Route Discovery Phase Research Articles

Reliable Air Quality Assessment in Dynamic Environments using Reward-learning Routing with Flying MANET Technology

<p>Air pollution poses significant threats to ecosystems, atmosphere, and the health of both humans and wildlife. It is primarily caused by industrial and chemical pollutants, leading to deterioration in air, water, and soil quality. As a result, effective air quality monitoring is crucial for environmental management. Flying Mobile Ad hoc Networks (FMANETs) offer a promising solution for intelligent air quality monitoring and assessment by employing unmanned aerial vehicles (UAVs) to measure air pollutants. However, FMANET-based systems face unique challenges, including UAVs' three-dimensional movement, high dynamism, rapid topological changes, resource constraints, and low UAV density. Therefore, routing optimization becomes a fundamental issue in these systems. In this paper, we propose a novel routing method named RFMAN (Reward-learning-based FMANET) for intelligent air quality monitoring systems. RFMAN consists of two main components: route discovery and route maintenance. In the route discovery phase, we introduce a Reward-learning-based mechanism to identify optimal routes, while also implementing a filtering parameter to refine the UAV selection process and reduce the search space. The route maintenance phase of RFMAN focuses on detecting and correcting paths nearing breakdowns, as well as promptly replacing failed paths to ensure continuous monitoring efficiency. The result section pictures that RFMAN outperforms other methods. Overall, RFMAN offers a promising solution for enhancing the effectiveness and reliability of air quality monitoring in FMANET-based systems.</p>

Routing networking technology based on improved ant colony algorithm in space-air-ground integrated network

Space-air-ground integrated networks comprise a multi-level heterogeneous integrated network that combines satellite-based, aerial, and terrestrial networks. With the increasing human exploration of space and growing demands for internet applications, space-air-ground integrated networks have gradually emerged as the direction for communication network development. These networks face various challenges such as extensive coverage, diverse communication node types, low-quality communication links, and simultaneous operation of multiple network protocols. However, the rapid development and widespread application of artificial intelligence and machine learning technologies in recent years have offered new perspectives and solutions for the communication architecture and routing algorithm research within space-air-ground integrated networks. In these networks, not all nodes can typically communicate directly with satellites; instead, a specific set of specialized communication nodes facilitates data communication between aerial and satellite networks due to their superior communication capabilities. Consequently, in contrast to traditional communication architectures, space-air-ground integrated networks, particularly in the terrestrial layer, often need to address challenges related to the diversity of communication node types and low-quality communication links. A well-designed routing approach becomes crucial in addressing these issues. Therefore, this paper proposes an AODV routing network protocol based on an improved ant colony algorithm (AC-AODV), specifically designed for the terrestrial layer within the space-air-ground integrated networks. By integrating information such as the type, energy, and location of communication nodes, this protocol aims to facilitate network communication. The objective is to guide information flow through nodes that are more suitable for communication, either by relaying communication or by connecting with satellites through specialized nodes. This approach alleviates the burden on ordinary nodes within the terrestrial communication network, thereby enhancing the overall network performance. In this protocol, specialized nodes hold a higher forwarding priority than regular nodes. When a source node needs to transmit data, it enters the route discovery phase, utilizing its own type, location, and energy information as heuristic data to calculate forwarding probabilities. Subsequently, it broadcasts route request (RREQ) messages to find the path. Upon receiving the RREQ message, the destination node sends an RREP message for updating information elements and selects the optimal path based on these information elements. Compared to AODV, AC-AODV shows significant improvements in performance metrics such as transmission latency, throughput, energy conversion rate, and packet loss rate.

Traffic-Predictive Routing Strategy for Satellite Networks

To address the issues of uneven satellite network load and unstable link connections, a globally adaptive satellite network routing strategy based on traffic prediction (G-AODV) is proposed by enhancing the existing Ad hoc On-Demand Distance Vector Routing (AODV) protocol. To prevent heavily loaded nodes from becoming intermediate nodes, G-AODV introduces a traffic prediction mechanism in the route discovery phase. The routing request packet adopts the corresponding forwarding control policy based on the comparison between the predicted traffic load value at the next moment and the dynamic threshold. At the same time, a path replacement strategy is adopted to replace paths before node congestion occurs to achieve load balancing. Considering the unstable characteristics of the satellite chain that easily breaks, the route maintenance phase selects a path repair method by judging the node stability to avoid secondary breaks in the route. The simulation results show that in scenarios with different packet delivery rates, compared with the three comparative routing strategies, the packet delivery rate of G-AODV is increased by up to 20%, the packet loss rate is reduced by 22%, and the end-to-end delay is significantly reduced. In scenarios with different communication connection pairs, G-AODV’s packet delivery rate increased by up to 20%, the packet loss rate decreased by 18%, and the end-to-end delay was still reduced.

