Routing Scheme For Wireless Sensor Networks Research Articles

An Intelligent Energy-Efficient Data Routing Scheme for Wireless Sensor Networks Utilizing Mobile Sink

Data collection and energy consumption are critical concerns in Wireless sensor networks (WSNs). To address these issues, both clustering and routing algorithms are utilized. Therefore, this paper proposes an intelligent energy-efficient data routing scheme for WSNs utilizing a mobile sink (MS) to save energy and prolong network lifetime. The proposed scheme operates in two major modes: configure and operational modes. During the configure mode, a novel clustering mechanism is applied once, and a prescheduling cluster head (CH) selection is introduced to ensure uniform energy expenditure among sensor nodes (SNs). The scheduling technique selects successive CHs for each cluster throughout the WSNs’ lifetime rounds, managed at the base station (BS) to minimize SN energy consumption. In the operational mode, two main objectives are achieved: sensing and gathering data by each CH with minimal message overhead, and establishing an optimal path for the MS using the genetic algorithm. Finally, the MS uploads the gathered data to the BS. Extensive simulations are conducted to verify the efficiency of the proposed scheme in terms of stability period, network lifetime, average energy consumption, data transmission latency, message overhead, and throughput. The results demonstrate that the proposed scheme outperforms the most recent state-of-the-art methods significantly. The results are substantiated through statistical validation via hypothesis testing utilizing ANOVA, as well as post hoc analysis.

Block chain technology for secured dynamic optimal routing in WSN with optimized generative adversarial capsule network

SummaryOne of the key strategies in wireless sensor network (WSN) for sending data packets to the base station (BC) is known as routing. However, malicious node outbreaks will occur, which exaggerate the functions of WSNs during the routing procedure. A secure routing protocol is necessary to protect the effectiveness of WSN and routing fortification. In real‐time scenarios, the existing routing protocol is volatile dynamically; it makes difficult to identify the performance of unprotected routing nodes. In this manuscript, a unique routing strategy is proposed for secured dynamic optimal routing (SDOR) in WSN that combines block chain technology optimized with a generative adversarial capsule network. Every routing sensor node contains a secret key, which is used to construct a crypto hash signature (CHS) token for flow access. The proposed block chain‐based WSN is used to provide SDOR information using a self‐attention‐based generative adversarial capsule network that is improved using the flamingo search algorithm. Following that, the security on the proposed block chain WSN is assessed from six angles. Block chain token transactions are evaluated using measures including average latency, average energy usage, and throughput. The proposed SDOR‐SA‐GAC‐FSA‐CHS‐BWSN delivers 53.87%, 42.57%, and 32.87% lower average packet delay, 28.97%, 37.73%, and 34.75% lesser identification time analyzed to the existing methods, such as trusted distributed routing scheme for WSNs using block chain (SDOR‐DCNN‐SSOA‐BWSN), secure authentication with DSM‐KL ascertained presentation optimization of hybrid block chain‐enabled model for multi‐WSN (SDOR‐DSM‐KL‐BWSN), and optimizing the valid transaction utilizing reinforcement learning‐based block chain ecosystem in WSN (SDOR‐RIL‐BWSN).

Energy Efficient Cluster based Routing Scheme for WSN based IoT to Extend Network Lifetime

With the development and advancement of wireless sensor networks (WSN), the emergence of the Internet of Things (IoT) has achieved prominence in the modern era. With the increasing number of connected devices, WSN has become a key factor in the communication component of the IoT. In IoT-based WSN infrastructure, devices are equipped with intelligent sensors that sense the environment to collect data, process data, and deliver information to the sink or base station (BS). WSN-assisted IoT has become a key technology for various data-centric applications such as health care, smart cities, and the military. Sensor nodes in IoT devices are equipped with bound and irreplaceable batteries. An increased number of connected devices face serious issues of energy depletion, maintenance, and load balancing, which might result in device failure. Energy efficiency is considered a vital parameter in the design of an IoT based WSN, and this can be accomplished through clustering and multihop routing techniques. In this paper, we propose an energy-aware multihop routing scheme (EAMRS) for hierarchical cluster-based WSN-assisted IoT. EAMRS considers the improved low-energy adaptive clustering algorithm (I-LEACH) to select optimal cluster heads (CH). During data transmission, multihop routing is involved by considering routing metrics such as residual energy, distance to BS and optimal route choice to balance the energy load. However, conventional routing schemes fail to achieve the flexibility and adaptability prerequisites of load balancing mechanisms. EAMRS decreases computation overhead and restricts energy usage, resulting in a prolonged network lifetime.

