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Clustering strategy in wireless sensor networks (WSNs) affects the lifetime, adaptability, and energy productivity of the wireless network system. The low-energy adaptive clustering hierarchy (LEACH) protocol is a convention used to improve the lifetime of WSNs. In this paper, a novel energy-efficient clustering algorithm is proposed, with the aim of improving the energy efficiency of WSNs by reducing and balancing the energy consumptions. The clustering-based convention adjusts the energy utilization by allowing an equal opportunity for each node to turn them into a cluster head (CH). Two-level clustering (TLC) is introduced by adopting LEACH convention where CH selection process undergoes first and second level of clustering to overcome boundary problem in LEACH protocol. The TLC method structures nodes within the scope of the appointed CHs, in order to extend the lifetime of the system. The simulation results show that, in comparison with state-of-the-art methodologies, our proposed method significantly enhanced the system lifetime.

Abstract The extensive utilization of IoT applications leads to the aggregation of a substantial volume of data, presenting a crucial challenge in terms of data routing within these networks. RPL intentionally surpasses the limitations sometimes observed in low-power and lossy networks, which are particularly prevalent in IoT networks. The RPL protocol is designed specifically for static networks that do not involve mobility or topological changes. The RPL protocol guarantees continuous connectivity between nodes and mitigates the risk of data loss in stationary IoT applications that do not involve mobility or alterations in network configuration. The article utilizes a mobility aid technology known as network performance stability using the intelligent routing protocol (nPSIR), which expands upon RPL. The Mobility Support Entity (nPSIR) facilitates the displacement of all nodes, with the exception of the root node, and ensures uninterrupted connection during mobility. Moreover, it deals with the situation where there is a physical barrier between two interconnected nodes in a changing environment. In order to achieve this objective, it employs a dynamic trickle timer that operates within two distinct ranges. Furthermore, it utilizes a neighbor link quality table, a mechanism for selecting the most beneficial parent node in the event of migration, a measure of confidence, the identification of crucial regions, and a blacklist. Multiple simulations validate that nPSIR effectively decreases hand-off delay and improves packet delivery, despite the minor drawbacks of increased signaling costs and power consumption. The delivery ratio decreases the quantity of lost data packets and surpasses both RPL as a responsive protocol and mRPL as a proactive protocol in relation to mobility.

Penelitian ini merupakan penerapan sistem Wireless Sensor Network yang dipadukan dengan Internet of Thing (IoT). Sistem ini sangat memungkinkan untuk diaplikasikan pada perangkat pemantauan bidang pertanian seperti Light Insect Trap (LIT), dimana dalam pemasangannya dilakukan secara terdistribusi di area yang luas dan jauh dari jaringan internet lokal. Sistem ini menggunakan LoRa sebagai sistem komunikasi nirkabel antar perangkat dengan menerapkan topologi mesh untuk menghubungkan end node dan gateway. Pengujian sistem komunikasi perangkat meliputi pengujian performa komunikasi LoRa, pengujian topologi mesh pada perangkat, dan pengujian pengiriman data ke ThingSpeak melalui modul GSM SIM800L. Hasil pengujian meunjukkan bahwa penelitian ini berhasil mengusulkan sistem komunikasi nirkabel yang dapat digunakan untuk pemantauan parameter-parameter perangkat pertanian, termasuk LIT, yang dipasang tersebar di lahan yang luas dan jauh dari jaringan internet lokal. Beberapa perbaikan perlu untuk dilakukan untuk menjadikan sistem komunikasi yang diusulkan lebih handal.

