Editorial

14 pages, 635 KiB

Open AccessEditorial

by Rajagopal Maheswar, Murugan Kathirvelu and Kuppusamy Mohanasundaram

Energies 2024, 17(2), 417; https://doi.org/10.3390/en17020417 - 15 Jan 2024

Viewed by 818

The pervasive integration of wireless devices across diverse sectors has experienced an unprecedented surge in recent years [...] Full article

(This article belongs to the Special Issue Energy Efficiency in Wireless Networks)

Research

Jump to: Editorial, Review

19 pages, 1102 KiB

Open AccessArticle

MHSEER: A Meta-Heuristic Secure and Energy-Efficient Routing Protocol for Wireless Sensor Network-Based Industrial IoT

by Anshika Sharma, Himanshi Babbar, Shalli Rani, Dipak Kumar Sah, Sountharrajan Sehar and Gabriele Gianini

Energies 2023, 16(10), 4198; https://doi.org/10.3390/en16104198 - 19 May 2023

Cited by 9 | Viewed by 1477

Abstract

Several industries use wireless sensor networks (WSN) for various tasks such as monitoring, data transmission, and data gathering. They find applications in the industrial internet of things (IIoT). WSNs are utilized to track and monitor changes in the environment. Since they include multiple [...] Read more.

Several industries use wireless sensor networks (WSN) for various tasks such as monitoring, data transmission, and data gathering. They find applications in the industrial internet of things (IIoT). WSNs are utilized to track and monitor changes in the environment. Since they include multiple small sensor nodes (SN), they are severely constrained, so resource management geared toward energy efficiency is crucial in this kind of network. Minimizing the power to interpret, transmit, and store data between various sensors poses important challenges. Experts have considered various ways to address these issues that unavoidably affect the network’s performance: reducing energy usage while maintaining system throughput remains the primary research issue. Another important concern relates to network security. Specifically, intrusion detection and avoidance are major concerns. In this work, we introduce the meta-heuristic-based secure and energy-efficient routing (MHSEER) protocol for WSN-IIoT. The protocol learns the forwarding decisions using the number of hops, connection integrity characteristics, and accumulated remaining energy. To make the method more secure, the protocol also employs counter-encryption mode (CEM) to encrypt the data. A meta-heuristics study designed to achieve reliable learning is used in the suggested protocol. The protocol consists of two stages. The first stage uses a heuristics method to improve the option for dependable data routing. Security based on a computationally simple and random CEM is accomplished in the second stage. The proposed MHSEER protocol has been compared to the secure trust routing protocol for low power (Sectrust-RPL), heuristic-based energy-efficient routing (HBEER), secure and energy-aware heuristic-based routing (SEHR), and secure energy-aware meta-heuristic routing (SEAMHR) in terms of packet drop ratio, throughput, network delay, energy usage, and faulty pathways. The proposed protocol increases throughput to 95.81% and decreases the packet drop ratio, packet delay, energy consumption, and faulty pathways to 5.12%, 0.10 ms, 0.0102 mJ, and 6.51%, respectively. Full article

(This article belongs to the Special Issue Energy Efficiency in Wireless Networks)

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28 pages, 2656 KiB

Open AccessArticle

Multi-Channel Assessment Policies for Energy-Efficient Data Transmission in Wireless Underground Sensor Networks

by Rajasoundaran Soundararajan, Prince Mary Stanislaus, Senthil Ganesh Ramasamy, Dharmesh Dhabliya, Vivek Deshpande, Sountharrajan Sehar and Durga Prasad Bavirisetti

Energies 2023, 16(5), 2285; https://doi.org/10.3390/en16052285 - 27 Feb 2023

Cited by 20 | Viewed by 1474

Abstract

Wireless Underground Sensor Networks (WUGSNs) transmit data collected from underground objects such as water substances, oil substances, soil contents, and others. In addition, the underground sensor nodes transmit the data to the surface nodes regarding underground irregularities, earthquake, landslides, military border surveillance, and [...] Read more.

