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The adoption of UAVs in defence and civilian sectors necessitates robust communication networks. This paper presents a routing protocol for Cognitive Radio Unmanned Aerial Vehicles (CR-UAVs) in Flying Ad-hoc Networks (FANETs). The protocol is engineered to optimize route selection by considering crucial parameters such as distance, speed, link quality, and energy consumption. A standout feature is the introduction of the Central Node Resolution Factor (CNRF), which enhances routing decisions. Leveraging the Received Signal Strength Indicator (RSSI) enables accurate distance estimation, crucial for effective routing. Moreover, predictive algorithms are integrated to tackle the challenges posed by high mobility scenarios. Security measures include the identification of malicious nodes, while the protocol ensures resilience by managing multiple routes. Furthermore, it addresses route maintenance and handles link failures efficiently, cluster formation, and re-clustering with joining and leaving new nodes along with the predictive algorithm. Simulation results showcase the protocol's self-comparison under different packet sizes, particularly in terms of end-to-end delay, throughput, packet delivery ratio, and normalized routing load. However, superior performance compared to existing methods, particularly in terms of throughput and packet transmission delay, underscoring its potential for widespread adoption in both defence and civilian UAV applications. [ABSTRACT FROM AUTHOR]

Copyright of Systems Engineering & Electronics is the property of Journal of Systems Engineering & Electronics Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Mobility has ultimate applications in Wireless Sensor Networks (WSNs) including several areas such as wildlife intensive care, health monitoring, flood and fire detection, and much more. Mobile WSNs (MWSNs) have captivated customer attention in recent centuries because of their applications in numerous areas. Mobile WSNs are source constraints and request performance studies by many nodes' movement outlines. Usually, routing algorithms in MWSN have been examined for specified movement. However, for instantaneous network scenarios, designing an efficient routing protocol/algorithm and analysing changes in numerous movement outlines on routing approaches are important to provide efficient results. Hence, keeping in the assessment of the aforesaid problem, an Energy Proficient Mobile Routing (EPMR) protocol is proposed. All the simulations have been completed in MATLAB on varied constraints to assess the effectiveness of EPMR and state-of-the-art routing protocols. Simulation outcomes demonstrate that EPMR provides improved performance than Distributed Efficient Multi-hop Clustering (DEMC), Geographic Robust Clustering (GRC), Mobility Aware Routing (MAR), Distributed Efficient Clustering Approach (DECA), and Improved Energy Mobile Routing (ECMR). EPMR enhances packet delivery ratio by 13–15%, reduces packet loss percentage by 12–14%, extends throughput by 14–16%, decreases overhead by 13–14%, minimizes average end-to-end delay by 13–15%, minimizes energy consumption by 16–18%, and extends network lifetime 17–19% on sensors' mobility. EPMR achieves better outcomes with the Random Waypoint Mobility (RWPM) model than the Random Walk Mobility (RWM) model and Pathway Mobility (PM) model. [ABSTRACT FROM AUTHOR]

Recently, with the development of nanotechnology and the emergence of new materials, Wireless Nanosensor Networks (WNSNs) have been presented. To address the problems of link instability in WNSNs and poor adaptability of the EBCNF framework to network topology changes, a reliable multi-path routing based on link stability called RMRLS is proposed. Based on the EBCNF framework, this protocol introduces a path similarity judgment model to judge the similarity between paths. In the route establishment process, the link stability evaluation model is used to measure the stability of each path and as a criterion for path selection. Then alternative route is selected through the routing similarity judgment model. Optimal path and backup path are two routing paths to cope with changes in the network topology. The simulation results show that the RMRLS protocol has advantages in energy efficiency, data packet transmission success rate and average throughput, which are 28.84% lower, 53.8% higher, and more than double compared to EBCNF at a distance of 10 mm, respectively. These findings proved the RMRLS protocol's capacity to significantly boost the stability and reliability of the network. [ABSTRACT FROM AUTHOR]

Addressing latency concerns and ensuring high-quality video services in Heterogeneous Mobile Adhoc Networks (H-MANETs) are paramount challenges. This paper presents a pioneering solution: the Pre-emptive Priority Queueing based Multipath Routing algorithm (PPQM). Our approach prioritizes video traffic within OpenFlow switches, directing it across multiple paths in H-MANETs. Integrating the PPQ module within Cluster Heads operating in the software-defined networking (SDN) architecture is central to our design. We rigorously evaluate delay for each path by employing an M/M/1 queueing policy based on a Poisson arrival process and an exponential service time distribution. Utilizing Burke's theorem, our calculation spans the entire route from the cluster head to a sink node. By meticulously assessing the delay characteristics of individual paths, our model facilitates the selection of the most optimal path to minimize overall delay and enhance network performance. Our proposed model amalgamates clustering, FIFO with M/M/1 queueing, and SDN techniques. In a comprehensive evaluation against existing technologies, the implementation of PPQM demonstrates superior performance in crucial Quality of Service (QoS) metrics, including end-to-end delay, queue size, waiting time, throughput, and response time. Furthermore, our research achieves a significant 4.2% improvement in QoS metrics compared to contemporary approaches, highlighting the effectiveness of the PPQM algorithm in enhancing network performance. This research contributes a robust solution for advancing QoS in H-MANETs, demonstrating the efficacy of the PPQM algorithm compared to contemporary approaches. [ABSTRACT FROM AUTHOR]

