering Approaches to Improve DoS Detection and Maintain WSNs' Lifetime.

Wireless Sensor Networks (WSNs) continue to face two major challenges: energy and security. As a consequence, one of the WSN-related security tasks is to protect them from Denial of Service (DoS) and Distributed DoS (DDoS) attacks. Machine learning-based systems are the only viable option for these types of attacks, as traditional packet deep scan systems depend on open field inspection in transport layer security packets and the open field encryption trend. Moreover, network data traffic will become more complex due to increases in the amount of data transmitted between WSN nodes as a result of increasing usage in the future. Therefore, there is a need to use feature selection techniques with machine learning in order to determine which data in the DoS detection process are most important. This paper examined techniques for improving DoS anomalies detection along with power reservation in WSNs to balance them. A new clustering technique was introduced, called the CH_Rotations algorithm, to improve anomaly detection efficiency over a WSN’s lifetime. Furthermore, the use of feature selection techniques with machine learning algorithms in examining WSN node traffic and the effect of these techniques on the lifetime of WSNs was evaluated. The evaluation results showed that the Water Cycle (WC) feature selection displayed the best average performance accuracy of 2%, 5%, 3%, and 3% greater than Particle Swarm Optimization (PSO), Simulated Annealing (SA), Harmony Search (HS), and Genetic Algorithm (GA), respectively. Moreover, the WC with Decision Tree (DT) classifier showed 100% accuracy with only one feature. In addition, the CH_Rotations algorithm improved network lifetime by 30% compared to the standard LEACH protocol. Network lifetime using the WC + DT technique was reduced by 5% compared to other WC + DT-free scenarios.

Analysis of Relay Node Failure in Heterogeneous Wireless Sensor Networks

Introduction: Fault tolerance is an important issue for assuring data reliability, energy saving and prolonging the lifetime of wireless sensor networks. Since, sensor node, relay node, etc. are prone to failure, there is a need an effective fault tolerance mechanism. Methods: Relay nodes are used as cluster heads and the concept of two disjoint paths is employed for proving fault tolerance against link failure. To evaluate the fault tolerance level, mean time to failure and subsequently, failure rate are calculated, that reflect the reliability of the network. Results: The results show that as the area size of the network increases, the average fault tolerance level of the network becomes constant. Furthermore, when the mean time to failure of the network decreases, then the failure rate increases. It means the overall reliability of the network with a smaller network size is more than the larger network size. Discussion: This paper presents a detailed analysis of relay nodes failure under distinct network configurations in heterogeneous wireless sensor networks. Conclusion: This analysis helps the network designers to decide the quantity of deployment of relay nodes with respect to fault tolerance level. It may also help to prevent relay nodes failure by taking appropriate actions so as to increase the fault tolerance level of the network as well as network reliability.

An Efficient Routing Approach to Maximize the Lifetime of IoT-Based Wireless Sensor Networks in 5G and Beyond

The Internet of Things grew rapidly, and many services, applications, sensor-embedded electronic devices, and related protocols were created and are still being developed. The Internet of Things (IoT) allows physically existing things to see, hear, think, and perform a significant task by allowing them to interact with one another and exchange valuable knowledge when making decisions and caring out their vital tasks. The fifth-generation (5G) communications require that the Internet of Things (IoT) is aided greatly by wireless sensor networks, which serve as a permanent layer for it. A wireless sensor network comprises a collection of sensor nodes to monitor and transmit data to the destination known as the sink. The sink (or base station) is the endpoint of data transmission in every round. The major concerns of IoT-based WSNs are improving the network lifetime and energy efficiency. In the proposed system, Optimal Cluster-Based Routing (Optimal-CBR), the energy efficiency, and network lifetime are improved using a hierarchical routing approach for applications on the IoT in the 5G environment and beyond. The Optimal-CBR protocol uses the k-means algorithm for clustering the nodes and the multihop approach for chain routing. The clustering phase is invoked until two-thirds of the nodes are dead and then the chaining phase is invoked for the rest of the data transmission. The nodes are clustered using the basic k-means algorithm during the cluster phase and the highest energy of the node nearest to the centroid is selected as the cluster head (CH). The CH collects the packets from its members and forwards them to the base station (BS). During the chaining phase, since two-thirds of the nodes are dead and the residual energy is insufficient for clustering, the remaining nodes perform multihop routing to create chaining until the data are transmitted to the BS. This enriches the energy efficiency and the network lifespan, as found in both the theoretical and simulation analyses.

