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Real-time status monitoring is crucial in ensuring the safety of railway tunnel traffic. The primary monitoring method currently involves deploying sensors to form a Wireless Sensor Network (WSN). Due to the linear characteristics of railway tunnels, the resulting sensor networks usually have a linear topology known as a thick Linear Wireless Sensor Network (LWSN). In practice, sensors are deployed randomly within the area, and to balance the energy consumption among nodes and extend the network's lifespan, this paper proposes a self-organizing network and routing method based on thick LWSNs. This method can discover the topology, form the network from randomly deployed sensor nodes, establish adjacency relationships, and automatically form clusters using a timing mechanism. In the routing, considering the cluster heads' load, residual energy, and the distance to the sink node, the optimal next-hop cluster head is selected to minimize energy disparity among nodes. Simulation experiments demonstrate that this method has significant advantages in balancing network energy and extending network lifespan for LWSNs. [ABSTRACT FROM AUTHOR]

In this work, the concept of peer-to-peer energy sharing in wildlife communication systems is explored. In this context, wild animals can share energy wirelessly besides their data communications as they opportunistically come into range of each other. Our goal is to find a way to balance the energy among the nodes and minimize this energy loss. We propose a novel encounter-based energy-sharing scheme, called EBES, that utilizes single and multi-hop transmission to achieve energy balance, minimize energy losses, and maximize the lifetime of the wildlife communication system. EBES is based on a variety of parameters, including the amount of energy left in the system and the nodes' encounter rate, and buffer sizes. In the simulation studies, we considered a wildlife communication network that is involved in data communication and applied EBES over the opportunistic routing protocols such as EBR, Spray&Wait, and Epidemic resulting in a network lifetime increase of 35% and improving the routing protocols performance. Additionally, we compared EBES with the other well-known energy balancing techniques that also contribute to data communication such as EA-Epidemic, EERPFAnt, and OE-OLSR and the results show the remaining energy was improved by 31%, 26%, and 15%, respectively. [ABSTRACT FROM AUTHOR]

In existing schemes, there has been no analysis or steps built for balancing data integrity and energy consumption of clusters in the network, and providing security in WSN is difficult. In this research work, to overcome these troubles, we have used a Query-based Location-Aware Secure Multicast Routing for Wireless Sensor Networks (QLAMSR) is proposed to attain energy efficiency and security. There are three modules involved here. The first module is about the network model and the system overview to obtain more network lifetime. In the second module, an advanced encryption standard and RC6 algorithms is used here to provide authentication and data integrity. In the third module, efficient energy routes are established and demonstrated to illustrate network reliability. Node trust and reliable route energy efficiency are calculated to produce efficient data integrity through the idea of a fuzzy decision model. The proposed protocol is simulated with the Network Simulator tool (NS 2.34) to analyze the network performance metrics and finally its shown that proposed QLAMSR attains route energy efficiency by 39–92% and data integrity rate by 18–89(packets/sec). [ABSTRACT FROM AUTHOR]

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Copyright of Journal of Chongqing University of Posts & Telecommunications (Natural Science Edition) is the property of Chongqing University of Posts & Telecommunications 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.)

Delay Tolerant Network (DTN) provides communication in environments composed of nodes with heterogeneous characteristics such as frequent disconnections, limited transmission range, dynamic topology, and scarce resources. Data delivery is achieved via the mobility of nodes by employing multi-copy protocols in which each node is allowed to create and transmit multiple copies of each message. The data is delivered at a higher consumption of node energy, buffer space, and network bandwidth. Similarly, buffer space is a critical resource to store and carry messages. Effective management can reduce message drops and increase delivery rate. The existing techniques observe message transmissions to evaluate energy consumption and basic buffer management policies to overcome congestion. In this paper, we have proposed an Energy Estimation based Routing Protocol (EERP) in which instead of number of transmissions the energy quota has been assigned to each message. In addition, buffer management of DTN node has been considered more critical. Therefore, we have proposed a buffer management policy in which messages are dropped based on their level of energy consumption. The simulation results prove that the proposed EERP has performed better in terms of increasing delivery ratio, buffer time average, and reducing message transmission, drop, and hop count average. [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: In wireless sensor networks (WSNs), routing based on cluster construction is highly preferred as it greatly supports reliable data communication, load balancing, and fault tolerance with extended network lifetime. In specific, metaheuristic approach‐based dynamic cluster heads (CHs) selection has the possibility of enhancing the lifespan of network and at the same time is capable in reducing the energy consumption. In this paper, hybrid grasshopper and Harris hawk optimization algorithm‐based energy efficient routing protocol (HGHHOA) is propounded for optimal CH selection. This proposed HGHHOA approach adopted a fitness function that incorporated the factors of residual energy, distance between CH and cluster members, distance between selected CHs and the sink, node centrality, and node degree into account. The fitness function values of optimality facilitate a potential CH selection with significant cost‐effective routing. It is proposed with primary objective of improving the network lifespan through optimized selection of CHs that balances the available energy in a predominant way. It is proposed with significance of handling premature convergence with minimized energy consumption and network lifetime through the possibility of establishing an ideal balance between number of alive and dead nodes. The results of this proposed HGHHOA approach with varying rounds of implementation exhibited better results in throughput and residual energy which is 23.98% and 29.21%, better than the bassline CH selection mechanisms. [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 In this manuscript, a nature‐inspired optimization method, named transient search optimization (TSO), is proposed. Energy‐based monetary custom is a serious issue on the wireless sensor network (WSN). Here, the network clustering is an effectual technique to reduce node energy depletion and increased network lifetime. The proposed method aims to improve the efficiency of sensor nodes (SNs) by reducing their detachment, minimizing energy transmission, and protecting excessive energy stored in the nodes. This approach helps decrease delays, reduce traffic flow, and optimize network performance. The execution is implemented on the NS2 software. The experimental outcomes exhibit that the proposed system performs better based on two wireless sensor architectures, such as 50 nodes and 100 nodes. The parameter produces 52.24%, 54.38%, and 56.37% better network lifetime; 44.71%, 46.24%, and 49.45% higher alive node; and 39.26%, 36.26%, and 28.65% lesser dead SNs compared with existing techniques like multi‐objective cluster head (CH)–based energy‐aware optimized routing approach in wireless sensor network (MOCH‐ORR‐WSN), energy effective CH selection with improved sparrow search algorithm in WSN (ECH‐ISS‐WSN), and energy effectual cluster basis routing protocol under butterfly optimization along ant colony optimization algorithms for WSN (EEC‐BOA‐ACO‐WSN). [ABSTRACT FROM AUTHOR]