MCSO-MW: An Energy Optimized Data Switching Scheme for Multi-hop Wireless Sensor Networks

Due to continuous growth in the field of wireless sensor networks (WSN), it holds enormous growth in the multidisciplinary domains to provide a promising solution. Especially, on the internet of things (IoT) based edge device network, WSN plays a significant area in the field of data collection and physical entity monitoring. The effectiveness of the routing scheme in WSN can be directly measured through the amount of data transmission, network topology, intermediate hop counts, and data transmission distance. Similarly, an ideal energy model can improve the entire system’s performance and sustainability over successive data transmission. In this paper, a multi-objective chicken swarm optimization (CSO) algorithm is adopted to optimize energy consumption over WSN and improve the system performance through an effective routing approach. Furthermore, the proposed approach is adopted to partition the entire sensor network into multiple clusters and select the partitioned head among the sensor nodes. The competence of the proposed approach is validated against other existing approaches.

A fuzzy based approach to enhance the lifespan of sensor network

The use of wireless sensor networks (WSNs) for data collection is widespread. The resource constraint is an important factor in WSN communications design. The issue arises naturally in WSNs as a result of uneven energy consumption caused by multi-hop routing and dynamic network models, which substantially affects network lifetime. The nodes are dispersed over distant sensing areas and are powered by finite or limited energy batteries that are difficult to replace. The energy of nodes is reduced as a result of changes in network topology or the network’s lifespan and the main intention of this research is to figure out how to make sensor networks last longer. The suggested study work focuses on a specific routing strategy for WSNs that employs the AO-star algorithm with a Fuzzy approach and link stability for extending the network lifetime. The technique chooses the optimum routing path by the sensing point to the receiving node based on how much energy is consumed, the smallest number of nodes with the shortest latency, and lower transmission loads with higher throughput. To compare the proposed strategy’s efficiency in energy consumption balancing and network lifespan enhancement, the proposed technique may achieve a 30% longer average network lifetime than the A-star algorithm.

Energy-Efficient Mobile Sink-Based Intelligent Data Routing Scheme for Wireless Sensor Networks

Wireless Sensor Networks (WSNs) have become an indistinguishable part of any Internet of Things (IoT) based system. In an IoT-based system, WSN monitors different physical objects and forwards the collected data to the base station or gateway node for further processing. Existing routing protocols designed for WSNs are not suitable for IoT-based systems. An intelligent and high-performance routing protocol is essential for real-time data analysis and decision-making. Therefore, this paper proposes a mobile sink-based intelligent data routing scheme for WSNs. Initially, Particle Swarm Optimization is used for optimal cluster formation. After cluster formation, the optimal number of rendezvous points are selected, and a data-gathering tour is planned for the mobile sink. Furthermore, a mobile sink-based intelligent data gathering scheme is proposed to collect the data from the cluster heads. Extensive simulations and mathematical analysis are performed to verify the effectiveness of the proposed scheme. The simulation results are compared with state-of-the-art algorithms in terms of stability period, network lifetime, throughput, average energy consumption, fairness index, data transmission latency, and message overhead.

An Overview of Machine Learning-Based Energy-Efficient Routing Algorithms in Wireless Sensor Networks

Machine learning (ML) technology has shown its unique advantages in many fields and has excellent performance in many applications, such as image recognition, speech recognition, recommendation systems, and natural language processing. Recently, the applicability of ML in wireless sensor networks (WSNs) has attracted much attention. As resources are limited in WSNs, identifying how to improve resource utilization and achieve power-efficient load balancing is becoming a critical issue in WSNs. Traditional green routing algorithms aim to achieve this by reducing energy consumption and prolonging network lifetime through optimized routing schemes in WSNs. However, there are usually problems such as poor flexibility, a single consideration factor, and a reliance on accurate mathematical models. ML techniques can quickly adapt to environmental changes and integrate multiple factors for routing decisions, which provides new ideas for intelligent energy-efficient routing algorithms in WSNs. In this paper, we survey and propose a theoretical hypothetic model formulation of ML as an effective method for creating a power-efficient green routing model that can overcome the limitations of traditional green routing methods. In addition, the study also provides an overview of past, present, and future progress in green routing schemes in WSNs. The contents of this paper will appeal to a wide range of audiences interested in ML-based WSNs.