A P2P multi-path routing algorithm based on Skyline operator for data aggregation in IoMT environments

The integration of Internet of Things (IoT) technologies, particularly the Internet of Medical Things (IoMT), with wireless sensor networks (WSNs) has revolutionized the healthcare industry. However, despite the undeniable benefits of WSNs, their limited communication capabilities and network congestion have emerged as critical challenges in the context of healthcare applications. This research addresses these challenges through a dynamic and on-demand route-finding protocol called P2P-IoMT, based on LOADng for point-to-point routing in IoMT. To reduce congestion, dynamic composite routing metrics allow nodes to select the optimal parent based on the application requirements during the routing discovery phase. Nodes running the proposed routing protocol use the multi-criteria decision-making Skyline technique for parent selection. Experimental evaluation results show that P2P-IoMT protocol outperforms its best rivals in the literature in terms of residual network energy and packet delivery ratio. The network lifetime is extended by 4% while achieving a comparable packet delivery ratio and communication delay compared to LRRE. These performances are offered on top of the dynamic path selection and configurable route metrics capabilities of P2P-IoMT.

Detecting Sybil Attack During Data Transmission Using Concealed Data Sharing Algorithm in Manet

As the mobile users are increasing sharply, the wireless or mobile ad hoc network data transmission is on the rise and gaining lot of attention from the research communities. The most important issue that has to be handled is the detecting the Sybil attack and increase the reliability and confidentiality of the data transmission. The foremost aim of this paper is to develop a mechanism to detect the Sybil attack early and evade the data loss and privacy to ensure credibility to the users. The proposed algorithm employs a concealed data sharing plan during the route discovery phase and detects and alleviates the attack to guarantee attack free data transmission in the MANET. The data sharing plan allows only the nodes that are trustworthy and permit the data to be transmitted across them, thereby evading the malicious nodes during the route discovery process and curtails the wastage of time and energy of the nodes.

A Method to Reduce Route Discovery Cost of UAV Ad Hoc Network

The unmanned aerial vehicle communication networks (UAVCNs) are composed of unmanned aerial vehicles (UAVs) connected in ad hoc mode to facilitate vertical communication in 5G and beyond networks. UAVs operating in an ad hoc mode of operation mostly use reactive routing protocols to establish routes in the network to reduce the energy consumption of the nodes. In this article, a route discovery method is presented to reduce the overhead faced by reactive routing protocols during the route discovery phase. The expanding ring search (ERS) method is mostly used by reactive routing protocols in the destination discovery phase of the routing algorithm. Although the performance of the ERS method is better than simple flooding, the presented method further reduces energy consumption and routing overhead as compared to the conventional ERS method. To achieve the task, the time to live (TTL) is modified to accommodate a large number of nodes in a search attempt. We proposed variants of the proposed techniques for diverse application requirements and compared the performance with the state-of-the-art ERS technique. It has been demonstrated with the help of simulations that the presented algorithm outperforms the ERS method in terms of reduced routing overhead and reduced energy consumption.

SAOA: Multi-Objective Fault-Tolerance Based Optimized RPL Routing Protocol in Internet of Things

Several technologies are implemented for serving industrial information and controlling the process in which the increased complexity and allied fault failed to achieve a reliable transmission to activate the timely network. These data must be transferred from one node to another node without any fault or delay in their nodes. To resolve this problem, an algorithm named SAOA is proposed to communicate the messages from various services without any delay in their nodes. IoT with mobile sink node is simulated in the network based on the MoO4RPL objective and the phases involved in this strategy are topology, route discovery, communication, and route maintenance phase. The topology network is generated for network topology and the rank is computed based on the energy, trust, delay, fault tolerance, and link quality in the multi-objective route discovery phase. In the communication phase, the optimal route is selected using proposed SAOA with fitness function factors. At last, the route maintenance phase is performed, and the proposed SAOA has achieved a minimum distance of 53.807 m, maximum energy of 0.415 J, maximum link quality of 2.163, and maximum trust of 0.701, respectively. In the future, another algorithm is implemented in IoT applications with minimum modifications to evaluate the various metric values.