Mobile Ad-hoc Networks (MANETs) are used in a wide range of applications because of their unique capabilities. The routing in MANET is regarded as a main challenge on account of its permanent movement and nodes' randomness that can cause a continual change of network topology, thus finding correct paths among the nodes is the fundamental task of routing protocols. There is a rise in protocols that depend on cross-layer communication across several layers to increase the MANET performance. In this manuscript, a Hybrid Clustering Approach (SG-MFOA) using a Multipath Cross-Layer Design in a MANET Network is proposed. Here, multiple routes are selected for data packet transmission with the help of hybrid routing. Furthermore, a cross-layer metric is acquired depending upon Expected Transmission Time (ETT), Residual Energy and Load Balancing Factor. It is necessary to select a Cluster Head (CH) depending on this trade for proficient routing. So, the cluster head is optimally chosen to utilize SG-MFOA. Thus, the multipath route selection is performed by the multi-objective functions containing bandwidth, congestion delay, transmission delay and to ensure the prolonging of network lifetime, queue delay at each connection Access Category from the available routes to a destination. When compared with the existing methods, like a proficient self-attention-based conditional variational auto-encoder generative adversarial networks-based multipath cross-layer design routing paradigm for MANET (SCVAGAN-MCDR-MANET), Energy Aware Cross Layer Routing Protocol to Increase Route Reliability in MANETs (EACLRP-RR-MANET), Cross-layer Adaptive Fuzzy-based Ad hoc On-Demand Distance Vector Routing Protocol for MANET (CLAF-DVRP-MANET), respectively. [ABSTRACT FROM AUTHOR]

Unmanned aerial vehicle (UAV) clusters offer significant potential in civil, military, and commercial fields due to their flexibility and cooperative capabilities. However, characteristics such as dynamic topology and limited energy storage bring challenges to the design of routing protocols for UAV networks. This study leverages the Deep Double Q-Learning Network (DDQN) algorithm to optimize the traditional Greedy Perimeter Stateless Routing (GPSR) protocol, resulting in a multi-objective optimized GPSR routing protocol (DDQN-MTGPSR). By constructing a multi-objective routing optimization model through cross-layer data fusion, the proposed approach aims to enhance UAV network communication performance comprehensively. In addition, this study develops the above DDQN-MTGPSR intelligent routing algorithm based on the NS-3 platform and uses an artificial intelligence framework. In order to verify the effectiveness of the DDQN-MTGPSR algorithm, it is simulated and compared with the traditional ad hoc routing protocols, and the experimental results show that compared with the GPSR protocol, the DDQN-MTGPSR has achieved significant optimization in the key metrics such as the average end-to-end delay, packet delivery rate, node average residual energy variance and percentage of node average residual energy. In high dynamic scenarios, the above indicators were optimized by 20.05%, 12.72%, 0.47%, and 50.15%, respectively, while optimizing 36.31%, 26.26%, 8.709%, and 69.3% in large-scale scenarios, respectively. [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]

The increasing demand for efficient data transmission in wireless networks, such as mobile ad-hoc networks (MANETs) and vehicular ad-hoc networks (VANETs), presents significant challenges in maintaining reliable communication and minimizing energy consumption. Traditional routing protocols often fail to adapt dynamically to varying network conditions, leading to suboptimal performance and increased latency. To address these limitations, this study introduces an AI-enhanced Position Assisted Routing Protocol (PARP) designed for efficient data transmission in wireless networks. The proposed protocol leverages machine learning algorithms, specifically deep reinforcement learning (DRL), to optimize routing decisions based on real-time network conditions and node positions. The PARP integrates position-based information with AI-driven prediction models to proactively determine the optimal routing paths, thus reducing packet loss and improving transmission efficiency. Extensive simulations were conducted using the NS-3 simulator to evaluate the performance of the AI-enhanced PARP against existing protocols such as AODV and DSR. The results demonstrate a significant improvement in key performance metrics: packet delivery ratio increased by 23%, average end-to-end delay reduced by 35%, and network throughput improved by 28% compared to conventional protocols. Additionally, the proposed protocol achieved a 15% reduction in energy consumption, highlighting its suitability for energy-constrained wireless networks. These findings indicate that the AI-enhanced PARP can dynamically adapt to network changes, providing a robust and efficient solution for data transmission in various wireless network scenarios. Future research will focus on incorporating additional environmental factors, such as interference and mobility patterns, to further enhance the protocol's adaptability and performance. [ABSTRACT FROM AUTHOR]