A Survey of Chain Cluster-Based Routing Protocols in Wireless Sensor Network

Over a period, Wireless sensor networks (WSNs) have turned out to be continuously increasingly appealing and discovered the way into a wide assortment of uses and also frameworks in view of their relatively inexpensive, self-sustaining ability, and their detecting capacity in harsh environment. It is a collection of hubs composed onto a system. Based on their routing architecture they are generally separated into two classes: Hierarchical routing topology and Flat routing topology. In a flat routing topology every nodes will have the similar use and they perform similar task presented by the network. Nodes present in hierarchical topology carry out unique tasks and they are normally formed into clusters in WSNs. In this paper, a detailed study is made on chain cluster-based routing schemes for WSNs and few comparisons made by considering performance features such as Fault tolerance, scalability and topology Strengths and limitations of each scheme and the same is presented.

Systematic Literature Review on Energy Efficient Routing Schemes in WSN – A Survey

In wireless sensor networks (WSN), routing is quite challenging area of research where packets are forwarded through multiple nodes to the base station. The packet being sent over the network should be shared in an energy efficient manner. It also considers the residual power of battery to enhance the network life time. Existing energy efficient routing solutions and surveys are presented but still there is a need for Systematic Literature Review (SLR) to identify the valid problems. This paper performs SLR for energy efficiency routing with 172 papers at initial stage. Next, 50 papers are shortlisted after filtration based on quality valuation and selection criteria by ensuring relevance with energy efficiency. Initially, we present literature that includes schemes for threshold sensitive, adaptive periodic threshold sensitive, power efficient, hybrid energy efficient distribution and low energy adaptive mechanisms. Result of systematic review reveals that consumption of energy is the most fundamental issue in WSN however, is not noticed by the researchers and practitioners where as it can contribute for the improvement of the energy efficiency. It also elaborates the weaknesses of the existing approaches which make them inappropriate for energy efficient routing in WSN.

ELDC: An Artificial Neural Network Based Energy-Efficient and Robust Routing Scheme for Pollution Monitoring in WSNs

The range of applications of Wireless Sensor Networks (WSNs) is increasing continuously despite of their serious constraints of the sensor nodes’ resources such as storage, processing capacity, communication range and energy. The main issues in WSN are the energy consumption and the delay in relaying data to the Sink node. This becomes extremely important when deploying a big number of nodes, like the case of industry pollution monitoring. We propose an artificial neural network based energy-efficient and robust routing scheme for WSNs called ELDC. In this technique, the network is trained on huge data set containing almost all scenarios to make the network more reliable and adaptive to the environment. Additionally, it uses group based methodology to increase the life-span of the overall network, where groups may have different sizes. An artificial neural network provides an efficient threshold values for the selection of a group's CN and a cluster head based on back propagation technique and allows intelligent, efficient, and robust group organization. Thus, our proposed technique is highly energy-efficient capable to increase sensor nodes’ lifetime. Simulation results show that it outperforms LEACH protocol by 42 percent, and other state-of-the-art protocols by more than 30 percent.

QoS integrated energy aware routing for wireless sensor networks

Quality of service (QoS) in wireless sensor networks (WSNs) has got limited attention due to multiple bottlenecks such as limited bandwidth and energy storage. Until now, most of the focus has been to develop energy efficient routing schemes for WSN. It is important to provide effective QoS mechanism along with energy efficient data transmission. In this work, QoS mechanism is incorporated inside energy aware routing protocol proposed in Shah and Rabaey (2002). This new integrated protocol achieves dual goal of energy efficient data transmission and effective QoS functionalities. Empirical results are demonstrated on NS3 simulator. The proposed approach is compared against existing state of the art technique. The proposed approach outperforms the existing state of the art technique in prolonging the network lifetime.