Summary: Wireless body area networks (WBANs) are becoming widely considered in remote healthcare monitoring applications. However, WBAN nodes have limited resources; therefore, effective and reliable routing protocols are pivotal research challenges. Furthermore, balancing the traffic load among sensor nodes is also highly required to increase network stability. In recent years, many interesting routing solutions have been proposed for WBANs; however, the significant feature in terms of stability and energy in these solutions has not been sufficiently addressed. Therefore, in this context, the Hot‐Sspot Aaware Multicost‐based Energy‐efficient Routing (H‐SAMER) protocol is proposed in this paper. The suggested protocol used multieffective cost function for next‐hop node selection based on the data type, where the patient's data are categorized into three classes: normal data, on‐demand data, and emergency data. Furthermore, the H‐SAMER protocol adds awareness to the transmission of control packets by adding the cost value to the RREQ packets. Thus, the simulation scenario shows that the H‐SAMER saves energy 8.57%, 88%, 98%, 97%, and 100% greater than E‐HARP, EH‐RCP, CO‐LAEEBA, EECBSR, and ELR‐W, respectively. Moreover, the first node death of the proposed H‐SAMER is delayed to round number 7500, which proves H‐SAMER to be a stable and reliable effective solution for WBANs. [ABSTRACT FROM AUTHOR]

Summary Wireless sensor networks (WSNs) contain different sensors, which collect various data in the monitoring area. In general, one of the significant resources in WSNs is energy, which prolongs the network's lifetime. The energy‐efficient routing algorithms reduce energy consumption and enhance the survival cycle of WSNs. Thus, this work developed the optimization‐based WSN routing and deep learning (DL)–enabled energy prediction scheme for efficient routing in WSNs. Initially, the WSN simulation is carried out, and then, the node with minimum energy consumption is chosen as the cluster head (CH). Here, the proposed rat hawk optimization (RHO) algorithm is established for finding the best CH, and the RHO is the integration of rat swarm optimization (RSO) and fire hawk optimization (FHO). Furthermore, the routing is accomplished by the developed fractional rat hawk optimization (FRHO) using the fitness function includes delay, distance, link lifetime, and predicted energy of a network for predicting the finest route. Here, the fractional calculus (FC) is incorporated with the RHO to form the FRHO. The energy prediction is achieved by deep recurrent neural network (DRNN). The energy, delay, and throughput evaluation metrics are considered for revealing the efficiency of the proposed system, and the proposed system achieves the best results of 0.246 J, 0.190 s, and 67.13 Mbps, respectively. [ABSTRACT FROM AUTHOR]

Wireless sensor networks (WSNs) are crucial in collecting environmental information through sensor nodes. However, limited energy resources pose a challenge, necessitating efficient routing algorithms to minimize energy consumption. Failure to address issues can consume energy and reduce network lifespan and overall efficiency. This research paper presents a cutting-edge approach for minimizing the consumption of energy within WSN through the implementation of an optimal routing method. The approach involves two steps: first, clustering sensor nodes using the pond skater algorithm (PSA) to select cluster head (CHs) for routing; second, by leveraging the ant colony optimization (ACO) algorithm, this study introduces an innovative technique that empowers a mobile sink to gather packets from given CHs and transmit effectively, send them back to the base station (BS). Notably, the authors make a significant contribution by introducing a different variant of the PSA algorithm to select CH. This novel approach aims to curtail the consumption of energy within WSN significantly. The authors also present an ACO-based head traversal for cluster method, resembling the traveling salesman problem coding, for minimized energy consumption. The study's primary objectives include reducing energy consumption, minimizing packet delivery ratio, and prolonging the lifetime of the WSN. The assessment efficacy of the proposed method was achieved by regressive simulations using MATLAB on diverse scenarios. Through meticulous comparative analyses with several efficient algorithms, the method proposed here has shown significant performance in network lifetime comparison of PSACO in terms of Alive nodes with number of rounds PSO: 17.65%, GWO: 25%, CS: 33.33%, CBR-ICWSN: 66.66%, CCP-IC: 17.65%. [ABSTRACT FROM AUTHOR]

With technological advancements in networking and wireless communication, the flying ad hoc network has emerged as a cost-effective relay network. Networks of unmanned aerial vehicles (UAVs) can be cooperatively organized as an ad hoc network for effectively accomplishing complex tasks. Such a UAV network is deployed as a relay network that forwards and exchanges accurate and reliable end-to-end in-formation. However, the design of routing protocols is rendered difficult by flying constraints and extreme topology changes over a short time period. The performance of the routing protocols in such networks is considerably affected by high-speed nodes and extreme topology changes. Evaluating the routing protocol in a UAV network gives insight regarding the performance of the entire network. This paper evaluates, analyzes, and compares the performances of three routing protocols: Ad hoc On-demand Distance Vector (AODV), Optimized Link State Routing (OLSR), and Destination-Sequenced Distance-Vector (DSDV). In most of the simulated cases, the AODV outperformed the OLSR and DSDV. The number of nodes, i.e., the network size, largely affected the throughput, packet delivery ratio (PDR), and end-to-end delay (E2E) of the network. However, the OLSR improved the performance of the average E2E; therefore, it is suitable for delay-sensitive applications. However, AODV outperformed the other protocols in terms of throughput and PDR because it reacts to topology changes. DSDV delivered the poorest PDR and throughput. [ABSTRACT FROM AUTHOR]

In wireless sensor networks, the implementation of routing protocols is crucial owing to their limited computational capacities. Tree routing is a suitable method in wireless sensors owing to its minimal routing overhead. However, single-hop metric schemes, such as hop count, cause congestion at specific nodes, whereas multiple metric schemes cannot control dynamically changing network environments. To address these issues, we propose a scheme to implement enhanced tree routing with adaptive metrics based on hop count. This approach assigns different weights to metrics to select suitable parent nodes based on hop count. The parent-selection algorithm utilizes hop count, buffer occupancy, and received signal strength indicator (RSSI) as metrics. This study evaluates the performance through simulation scenarios to analyze whether improvements can be made to address problems encountered in traditional tree routing. The performance metrics include packet delivery speed, throughput, and end-to-end delay, which vary depending on the volume of network traffic. [ABSTRACT FROM AUTHOR]