Trusted routing protocol for federated UAV ad hoc network

PurposeIn the final step, the trust model is applied to the on-demand federated multipath distance vector routing protocol (AOMDV) to introduce path trust as a foundation for routing selection in the route discovery phase, construct a trusted path, and implement a path warning mechanism to detect malicious nodes in the route maintenance phase, respectively.Design/methodology/approachA trust-based on-demand multipath distance vector routing protocol is being developed to address the problem of flying ad-hoc network being subjected to internal attacks and experiencing frequent connection interruptions. Following the construction of the node trust assessment model and the presentation of trust evaluation criteria, the data packet forwarding rate, trusted interaction degree and detection packet receipt rate are discussed. In the next step, the direct trust degree of the adaptive fuzzy trust aggregation network compute node is constructed. After then, rely on the indirect trust degree of neighbouring nodes to calculate the trust degree of the node in the network. Design a trust fluctuation penalty mechanism, as a second step, to defend against the switch attack in the trust model.FindingsWhen compared to the lightweight trust-enhanced routing protocol (TEAOMDV), it significantly improves the data packet delivery rate and throughput of the network significantly.Originality/valueAdditionally, it reduces the amount of routing overhead and the average end-to-end delay.

Efficient Load Balancing with MANET Propagation of Least Common Multiple Routing and Fuzzy Logic

Mobile Ad Hoc Network (MANET) is a group of node that would interrelate among each other through one multi-hop wireless link, wherein the nodes were able to move in response to sudden modifications. The objective of MANET routing protocol is to quantify the route and compute the best path, but there exists a major decrease in energy efficiency, difficulty in hop selection, cost estimation, and efficient load-balancing. In this paper, a novel least common multipath-based routing has been proposed. Multipath routing is used to find a multipath route from source and destination. Load balancing is of primary importance in the mobile ad-hoc networks, due to limited bandwidth among the nodes and the initiator of the load routing discovery phase in the multipath routing protocol. Fuzzy logic for load balancing multipath routing in MANETs is proposed, which ensures the data packets are sent through a path with the variance of binary sets to predict the original transformation of the data to be received in the system. The main objective of the proposed system is to reduce the routing time of data packets and avoid the traffic based on multipath source and destination. The experimental results have to verify 96.7% efficiency in balancing the load.

A Multi-Agent Reinforcement Learning-Based Optimized Routing for QoS in IoT

Abstract The Routing Protocol for Low power and lossy networks (RPL) is used as a routing protocol in IoT applications. In an endeavor to bring out an optimized approach for providing Quality of Service (QoS) routing for heavy volume IoT data transmissions this paper proposes a machine learning-based routing algorithm with a multi-agent environment. The overall routing process is divided into two phases: route discovery phase and route maintenance phase. The route discovery or path finding phase is performed using rank calculation and Q-routing. Q-routing is performed with Q-Learning reinforcement machine learning approach, for selecting the next hop node. The proposed routing protocol first creates a Destination Oriented Directed Acyclic Graph (DODAG) using Q-Learning. The second phase is route maintenance. In this paper, we also propose an approach for route maintenance that considerably reduces control overheads as shown by the simulation and has shown less delay in routing convergence.

