Secure Energy Aware Routingin Wireless Sensor Networks

Singh, Onkar; Rishiwal, Vinay; Kumar, Lalit; Yadav, Preeti

doi:10.1109/iot-siu.2019.8777705

Cited by 10 publications

(7 citation statements)

References 8 publications

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“…The performance is evaluated in terms of packet delivery rate, energy consumption, average throughput, network lifetime, packet loss rate, and end‐to‐end delay. The performance of the suggested approach is compared with existing schemes like energy aware data centric Caleed (EAD), energy aware secure routing (EASER), and secure energy aware routing (SEAR) 26 …”

Section: Resultsmentioning

confidence: 99%

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EE‐hHHSS: Energy‐efficient wireless sensor network with mobile sink strategy using hybrid Harris hawk‐salp swarm optimization algorithm

Srinivas

Amgoth

2020

Int J Communication

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Wireless sensor network (WSN) includes power-efficient sensor nodes to convey information to the base station (BS). This network comprises a number of sensor nodes that perform sensing, processing, and wireless communication abilities to monitor a specified sensing field. Therefore, it is necessary to prolong WSN lifetime using energy efficient optimization methods, because the sensor nodes are operated by battery. Also, it is difficult to replace the battery of the nodes located in harsh environments. Thus, energy-efficient routing is a crucial phenomenon in WSN. In this article, energy-efficient WSN with mobile sink (MS) strategy is proposed using hybrid Harris hawk and salp swarm (Hybrid HH-SS) optimization algorithm. In order to achieve energy efficiency, finding an optimal route for MS is a critical task. The MS discovers an optimal path to interconnect with the cluster heads (CHs) by adaptive ant colony optimization (AACO) algorithm. Hence, the proposed hybrid algorithm minimizes the energy consumption (EC), packet loss rate (PLR), and end-to-end (E2E) delay and enhances the lifetime of the network. The proposed work is implemented in JAVA platform, and simulation outcomes show that the proposed approach enhances the wireless sensor network performances. Simulation results show enhancement in energy efficiency in terms of network lifetime, packet delivery rate, average throughput, packet loss rate, energy efficiency, and end-to-end delay. K E Y W O R D S cluster heads (CHs), energy consumption, lifetime, mobile sink, WSN 1 | INTRODUCTION Recently, a well-organized design of WSN has turned into the main zone of research. 1,2 The main features of WSN are environment friendly, appropriate deployment, and self-organizing. For this reason, WSNs are widely useful in fields such as smart health care, environment detection, smart home, and industrial manufacturing. As the sensor nodes are powered using energy-limited batteries, it seems complicated to replace the batteries due to its high cost and a large number of sensors. Hence, it is necessary to adopt an energy efficient WSN with a mobile sink. A device used to identify some sort of input from natural or else physical conditions is called a sensor. The outcome of the sensor is an electrical sign that is transmitted to a controller for further process.

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Section: Resultsmentioning

confidence: 99%

“…Singh et al 26 introduced a routing method called SEAR (secure energy aware routing) to balance energy consumption throughout the network. SEAR was based on the evaluation of trust and transmits the data via trust nodes.…”

Section: Related Workmentioning

confidence: 99%

EE‐hHHSS: Energy‐efficient wireless sensor network with mobile sink strategy using hybrid Harris hawk‐salp swarm optimization algorithm

Srinivas

Amgoth

2020

Int J Communication

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“…Advances in the microwave and digital electronics have created low-cost power sensors that can connect wireless networks and build wireless sensor networks [7]. To achieve its potential, WSN requires new technologies and methods that take into account the size and extreme mobility of these networks, the limited resources of sensor devices, and the inaccessible open communication configuration.…”

Section: Introductionmentioning

confidence: 99%

Trusted Cluster-Based Communication for Wireless Sensor Network Using Meta-Heuristic Algorithms