Wireless Underground Sensor Networks (WUGSNs) transmit data collected from underground objects such as water substances, oil substances, soil contents, and others. In addition, the underground sensor nodes transmit the data to the surface nodes regarding underground irregularities, earthquake, landslides, military border surveillance, and other issues. The channel difficulties of WUGSNs create uncertain communication barriers. Recent research works have proposed different types of channel assessment techniques and security approaches. Moreover, the existing techniques are inadequate to learn the real-time channel attributes in order to build reactive data transmission models. The proposed system implements Deep Learning-based Multi-Channel Learning and Protection Model (DMCAP) using the optimal set of channel attribute classification techniques. The proposed model uses Multi-Channel Ensemble Model, Ensemble Multi-Layer Perceptron (EMLP) Classifiers, Nonlinear Channel Regression models and Nonlinear Entropy Analysis Model, and Ensemble Nonlinear Support Vector Machine (ENLSVM) for evaluating the channel conditions. Additionally, Variable Generative Adversarial Network (VGAN) engine makes the intrusion detection routines under distributed environment. According to the proposed principles, WUGSN channels are classified based on the characteristics such as underground acoustic channels, underground to surface channels and surface to ground station channels. On the classified channel behaviors, EMLP and ENLSVM are operated to extract the Signal to Noise Interference Ratio (SNIR) and channel entropy distortions of multiple channels. Furthermore, the nonlinear regression model was trained for understanding and predicting the link (channel behaviors). The proposed DMCAP has extreme difficulty finding the differences of impacts due to channel issues and malicious attacks. In this regard, the VGAN-Intrusion Detection System (VGAN-IDS) model was configured in the sensor nodes to monitor the channel instabilities against malicious nodes. Thus, the proposed system deeply analyzes multi-channel attribute qualities to improve throughput in uncertain WUGSN. The testbed was created for classified channel parameters (acoustic and air) with uncertain network parameters; the uncertainties of testbed are considered as link failures, noise distortions, interference, node failures, and number of retransmissions. Consequently, the experimental results show that DMCAP attains 10% to 15% of better performance than existing systems through better throughput, minimum retransmission rate, minimum delay, and minimum energy consumption rate. The existing techniques such as Support Vector Machine (SVM) and Random Forest (RF)-based Classification (SMC), Optimal Energy-Efficient Transmission (OETN), and channel-aware multi-path routing principles using Reinforcement Learning model (CRLR) are identified as suitable for the proposed experiments. Full article

(This article belongs to the Special Issue Energy Efficiency in Wireless Networks)

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16 pages, 1447 KiB

Open AccessArticle

Energy Saving Optimization Technique-Based Routing Protocol in Mobile Ad-Hoc Network with IoT Environment

by Vinoth Kumar Krishnamoorthy, Ivan Izonin, Sugumaran Subramanian, Shishir Kumar Shandilya, Sivasankaran Velayutham, Thillai Rani Munichamy and Myroslav Havryliuk

Energies 2023, 16(3), 1385; https://doi.org/10.3390/en16031385 - 30 Jan 2023

Cited by 11 | Viewed by 2081

Abstract

The Mobile Ad-hoc Network is a self-configuring decentralized network, where the network topology is dynamically modifiable. The IoT (Internet of Things) based Wireless Sensor Network contains more sensors and shares information over the Internet to a cloud server. However, the IoT-based wireless sensor [...] Read more.

The Mobile Ad-hoc Network is a self-configuring decentralized network, where the network topology is dynamically modifiable. The IoT (Internet of Things) based Wireless Sensor Network contains more sensors and shares information over the Internet to a cloud server. However, the IoT-based wireless sensor network channel has moderate security is poor compared to MANET and packet loss is increased due to attackers. In IoT, all the sensors forward the detected data frequently to the internet gateway, so the energy saving in the network is low compared to MANET. In this work, the smart environment of IoT, Wireless Sensor Networks (WSN) and MANET make a great heterogeneous network in IT Technology; the combination of this heterogeneous network has new challenging issues. In this heterogeneous network, MANET provides a trusted route between the sensor to gateway nodes into the IoT environment using Energy Saving Optimization Techniques [MANET-ESO in IoT]. It saves energy for each node and reduces the economic level. The results of the ns-3 simulation show that the proposed method provides better results in Alive node counts, residual Energy, throughput, packet delivery ratio and routing overhead. Full article

(This article belongs to the Special Issue Energy Efficiency in Wireless Networks)

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13 pages, 17918 KiB

Open AccessArticle

IEDA-HGEO: Improved Energy Efficient with Clustering-Based Data Aggregation and Transmission Protocol for Underwater Wireless Sensor Networks

by Shubham Joshi, T.P Anithaashri, Ravi Rastogi, Gaurav Choudhary and Nicola Dragoni

Energies 2023, 16(1), 353; https://doi.org/10.3390/en16010353 - 28 Dec 2022

Cited by 5 | Viewed by 1494

Abstract

With the emerging technology in underwater wireless sensor networks (UWSN), many researchers are undergoing this field since it cannot maintain the batteries and recharge them manually. Network duration should be taken into account because they can easily be recharged by a non-conventional resource [...] Read more.

With the emerging technology in underwater wireless sensor networks (UWSN), many researchers are undergoing this field since it cannot maintain the batteries and recharge them manually. Network duration should be taken into account because they can easily be recharged by a non-conventional resource like solar energy. When coming to the data collection process, clustering is an effective method to construct vitality effective UWSNs. The clustering properties of UWSNs differ from those of terrestrial wireless sensor networks (TWSNs) due to the sparse deployment of nodes as well as the dynamic nature of the channel. This paper proposes improved efficient data aggregation in a Hexagonal grid with energy optimization (IEDA-HGEO) protocol for effective data transmission with an optimal clustering process. It is further compared with ERP²R n energy-efficient routing protocol and EGRC (Energy-efficiency Grid Routing based on 3D Cubes). The three techniques mentioned above are specifically examined for their applicability to underwater communication, and their performance is compared in terms of energy consumption, efficiency, throughput, packet delivery ratio, and delay. The proposed method achieved the following metrics: delay 41%, energy consumption 48%, efficiency 95%, throughput 95%, and PDR 92%. Full article