Resilient of routing processes is one of the biggest challenges for data transmission in mobile networks without infrastructure. Communication under current routing protocols is through a communication path that, although the shortest, may not perform satisfactorily in terms of resilient. Routing and communication within such a path may take place using nodes that are malicious or inappropriate in the communication process due to malicious or poor technical state. This paper presents a new algorithm for various uses of mobile ad hoc networks not only in edge networks with infrastructure but also with the possibility of being used in the cloud solutions. We have modified decentralized blockchain technology and artificial intelligence using deep learning methods that have been implemented in routing processes. The objective of this algorithm was to select the most resilient communication path from the source to the destination node. Such a communication path selection consisted of selecting the nodes that were most suitable in terms of resilience, where the selection nodes was provided through a network and technical parameters. The key quality of service metrics, throughput, total delay, number of delivered signaling and data packets and the ratio between them were used to evaluate the proposed resilient routing algorithm. Modified resilient routing protocols achieved improvement in all the analyzed parameters compared to the original routing protocols. The improvement in these parameters led to an increase in the resilience of the routing process based on the actual data obtained from each node in the network and previous communications. [ABSTRACT FROM AUTHOR]

Delay tolerant networks (DTNs) are a kind of sporadically connected mobile networks in which the network is intermittent, and end-to-end path is hard to establish. However, as devices in DTNs may often have limited energy and buffer, the network performance will be inevitably affected, especially in our application domain, i.e. the post-disaster scenario. Thus, to start with, we present an appropriate energy and buffer efficient routing protocol (EBRout) for efficient message transmission over a smartphone based DTN. Due to limited battery and storage capacity in mobile devices, a major problem in DTNs is to convince forwarder nodes to participate in forwarding messages. Thus, for improving cooperation among the nodes, an incentivizing scheme is proposed which works in two steps. As the first step, we propose an optimization model to find the minimum incentive. Next, we propose a blockchain-based incentive allocation model that uses Ethereum platform built on top of a DTN-Blockchain integrated environment. The use of blockchain helps to create an immutable and globally accessible record for incentive allocation. The performance of the entire scheme is estimated through extensive simulation in ONE simulator, Python PuLP and Ethereum platform. Performance analyses indicate that the average incentive paid using our proposed optimization model is much lower than the average incentive paid without using the optimization model. Also, the results substantiate the efficiency of the proposed scheme over the competing schemes, in terms of delivery ratio, energy and message overhead without negotiating the blockchain performance in terms of processing time and gas consumption. [ABSTRACT FROM AUTHOR]

The Internet of Things (IoT) is a promising technology for sensing and monitoring the environment to reduce disaster impact. Energy is one of the major concerns for IoT devices, as sensors used in IoT devices are battery-operated. Thus, it is important to reduce energy consumption, especially during data transmission in disaster-prone situations. Clustering-based communication helps reduce a node's energy decay during data transmission and enhances network lifetime. Many hybrid combination algorithms have been proposed for clustering and routing protocols to improve network lifetime in disaster scenarios. However, the performance of these protocols varies widely based on the underlying network configuration and the optimisation parameters considered. In this research, we used the clustering parameters most relevant to disaster scenarios, such as the node's residual energy, distance to sink, and network coverage. We then proposed the bio-inspired hybrid BOA-PSO algorithm, where the Butterfly Optimisation Algorithm (BOA) is used for clustering and Particle Swarm Optimisation (PSO) is used for the routing protocol. The performance of the proposed algorithm was compared with that of various benchmark protocols: LEACH, DEEC, PSO, PSO-GA, and PSO-HAS. Residual energy, network throughput, and network lifetime were considered performance metrics. The simulation results demonstrate that the proposed algorithm effectively conserves residual energy, achieving more than a 17% improvement for short-range scenarios and a 10% improvement for long-range scenarios. In terms of throughput, the proposed method delivers a 60% performance enhancement compared to LEACH, a 53% enhancement compared to DEEC, and a 37% enhancement compared to PSO. Additionally, the proposed method results in a 60% reduction in packet drops compared to LEACH and DEEC, and a 30% reduction compared to PSO. It increases network lifetime by 10–20% compared to the benchmark algorithms. [ABSTRACT FROM AUTHOR]

For remote health monitoring, activity tracking, and other applications in healthcare such as sports, Wireless Body Area Networks (WBANs) have become a feasible technology. However, the limited resources and dynamic nature of WBANs pose significant challenges to designing efficient and reliable routing protocols. To address these challenges, the proposed work suggests a thermal-aware, energy-efficient, and congestion-aware routing protocol (TECRP) for WBAN. TECRP focuses on improving transmission in both inter-WBAN and intra-WBAN scenarios. It addresses three key Quality of Service (QoS) parameters: energy efficiency, node temperature, and congestion, aiming to enhance overall WBAN communication efficiency. To achieve all these parameters, the algorithm is considered a multi-objective problem. The analysis shows that the temperature rises and delay increases with the number of data transmission, but the multi-objective approach helps to mitigate such effects. The result analysis shows that the path loss values fluctuate with increasing data transmission and network traffic. But the temperature rise increases with more data transmission and larger packets. On the other hand, the Packet Delivery Ratio (PDR) decreases with an increase in data transmission and with larger packet sizes. This shows that with higher congestion ratios, a higher likelihood of packet loss is seen. But in overall performance, the proposed TECRP shows better efficiency and congestion management as compared to other existing state-of-art-models and achieves high PDR, and minimizes packet loss. The proposed approach shows 0.42% improvement in energy efficiency as compared to existing approaches. [ABSTRACT FROM AUTHOR]