Some challenges when implementing the optimized link state routing (OLSR) protocol on real-life devices and simulators are unmanageable: link quality, rapid energy depletion, and high processor loads. The causes of these challenges are link state processing, unsuitable multipoint relay (MPR) nodes, and information base maintenance. This paper proposes a structured, energy-efficient link sensing and database maintenance technique. The improved OLSR in the paper replaces the OLSRv2's HELLO, HELLO, and Topology Control (TC) message sequence with a new sequence. MPR nodes are not mandated to broadcast TC messages if the number of nodes and their OLSRv2 addresses remain unchanged after subsequent broadcasts or if no node reported 2-hop symmetric connections. The paper further proposes an MPR selection technique that considers four parameters: node battery level, mobility speed, node degree, and connection to the base station for optimum relay selection. It combines the four parameters into one metric to reduce energy dissipation and control routing overhead. The modifications were implemented in NS-3, and the simulation results show that our improved OLSR outperforms the existing OLSR, OLSRv2 and other improved routing protocols in energy consumption, routing overhead, the packet delivery ratio and end-to-end delay, as compared to the related literature. [ABSTRACT FROM AUTHOR]

The purpose of this study is to evaluate and compare how well different routing protocols perform in terms of load sharing, link failover, and overall network performance. Wireshark was used for packet-level analysis, VMWare was used for virtualization, GNS3 was used for network simulation, and Iperf3 was used to measure network performance parameters. Convergence time, packet losses, network jitter, and network delay are the parameters that were selected for assessment. To examine the behaviors of Open Shortest Path First (OSPF) and Enhanced Interior Gateway Routing Protocol (EIGRP) routing protocols in a variety of network settings, a simulated network environment incorporating both protocols along with Border Gateway Protocol (BGP) is created for the research. The setup for the experiment entails simulating different network conditions, such as fluctuating traffic loads and connection failures, to track how the protocols function in dynamic situations. The efficiency metrics for OSPF and EIGRP with BGP are measured and evaluated using the data generated by Wireshark and Iperf3. The results of this research show that EIGRP has a better failover convergence time and packet loss percentage as compared to the OSPF. [ABSTRACT FROM AUTHOR]

Routing in vehicular ad hoc networks (VANETs) enables vehicles to communicate for safety and non-safety applications. However, there are limitations in wireless communication that can degrade VANET performance, so it is crucial to optimize the operation of routing protocols to address this. Various routing protocols employed the expected transmission count (ETX) in their operation as one way to achieve the required efficiency and robustness. ETX is used to estimate link quality for improved route selection. While some studies have evaluated the utilization of ETX in specific protocols, they lack a comprehensive analysis across protocols under varied network conditions. This research provides a comprehensive comparative evaluation of ETX-based routing protocols for VANETs using the nomadic community mobility model. It covers a foundational routing protocol, ad hoc on-demand distance vector (AODV), as well as newer variants that utilize ETX, lightweight ETX (LETX), and power-based light reverse ETX (PLR-ETX), which are referred to herein as AODV-ETX, AODV-LETX, and AODV-PLR, respectively. The protocols are thoroughly analyzed via ns-3 simulations under different traffic and mobility scenarios. Our evaluation model considers five performance parameters including throughput, routing overhead, end-to-end delay, packet loss, and underutilization ratio. The analysis provides insight into designing robust and adaptive ETX routing for VANET to better serve emerging intelligent transportation system applications through a better understanding of protocol performance under different network conditions. The key findings show that ETX-optimized routing can provide significant performance enhancements in terms of end-to-end delay, throughput, routing overhead, packet loss and underutilization ratio. The extensive simulations demonstrated that AODV-PLR outperforms its counterparts AODV-ETX and AODV-LETX and the foundational AODV routing protocol across the performance metrics. [ABSTRACT FROM AUTHOR]

Research on wireless body area networks (WBAN), also known as wireless body sensor networks (WBSN), has been increasingly important in medical applications recently and is now crucial for patient monitoring. To create a dependable body area network (BAN) system, several factors need to be considered at both the software and hardware levels. One such factor is the designing and implementation of routing protocols in the network layers. Protocols for routing can detect and manage the routing paths in a network to facilitate efficient data transmission between nodes. Therefore, the routing protocol is crucial in wireless sensor networks (WSN) to provide dependable communication among the sensor nodes. Different clustering methods can be used in WBAN systems. However, these techniques often produce many cluster heads (CHs), which leads to higher energy consumption. Increased consumption of energy reduces the lifespan of WBANs and raises costs of monitoring. This research proposes a recent metaheuristic algorithm to select the optimal clusters to provide an energy-effective protocol for healthcare monitoring. This research aims to minimize the energy utilization of WBANs by choosing the most suitable CHs based on the BWO. The proposed BWO-based routing protocol demonstrates superior performance in WBANs based on energy consumption, packet loss, packet delivery ratio, network lifetime, end-to-end delay, and throughput. It optimizes energy consumption by effectively selecting CHs and routing paths, leading to balanced energy usage and prolonged network operation. The BWO model significantly reduces end-to-end delay by ensuring data packets follow the shortest and least congested routes, which is significant for real-time health monitoring. It achieves a high packet delivery ratio, typically between 95% and 98%, indicating reliable data transmission, while maintaining a low packet loss rate, generally between 1% and 5%. Additionally, the BWO-based routing protocol extends network lifetime by preventing early node depletion and enhances network throughput by reducing congestion and packet collisions, thereby supporting continuous and robust health data monitoring. [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]

Wireless sensor networks (WSNs) confront significant challenges related to battery capacity, as sensor nodes operate on limited energy resources. To address this issue, low energy adaptive clustering hierarchy (LEACH) protocol is commonly employed for power management in WSNs. LEACH is commonly used for power management. Here, sensing region is divided into clusters and sectors, placing a gateway node at the center to minimize energy consumption during data transmission. It employs one-hop, two-hop, or three-hop pathways based on node proximity to the base station (BS) to optimize energy usage. Network performance is assessed using rounds, throughput, and energy usage. MATLAB simulations compare the proposed approach with dual layer LEACH (DL-LEACH) and LEACH, showing significant improvements in network lifetime. The proposed scheme outperforms LEACH by 515% and 347% for 20% and 50% node depletion, respectively. Compared to DL-LEACH, it extends network lifetime by 27% and 59% under similar scenarios. Sectoring, clustering, and multi-hop communication reduce energy consumption, enhancing network lifetime and addressing WSN challenges effectively. [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]