(This article belongs to the Special Issue Energy Efficiency in Wireless Networks)

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16 pages, 2556 KiB

Open AccessArticle

Improved Secure Encryption with Energy Optimization Using Random Permutation Pseudo Algorithm Based on Internet of Thing in Wireless Sensor Networks

by S. Nagaraj, Atul B. Kathole, Leena Arya, Neha Tyagi, S. B. Goyal, Anand Singh Rajawat, Maria Simona Raboaca, Traian Candin Mihaltan, Chaman Verma and George Suciu

Energies 2023, 16(1), 8; https://doi.org/10.3390/en16010008 - 20 Dec 2022

Cited by 6 | Viewed by 1746

Abstract

The use of wireless and Internet of Things (IoT) devices is growing rapidly. Because of this expansion, nowadays, mobile apps are integrated into low-cost, low-power platforms. Low-power, inexpensive sensor nodes are used to facilitate this integration. Given that they self-organize, these systems qualify [...] Read more.

The use of wireless and Internet of Things (IoT) devices is growing rapidly. Because of this expansion, nowadays, mobile apps are integrated into low-cost, low-power platforms. Low-power, inexpensive sensor nodes are used to facilitate this integration. Given that they self-organize, these systems qualify as IoT-based wireless sensor networks. WSNs have gained tremendous popularity in recent years, but they are also subject to security breaches from multiple entities. WSNs pose various challenges, such as the possibility of numerous attacks, their innate power, and their unfeasibility for use in standard security solutions. In this paper, to overcome these issues, we propose the secure encryption random permutation pseudo algorithm (SERPPA) for achieving network security and energy consumption. SERPPA contains a major entity known as a cluster head responsible for backing up and monitoring the activities of the nodes in the network. The proposed work performance is compared with other work based on secure IoT devices. The calculation metrics taken for consideration are energy, overheads, computation cost, and time consumption. The obtained results show that the proposed SERPPA is very significant in comparison to the existing works, such as GKA (Group Key Agreement) and MPKE (Multipath Key Establishment), in terms of data transfer rate, energy consumption and throughput. Full article

(This article belongs to the Special Issue Energy Efficiency in Wireless Networks)

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33 pages, 8413 KiB

Open AccessArticle

Energy-Efficient Network Protocols and Resilient Data Transmission Schemes for Wireless Sensor Networks—An Experimental Survey

by Dharmesh Dhabliya, Rajasoundaran Soundararajan, Parthiban Selvarasu, Maruthi Shankar Balasubramaniam, Anand Singh Rajawat, S. B. Goyal, Maria Simona Raboaca, Traian Candin Mihaltan, Chaman Verma and George Suciu

Energies 2022, 15(23), 8883; https://doi.org/10.3390/en15238883 - 24 Nov 2022

Cited by 13 | Viewed by 1840

Abstract

Wireless sensor networks (WSNs) are considerably used for various environmental sensing applications. The architecture and internal specifications of WSNs have been chosen based on the requirements of particular applications. On this basis, WSNs consist of resource (energy and memory)-limited wireless sensor nodes. WSNs [...] Read more.

Wireless sensor networks (WSNs) are considerably used for various environmental sensing applications. The architecture and internal specifications of WSNs have been chosen based on the requirements of particular applications. On this basis, WSNs consist of resource (energy and memory)-limited wireless sensor nodes. WSNs initiate data communication from source to destination via physical layer management principles, channel slot scheduling principles (time division multiple access), wireless medium access control (WMAC) protocols, wireless routing protocols and application protocols. In this environment, the development of WMAC principles, routing protocols and channel allotment schemes play crucial roles in network communication phases. Consequently, these layering functions consume more energy at each sensor node, which leads to minimal network lifetime. Even though the channel management schemes, medium control protocols and routing protocols are functionally suitable, the excessive energy consumption affects the overall network performance. In this situation, energy optimization algorithms are advised to minimize the resource wastage of WSNs during regular operations (medium control and routing process). Many research works struggle to identify the optimal energy-efficient load balancing strategies to improve WSN functions. With this in mind, the proposed article has conducted a detailed literature review and notable experimental comparisons on energy-efficient MAC protocols, channel scheduling policies and energy-efficient routing protocols. To an extent, the detailed analysis over these wireless network operations helps to understand the benefits and limitations of recent research works. In the experimental section of this article, eight existing techniques are evaluated under energy optimization strategies (WMAC, channel allocation, sleep/wake protocols, integrated routing and WMAC policies, balanced routing and cooperative routing). The proposed review and the classified technical observations collected from notable recent works have been recognized as crucial contributions. The results infer the suggestions for feasible WSN communication strategies with optimal channel management policies and routing policies. Notably, the simulation results show that cross-layer or multi-layer energy optimization policies perform better than homogeneous energy optimization models. Full article

(This article belongs to the Special Issue Energy Efficiency in Wireless Networks)