One of the networking technologies is called a wireless sensor network, and what it does is link sensor nodes by using wireless communication as the channel of connection. A haphazard and random distribution of nodes is carried out throughout the deployment process within the network area. As a result, the distances between the nodes do not remain constant. The nodes have a high sensing capacity, but their range of perception and battery life are also severely limited. The wireless data may be sensed by all of the nodes inside their respective sensing regions. Consequently, there are a variety of new applications that make use of WSN applications, particularly in surveillance monitoring applications such as those used in hospitals, buildings, forests, and airspace monitoring. The transmission of the data to the appropriate server or data centre that is linked with the cloud or the internet is experiencing greater difficulties as a result of the growing amount of monitoring data. This indicates that a significant quantity of data is lost as a result of the fact that wireless transmission is affected by environmental factors such as precipitation, humidity, and wind storms. It is vital to create and execute an innovative routing protocol to deliver greater throughput and raise the overall Quality of Service of the WSN applications in order to solve the difficulties that have been outlined above. This study paper presents a metaheuristic algorithm based optimal routing protocol for WSN application, which boosts the overall quality of service of any surveillance monitoring applications. To achieve this goal, the protocol was designed for wireless sensor networks. It does so in an effective manner, resulting in decreased delay and energy consumption as well as enhanced throughput and PDR. Based on the findings of the experiments, it has been hypothesised that the proposed metaheuristic algorithm-based routing protocol is capable of performing better routing for any type of surveillance monitoring and remote monitoring, as well as successfully transmitting any type of data, including numerical, video, and image data. [ABSTRACT FROM AUTHOR]

The Internet of Things (IoT) concept is being extensively embraced in several industries, such as Intelligent Transportation Systems (ITS), to improve effectiveness and sustainability by utilizing advanced transportation resource data. Researching routing protocols is essential for maximizing the efficiency of dynamic Vehicular Ad Hoc Networks (VANETs) in ITS.VANETS utilize wireless technology, including both cellular and non-cellular, to facilitate the transmission of information. The former offers minimal latency but is expensive to operate, but the latter is preferable for lower-data-rate applications decreases costs, and is more energy-efficient. Developing countries are currently enhancing their 5G assistance, but the financial viability of Low Earth Orbit (LEO) satellite technology remains low. Underdeveloped nations require cost-effective, comprehensive wireless communication solutions in both urban and rural regions. One of the prominent choices for the Low Power Wide Area Network (LPWAN) in the 5G ecosystem is the Long Range Wide Area Network (LoRaWAN). This paper presents an enhanced routing protocol that is secure against attacks on the network and offers improved performance metrics. The protocol is designed for information routing in the proposed Vehicular Communication System (VCS). The VCS is tested to verify its efficacy in detecting blind spots. A proof-of-concept prototype for VCS is developed to integrate LoRaWAN technology with an enhanced routing protocol. This integration aims to enhance signal strength, improving communication reliability, network coverage, and security. Furthermore, the system is engineered to optimize vehicle energy efficiency, rendering it well-suited for communication in underdeveloped urban and rural regions. [ABSTRACT FROM AUTHOR]

Energy limitation is one of the essential parameters in the design of a Wireless body area networks (WBANs) as it is important to improve the lifetime of the network. WBAN routing is an effective approach for establishing energy efficiency sets and assign time slots for the network. Many algorithms that deal with interference model treats the whole WBAN as a minimum interference unit and increase their lifetime cycle. In this research, we report an effective low-energy adaptive clustering hierarchy (LEACH) routing protocol using MATLAB simulation and related C++ simulation codes to enhance the overall performance of the network by improving the energy efficiency and network lifetime cycles. Furthermore, the study sheds light up on the comparison of the protocol and proposes a modified protocol for WBAN. Based on the results obtained from conducting different configurations in the proposed design, the base station should be situated near the network to insure high network performance. [ABSTRACT FROM AUTHOR]

Copyright of Telecommunication Engineering is the property of Telecommunication Engineering and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

A wireless body area network (WBAN) is a type of wireless sensor network that plays a crucial role in monitoring patient healthcare. In this network, sensor nodes are typically placed inside or outside the patient's body. These nodes are capable of transmitting data to the sink node when any functional changes in the patient are detected. The routing and energy efficiency of the network nodes are challenging tasks in WBAN, as each sensor node operates on a battery. Therefore, in multi-hop routing designing a robust routing protocol has a significant impact on reducing energy consumption during the selection of the next hop. In this paper, a simple novel routing protocol named simple energy-aware and reliable (SEAR) routing protocol is proposed to transmit reliable data packets in a WBAN. The proposed routing scheme considers the remaining energy of sensor nodes, priority data, and hop count to the sink node as significant metrics for dynamically selecting the best forwarder node. Furthermore, the proposed protocol utilizes the route reliability factor (RRF) to select the optimal route among all possible routes between the source sensor node and the sink node. RRF selects the route with the maximum route residual energy and minimum hop count. As a result, SEAR has the ability to provide effective single-hop and multi-hop routing data transmission to improve the reliability of data transmission, decrease the energy consumption of the sensor nodes, and prolong the lifetime of the network. The simulation results show that the performance of the SEAR routing protocol outperforms the existing routing protocols for the metrics: packet loss ratio, throughput, end-to-end delay, normalized routing load, energy consumption, and network lifetime. The results indicate that the proposed protocol improves total energy consumption by 18.76% and 10.89% when compared to EERR-RLFL and AMCRP respectively. Meanwhile, SEAR reduces the average end-to-end delay by 17% and 9%, packet loss ratio by 29.48% and 17.69%, and normalized routing load by 31.17% and 20.91%. Additionally, SEAR achieves up to 16% and 9.71% higher throughput compared to EERR-RLFL and AMCRP routing protocols respectively. Overall, the results obtained indicate that the proposed SEAR routing scheme significantly enhances the overall performance of the network. [ABSTRACT FROM AUTHOR]