A Mobile Charger based on Wireless Power Transfer Technologies: A Survey of Concepts, Techniques, Challenges, and Applications on Rechargeable Wireless Sensor Networks

Battery power limitation of sensor nodes (SNs) is a major challenge for wireless sensor networks (WSNs) which affects network survival. Thus, optimizing the energy consumption of the SNs as well as increasing the lifetime of the SNs and thus, extending the lifetime of WSNs are of crucial importance in these types of networks. Mobile chargers (MCs) and wireless power transfer (WPT) technologies have played an important long role in WSNs, and much research has been done on how to use the MC to enhance the performance of WSNs in recent decades. In this paper, we first review the application of MCs and WPT technologies in WSNs. Then, forwarding issues the MC has been considered in the role of power transmitter in WSNs and the existing approaches are categorized, with the purposes and limitations of MC dispatching studied. Then an overview of the existing articles is presented and to better understand the contents, tables and figures are offered that summarize the existing methods. We examine them in different dimensions such as advantages and disadvantages etc. Finally, the future prospects of MC are discussed.

Enhanced Double Cluster Head Selection using Ant-Colony Optimization for Energy-Efficient Routing in Wireless Sensor Network

The energy-efficient routing strategies regulate the network lifetime for wireless sensor networks (WSNs). The researchers have continuously improved the WSN lifetime using their algorithms and strategies since the sensor world. Clustering significantly improves the network lifetime and energy efficiency in WSN. In this paper, the concept of double cluster heads (CHs) is introduced in a single cluster of the WSN and Ant Colony Optimization as the nature-inspired algorithm is applied for a CH selection between double CHs. The Ant Colony Optimization is based on the natural behavior of the ant. The simulation result presents that the proposed algorithm enhances the network lifetime and residual energy because a double cluster head significantly reduces the workload of a single cluster head. The other nature-inspired algorithms can be applied for the energy efficiency of WSN in the future.

INCREASE THE LIFETIME OF WIRELESS SENSOR NETWORKS USING HIERARCHICAL CLUSTERING WITH CLUSTER TOPOLOGY PRESERVATION

Wireless sensor networks consist of hundreds or thousands of nodes with limited energy. Since the life time of each sensor is equivalent to the battery life, the energy issue is considered as a major challenge. Clustering has been proposed as a strategy to extend the lifetime of wireless sensor networks. Cluster size, number of Cluster head per cluster and the selection of cluster head are considered as important factors in clustering. In this research by studying LEACH algorithm and optimized algorithms of this protocol and by evaluating the strengths and weaknesses, a new algorithm based on hierarchical clustering to increase the lifetime of the sensor network is proposed. In this study, with a special mechanism the environment of network is layered and the optimal number of cluster head in each layer is selected and then recruit for the formation of clusters in the same layer by controlling the topology of the clusters is done independently. Then the data is sent through the by cluster heads through the multi- stage to the main station. Simulation results show that the above mentioned method increases the life time about 70% compared to the LEACH.

Multifactorial evolutionary optimization to maximize lifetime of wireless sensor network

Prolonging network lifetime is a crucial issue for wireless sensor networks, as sensor nodes operate on limited amounts of battery energy, and replacing or recharging nodes is still quite challenging. One approach is using relay nodes to alleviate sensors’ energy usage when transmitting data. In this work, we tackle the issues of relay node assignment for wireless single-hop sensor and multi-hop sensor networks in three-dimensional terrains. Traditionally, researchers have focused on solving relay node selection for either single-hop or multi-hop networks, one at a time. We propose MFRSEA, a multifactorial evolutionary algorithm utilizing a network random key representation, a constraint-aware fitness function, and a novel crossover operator in order to optimize for both network types simultaneously. Experimental results show that our method outperforms the baseline in several key metrics.

A Competition-Based Unequal Clustering Multihop Approach for Wireless Sensor Networks

The energy efficiency and stability of wireless sensor networks (WSNs) have always been a hot issue in the research. Clustering is a typical architecture for WSNs, and cluster heads (CHs) play a vital role. Unreasonable CH selection causes a lot of energy consumption. In this paper, we propose a competition-based unequal clustering multihop approach (CUCMA). CHs are selected by competition. First, the cluster radius (CR) of a node is calculated according to the distance to base station (BS). Then, CR is resized based on the number of around nodes. Only the nodes with high residual energy and appropriate distances to the selected CHs maybe become CHs, which are usually closer to the surrounding nodes. CUCMA and four related approaches are simulated in different scenarios. The results are analyzed, and it is proved that CUCMA balances the energy consumption of the CHs and reduces the energy consumption of the whole networks, thus leading to prolong the lifetime of WSNs.