ABSTRACTElliptic Curve Cryptography (ECC) is a promising cryptosystem as it presents the ideal choice for implementing public-key cryptography in resource-limited devices, such as those found in envisioned Internet of Things applications, e.g. wireless sensors. Elliptic Curve ElGamal (ECEG) is a renowned member of the ECC family. However, it requires encoding the message before encryption and decoding it after decryption. To better improve the processing time and to avoid sharing a lookup table, we propose, in this document, a new method that exchanges encoding parameters and authenticates endpoints at the same time. So, our new protocol ensures the authentication of communication parties and integrity of ephemeral encoding parameters. The robustness of our solution is proven by the Scyther tool. Experimental tests have been carried out, and the performance of the new methods is provided and compared with RSA and related work. Security and performance analysis show that our new scheme has achieved improved functionality and higher security while maintaining low computational.

Abstract The maximum amount of sensor energy is consumed during broadcasting. Hence in order to make delay with the network lifetime of a wireless sensor network (WSN), there is a need of optimum utilization of sensor energy. Scheduling in media access control (MAC) layer plays a critical role in the designing of WSN to avoid collision and conserve more energy. The Distributed energy aware MAC (DE-MAC) is one such efficient and feasible MAC protocol that addresses the energy management issues in WSN. This work proposes an extension of DE-MAC framework by allocating varying period slots to the nodes based on their residual energy level. Energy of all the nodes is exchanged at regular intervals. Accordingly, the nodes with low energy are allocated less time slots for broadcast and are made to sleep for more time. Simulation is carried out using NS2 (network simulator 2) and the efficiency and performance results are compared with DE-MAC for analysis. Improvement in performance for various parameters such as residual energy, throughput, and packet delivery ratio can be observed.

Wireless sensor networks (WSNs) have recently been viewed as the foundation infrastructure that has paved the way for the emergence of the Internet of Things (IoT). However, there is a challenge when integrating WSNs into the IoT due to high-energy consumption in their nodes and poor network lifespan. As a result, the fundamental issues in WSN are sensor node energy scarcity, sensor data exchange, and routing protocols. To address the aforementioned shortcomings, this paper proposes an optimized energy-efficient path-planning approach that increases network lifetime and connectivity. These applications employ large amounts of data and need a data that are more effective sensing and data transfer method. This study presents Improvised DSHR (Dual Step Hybrid Routing) - a methodology for cluster-based routing efficiency. It consists of a two-phase method designed to identify the best route taking clustering into account. In addition, it consists of cluster head selection, optimum route building, node integration with the cluster head, and sensing range optimization. Furthermore, an efficient data transmission. Improvised DSHR is evaluated considering network lifetime, communication overhead, no active nodes, and Route Length evaluated, and then the model is compared to the current Leach protocol to demonstrate its efficiency. [ABSTRACT FROM AUTHOR]

The extensive utilization of IoT applications leads to the aggregation of a substantial volume of data, presenting a crucial challenge in terms of data routing within these networks. RPL intentionally surpasses the limitations sometimes observed in low-power and lossy networks, which are particularly prevalent in IoT networks. The RPL protocol is designed specifically for static networks that do not involve mobility or topological changes. The RPL protocol guarantees continuous connectivity between nodes and mitigates the risk of data loss in stationary IoT applications that do not involve mobility or alterations in network configuration. The article utilizes a mobility aid technology known as network performance stability using the intelligent routing protocol (nPSIR), which expands upon RPL. The Mobility Support Entity (nPSIR) facilitates the displacement of all nodes, with the exception of the root node, and ensures uninterrupted connection during mobility. Moreover, it deals with the situation where there is a physical barrier between two interconnected nodes in a changing environment. In order to achieve this objective, it employs a dynamic trickle timer that operates within two distinct ranges. Furthermore, it utilizes a neighbor link quality table, a mechanism for selecting the most beneficial parent node in the event of migration, a measure of confidence, the identification of crucial regions, and a blacklist. Multiple simulations validate that nPSIR effectively decreases hand-off delay and improves packet delivery, despite the minor drawbacks of increased signaling costs and power consumption. The delivery ratio decreases the quantity of lost data packets and surpasses both RPL as a responsive protocol and mRPL as a proactive protocol in relation to mobility. [ABSTRACT FROM AUTHOR]