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17 pages, 5595 KiB

Open AccessArticle

Energy-Aware UAV Based on Blockchain Model Using IoE Application in 6G Network-Driven Cybertwin

by Atul B. Kathole, Jayashree Katti, Dharmesh Dhabliya, Vivek Deshpande, Anand Singh Rajawat, S. B. Goyal, Maria Simona Raboaca, Traian Candin Mihaltan, Chaman Verma and George Suciu

Energies 2022, 15(21), 8304; https://doi.org/10.3390/en15218304 - 07 Nov 2022

Cited by 14 | Viewed by 1604

Abstract

Several advanced features exist in fifth-generation (5G) correspondence than in fourth-generation (4G) correspondence. Centric cloud-computing architecture achieves resource sharing and effectively handles big data explosion. For data security problems, researchers had developed many methods to protect data against cyber-attacks. Only a few solutions [...] Read more.

Several advanced features exist in fifth-generation (5G) correspondence than in fourth-generation (4G) correspondence. Centric cloud-computing architecture achieves resource sharing and effectively handles big data explosion. For data security problems, researchers had developed many methods to protect data against cyber-attacks. Only a few solutions are based on blockchain (BC), but are affected by expensive storage costs, network latency, confidence, and capacity. Things are represented in digital form in the virtual cyberspace which is the major responsibility of the communication model based on cybertwin. A novel cybertwin-based UAV 6G network architecture is proposed with new concepts such as cloud operators and cybertwin in UAV. Here, IoE applications have to be energy aware and provide scalability with less latency. A novel Compute first networking (CFN) framework named secure blockchain-based UAV communication (BC-UAV) is designed which offers network services such as computing, caching, and communication resources. The focus of the blockchain was to improve the security in the cloud using hashing technique. Edge clouds support core clouds to quickly respond to user requests. Full article

(This article belongs to the Special Issue Energy Efficiency in Wireless Networks)

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16 pages, 1727 KiB

Open AccessArticle

Energy-Efficient Offloading Based on Efficient Cognitive Energy Management Scheme in Edge Computing Device with Energy Optimization

by Vishnu Kumar Kaliappan, Aravind Babu Lalpet Ranganathan, Selvaraju Periasamy, Padmapriya Thirumalai, Tuan Anh Nguyen, Sangwoo Jeon, Dugki Min and Enumi Choi

Energies 2022, 15(21), 8273; https://doi.org/10.3390/en15218273 - 05 Nov 2022

Cited by 2 | Viewed by 1603

Abstract

Edge devices and their associated computing techniques require energy efficiency to improve sustainability over time. The operating edge devices are timed to swap between different states to achieve stabilized energy efficiency. This article introduces a Cognitive Energy Management Scheme (CEMS) by considering the [...] Read more.

Edge devices and their associated computing techniques require energy efficiency to improve sustainability over time. The operating edge devices are timed to swap between different states to achieve stabilized energy efficiency. This article introduces a Cognitive Energy Management Scheme (CEMS) by considering the offloading and computational states for energy efficacy. The proposed scheme employs state learning for swapping the computing intervals for scheduling or offloading depending on the load. The edge devices are distributed at the time of scheduling and organized for first come, first serve for offloading features. In state learning, the reward is allocated for successful scheduling over offloading to prevent device exhaustion. The computation is therefore swapped for energy-reserved scheduling or offloading based on the previous computed reward. This cognitive management induces device allocation based on energy availability and computing time to prevent energy convergence. Cognitive management is limited in recent works due to non-linear swapping and missing features. The proposed CEMS addresses this issue through precise scheduling and earlier device exhaustion identification. The convergence issue is addressed using rewards assigned to post the state transitions. In the transition process, multiple device energy levels are considered. This consideration prevents early detection of exhaustive devices, unlike conventional wireless networks. The proposed scheme’s performance is compared using the metrics computing rate and time, energy efficacy, offloading ratio, and scheduling failures. The experimental results show that this scheme improves the computing rate and energy efficacy by 7.2% and 9.32%, respectively, for the varying edge devices. It reduces the offloading ratio, scheduling failures, and computing time by 14.97%, 7.27%, and 14.48%, respectively. Full article

(This article belongs to the Special Issue Energy Efficiency in Wireless Networks)

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18 pages, 5571 KiB

Open AccessArticle

Energy Efficient Routing and Dynamic Cluster Head Selection Using Enhanced Optimization Algorithms for Wireless Sensor Networks

by I. Adumbabu and K. Selvakumar

Energies 2022, 15(21), 8016; https://doi.org/10.3390/en15218016 - 28 Oct 2022

Cited by 5 | Viewed by 1775

Abstract

A large number of spatially dispersed nodes on the wireless network create Wireless Sensor Networks (WSNs) to collect and analyze the physical data from the environment. The issues that affected the network and had an impact on network energy consumption were cluster head [...] Read more.