Sharma¹,

Modani²

2023

Computer Systems Science and Engineering

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The mobile transient and sensor network's routing algorithm detects available multi-hop paths between source and destination nodes. However, some methods are not as reliable or trustworthy as expected. Therefore, finding a reliable method is an important factor in improving communication security. For further enhancement of protected communication, we suggest a trust cluster based secure routing (TCSR) framework for wireless sensor network (WSN) using optimization algorithms. First, we introduce an efficient cluster formation using a modified tug of war optimization (MTWO) algorithm, which provides loadbalanced clusters for energy-efficient data transmission. Second, we illustrate the optimal head selection using multiple design constraints received signal strength, congestion rate, data loss rate, and throughput of the node. Those parameters are optimized by a butterfly optimal deep neural network (BO-DNN), which provides first-level security towards the selection of the best head node. Third, we utilize the lightweight signcryption to encrypt the data between two nodes during data transmission, which provides second-level security. The model provides an estimation of the trust level of each route to help a source node to select the most secure one. The nodes of the network improve reliability and security by maintaining the reliability component. Simulation results showed that the proposed scheme achieved 45.6% of delivery ratio.

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“…The environment's data is observed by means of the sensors. A routing technique or algorithm is required to create a network connection for collecting and transmitting data as of the source-destination node [14]. Routing Optimization (RO) strategies for flows are implemented for avoiding network congestion and ensure the QoS necessities of IoT applications [15].…”

Section: Introductionmentioning

confidence: 99%

An Energy Efficient and Bandwidth Aware Optimal Routing for IoT in Agriculture

Jain

Chauhan

Jain

2021

Preprint

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The agriculture that is enabled with the Internet of Things (IoT) in addition to Wireless Sensors Networks (WSN) can aid the farmers in monitoring their product along with conditions in real-time. The indispensable issues that one has to confront with WSN are Energy-saving along with effective bandwidth usage. Lately, for the amelioration of network stability together with lifetime, disparate cluster-centered solutions are modeled. Nevertheless, most techniques are merely modeled in an energy-aware manner and utilize merely a distance parameter aimed at the data communication. It is imperative for satisfying the bandwidth use of IoT. Here, a cluster-centered energy as well as bandwidth aware routing model is proposed for agriculture data on IoT-centered WSN. Optimal Clusters Head (CH) selection as well as clustering is performed on the WSN for carrying out cluster-centered Data Aggregation (DA). The novel chaos mapping and Opposition centered Learning Grasshopper Optimization Algorithm (CO2GA) chooses the collection of CH as of agricultural Sensor Nodes (SN). Next, centered upon the distance betwixt the chosen CH and SN, the clusters are generated. The clusters share the data to their CH, and the Chaos key generated Advanced Encryption Standard with Rivest–Shamir–Adleman (CKAES-RSA) algorithm encrypt the aggregated data of CH. Lastly, the encrypted data of IoT data are shared with the Base Stations (BS) or Sink Node (Sn) by means of the optimal routing. Aimed at Optimal Route Selection (ORS), the paper utilizes a Deep Learning (DL) approach, explicitly crossover and mutation-based optimal Multi-Layer Perceptrons (CM-OMLP), which computes the fitness of hidden layer by regarding energy, bandwidth, trust, delay, along with congestion level. The proposed encryption and routing mechanism’s results are weighted against the first-rate techniques. The proposed work achieves the highest level of security aimed at the IoT data and fulfills the QoS requirements regarding packet delivery, throughput, delay, along with Network LifeTimes (NLT).

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Secure Energy Aware Routingin Wireless Sensor Networks

Cited by 10 publications

References 8 publications

EE‐hHHSS: Energy‐efficient wireless sensor network with mobile sink strategy using hybrid Harris hawk‐salp swarm optimization algorithm

EE‐hHHSS: Energy‐efficient wireless sensor network with mobile sink strategy using hybrid Harris hawk‐salp swarm optimization algorithm

Trusted Cluster-Based Communication for Wireless Sensor Network Using Meta-Heuristic Algorithms

An Energy Efficient and Bandwidth Aware Optimal Routing for IoT in Agriculture

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