Summary: In the modern era, unmanned aerial vehicle (UAV) based wireless sensor networks (WSN) are rising technologies in wireless communication. Through UAV, the sensed data can be forwarded to the base station. However, the increase in network users leads to several malicious attacks on UAVs. Hence, it affects the performance of a WSN platform while transmitting private information through UAVs. Therefore, the proposed study intends to develop an effective malicious UAV detection approach using a machine‐learning algorithm. Initially, the deployed sensor nodes in WSN are utilized to collect the environmental data. These sensor nodes transmit the collected data to the UAV. During data transmission, the sensor nodes generate a feed packet (authentication parameter) and forward it to the UAV along with the sensed information. The feedback packet is encrypted through a proxy re‐encryption scheme to secure the input data. These encrypted packets with the sensed input data are then transmitted to the base station. Finally, the feedback packet is decrypted and attains the actual input information. From the received data, the classification is performed using a proposed support vector machine with a shuffled frog leap (SVM‐SFL) approach. The proposed approach is implemented with the NS3 Python tool, and the results are analyzed by evaluating several performance matrices. Compared with other existing methods, the proposed study obtained improved results in terms of accuracy (98.61%), precision (98.5%), sensitivity (98.63%), and F‐measure (98.62%). [ABSTRACT FROM AUTHOR]

The Internet of Things (IoT) represents an overarching ideology that blurs the boundaries between the physical and virtual worlds, encompassing a broad spectrum of computing systems and information technologies. IoT devices, such as wearable devices like smart watches and implantable medical devices, are connected to the Internet. Some IoT devices are even integrated into the human body. Generally, wireless communication technologies facilitate connectivity among intelligent and autonomous objects. However, security concerns within IoT pose significant challenges that impede its widespread adoption and evolution. This paper introduces a lightweight and robust security protocol designed to authenticate objects, ensure data integrity during transmission, and detect intrusions in case of attacks on the system. [ABSTRACT FROM AUTHOR]

The advent of Internet of Things (IoT) devices has revolutionized our daily routines, fostering interconnectedness and convenience. However, this interconnected network also presents significant security challenges concerning authentication and data integrity. Traditional security measures, such as Public Key Infrastructure (PKI), encounter limitations when applied to resource-constrained IoT devices. This paper proposes a novel decentralized PKI system tailored specifically for IoT environments to address these challenges. Our approach introduces a unique "zone" architecture overseen by zone masters, facilitating efficient certificate management within IoT clusters while reducing the risk of single points of failure. Furthermore, we prioritize the use of lightweight cryptographic techniques, including Elliptic Curve Cryptography (ECC), to optimize performance without compromising security. Through comprehensive evaluation and benchmarking, we demonstrate the effectiveness of our proposed solution in bolstering the security and efficiency of IoT ecosystems. This contribution underlines the critical need for innovative security solutions in IoT deployments and presents a scalable framework to meet the evolving demands of IoT environments. [ABSTRACT FROM AUTHOR]

In precision agriculture, a wireless sensor network (WSN) is employed to gather data pertaining to atmospheric conditions. WSN consists of sensor nodes installed at multiple points in a greenhouse for monitoring soil properties like moisture, pesticide levels, air temperature, humidity level and so on. Sensor nodes transmit the measured parametric digital information to a sink node. It further transmits the sensed data to a decision support system. The decision system uses a crop development model to effectively manage irrigation, fertilization, and climate control systems in a greenhouse. This allows for exact control over temperature and humidity levels. By using appropriate inputs, crops may be effectively managed, resulting in improved crop health and increased yield. Reliable transmission data is a crucial design objective for WSN in precision agriculture as the presence of foliage in the transmission channel causes significant attenuation of the radiated waves. Additionally, it may cause scattering and diffraction of signals as well. A dynamic data routing protocol selects the optimum data paths for node data transmission in a WSN. This paper presents a novel energy-efficient multi-hop data routing protocol for WSN precision agriculture applications. The proposed method is named Grey Wolf Optimized Coalitional Game Theory-based (GO_CGT) multi-hop routing protocol is adopted for selecting the required features to measure the importance of the corresponding fitness and dilate the feature map containing less information. Moreover, a rapid and highly which achieves 78.2% of PDR, 12% of energy consumption, 34.7% of end-to-end delay, and 247kbps of throughput. [ABSTRACT FROM AUTHOR]