A large number of spatially dispersed nodes on the wireless network create Wireless Sensor Networks (WSNs) to collect and analyze the physical data from the environment. The issues that affected the network and had an impact on network energy consumption were cluster head random selection, working node redundancy, and cluster head transmission path construction. Consequently, this energy constraint also has an impact on the network lifetime and energy-efficient routing. Therefore, the primary goals of this research are to decrease energy consumption and lengthen the network’s lifespan. So, using improved optimization algorithms, this paper presents a dynamic cluster head-based energy-efficient routing system. The Improved Coyote Optimization Algorithm (ICOA), in this case, consists of three phases setup, transmission, and measurement phase. The Improved Jaya Optimization Algorithm with Levy Flight (IJO-LF) then determines the route between the BS and the CH. It selects the most effective course based on the distance, node degree, and remaining energy. The proposed approach is compared with traditional methods and the routing protocols Power-Efficient Gathering in Sensor Information Systems (PEGASIS) and Threshold sensitive Energy Efficient Sensor Network protocol (TEEN) during implementation on the MATLAB platform. Performance indicators for the suggested methodology are evaluated based on data packets collected by the BS, energy usage, alive nodes, and dead nodes. The outputs of the suggested methodology performed better than the conventional plans. Full article

(This article belongs to the Special Issue Energy Efficiency in Wireless Networks)

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18 pages, 1374 KiB

Open AccessArticle

Multiagent Reinforcement Learning Based on Fusion-Multiactor-Attention-Critic for Multiple-Unmanned-Aerial-Vehicle Navigation Control

by Sangwoo Jeon, Hoeun Lee, Vishnu Kumar Kaliappan, Tuan Anh Nguyen, Hyungeun Jo, Hyeonseo Cho and Dugki Min

Energies 2022, 15(19), 7426; https://doi.org/10.3390/en15197426 - 10 Oct 2022

Cited by 3 | Viewed by 2265

Abstract

The proliferation of unmanned aerial vehicles (UAVs) has spawned a variety of intelligent services, where efficient coordination plays a significant role in increasing the effectiveness of cooperative execution. However, due to the limited operational time and range of UAVs, achieving highly efficient coordinated [...] Read more.

The proliferation of unmanned aerial vehicles (UAVs) has spawned a variety of intelligent services, where efficient coordination plays a significant role in increasing the effectiveness of cooperative execution. However, due to the limited operational time and range of UAVs, achieving highly efficient coordinated actions is difficult, particularly in unknown dynamic environments. This paper proposes a multiagent deep reinforcement learning (MADRL)-based fusion-multiactor-attention-critic (F-MAAC) model for multiple UAVs’ energy-efficient cooperative navigation control. The proposed model is built on the multiactor-attention-critic (MAAC) model, which offers two significant advances. The first is the sensor fusion layer, which enables the actor network to utilize all required sensor information effectively. Next, a layer that computes the dissimilarity weights of different agents is added to compensate for the information lost through the attention layer of the MAAC model. We utilize the UAV LDS (logistic delivery service) environment created by the Unity engine to train the proposed model and verify its energy efficiency. The feature that measures the total distance traveled by the UAVs is incorporated with the UAV LDS environment to validate the energy efficiency. To demonstrate the performance of the proposed model, the F-MAAC model is compared with several conventional reinforcement learning models with two use cases. First, we compare the F-MAAC model to the DDPG, MADDPG, and MAAC models based on the mean episode rewards for 20k episodes of training. The two top-performing models (F-MAAC and MAAC) are then chosen and retrained for 150k episodes. Our study determines the total amount of deliveries done within the same period and the total amount done within the same distance to represent energy efficiency. According to our simulation results, the F-MAAC model outperforms the MAAC model, making 38% more deliveries in 3000 time steps and 30% more deliveries per 1000 m of distance traveled. Full article

(This article belongs to the Special Issue Energy Efficiency in Wireless Networks)

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11 pages, 3792 KiB

Open AccessArticle

Design of Power Location Coefficient System for 6G Downlink Cooperative NOMA Network

by Mohamed Hassan, Manwinder Singh, Khalid Hamid, Rashid Saeed, Maha Abdelhaq and Raed Alsaqour

Energies 2022, 15(19), 6996; https://doi.org/10.3390/en15196996 - 23 Sep 2022

Cited by 13 | Viewed by 1082

Abstract

Cooperative non-orthogonal multiple access (NOMA) is a technology that addresses many challenges in future wireless generation networks by delivering a large amount of connectivity and huge system capacity. The aim of this paper is to design the varied distances and power location coefficients [...] Read more.