The seamless integration of intelligent Internet of Things devices with conventional wireless sensor networks has revolutionized data communication for different applications, such as remote health monitoring, industrial monitoring, transportation, and smart agriculture. Efficient and reliable data routing is one of the major challenges in the Internet of Things network due to the heterogeneity of nodes. This paper presents a traffic-aware, cluster-based, and energy-efficient routing protocol that employs traffic-aware and cluster-based techniques to improve the data delivery in such networks. The proposed protocol divides the network into clusters where optimal cluster heads are selected among super and normal nodes based on their residual energies. The protocol considers multi-criteria attributes, i.e. energy, traffic load, and distance parameters to select the next hop for data delivery towards the base station. The performance of the proposed protocol is evaluated through the network simulator NS3.40. For different traffic rates, number of nodes, and different packet sizes, the proposed protocol outperformed LoRaWAN in terms of end-to-end packet delivery ratio, energy consumption, end-to-end delay, and network lifetime. For 100 nodes, the proposed protocol achieved a 13% improvement in packet delivery ratio, 10 ms improvement in delay, and 10 mJ improvement in average energy consumption over LoRaWAN. [ABSTRACT FROM AUTHOR]

In recent years, the widespread adoption of wireless sensor networks (WSN) has resulted in the growing integration of the internet of things (IoT). However, WSN encounters limitations related to energy and sensor node lifespan, making the development of an efficient routing protocol a critical concern. Cluster technology offers a promising solution to this challenge. This study introduces a novel cluster routing protocol for WSN. The system selects cluster heads and relay nodes utilizing the multi-strategy fusion snake optimizer (MSSO) and employs the minimum spanning tree algorithm for inter-cluster routing planning, thereby extending the system's lifecycle and conserving network energy. In pursuit of an optimal clustering scheme, the paper also introduces tactics involving dynamic parameter updating, adaptive alpha mutation, and bi-directional search optimization within MSSO. These techniques significantly increase the algorithm convergence speed and expand the available search space. Furthermore, a novel efficient clustering routing model for WSN is presented. The model generates different objective functions for selecting cluster heads and relay nodes, considering factors such as location, energy, base station distance, intra-cluster compactness, inter-cluster separation, and other relevant criteria. When selecting cluster heads, the fuzzy c-means (FCM) algorithm is integrated into MSSO to improve the optimization performance of the algorithm. When planning inter-cluster routing, the next hop node is selected for the relay node based on distance, residual energy, and direction.The experimental results demonstrate that the proposed protocol reduces energy consumption by at least 26.64% compared to other cluster routing protocols including LEACH, ESO, EEWC, GWO, and EECHS-ISSADE. Additionally, it increases the network lifetime of WSN by at least 25.84%, extends the stable period by at least 52.43%, and boosts the network throughput by at least 40.99%. [ABSTRACT FROM AUTHOR]

A mobile ad-hoc network (MANET) is a network of mobile nodes that dynamically form a transitory network lacking any existence of infrastructure and any form of centralized management. Nodes in ad hoc networks are powered by batteries with a limited lifespan and communicate in a restricted bandwidth. The unpredictable environment of a MANET may run into a major concern in the routing mechanism, therefore the need for a routing protocol with robust performance is still one of the key challenges in MANET deployment. In this work, a comparative comparison and extensive simulation analysis have been carried out for three major routing protocols: destination sequenced distance vector (DSDV), dynamic source routing (DSR) and ad hoc on-demand distance vector (AODV). Protocol evaluation has been extended by considering several simulation arrangements, different classes of traffic load patterns and diverse performance metrics. Based on packet rate change, node quantity and node speed, simulation scenarios were generated. Protocols were investigated against energy consumption, throughput, lost packets, routing load and packet delivery fraction for three types of traffic load patterns regular, irregular and joint traffic. DSR and AODV protocols proved to be more reliable when joint traffic was implemented when node speed and packets variations are considered. DSDV protocol verifies outstanding response over other protocols in terms of energy consumption when either regular or irregular traffic is applied. The simulation results for DSR protocol have verified the superiority over other protocols in 9 simulation scenarios when diverse metrics are considered. DSDV showed optimal performance in 7 cases, especially at low packet rates and in networks with minimum number of nodes. Similarly, AODV protocol showed outstanding performance in 6 scenarios, when higher packet rates and node mobility are considered. [ABSTRACT FROM AUTHOR]

Summary: Recently, wireless sensor networks (WSNs) have been used for monitoring, sensing, processing, and communication purposes in real‐time applications. It is employed with a routing protocol that performs an effective data transmission process. However, while transmitting large data, there occurs an over fitting issue, which leads to determining a huge data leakage. Also, the delay is increased with heavy congestion in the network. Hence, a novel method is proposed to diminish the network congestion regarding distributed networks as well as cloud edge computing. Moreover, it diminished the data loss from an overloaded condition. However, the proposed technique controls congestion that resists the traffic in the network through lightweight, ultra‐dense label‐less federation and incorporates adaptive multi‐agent Markov reinforcement learning. Furthermore, a distributed energy‐efficient delay‐aware routing protocol is employed to analyze and regulate congestion control in the network. Also, it varies the network dynamically by adjusting the routing protocol that optimizes the congestion and implements the traffic mechanism. Moreover, the congestion in WSNs overwhelms the nodes and channels distributed in the packets. The evaluation of the proposed method is determined by various metrics such as queuing delay, network lifetime, energy efficiency, throughput, and packet delivery ratio. The experimental results revealed that the proposed method attained an enhanced performance by maximizing energy efficiency and packet delivery ratio by 94% as well as 89% and reducing the delay by 55%, respectively. [ABSTRACT FROM AUTHOR]