Detection and avoidance of water loss through municipality taps in India by using smart taps and ICT

Global climate change and the rapid population growth have been seriously impacting water sources. The existing traditional water distribution network (WDN) fails to manage proper water distribution according to the consumption rate. The current situation demands an intelligent water management and treatment model to keep water available in the long run. Information and Communications Technology (ICT) is a combination of the Internet of Things and information which introduces machine-to-machine communication with data for management. An ICT-based WDN which helps in monitoring excessive water supply and preventing water loss is proposed. The designed architecture is based on a heterogeneous wireless sensor network (WSN) and a smart tap which detects water loss and communicates the report to the utility centre. A fault-tolerant WSN routing scheme to handle the faulty situation during the transmission process is also proposed. The district of Sambalpur in Odisha, India is the chosen location for this study.

Secure big data communication for energy efficient intra-cluster in WSNs

Big data communications in wireless sensor networks (WSNs) play a very important role in the energy efficiency and lifetime of routing schemes. Nowadays, multi-hop path routing schemes in WSNs have been widespread focused by scholars at home and abroad. However, most of the scholars focus only on the data communication between the cluster head (CH) node and the base station (BS), resulting in why the impacts of intra-cluster communications has not been paid enough attention. In this paper, we propose a new energy efficient intra-cluster data communication scheme (EEICS), for WSNs, to solve the energy and secure problem of the intra-cluster data communication. The presented scheme includes three key parts: a new layer scheme in one cluster that enables self-organization of local nodes and the width of each layer is not equal, a new multi-hop path selection algorithm for choosing a suitable relay node to forward data packets to the CH nodes and a secure communication mechanism to preserve the privacy of source nodes in the cluster. The residual energy of nodes is taken into consideration in our scheme in particular when it comes to the selection of the relay node. Our analysis and simulation can prove the advantage of our scheme in view of lifetime and the amount of data packages. The simulation part plays a significant role in analysing the security and performance of our scheme. At the end of simulation part, we present the qualitative analysis among EEICS and the conventional schemes such as LEACH, LEACH-C and EECRP. It is noteworthy that EEICS in terms of the above indicators outperforms than the existing schemes.

Wireless sensor networks routing algorithm based on particle swarm optimisation

Routing policy is a key problem in wireless sensor network (WSN), and it aims to find an optimal path to transmit the data of source nodes to the destination nodes. Wireless sensor networks can represented as a graph model, where graph nodes refers the wireless sensors, and graph edges are used to connects various sensors. Furthermore, in this work, we suppose that wireless sensor networks contain three types of nodes, including base station, gateway, and sensor. In the proposed algorithm, each particle is exploited to provide a suitable route from each cluster head to the base station, and the dimension of each particle is equal to the number of gateways in WSN. In the end, experimental results demonstrate that the proposed algorithm is able to effectively prolong network lifetime and increase the number of packets received by base station. Furthermore, the conclusion can be drawn that the proposed method can effectively solve the WSN's routing problem, because particle swarm optimisation is able to effectively optimise WSN routing scheme.

An unequal cluster-based routing scheme for multi-level heterogeneous wireless sensor networks

In wireless sensor networks (WSNs), clustering can significantly reduce energy dissipation of nodes, and also increase communication load of cluster heads. When multi-hop communication model is adopted in clustering, “energy hole” problem may occur due to unbalanced energy consumption among cluster heads. Recently, many multi-hop clustering protocols have been proposed to solve this problem. And the main way is using unequal clustering to control the size of clusters. However, many of these protocols are about homogeneous networks and few are about heterogeneous networks. In this paper, we present an unequal cluster-based routing scheme for WSNs with multi-level energy heterogeneity called UCR-H. The sensor field is partitioned into a number of equal-size rectangular units. We first calculate the number of clusters in each unit by balancing energy consumption among the cluster heads in different units. And then we find the optimal number of units by minimizing the total energy consumption of inter-cluster forwarding. Finally, the size of clusters in each unit is elaborately designed based on node’s energy level and the number of clusters in this unit. And a threshold is also designed to avoid excessive punishment to the nodes with higher energy level. Simulation results show that our scheme effectively mitigates the “energy hole” problem and achieves an obvious improvement on the network lifetime.