Cooperative non-orthogonal multiple access (NOMA) is a technology that addresses many challenges in future wireless generation networks by delivering a large amount of connectivity and huge system capacity. The aim of this paper is to design the varied distances and power location coefficients for far users. In addition, this paper aims to evaluate the outage probability (OP) performance against a signal-to-noise ratio (SNR) for a 6G downlink (DL) NOMA power domain (PD) and DL cooperative NOMA PD networks. We combine a DL cooperative NOMA with a 16 × 16, a 32 × 23, and a 64 × 64 multiple-input multiple-output (MIMO) and a 128 × 128, a 256 × 256, and a 512 × 512 massive MIMO in an innovative method to enhance OP performance rate and mitigate the power location coefficient’s effect for remote users. The results were obtained from Rayleigh fading channels using the MATLAB simulation software program. According to the outcomes, increasing the power location coefficients for the far user from 0.6 to 0.8 reduces the OP rate because increasing the power location coefficient for the far user decreases the power location coefficient for the near user, which results in less interference between them. In terms of the OP performance rate, the DL cooperative NOMA outperforms the NOMA. According to the findings, the DL cooperative NOMA OP rate outperforms the DL NOMA by a rate of 10^−0.5. Whereas the 16 × 16 MIMO enhances the OP for the far user by 78.0 × 10⁻⁴, the 32 × 32 MIMO increases the OP for the far user by 19.0 × 10⁻⁴, and the 64 × 64 MIMO decreases the OP rate for the far user by 5.0 × 10⁻⁵. At a SNR of 10 dB, the 128 × 128 massive MIMO improves the OP for the far user by 1.0 × 10⁻⁵. The 256 × 256 massive MIMO decreases the OP for the far user by 43.0 × 10⁻⁵, and the 512 × 512 massive MIMO enhances the OP for the far user by 8.0 × 10⁻⁶. The MIMO techniques improve the OP performance, while the massive MIMO technology enhances the OP performance dramatically. Full article

(This article belongs to the Special Issue Energy Efficiency in Wireless Networks)

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18 pages, 5797 KiB

Open AccessArticle

A Novel Energy Efficient Threshold Based Algorithm for Wireless Body Sensor Network

by Suresh Kumar Arumugam, Amin Salih Mohammed, Kalpana Nagarajan, Kanagachidambaresan Ramasubramanian, S. B. Goyal, Chaman Verma, Traian Candin Mihaltan and Calin Ovidiu Safirescu

Energies 2022, 15(16), 6095; https://doi.org/10.3390/en15166095 - 22 Aug 2022

Cited by 12 | Viewed by 1437

Abstract

Wireless body sensor networks (WBSNs) monitor the changes within the human body by having continuous interactions within the nodes in the body network. Critical issues with these continuous interactions include the limited energy within the node and the nodes becoming isolated from the [...] Read more.

Wireless body sensor networks (WBSNs) monitor the changes within the human body by having continuous interactions within the nodes in the body network. Critical issues with these continuous interactions include the limited energy within the node and the nodes becoming isolated from the network easily when it fails. Moreover, when the node’s burden increases because of the failure of other nodes, the energy utilization as well as the heat dissipated increases much more, causing damage to the network as well as human body. In this paper, we propose a threshold-based fail proof lifetime enhancement algorithm which schedules the nodes in an optimal way depending upon the available energy level. The proposed algorithm is experimented with a real time system setup and the proposed algorithm is compared with different routing mechanisms in terms of various network parameters. It is inferred that the proposed algorithm outperforms the existing routing mechanisms. Full article

(This article belongs to the Special Issue Energy Efficiency in Wireless Networks)

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19 pages, 4716 KiB

Open AccessArticle

Modeling of NOMA-MIMO-Based Power Domain for 5G Network under Selective Rayleigh Fading Channels

by Mohamed Hassan, Manwinder Singh, Khalid Hamid, Rashid Saeed, Maha Abdelhaq and Raed Alsaqour

Energies 2022, 15(15), 5668; https://doi.org/10.3390/en15155668 - 04 Aug 2022

Cited by 13 | Viewed by 2220

Abstract

The integration of multiple-input multiple-output (MIMO) and non-orthogonal multiple access (NOMA) technologies is a hybrid technology that overcomes a myriad of problems in the 5G cellular system and beyond, including massive connectivity, low latency, and high dependability. The goal of this paper is [...] Read more.

The integration of multiple-input multiple-output (MIMO) and non-orthogonal multiple access (NOMA) technologies is a hybrid technology that overcomes a myriad of problems in the 5G cellular system and beyond, including massive connectivity, low latency, and high dependability. The goal of this paper is to improve and reassess the bit error rate (BER), spectrum efficiency (SE) of the downlink (DL), average capacity rate, and outage probability (OP) of the uplink (UL) in a 5G network using MIMO. The proposed model utilizes QPSK modulation, four users with different power location coefficients, SNR, transmit power, and two contrasting bandwidths 80 and 200 MHz under selective frequency Rayleigh fading channels. The proposed model’s performance is evaluated using the MATLAB software program. The DL results found that the BER and SE against transmitted power showed the MIMO-NOMA enhanced the BER performance for the best user U4 from 10^−1.7 to 10^−5.2 at 80 MHz bandwidth (BW), and from 10^−1.5 to 10⁻⁵ at 200 MHz for transmitting power of 40 dBm. In contrast, the SE performance for the best user U4 is enhanced from 24 × 10⁻³ to 25 × 10⁻³ bits/second/Hz at 80 MHz BW and from 19.8 × 10⁻³ to 20 × 10⁻³ bps/Hz at 200 MHz BW. Although the outcomes for the UL were obtained in terms of average capacity rate and OP versus SNR at 80, and 200 MHz BW, the MIMO-NOMA result showed that the average capacity rate for the best user U4 performance improves by 12 bps/Hz for 1 dB SNR and the OP is reduced by 15 × 10⁻³ for 80 MHz BW and by 12 × 10⁻³ for 200 MHz BW at an SNR of 0.17 dB. As the BW increased the BER, the average capacity rate increased while the SE and OP decreased. For both DL/UL NOMA with and without MIMO, closed-form expressions for BER, SE, average capacity rate, and OP were obtained. All users’ performance, even those whose connections were affected by interference or Rayleigh fading channels significantly improved, when MIMO-NOMA was implemented. Full article