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]

The main limitation of wireless sensor networks (WSNs) lies in their reliance on battery power. Therefore, the primary focus of the current research is to determine how to transmit data in a rational and efficient way while simultaneously extending the network's lifespan. In this paper, a hybrid of a fuzzy logic system and a quantum annealing algorithm-based clustering and routing protocol (FQA) is proposed to improve the stability of the network and minimize energy consumption. The protocol uses a fuzzy inference system (FIS) to select appropriate cluster heads (CHs). In the routing phase, we used the quantum annealing algorithm to select the optimal route from the CHs and the base station (BS). Furthermore, we defined an energy threshold to filter candidate CHs in order to save computation time. Unlike with periodic clustering, we adopted an on-demand re-clustering mechanism to perform global maintenance of the network, thereby effectively reducing the computation and overhead. The FQA was compared with FRNSEER, BOA-ACO, OAFS-IMFO, and FC-RBAT in different scenarios from the perspective of energy consumption, alive nodes, network lifetime, and throughput. According to the simulation results, the FQA outperformed all the other methods in all scenarios. [ABSTRACT FROM AUTHOR]

A wireless sensor network (WSN) consists of specialized sensor nodes that perform sensing services for Internet of Things devices with limited battery power. As the replacement or recharging of batteries is not possible, energy consumption becomes the most important design issue in WSNs. The energy‐efficient routing protocol gets the most priority in such energy‐constrained networks. The utilization of clustering‐based routing protocols like stable election protocol (SEP) has gained much attention as the network's lifetime is significantly improved due to the clustering of sensor nodes. Moreover, the inclusion of a secondary CH (SCH) is beneficial when the member node with the most remaining energy performs data aggregation and reduces the energy burden of the CH. This article characterizes SEP and Prolong SEP (P‐SEP) protocols and then extends them by incorporating SCH, which ensures balanced energy consumption. The performance of the proposed Extended SEP and Extended P‐SEP protocols has been analysed regarding stability period, network lifetime, energy usage and throughput. The simulation results demonstrate that the proposed protocols outperform state‐of‐the‐art protocols like P‐SEP, Modified SEP (M‐SEP) and SEP. In particular, the stability period of Extended SEP and Extended P‐SEP has improved up to 42% and 89%, respectively, compared to M‐SEP. [ABSTRACT FROM AUTHOR]

Energy resource limitations, data packet traffic congestion, mobility, and communication link failure of relay nodes are vital challenges in establishing a reliable and efficient path between end-to-end users in IoT Communication toward 6G. These factors can severely affect routing and network performance. Hence, it is imperative to design a routing approach to adapt to such heterogeneity to improve the quality of service (QoS) performance toward 6G networks. This paper proposes a multi-criteria-aware integrated decision-making (MCAIDeM) routing protocol in which relay nodes' residual energy, queue length, mobility, and link quality are integrated into a single routing approach for efficient and reliable route selection. In particular, the MCAIDeM routing protocol utilizes an analytic hierarchy process (AHP) approach for multi-criteria decision-making, which determines appropriate weights according to the parameter values of the nodes to select suitable relay nodes during the route selection process. Extensive simulations are performed to evaluate the performance, and the obtained simulation results showed that the proposed MCAIDeM routing protocol outperforms conventional routing protocols in terms of network throughput, latency, and energy consumption with various network parameters. The end-to-end delay obtained by MCAIDeM was 9.03% and 11.26% lower than that of MBMQA, 11.21%, and 13.67% lower than that of MEQSA-OLSRv2, and 19.15% and 16.61% lower than that of the MP-OLSRv2 routing protocols when the node speed increased from 5 m/s to 30 m/s, respectively. [ABSTRACT FROM AUTHOR]

In flying Ad hoc networks (FANETs), traditional geographic routing protocols such as greedy perimeter stateless routing (GPSR) protocol, usually adopts a periodic Hello mechanism and a greedy forwarding mechanism based on maximum advanced distance. However, the traditional periodic Hello mechanism ignores node mobility, network connectivity, and traffic type, thus causing temporary communication blindness (TCB). Additionally, the traditionally geographic routing protocols choose the next-hop node based on the maximum advanced distance. The greedy forwarding mechanism based on maximum advanced distance towards the destination ignores the impact of network dynamics on links, leading to short link lifetime and frequent link breakage. To address these problems, a novel airborne greedy geographic routing (AGGR) protocol for FANETs is proposed in this paper. It includes an adaptive Hello mechanism and a greedy forwarding mechanism based on the relative motion of nodes. In the adaptive Hello mechanism, the Hello period of working nodes is calculated according to the real-time relative characteristic values between the node and its upstream node, and the Hello period of idle nodes adopts a fixed value according to the movement characteristics relative to all neighbor nodes. In the greedy forwarding mechanism based on the relative motion of nodes, in order to adapt to the high dynamic changes of network topology, the time to enter the communication range of the destination is taken as routing criteria to choose the next-hop node. Moreover, the AGGR protocol is compared with the original GPSR in simulation. The results show that it significantly mitigates the TCB problem and gains significant improvement in network performance. [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]