Wireless body area networks (WBANs) are an emerging field in the domain of healthcare which are typically composed of biomedical sensors. These sensors are implanted inside or attached to the human body for monitoring a patient's condition and providing accurate treatment to patients. In WBANs, energy efficiency is a critical concern due to the restricted battery capacity of the sensors. Extending the network lifetime and reducing the energy consumption of these sensor nodes can significantly impact the reliability and effectiveness of WBANs in monitoring patients' health. An efficient routing protocol based on energy-related parameters is crucial in designing these networks. Although many routing protocols have been proposed for routing in WBANs, sufficient features have not been properly handled in these methods. To overcome these issues, a novel routing protocol named Simple Energy Efficient and Bandwidth Aware (SEBA) routing protocol is proposed for routing in WBANs. The proposed scheme considers multiple metrics of the network node, such as remaining energy, energy harvesting, draining rate energy, available bandwidth, and number of hops in a route selection to minimize energy consumption, increase network lifetimes, and enhance the reliability of data transmission in WBANs. Additionally, the SEBA uses a novel mechanism to change the route dynamically based on energy consumption. This mechanism plays a significant role in reducing the number of route errors, route discoveries, and distributing energy consumption among sensor nodes. The experimental results reveal that the proposed scheme performs well in terms of average network throughput, packet delivery ratio, normalized routing load, average end-to-end delay, energy consumption, and network lifetime compared with the existing AMCRP, EEMP, and EAR protocols. [ABSTRACT FROM AUTHOR]

Recently, wireless sensor networks have been widely used for environmental and structural safety monitoring. However, node batteries cannot be replaced or easily recharged in harsh environments. Maximizing network lifetime remains a challenging issue in designing WSN routing. This paper introduces GTIACO, a novel metaheuristic clustering protocol. It employs an optimal cluster head function to determine cluster number and utilizes game theory for selecting optimal cluster heads. To optimize inter-cluster routing, improved ant colony optimization (ACO) is introduced to construct gathering paths from clusters to the base station. Both blind pathways, pheromone concentration, and angle factors are considered to improve path exploration and transmission efficiency in ant colonies. To assess network performance, various scenarios involving different base station placements and network densities are examined. Experimental results demonstrate GTIACO's superiority over LEACH, ACO, SEP, and PRESPE protocols in network lifetime, stability, energy, and throughput. The proposed GTIACO shows an improvement of at least 4.3% in network lifetime and 32.8% in network throughout. It exhibits superior stability and transmission efficiency across diverse network densities. [ABSTRACT FROM AUTHOR]

The growing ubiquity of Internet of Things (IoT) devices within smart homes demands the use of advanced strategies in IoT implementation, with an emphasis on energy efficiency and security. The incorporation of Artificial Intelligence (AI) within the IoT framework improves the overall efficiency of the network. An inefficient mechanism of parent selection at the network layer of IoT causes energy drain in the nodes, particularly near the sink node. As a result, nodes die earlier, causing network holes that further increase the control message overhead as well as the energy consumption of the network, compromising network security. This research introduces an AI‐based approach to parent selection of the Routing Protocol for Low Power and Lossy networks (RPL) at the network layer of IoT to enhance security and energy efficiency. A novel objective function, named Energy and Parent Load Objective Function (EA‐EPL), is also proposed that considers the composite metrics, including energy and parent load. Extensive experiments are conducted to assess EA‐EPL against OF0 and MRHOF algorithms. Experimental results show that EA‐EPL outperformed these algorithms in improving energy efficiency, network stability, and packet delivery ratio. The results also demonstrate a significant enhancement in the overall efficiency of IoT networks and increased security in smart home environments. [ABSTRACT FROM AUTHOR]

Mobile ad hoc networks (MANETs) face inherent challenges in maintaining reliable data transmission because of their dynamic and unpredictable nature. This research conducts a comprehensive reliability analysis of data transmission in MANETs, emphasizing the influence of dynamic conditions such as node mobility, changing network topologies, and fluctuating channel conditions. Through the utilization of mathematical models and simulations, the study assesses the overall reliability of data transmission, considering scenarios with diverse node densities, mobility patterns, and network sizes. Existing routing protocols, error correction mechanisms, and adaptive transmission strategies are examined for their effectiveness in reducing the impact of dynamic conditions on reliability. The research not only examines the current state of protocols but also explores potential enhancements and introduces novel approaches to enhance data transmission reliability under dynamic conditions. The findings offer a nuanced understanding of the challenges and opportunities related to reliable communication in MANETs. This research provides crucial insights for designing resilient communication systems in dynamic and mobile network scenarios, offering valuable guidance to researchers, network designers, and practitioners involved in optimizing the performance of MANETs in real-world applications. [ABSTRACT FROM AUTHOR]