Wireless Sensor Networks (WSNs) are extensively utilized across diverse applications, ranging from environmental monitoring to industrial automation. These networks deploy autonomous devices equipped with sensors to monitor environmental conditions such as temperature, humidity, and light. They play crucial roles in fields like precision agriculture, healthcare monitoring, and smart cities infrastructure. In the domain of WSNs, ensuring both security and precise localization is vital for sustaining optimal network performance and facilitating timely event detection. Despite numerous localization studies, existing approaches often fall short in 3D localization due to low beacon node accuracy and sparse environment coverage. Furthermore, achieving higher localization accuracy is challenging due to potential attacks that can compromise network integrity and reduce battery life. To address these issues, a novel Secure 3D algorithm is introduced in this paper to combat malicious beacon nodes as well as to enhance localization accuracy. The proposed Secure 3D algorithm demonstrates superior performance compared to the 3D DV-Hop, 3D APIT and Improved 3D localization algorithms in terms of Average Localization Error (ALE), Bad Node Proportion (BNP), and Localized Node Proportion (LNP), while also being energy-efficient. This algorithm achieves an ALE ranging from 3.0 to 6.5, a BNP below 0.2, and an LNP exceeding 0.8, all while consuming 100–130mW of energy. By addressing the challenges of malicious beacon nodes and enhancing localization accuracy, the proposed work not only improves network reliability but also ensures energy-efficient energy localization, making it a promising solution for enhancing the performance and security of WSNs in 3D environments. [ABSTRACT FROM AUTHOR]

Presently, wireless sensor networks (WSNs) are emerging as a vibrant field of research due to various challenging aspects such as energy consumption, routing strategies, effectiveness, among others. Despite unresolved issues within WSNs, a substantial array of applications has already been developed. For any application design, a primary objective is to optimize the WSN in terms of its lifecycle and functionality. Recent studies on data reduction methods have shown that sensor nodes often transmit data directly (single hop) to the base station (BS). However, a significant concern is that most existing multi-hop routing protocols do not address data reduction before forwarding data to the BS. Consequently, this study introduces a Hybrid Data Reduction and Routing Algorithm (HDRA). The principal aim of HDRA is to prolong the lifespan of cluster-based WSNs. It strives to decrease the packet transmission by sensor nodes, especially when there is minimal change in sensor readings. The findings indicate that HDRA outperforms the LEACH protocol in terms of energy efficiency in sensor networks, irrespective of network type (T, H, or TH) or deployment scenarios (200x200m or 400x400m). Overall, the proposed algorithm enhances network performance by conserving energy and extending network lifespan. [ABSTRACT FROM AUTHOR]

With the increasing demand for the use of technology in all matters of daily life and business, the demand has increased dramatically to transform business electronically especially regards COVID-19. The Internet of Things (IoT) has greatly helped in accomplishing tasks. For example, at a high temperature, it would be possible to switch on the air conditioner using a personal mobile device while the person is in the car. The Internet of Things (IoT) eases lots of tasks. A wireless sensor network is an example of IoT. Wireless sensor network (WSN) is an infrastructure less self-configured that can monitor environmental conditions such as vibration, temperature, wind speed, sound, pressure, and vital signs. Thus, WSNs can occur in many fields. Smart homes give a good example of that. The security concern is important, and it is an essential requirement to ensure secure data. Different attacks and privacy concerns can affect the data. Authentication is the first defence line against threats and attacks. This study proposed a new protocol based on using four factors of authentication to improve the security level in WSN to secure communications. The simulation results prove the strength of the proposed method which reflects the importance of the usage of such protocol in authentication areas. [ABSTRACT FROM AUTHOR]