In delaytolerant networks (DTN), energyefficient node operation is vital due to battery life constraints. Energy con sumption significantly impacts data forwarding, necessitating novel energyefficient routing protocols. We begin by comparing the performance of several protocols, including CASPaR, Direct Delivery, Epidemic, SprayandWait, and PRoPHETv2, using the Opportunistic Network Environment (ONE) simulator. Our findings demonstrate the superiority of CASPaR in terms of message delivery and latency. To further optimize energy usage, we propose EECASPaR, a combination of a threshold algorithm with CASPaR. EECASPaR is a singlecopy, congestionavoidance, energyefficient protocol suitable for energyconstrained applications, promoting sustainable communication. This protocol considers the remaining node energy to make informed decisions regarding message acceptance or forwarding to neighbor nodes. Through extensive simulations with varying energy thresholds, our results confirm that EECASPaR enhances remaining node energy and reduces the occurrence of dead nodes. [ABSTRACT FROM AUTHOR]

In the design of Wireless sensor networks (WSNs), maximizing network lifetime and sustaining energy stability is identified as the challenging problem since it comprises of compact sized and energy limited sensor nodes that cooperates during data routing. The existing clustering-based routing mechanisms accomplished energy efficiency and attempted to minimize the distance between the cluster head (CH) and the sink node for network lifetime improvement. The adoption of swarm intelligence algorithms and fuzzy logic is determined to the ideal computational intelligence techniques which are suitable for NP-hard problem like the multi-hop route selection process. In this paper, A Modified Dingo Optimization Algorithm-based Clustering Mechanism (MDOACM) is proposed for addressing the limitations of the clustering protocol with respect to cluster head (CH) lifetime and cluster quality. This MDOACM-based clustering protocol utilized Interval Type-2 Fuzzy Logic (IT2FL) for determining the trust level of each sensor node since the existence of an untrustworthy node introduces adverse impact on the data quality and reliability. It specifically used MDOA for achieving better clustering with balanced trade-off between the rate of exploration and exploitation such that frequent re-clustering is prevented. It effectively prevented malicious nodes with minimized energy consumption and enhanced network lifetime. It also adopted a communication system that supports the sensors in attaining the objective with reduced energy and maximized confidence level during the transmission of full exploration data. The results of MDOACM confirmed an average improvement in network lifetime of 23.18% and 25.16% with respect to different energy levels and density of sensor nodes. [ABSTRACT FROM AUTHOR]

Intelligent technology and devices have affected nearly every aspect of human lives. The type of connection and means of communication among such a huge number of devices has led to development of Internet of Things (IoT), broad sector that has considerably increased awareness of the problem of energy management and lengthened the lifespan of networks. The design of networks has been made more difficult by complex communications. In this paper, a Hybrid Multipath Routing Cluster head prediction based on software defined networking enabled IoT and Heterogeneous context-aware graph convolution network Using Eagle Swarm Optimization (SDN-IOT-HCAGCN) is proposed. In this method, cluster is formed by coati optimization and cluster head selection by Heterogeneous context-aware graph convolution network, after that Eagle Swarm Optimization is used for multipath routing. The simulations are executed in MATLAB. The proposed technique is evaluated through different metrics, likes delay, number of dead nodes, packet delivery ratio, number of alive node, energy consumption and network life time. The proposed SDN-IOT-HCAGCN model provides 34.49%, 26.44% and 20.51% highest number of alive sensor nodes, 39.45%, 22.44% and 30.24% lowest number of delay when analyzed with the existing models, like Intelligent Energy-Aware Routing Protocol in Mobile IoT depending upon SDN (SDN IEAR-IOT-SDN), Edge-based Optimal Routing in SDN-enabled Industrial Internet of Things (EOR-SDN-IOT), Cooperative Self-scheduling routing protocol basis IoT communication for increasing lifetime duty cycled energy efficient protocol in SDN controlled embedded network (CSR-IOT-SDN) respectively. [ABSTRACT FROM AUTHOR]

Vehicular Ad-hoc Networks (VANETs) have received extensive consideration from the industry and the research community because of their expanding emphasis on constructing Intelligent Transportation Systems (ITS) to enhance road safety. ITS is a collection of technologies and applications that aim to improve transportation safety and mobility while lowering the number of accidents. In VANET, routing protocols play a significant role in enhancing communication safety for the transportation system. The high mobility of nodes in VANET and inconsistent network coverage in different areas make routing a challenging task. As a result, ensuring that the VANET routing protocol has the maximum packet delivery ratio (PDR) and low latency is of utmost necessity. Due to the high dynamicity of the VANET environment, position-based routing protocols are paramount for VANET communication. VANET is subjected to frequent network disconnection due to the varied speeds of moving vehicles. Managing and controlling network connections among V2V and V2I is the most critical issue in VANET communication. Therefore, reliable routing protocols that can adapt to frequent network failures and select alternative paths are still an area to be explored further. Majorly, VANET routing protocols follow the greedy approach; once the local maximum is reached, the packets start dropping, resulting in a lower packet delivery ratio. Therefore, lower PDR is still an issue to be resolved in VANET's routing protocols. This paper investigates recent position-based routing protocols proposed for VANET communication in urban and highway scenarios. It also elaborates on topology-based routing, which was initially used in VANET, and its research gaps, which are the major reason for the advent of position-based routing techniques proposed for VANET communication by various researchers. It provides an in-depth comparison of different routing protocols based on their performance metrics and communication strategies. The paper highlights various application areas of the VANET, research challenges encountered, and possible solutions. Further, a summary and discussion on topology-based and position-based routing protocols mark the strengths, limitations, application areas, and future enhancements in this domain. [ABSTRACT FROM AUTHOR]