A wireless sensor network is a wireless communication network, and each sensor node has several sensors to collect environmental information. Wireless sensor network nodes have limited energy resources and need optimal routing protocols to reduce energy consumption. Failure to reduce energy consumption by sensor nodes reduces network life and efficiency. The main problem in routing is finding optimal paths for sending packets by reducing energy consumption in sensor nodes. This paper proposes an optimal routing method to reduce energy consumption in wireless sensor networks. In the first step, wireless sensor nodes are clustered with the Water strider algorithms (WSA), and cluster heads are selected for routing. In the second step, a mobile sink collects the packets from the cluster heads and sends them to the base station. The mobile sink uses the Ant colony optimization (ACO) algorithms to travel a shorter path between the cluster heads. The authors contribute to presenting a discrete version of the WSA algorithm for cluster head selection to reduce energy consumption. The authors contribute by providing a more comprehensive objective function for clustering network nodes considering error rate, energy consumption, PDR rate, and Euclidean distance. Cluster head traversal with a version of the ACO algorithm to reduce energy consumption and cluster head traversal coding like the TSP problem is the contribution of other authors. The paper aims to reduce energy consumption, reduce the error rate of sending packets and increase the lifetime of the wireless sensor network. Experiments are simulated on several simulated scenarios in Matlab. Criteria such as energy consumption, Packet delivery ratio (PDR), package loss rates, and the number of alive nodes to evaluate the proposed method are used. Experiments show that the proposed algorithm reduces the energy consumption and loss rates of packages of the wireless sensor network by optimally selecting cluster heads and increasing the PDR and number of alive nodes. Comparisons show In terms of energy consumption, Packet delivery ratio (PDR), Loss rates of packages, and the number of alive nodes, the proposed method is more efficient than Particle swarm optimization (PSO), Grey Wolf Optimizer (GWO), Information-centric wireless sensor networks, and Cluster based routing (CBR) routing methods. The PDR index in the proposed method is equal to 97.3% and is higher than PSO, GWO, and CS algorithms. The delay of the proposed method in routing is 25.97%, 5.78%, and 17.98% less than HHO, WOA, and GWO algorithms, respectively. [ABSTRACT FROM AUTHOR]

5 G wireless sensor network is a network of sensors that can collect data on its own and can be set up anywhere.The most important goals for designing a WSN are to save energy and keep data transfers safe. As workstation networks get more complicated, researchers from a wide range of fields are starting to pay attention to the rise of network-based threats. In this paper IDS automation is made to help get back to energy-efficient routing in wireless sensor networks for security aspect. In the planned network model, particle swarm optimization is used to find weaknesses and transfer data securely along a different or better route. Best-path routing was used to put a wireless sensor network that had been controlled in different ways back together again (such as power expenditure, capacity, network life, active nodes and dead nodes). The simulation result shows that the proposed protocol give better result in terms of energy efficiency, throughput and packet delivery ratio as compared to the other traditional protocols. [ABSTRACT FROM AUTHOR]

Wireless sensor network (WSN) is widely used for field data acquisition and monitoring in different domains. To make this type of network functional, efficient routing protocols must be implemented. Nevertheless, WSNs have an energy constraint due to limited batteries. Many clustered protocols are proposed to overcome it. However, the implementation of these protocols would be difficult to understand without a simulation tool, as some problems may arise during their development. Testing real-world applications requires a lot of effort and cost because they often use many nodes in large networks. Therefore, the simulation tool is the most relative way to evaluate these protocols. This paper presents graphical-based cluster protocols simulation interface for WSN (GCPS-WSN), a new interface to simulate some clustered protocols in WSNs. GCPS-WSN allows the user to evaluate the performance of certain low energy adaptive clustering hierarchy (LEACH) enhanced protocols to choose the most appropriate one for his system. The user can simulate protocols without any knowledge of software programming. [ABSTRACT FROM AUTHOR]

Wireless sensor network is a collection of numerous compatible sensor nodes which are deployed in a random manner to study the phenomena for variety of applications such as disaster management, environment and medical monitoring. The energy consumption is an important challenge in WSN. Many protocols are developed to enhance the energy management of which cluster based protocols play a vital role in solving the problem of efficient energy utilization. In order to achieve the better energy management, we have proposed a novel protocol energy efficient clustering and aggregator node selection (EECAS) for better data gathering and longevity of the network. The aggregator node (AGN) is selected based on node which is having minimum distance between node and base station. The cluster head selection is based on Energy efficient cluster head selection algorithm which considers the highest residual energy, high probability weight and minimum distance between chosen node and AGN. The proposed protocol considers transmission cost, optimal energy consumption among cluster head and AGN. The simulation results have shown that the performance of EECAS is better than the existing algorithms such as energy efficient cluster head rotation and relay node selection, energy aware and density based clustering and relaying protocol and improved energy efficient energy adaptive clustering hierarchy with respect to the number of alive nodes, average residual energy and total number of packets received by base station. [ABSTRACT FROM AUTHOR]

Medical breakthroughs are currently being made to widen human beings' existence. For the vast majority of online medical care applications, Wireless Body Area Networks (WBANs) have emerged as an intriguing and important invention. Route loss and obstacles in offering essential information are significant criteria that drain power from the battery source and impair battery lifespan. By employing Optimal K-Means Clustering (OKMC), all body sensor nodes are positioned in tandem to construct cluster head selection. This research explores a novel metaheuristic method for strengthening network lifetime optimization and a sophisticated route selection strategy incorporating the Energy Enrichment Multi-Hop Routing (EEMR) protocol. The EEMR is intended to operate in a pair of phases. The Enhanced Flower Bee Optimisation Algorithm (EFBOA) is laid out as the initial phase, with the key objective of augmenting the network lifetime of the WBAN by laying down a network of clusters. The next phase employs Dynamic Local Hunting and Location Discarding (DLH-LD) to figure out the fastest route among all possible paths. The results of this analysis are validated and implemented in real-time using MATLAB and the Network Simulator. Various protocols, such as Mobility-supporting Adaptive Threshold-based Thermal-aware Energy-efficient Multi-hop Protocol (M-ATTEMPT), Even Energy Utilization Convention Routing (EECR), and Energy Mindful Posterior Routing (EMPR), are being compared to parameters such as path loss, throughput rate, energy consumption, cost estimation, and network lifetime. The outcomes revealed that, in comparison with conventional approaches, the suggested EEMR performs substantially better than existing routing protocols, spanning a range of performance indicators. Additionally, the research and simulation findings show that the suggested protocol is 30% more energy efficient than existing protocols, extending the life of the network. The numerical results exhibit an extensive performance enhancement of 95% in network throughput rate. [ABSTRACT FROM AUTHOR]