(This article belongs to the Special Issue Energy Efficiency in Wireless Networks)

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20 pages, 1388 KiB

Open AccessArticle

Key Technologies, Applications and Trends of Internet of Things for Energy-Efficient 6G Wireless Communication in Smart Cities

by M. M. Kamruzzaman

Energies 2022, 15(15), 5608; https://doi.org/10.3390/en15155608 - 02 Aug 2022

Cited by 19 | Viewed by 3052

Abstract

Smart cities can be made into super-smart cities through IoT devices’ implication of energy-efficient 6G. IoT devices are expected to reach fifty billion, but limited information is available regarding the energy-efficient 6G wireless communication standard. This article highlights the key technologies, applications, and [...] Read more.

Smart cities can be made into super-smart cities through IoT devices’ implication of energy-efficient 6G. IoT devices are expected to reach fifty billion, but limited information is available regarding the energy-efficient 6G wireless communication standard. This article highlights the key technologies, applications, and trends in the Internet of Things (IoT) for energy-efficient 6G wireless communication in smart cities. The systematic review helped to achieve the aim of the study by considering the 20 articles extracted from databases and Google that fell between 2015 and 2021 and are written in English. The findings identified that quantum communication, blockchain, visible light communication (VLC), 6G brain–computer interface (BCI), symbiotic radio, and others are the key technologies. The applications of IoT technologies and energy-efficient 6G are found in 15 Minute City, Industrial Town, Intelligent Transport systems and others. Furthermore, the trend of using 6G through IoT devices in smart cities is promising. Full article

(This article belongs to the Special Issue Energy Efficiency in Wireless Networks)

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16 pages, 507 KiB

Open AccessArticle

High-Secured Data Communication for Cloud Enabled Secure Docker Image Sharing Technique Using Blockchain-Based Homomorphic Encryption

by Vishnu Kumar Kaliappan, Seungjin Yu, Rajasoundaran Soundararajan, Sangwoo Jeon, Dugki Min and Eunmi Choi

Energies 2022, 15(15), 5544; https://doi.org/10.3390/en15155544 - 30 Jul 2022

Cited by 4 | Viewed by 2467

Abstract

In recent years, container-based virtualization technology for edge and cloud computing has advanced dramatically. Virtualization solutions based on Docker Containers provide a more lightweight and efficient virtual environment for Edge and cloud-based applications. Because their use is growing on its own and is [...] Read more.

In recent years, container-based virtualization technology for edge and cloud computing has advanced dramatically. Virtualization solutions based on Docker Containers provide a more lightweight and efficient virtual environment for Edge and cloud-based applications. Because their use is growing on its own and is still in its early phases, these technologies will face a slew of security issues. Vulnerabilities and malware in Docker container images are two serious security concerns. The risk of privilege escalation is increased because Docker containers share the Linux kernel. This study presents a distributed system framework called Safe Docker Image Sharing with Homomorphic Encryption and Blockchain (SeDIS-HEB). Through homomorphic encryption, authentication, and access management, SeDIS-HEB provides secure docker image sharing. The SeDIS-HEB framework prioritizes the following three major functions: (1) secure docker image upload, (2) secure docker image sharing, and (3) secure docker image download. The proposed framework was evaluated using the InterPlanetary File System (IPFS). Secure Docker images were uploaded using IPFS, preventing unauthorized users from accessing the data contained within the secure Docker images. The SeDIS-HEB results were transparent and ensured the quality of blockchain data access control authentication, docker image metadata denial-of-service protection, and docker image availability. Full article

(This article belongs to the Special Issue Energy Efficiency in Wireless Networks)

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16 pages, 3176 KiB

Open AccessArticle

Secure Routing-Based Energy Optimization for IoT Application with Heterogeneous Wireless Sensor Networks

by Regonda Nagaraju, Venkatesan C, Kalaivani J, Manju G, S. B. Goyal, Chaman Verma, Calin Ovidiu Safirescu and Traian Candin Mihaltan

Energies 2022, 15(13), 4777; https://doi.org/10.3390/en15134777 - 29 Jun 2022

Cited by 39 | Viewed by 2167

Abstract

Wireless sensor networks (WSNs) and the Internet of Things (IoT) are increasingly making an impact in a wide range of domain-specific applications. In IoT-integrated WSNs, nodes generally function with limited battery units and, hence, energy efficiency is considered as the main design challenge. [...] Read more.