Simulation continues to be highly attractive and indispensable for studying networked systems. There remains the need for simulators that can support efficient execution in large-scale, complex models and can offer a theoretical underpinning with model abstractions. A qualified and effective simulator is still hard to find in education and research. To obtain a better solution in education and research, a collection of the parallel DEVS-based computer network model components is presented in this article. The Discrete Event System Specification (DEVS) is a mathematical modeling formalism for describing (discrete and continuous) dynamical systems. Among discrete event modeling approaches, it is well suited for formally describing concurrent processing and the event-driven nature of arbitrary configuration of nodes and links forming network systems. The suggested system is developed by emphasizing the Open Shortest Path First (OSPF) protocol. These expressive models are realized in the DEVS-Suite simulator as DEVS-Suite provides a robust environment with rich support for designing experiments and visualization. Visualization representation of a typical routing protocol logic with routing tables and control packet provides better support for active learning, particularly for distance education in COVID-19 disease. The resulting OSPF-DEVS simulation environment offers a model abstraction well-suited to educational environments. An exemplary computer network model is developed and evaluated in both simulators. The simulation models have proved very helpful in understanding the basics of the computer network's principles, designs, routing protocols, etc. [ABSTRACT FROM AUTHOR]

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]

Energy efficiency and data reliability are important indicators to measure network performance in wireless sensor networks. In existing research schemes of routing protocols, the impact of node coverage on the network is often ignored, and the possibility that multiple sensor nodes may sense the same spatial point is not taken into account, which results in a waste of network resources, especially in large-scale networks. Apart from that, the blindness of geographic routing in data transmission has been troubling researchers, which means that the nodes are unable to determine the validity of data transmission. In order to solve the above problems, this paper innovatively combines the routing protocol with the coverage control technique and proposes the node collaborative scheduling algorithm, which fully considers the correlation characteristics between sensor nodes to reduce the number of active working nodes and the number of packets generated, to further reduce energy consumption and network delay and improve packet delivery rate. In order to solve the problem of unreliability of geographic routing, a highly reliable link detection and repair scheme is proposed to check the communication link status and repair the invalid link, which can greatly improve the packet delivery rate and throughput of the network, and has good robustness. A large number of experiments demonstrate the effectiveness and superiority of our proposed scheme and algorithm. [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]

With the development of artificial intelligence technology, deep reinforcement learning (DRL) has become a major approach to the design of intelligent vehicle-to-everything (V2X) routing protocols for vehicular ad hoc networks (VANETs). However, if the V2X routing protocol does not consider both real-time traffic conditions and historical vehicle trajectory information, the source vehicle may not transfer its packet to the correct relay vehicles and, finally, to the destination. Thus, this kind of routing protocol fails to guarantee successful packet delivery. Using the greater network flexibility and scalability of the software-defined network (SDN) architecture, this study designs a two-phase integrated DQN and RF Packet Routing Framework (IDRF) that combines the deep Q-learning network (DQN) and random forest (RF) approaches. First, the IDRF offline phase corrects the vehicle's historical trajectory information using the vehicle trajectory continuity algorithm and trains the DQN model. Then, the IDRF real-time phase judges whether vehicles can meet each other and makes a real-time routing decision to select the most appropriate relay vehicle after adding real-time vehicles to the VANET. In this way, the IDRF can obtain the packet transfer path with the shortest end-to-end delay. Compared to two DQN-based approaches, i.e., TDRL-RP and VRDRT, and traditional VANET routing algorithms, the IDRF exhibits significant performance improvements for both sparse and congested periods during intensive simulations of the historical GPS trajectories of 10,357 taxis within Beijing city. Performance improvements in the average packet delivery ratio, end-to-end delay, and overhead ratio of the IDRF over TDRL-RP and VRDRT under different numbers of pairs and transmission ranges are at least 3.56%, 12.73%, and 5.14% and 6.06%, 11.84%, and 7.08%, respectively. [ABSTRACT FROM AUTHOR]

Mobile Ad hoc Network (MANET) is an infrastructure-less network of mobile nodes which used in military, rescue operations, disaster relief, and rural areas for communications. To process the data packets, MANET nodes consume a lot of energy during real time data transmission. The conventional protocol selects the random route path in the network. Due to overhead in the random route path the power consumptions may exhaust the energy of nodes which causes the communication delay or may path failure. To address these issues an optimized energy efficient routing protocol could be used which prevents excessive consumption of node energy and enhances the network lifespan. In our research work, a novel nature-inspired Energy Efficient Optimized Sleep Scheduling (EEOSS) protocol is proposed to enhance the effectiveness and increase lifetime of ad hoc network. EEOSS protocol is the hybridization of ad hoc on-demand multi-path distance vector (AOMDV), Ant colony optimization (ACO), Particle swarm optimization (PSO) and sleep scheduling (SS) algorithms. AOMDV selects the multiple paths for data transmission whereas, ACO and PSO are used to identify the optimum route path based on number of nodes, packet size and node speed. To save the energy of nodes the SS algorithm puts nodes into sleep state when nodes are not participating actively in the network. The suggested protocol is compared experimentally with other existing routing protocols and measures performance based on throughput, energy consumption, end-to-end delay (E2ED), and network lifetime. The experiments are simulated on NS 2.35 and the results find that the EEOSS protocol has 12% improvement in throughput, 18% improvement in network lifetime, 12% improvement in E2ED and 9% improvement for energy consumption as compare to other state of art. [ABSTRACT FROM AUTHOR]