Data compression and optimal path discovery for data communication are vital for enhancing energy efficiency in wireless sensor networks (WSNs), crucial for their sustainability due to limited power resources. This study proposes a strategy that combines data compression and routing to optimize energy in WSNs. It is based on a Bio-Inspired Ant-Cuckoo optimized Relay-based Energy Efficient Data Aggregation (BACREED) algorithm which leverages both Ant Colony Optimization (ACO) and Cuckoo Search (CS) algorithms to enhance communication efficiency between cluster leads (CLs) and the destination node through a forwarding node. Comparative evaluation against Low Energy Adaptive Clustering Hierarchy (LEACH) and its variants, Genetic Algorithm Data Aggregation, Ant optimized using Energy Efficient Data aggregation, and Bio-inspired Ant Cuckoo Energy Efficient Data aggregation demonstrate superior performance in energy efficiency, throughput, and network longevity. This work integrates ‘Fast and Efficient Lossless Adaptive Compression Scheme with Outlier Detection and Replacement (FELACS-ODR) data compression algorithm with CS to improve network performance in terms of energy efficiency and optimal path discovery. Simulation results using MATLAB exhibit a path length reduction of 84 % for the proposed algorithm compared to a 73 % rate for the baseline algorithm with an optimal cluster-lead count between 40 to 80. Energy consumption increases slowly with data compression, significantly outperforming rapid increase scenarios without compression, particularly evident as the node count increases from 1100 and 200 nodes respectively. This research underscores the potential of leveraging FELACS-ODR and CS techniques for substantial enhancements in WSN energy efficiency.

Named data networking (NDN) is a novel network architecture that revolves around information-centric principles. In order to acquire global routing information within the network, typical NDN routing protocols rely on data synchronization mechanisms to achieve global routing updates. However, such synchronization protocols operate at the application layer, which introduces challenges in dynamic network environments, such as high costs associated with network information updates and limited ability to perceive network dynamics. To address these issues, this paper designs and implements a lightweight named-binding routing protocol (NBRP). This approach binds routing node names with their published content names, enabling routing nodes to make targeted requests for routing update information without requiring additional synchronization protocols, thus achieving lightweight routing information exchange. To further reduce the transmission costs of routing updates, this paper introduces a reusable routing information packet naming format and a routing information incremental transmission mechanism. Additionally, to validate the effectiveness of the proposed solution, corresponding functional modules are implemented and tested within the Linux kernel. Experimental results demonstrate that, in dynamic network environments, compared with traditional NDN link-state routing protocols, the proposed method can reduce routing update synchronization costs by 72% and increase link-state awareness and response speed by nearly twofold.

Existing routing protocols without awareness of the topology causes excessive retransmissions, energy holes, and long delay, data routing performance was seriously deteriorated.Considering the relation of topology and routing, an intelligent route planning with jointing topology control (IRPJTC) method was proposed.IRPJTC consisted of two part, the virtual force-based adaptive topology control (VFATC), and the PPO-based geographic routing protocol (PPO-GRP).Based on neighbor’s mobility information, the distance between UAVs was adaptively adjusted by VFATC to provide stable links between UAVs.Combined with link stability metric in VFATC, end-to-end delay and energy consumption, a multi-objective reward function was designed by PPO-GRP to train optimal routing strategy.According to the performance study, the proposed IRPJTC reduces existing routing protocols by 12.11% of end-to-end delay, and 4.56% of energy consumption, and has a better energy balance ability.

Abstract Biosensor nodes of a wireless body area network (WBAN) transmit physiological parameter data to a central hub node, spending a substantial portion of their energy. Therefore, it is crucial to determine an optimal location for hub placement to minimize node energy consumption in data transmission. Existing methods determine the optimal hub location by sequentially placing the hub at multiple random locations within the WBAN. Performance measures like link reliability or overall node energy consumption in data transmission are estimated for each hub location. The best-performing location is finally selected for hub placement. Such methods are time-consuming. Moreover, the involvement of other nodes in the process of hub placement results in an undesirable loss of network energy. This paper shows the whale optimization algorithm (WOA)-based hub placement scheme. This scheme directly gives the best location for the hub in the least amount of time and with the least amount of help from other nodes. The presented scheme incorporates a population of candidate solutions called "whale search agents". These agents carry out the iterative steps of encircling the prey (identifying the best candidate solution), bubble-net feeding (exploitation phase), and random prey search (exploration phase). The WOA-based model eventually converges into an optimized solution that determines the optimal location for hub placement. The resultant hub location minimizes the overall amount of energy consumed by the WBAN nodes for data transmission, which ultimately results in an elongated lifespan of WBAN operation. The results show that the proposed WOA-based hub placement scheme outperforms various state-of-the-art related WBAN protocols by achieving a network lifetime of 8937 data transmission rounds with 93.8% network throughput and 9.74 ms network latency.