Wireless sensor networks (WSNs) and the Internet of Things (IoT) are increasingly making an impact in a wide range of domain-specific applications. In IoT-integrated WSNs, nodes generally function with limited battery units and, hence, energy efficiency is considered as the main design challenge. For homogeneous WSNs, several routing techniques based on clusters are available, but only a few of them are focused on energy-efficient heterogeneous WSNs (HWSNs). However, security provisioning in end-to-end communication is the main design challenge in HWSNs. This research work presents an energy optimizing secure routing scheme for IoT application in heterogeneous WSNs. In our proposed scheme, secure routing is established for confidential data of the IoT through sensor nodes with heterogeneous energy using the multipath link routing protocol (MLRP). After establishing the secure routing, the energy and network lifetime is improved using the hybrid-based TEEN (H-TEEN) protocol, which also has load balancing capacity. Furthermore, the data storage capacity is improved using the ubiquitous data storage protocol (U-DSP). This routing protocol has been implemented and compared with two other existing routing protocols, and it shows an improvement in performance parameters such as throughput, energy efficiency, end-to-end delay, network lifetime and data storage capacity. Full article

(This article belongs to the Special Issue Energy Efficiency in Wireless Networks)

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14 pages, 2686 KiB

Open AccessArticle

Clustering Based Optimal Cluster Head Selection Using Bio-Inspired Neural Network in Energy Optimization of 6LowPAN

by Mudassir Khan, A. Ilavendhan, C. Nelson Kennedy Babu, Vishal Jain, S. B. Goyal, Chaman Verma, Calin Ovidiu Safirescu and Traian Candin Mihaltan

Energies 2022, 15(13), 4528; https://doi.org/10.3390/en15134528 - 21 Jun 2022

Cited by 1 | Viewed by 2079

Abstract

The goal of today’s technological era is to make every item smart. Internet of Things (IoT) is a model shift that gives a whole new dimension to the common items and things. Wireless sensor networks, particularly Low-Power and Lossy Networks (LLNs), are essential [...] Read more.

The goal of today’s technological era is to make every item smart. Internet of Things (IoT) is a model shift that gives a whole new dimension to the common items and things. Wireless sensor networks, particularly Low-Power and Lossy Networks (LLNs), are essential components of IoT that has a significant influence on daily living. Routing Protocol for Low Power and Lossy Networks (RPL) has become the standard protocol for IoT and LLNs. It is not only used widely but also researched by various groups of people. The extensive use of RPL and its customization has led to demanding research and improvements. There are certain issues in the current RPL mechanism, such as an energy hole, which is a huge issue in the context of IoT. By the initiation of Grid formation across the sensor nodes, which can simplify the cluster formation, the Cluster Head (CH) selection is accomplished using fish swarm optimization (FSO). The performance of the Graph-Grid-based Convolution clustered neural network with fish swarm optimization (GG-Conv_Clus-FSO) in energy optimization of the network is compared with existing state-of-the-art protocols, and GG-Conv_Clus-FSO outperforms the existing approaches, whereby the packet delivery ratio (PDR) is enhanced by 95.14%. Full article

(This article belongs to the Special Issue Energy Efficiency in Wireless Networks)

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Review

Jump to: Editorial, Research

15 pages, 2036 KiB

Open AccessReview

Review of Next-Generation Wireless Devices with Self-Energy Harvesting for Sustainability Improvement

by James Deva Koresh Hezekiah, Karnam Chandrakumar Ramya, Sathya Bama Krishna Radhakrishnan, Vishnu Murthy Kumarasamy, Malathi Devendran, Avudaiammal Ramalingam and Rajagopal Maheswar

Energies 2023, 16(13), 5174; https://doi.org/10.3390/en16135174 - 05 Jul 2023

Cited by 1 | Viewed by 1356

Abstract

Wireless methodologies are the focal point of electronic devices, including telephones, computers, sensors, mobile phones, laptops, and wearables. However, wireless technology is not yet utilized extensively in underwater and deep-space communications applications, and it is also not applied in certain critical medical, military, [...] Read more.

Wireless methodologies are the focal point of electronic devices, including telephones, computers, sensors, mobile phones, laptops, and wearables. However, wireless technology is not yet utilized extensively in underwater and deep-space communications applications, and it is also not applied in certain critical medical, military, and industrial applications due to its limited battery life. Self-energy-harvesting techniques overcome this issue by converting ambient energy from the surroundings into usable power for electronic devices; devices that use such techniques are next-generation wireless devices that can operate without relying on external power sources. This methodology improves the sustainability of the wireless device and ensures its prolonged operation. This article gives an in-depth analysis of the recent techniques that are implemented to design an efficient energy-harvesting wireless device. It also summarizes the most preferred energy sources and generator systems in the present trends. This review and its summary explore the common scope of researchers in narrowing their focus in designing new self-energy-harvesting wireless devices. Full article

(This article belongs to the Special Issue Energy Efficiency in Wireless Networks)

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