The Internet of Things (IoT) has significantly altered our way of life, being integrated into many application types. These applications require a certain level of security, which is always a top priority when offering various services. It is particularly difficult to protect the information produced by IoT devices from security threats and protect the exchanged data as they pass through various nodes and gateways. Group Key Management (GKM) is an essential method for controlling the deployment of keys for network access and safe data delivery in such dynamic situations. However, the huge volume of IoT devices and the growing subscriber base present a scalability difficulty that is not addressed by the current IoT authentication techniques based on GKM. Moreover, all GKM models currently in use enable the independence of participants. They only concentrate on dependent symmetrical group keys for each subgroup, which is ineffective for subscriptions with very dynamic behavior. To address these issues, this study proposes a unique Decentralized Lightweight Group Key Management (DLGKM) framework integrated with a Reliable and Secure Multicast Routing Protocol (REMI-DLGKM), which is a reliable and efficient multicast routing system for IoT networks. REMI-DLGKM is a cluster-based routing protocol that qualifies for faster multiplex message distribution within the system. According to simulation results, this protocol is more effective than cutting-edge protocols in terms of end-to-end delay, energy consumption, and packet delivery ratio. The packet delivery ratio of REMI-DLGKM was 99.21%, which is 4.395 higher than other methods, such as SRPL, QMR, and MAODV. The proposed routing protocol can reduce energy consumption in IoT devices by employing effective key management strategies. [ABSTRACT FROM AUTHOR]

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]

Opportunistic networks, an evolution of mobile Ad Hoc networks (MANETs), offer decentralized communication without relying on preinstalled infrastructure, enabling nodes to route packets through different mobile nodes dynamically. However, due to the absence of complete paths and rapidly changing connectivity, routing in opportunistic networks presents unique challenges. This paper proposes a novel probabilistic routing model for opportunistic networks, leveraging nodes' meeting probabilities to route packets towards their destinations. Thismodel dynamically builds routes based on the likelihood of encountering the destination node, considering factors such as the last meeting time and acknowledgment tables to manage network overload. Additionally, an efficient message detection scheme is introduced to alleviate high overhead by selectively deleting messages from buffers during congestion. Furthermore, the proposed model incorporates cross-layer optimization techniques, integrating optimization strategies across multiple protocol layers to maximize energy efficiency, adaptability, and message delivery reliability. Through extensive simulations, the effectiveness of the proposed model is demonstrated, showing improved message delivery probability while maintaining reasonable overhead and latency. This research contributes to the advancement of opportunistic networks, particularly in enhancing connectivity and efficiency for Internet of Things (IoT) applications deployed in challenging environments. [ABSTRACT FROM AUTHOR]

The paradigm of multi-layer networks can help devise a set of robotic swarms interacting with mobile computing centrals. We present here a distributed hierarchical network model and a related routing protocol (based on static routing and/or AODV protocol for peer nodes) for swarm robotics in aquatic environment, defining also which packets need to be exchanged to guarantee the mission accomplishment. Joining concepts and techniques from different disciplines allows us building a robust system with potential practical applications in scenarios such as environmental care. We discuss our results and further developments of the proposed approach. [ABSTRACT FROM AUTHOR]

In unmanned aerial vehicle ad‐hoc network (UANET), the node speed of unmanned aerial vehicles (UAVs) may reach up to 400 km/h. The fast or slow movement of UAV nodes leads to different speeds of topology change of the nodes. Traditional optimized link state routing (OLSR) protocol cannot adaptively adjust the routing update period when the network topology changes, which may lead to the nodes calculating incorrect routing tables. This increases the average end‐to‐end delay and packet loss rate for packet transmission. To enhance the adaptability of OLSR routing protocol to network topology changes, this paper proposes a multi‐agent independent deep deterministic policy gradient‐OLSR (MA‐IDDPG‐OLSR) routing protocol based on distributed multi‐agent reinforcement learning. The protocol deploys DDPG algorithm on each UAV node, and each UAV node adaptively adjusts the Hello and TC message sending intervals, according to the one‐hop neighbouring nodes as well as its own state. Simulation results show that the proposed protocol is able to improve the throughput and reduce the packet loss rate as compared to traditional AODV, GRP, OLSR, and distributed multiple‐agent independent proximal policy optimization‐OLSR (MA‐IPPO‐OLSR), distributed multiple‐agent independent twin delayed deep deterministic policy gradient‐OLSR (MA‐ITD3‐OLSR) routing protocols. Since MA‐IDDPG‐OLSR relies only on local information, there is a minor performance degradation in MA‐IDDPG‐OLSR compared to centralized single‐agent DQN‐OLSR routing protocol. But it is more suitable to a completely distributed UAV network without a centralized node. [ABSTRACT FROM AUTHOR]

This FANETs (Flying Adhoc NETworks) are supported by UAVs (Unmanned Aerial Vehicles) which carry out the task of transmitting and receiving data. Transmission and routing are complicated by the highly mobile AUVs. Node links are temporary and may result in transmission related issues. FANETs are prone to network attacks, especially black hole attacks leading to heavy data loss. This may lead to packet drops which might compromise the transmitted data. The proposed Eagle Optimized Energy Efficient Optimal Route-Finding Protocol (EOEEORFP) selects an efficient route towards the destination. Factors like trust degree, priority queue, network delay, hop count and energy consumption levels are taken into consideration in designing the routing strategy. These factors help in identifying the nodes that form the trusted nodes in the routing path. This is achieved by employing the biological behavior of eagles in finding their prey. The suggested protocol works in two stages. In the initial stage, it sets up an optimal route with selective nodes (trusted nodes). In the second stage, the network security is fortified by eradicating black hole attacks by using RREP (Route Reply) packets strategically. The EOEEORFP protocol assures the successful data delivery by employing a trusted routing path. The proposed EOEEORFP protocol is assessed against Adhoc On demand Distance Vector (AODV) and AODV-V2 protocols to measure its performance. EOEEORFP achieves very good PDR and throughput while conserving the network energy by minimizing the network delay. [ABSTRACT FROM AUTHOR]