ANCR—An Adaptive Network Coding Routing Scheme for WSNs with Different-Success-Rate Links

As the underlying infrastructure of the Internet of Things (IoT), wireless sensor networks (WSNs) have been widely used in many applications. Network coding is a technique in WSNs to combine multiple channels of data in one transmission, wherever possible, to save node’s energy as well as increase the network throughput. So far most works on network coding are based on two assumptions to determine coding opportunities: (1) All the links in the network have the same transmission success rate; (2) Each link is bidirectional, and has the same transmission success rate on both ways. However, these assumptions may not be true in many actual WSNs—the wireless links among nodes are often subject to all kinds of disturbance, obstruction, etc., and may transmit with different success rates. This paper proposes a new routing strategy, named Adaptive Network Coding Routing (ANCR). ANCR firstly establishes a routing path with the traditional network coding routing (NCR), and then applies the neighborhood search algorithm to adaptively determine nodes’ coding opportunities based on the links’ transmission success rates, with the target of reducing the total number of transmission. The simulation results show that, in WSNs with different-success-rate links, ANCR can reduce the network delay by about 50%, and increase the network throughput by about 67%, compared with the traditional NCR.

An Energy Conserving Reversible and Irreversible Digital Watermarking Hybrid Scheme for Cluster-based Wireless Sensor Networks

Wireless sensor networks (WSNs) are composed of a large number of sensor nodes that are scattered within a monitoring region and in which one or more sinks are responsible for the sensed data collecting. The sensor nodes are equipped with limited battery energy and are generally deployed in unattended environments such as in forests, on volcanoes, etc., to regularly report sensed data to the sink via wireless communication. Therefore, they cannot be recharged when a node depletes its battery energy. To design energy-conserving methods to prolong the network lifetime has become an important issue for WSNs. Nowadays the privacy and accuracy of data transmission are taken seriously; thus this paper aims at designing a data authentication mechanism integrated with an energy conserving routing scheme for WSNs to protect the integrity of receiving sensed data while at the same time conserving the battery energy of the sensor nodes. An energy-conserving reversible and irreversible digital watermarking hybrid scheme is proposed to balance the energy consumption and the robustness of the security.

Addressing Mobility in RPL With Position Assisted Metrics

Mobility is still an open challenge in wireless sensor networks (WSNs). Energy efficient routing strategies designed for static WSNs, such as routing protocol for low-power and lossy networks (RPL), generally have a slow response to topology changes. Moreover, their high signalling cost to keep up-to-date routes in the presence of mobile nodes makes them inefficient in these scenarios. In this paper, we introduce Kalman positioning RPL (KP-RPL), a novel routing strategy for WSNs with both static and mobile nodes, based on RPL. The objective of KP-RPL is to provide robust and reliable routing, considering the positioning inaccuracies and node disconnections that arise in real-life WSNs. This considers the original RPL for the communication among static nodes and position-based routing for mobile nodes, which use a novel RPL metric that combines Kalman positioning and blacklisting. The simulation results show that the reliability and the robustness of the network in harsh conditions are enhanced compared with geographical routing. Moreover, KP-RPL reduces the density and the number of simultaneously active anchor nodes for positioning. As a result, the infrastructure cost is lower, and the network lifetime is extended.

A Survey of Cluster-based Routing Schemes for Wireless Sensor Networks

In recent times, wireless sensor networks (WSNs) have become progressively more attractive and have found their way into a wide variety of applications and systems because of their low cost, self-organizing behavior, and sensing ability in harsh environments. A WSN is a collection of nodes organized into a network. Routing is a vital technology in WSNs and can be roughly divided into two categories: flat routing and hierarchical routing. In a flat routing topology, all nodes have identical functionality and carry out the same task in the network. Nodes in a hierarchical topology do different tasks in WSNs and are usually arranged into clusters. In this paper, a survey on cluster-based routing schemes for WSNs has been done and comparisons made on the basis of performance factors such as latency, scalability, and energy awareness. Strengths and limitations of each scheme are presented, and open issues that must be addressed in the design of cluster-based routing algorithms are discussed.

A Wireless Sensor Network Routing Scheme for Timely Environmental Monitoring System

Environmental Monitoring system has become more and more critical for biological protection recently. To get timely information from monitored environment, a timely wireless senor network routing scheme (TNRS) is proposed, which is made up of three phrases: initial setup, route discovery and establishment, data communication and route maintenance. In the first phrase, every sensor node will get the initial route table. In the second phrase, source node will find its own path with high fitness value. In the third phrase, data transmission and route maintenance are done under ACK confirmation mechanism. Simulation shows that TNRS routing scheme can decrease data miss ratio by 24.88%, and reduce average data latency by 14.85%, compared to SPEED routing scheme. So TNRS scheme can provide better real time service for environmental monitoring system.