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Wireless Sensor Networks (WSN) can be part of a tremendous number of applications. Many WSN applications require real-time communication where the sensed data have to be delivered to the sink node within a predetermined deadline decided by the application. In WSNs, the sensor nodes' constrained resources (e.g. memory and power) and the lossy wireless links, give rise to significant difficulties in supporting real-time applications. In addition, many WSN routing algorithms strongly emphasize energy efficiency, while delay is not the primary concern. Thus, WSNs desperately need new routing protocols that are reliable, energy-efficient, and appropriate for real-time applications. The proposed algorithm is a real-time routing algorithm appropriate for delay-sensitive applications in WSNs. It has the ability to deliver data on time while also enabling communications that are reliable and energy-efficient. It achieves this by deciding which candidate neighbors are eligible to participate in the routing process and can deliver the packet before its deadline. In order to lessen the delay of the chosen paths, it also computes the relaying speed for each eligible candidate. Moreover, it takes into account link quality, hop count, and available buffer size of the selected relays, which leads to end-to-end delay reduction while also minimizing energy consumption. Finally, it considers the node's energy consumption rate when selecting the next forwarder to extend the network lifetime. Through simulation experiments, the proposed algorithm has shown improved performance in terms of packet delivery ratio, network lifetime packets miss ratio, average end-to-end delay, and energy imbalance factor. [ABSTRACT FROM AUTHOR]

Elliptic Curve Cryptography (ECC) is a promising cryptosystem as it presents the ideal choice for implementing public-key cryptography in resource-limited devices, such as those found in envisioned Internet of Things applications, e.g. wireless sensors. Elliptic Curve ElGamal (ECEG) is a renowned member of the ECC family. However, it requires encoding the message before encryption and decoding it after decryption. To better improve the processing time and to avoid sharing a lookup table, we propose, in this document, a new method that exchanges encoding parameters and authenticates endpoints at the same time. So, our new protocol ensures the authentication of communication parties and integrity of ephemeral encoding parameters. The robustness of our solution is proven by the Scyther tool. Experimental tests have been carried out, and the performance of the new methods is provided and compared with RSA and related work. Security and performance analysis show that our new scheme has achieved improved functionality and higher security while maintaining low computational. [ABSTRACT FROM AUTHOR]

Summary: The Internet of Things (IoT) has become widely used in applications such as smart homes, industrial automation, and transportation due to its affordable hardware and fast internet connectivity. However, the increase in IoT‐enabled gadgets, particularly those running on batteries or connected to other sources, is putting strain on the world's energy requirements. Therefore, this study focuses on a green routing solution for battery‐powered IoT‐enabled Software‐defined Wireless Sensor Networks (IoT‐SDWSN). Finding green solutions for IoT‐based networks to address this energy challenge has become crucial. This study focuses on developing a green routing solution for battery‐powered IoT‐SDWSN. Energy efficiency in IoT‐SDWSN is attained by the process of clustering nodes. The network is partitioned into small clusters, and a Control Node (CN) is set up by a Control Server (CS) to transmit the data packets sent by sensor nodes. Choosing a CN in these networks is a critical concern due to the substantial energy consumption involved in delivering data to the CS. This research focuses on the problem of energy‐efficient cluster routing in IoT‐based SD‐WSN. It introduces the Energy‐optimized Artificial Hummingbird Algorithm (EOAHA) as a green routing technique. EOAHA aims to extend the lifespan of IoT‐based SD‐WSNs by intelligently selecting (based on a new fitness function) CNs to distribute the network load and increase its overall longevity. To evaluate the performance of EOAHA, a comparative analysis is conducted against other state‐of‐the‐art algorithms. The results demonstrate that EOAHA outperforms these algorithms by a minimum of 13.5% in terms of network longevity. [ABSTRACT FROM AUTHOR]