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Advancements in the Internet of things (IoT) make a way for medical devices to coordinate in an environment that is the Internet of Medical Things (IoMT). In IoMT, some dedicated health monitoring devices are coordinated in an environment to accomplish a specified task. In this sector, patient information is periodically collected for early diagnosis of diseases. Various wearable sensors have been developed for smart sensing in the IoMT meanwhile, the sensed data are forwarded to the smart data collecting devices. Besides the advantages of remote monitoring and lower healthcare cost in IoT-based health monitoring systems, intrusion can occur during data transmission. Moreover, the large energy consumption of devices will result in higher system costs. An energy-efficient data routing protocol is developed in this area to cater to these issues. A swarm intelligence based approach is one of the most prominent methods for energy efficient routing of the data in IoT. The major goal of this paper is to provide deep insight into the lightweight, secure energy efficient routing protocol in IoMT. Furthermore, the limitations of existing methodologies are outlined. [ABSTRACT FROM AUTHOR]

The advancement in the research of wireless network technology, paved the way for the advent of Flying Ad hoc Network (FANET). FANET is formed with a team of unmanned flying nodes, termed as Unmanned Ariel Vehicle (UAV). UAV is highly mobile in nature. This dynamicity may increase difficulty in establishing connection between the nodes. Thus, in turn, increases the chances of having a higher rate of unsuccessful data transfers. An efficient routing protocol is the only solution for the problem. The goal of a routing protocol is to obtain more successful data transfers. Its design methodology mainly focuses on detecting the most stable neighboring hops so that a stable path can be obtained for data transfer. The establishment of a stable path, also, depends on the factor of noise. More the degree of noise, lesser the stability. So, detection of noise is also an important factor. But, after a thorough study of the present routing protocols, it is observed that most of them do not focus much on the detection of noise. In this research article, a novel routing protocol, Q-FANETGS-BS is presented. The mentioned protocol is a six-state model which bears an improvised noise detection component, which helps in obtaining a stable path with higher capacity, for carrying the data. This, in turn, increases the performance of the FANET in terms of throughput, end-to-end delay and jitter. [ABSTRACT FROM AUTHOR]

Wireless multimedia sensor networks (WMSNs) have characteristics that may influence the routing decisions, such as limited energy resources, storage and computing capacity. Therefore, a routing optimization needs to be done to match the characteristics of the WMSNs. Existing routing protocols only consider energy efficiency regardless of energy threshold, maximum energy, and link cost collectively as the primary basis of routing. In this work, the energy-efficient dynamic programming (EEDP) protocol is proposed to optimize routing decisions that take into account the energy threshold, the maximum energy, and the link cost. Then, the protocol is compared with the dynamic programming (DP), and the ant colony optimization (ACO) protocol. The simulation results show that the EEDP protocol can improve energy efficiency of nodes and network lifetime of the WMSNs. Then, the EEDP protocol is also implemented into a network topology of 10 NodeMCU ESP32 devices. As a result, the EEDP protocol can work very well by selecting routes based on nodes that have the remaining energy above 50 and has the shortest distance. The average delay in sending data for the entire route for the 10 iterations of sending data is 3.99 seconds. [ABSTRACT FROM AUTHOR]

Generally, Wireless Body Area Networks (WBANs) are regarded as the collection of small sensor devices that are effectively implanted or embedded into the human body. Moreover, the nodes included in the WBAN have large resource constraints. Hence, reliable and energy-efficient data transmission plays a significant role in the implementation and in constructing of most of the merging applications. Regarded to complicated channel environment, limited power supply, as well as varying link connectivity has made the construction of WBANs routing protocol become difficult. In order to provide the routing protocol in a high energy-efficient manner, a new approach is suggested using hybrid meta-heuristic development. Initially, all the sensor nodes in WBAN are considered for experimentation. In general, the WBAN is comprised of mobile nodes as well as fixed sensor nodes. Since the existing models are ineffective to achieve high energy efficiency, the new routing protocol is developed by proposing the Hybrid Tunicate-Whale Swarm Optimization (HT-WSO) algorithm. Subsequently, the proposed work considers the multiple constraints for deriving the objective function. The network efficiency is analyzed using the objective function that is formulated by distance, hop count, energy, path loss, and load and packet loss ratio. To attain the optimum value, the HT-WSO derived from Tunicate Swarm Algorithm (TSA) and Whale Optimization Algorithm (WOA) is employed. In the end, the ability of the working model is estimated by diverse parameters and compared with existing traditional approaches. The simulation outcome of the designed method achieves 13.3%, 23.5%, 25.7%, and 27.7% improved performance than DHOA, Jaya, TSA, and WOA. Thus, the results illustrate that the recommended protocol attains better energy efficiency over WBANs. [ABSTRACT FROM AUTHOR]

In situations where a regular network may not be appropriate or is unable to function correctly, data collection and real-time transmission are commonly done using Wireless Sensor Networks (WSNs). In order to accomplish this type of operation, the network's durability and performance are extremely vital. One of the key elements that directly affect a network's lifespan and performance is the routing protocol. This study proposes a Geographic Forwarding Energy Efficient Routing Protocol (GF-EERP), an enhanced version of the Geographic Energy Aware Routing (GEAR) protocol that helps to extend the network's lifespan and performance. The introduction of node categorization, a unique technique for choosing the region head, use of multi-hop communication method and removal of dead nodes serve as the foundation of the GF-EERP. In this study, the proposed protocol's performance is also compared to other protocols already in use, like Geographic Adaptive Fidelity (GAF), Geographic Energy Aware Routing (GEAR), Greedy Perimeter Stateless Routing (GPSR) and Multihop-Geographic Energy Aware Routing (M-GEAR), using a variety of performance metrics including Network Delay, Data Delivery Ratio and Network Throughput. The simulation outcomes prove that the performance of GF-EERP, with its distinct node categorization and region head selection mechanism is superior to the existing protocols. [ABSTRACT FROM AUTHOR]