MRIRS: Mobile Ad Hoc Routing Assisted With Intelligent Reflecting Surfaces

A mobile ad hoc network (MANET) poses significant challenges such as route failure and end-to-end delay due to the decentralized nature of mobile ad hoc wireless networks, mobility of devices, and resource constraints. Motivated by this, in this work, a new routing protocol by implementing intelligent reflecting surfaces (IRSs) in MANET, called MRIRS, is proposed. The developed MRIRS investigates the role of IRS as an intermediate node which helps not only for multi-flow multi-path routing even in non-line-of-sight (NLoS) scenarios but also supports delay minimization in the route discovery phase and helps with interference-avoiding channel assignment to the primary users (PUs). Comparison in terms of packet delivery ratio (PDR) and end-to-end delay (PD) averaged on 40 topologies based on the same source and destination pair with 3 flows shows that MRIRS has an 8% improvement in PDR and 800 msec improvement in PD. In environments with 8 m/s average node speed, MRIRS shows 114.88 kbps improvement in terms of throughput where 15.97% link failure is recorded on average. In environments with 16 m/s, link failure is around 24% where it is almost 98% for other routing protocols.

Highly Reliable Fuzzy-Logic-Assisted AODV Routing Algorithm for Mobile Ad Hoc Networks.

Due to the noncentered, self-organizing, and self-healing characteristics, mobile ad hoc networks (MANET) have been more and more widely used as an alternative access technology for regions having no fixed infrastructure. On-demand routing protocols (e.g., ad hoc on-demand distance vector (AODV)) are used to cope with the rapidly changing topology of MANET and reduce the network overhead. Taking delay, stability, and remaining energy of nodes into consideration, a fuzzy-logic-assisted AODV (FL-AODV) routing algorithm is proposed in this paper to further improve the reliability of the route in MANET. In the route discovery phase, the node with the highest reliability is selected as the relay node, and the route with the highest accumulated reliability is reserved for data transmission. Simulation results show that, compared with the traditional AODV protocol and the fuzzy logic routing algorithm (FLRA), the proposed routing protocol has higher reliability without increasing delay, i.e., better link connectivity and longer route life. The average routing reliability is about 18% higher than AODV while the average delay is the same low when the number of node greater than 70.

Multiobjective Multicast DSR Algorithm for Routing in Mobile Networks with Cost, Delay, and Hop Count

Tremendous evaluation of wireless mobile communication needs more efficient algorithms for communication systems. The use of conventional single-objective optimization algorithms may be unsuitable for real applications, because they act to the detriment of the rest of the performance parameters like lifetime network, delay, cost, and hop count; for this reason, multiobjective is needed. This paper presents performance evaluation and compares between the Multicast MDSR and MAODV with MACO. The proposed MDSR is concerned with change of the route discovery phase, where the route selection is based on the shortest path of route reply packets on the route with calculating the number of hop counts. Also, this article compares our MDSR modification with the evaluation algorithm based on Ant Colony Optimization (ACO), which finds the best path and multicast tree optimizes total weight (cost, delay, and hop count) of the multicast tree using multiobjective. Experimental results proved that the proposed MDSR algorithm is more efficient than MAODV and MACO in the total weight (cost, delay, and hop count), respectively. Moreover, the MACO outperforms MAODV for multicast routing problem.

An Energy-Aware and Predictive Fuzzy Logic-Based Routing Scheme in Flying Ad Hoc Networks (FANETs)

Today, unmanned aerial vehicles (UAVs), also known as drones, have become very popular in military applications, commercial applications, and academic research. Flying ad hoc network (FANET) is a new type of ad hoc network, which groups small drones into an ad hoc form. These networks have unique characteristics, including moving in a 3D space, high mobility, frequent topological changes, limited resources, low density of nodes, and so on, which impose various challenges when designing a proper and efficient routing scheme. In this paper, we present a fuzzy logic-based routing scheme for flying ad hoc networks. The proposed routing scheme has two phases: route discovery phase and route maintenance phase. In the first phase, we propose a technique for calculating the score of each node in the network to prevent the broadcast storm problem and control the flood of the control messages, which have been broadcast to discover a new route in the network. This score is calculated based on various parameters such as movement direction, residual energy of nodes, link quality, and node stability. Moreover, in the route selection process, we design a fuzzy system to select routes with more fitness, less delay, and fewer hops for data transfer. The second phase includes two steps: preventing route failure in order to detect and modify paths at the failure threshold, and reconstructing failed routes in order to recognize and quickly replace these routes. Finally, the proposed routing scheme is implemented in NS2 to evaluate its performance and determine its efficiency. The simulation results are compared with three routing methods, namely ECaD, LEPR, and AODV. These results show that the proposed routing method outperforms other routing schemes in terms of end to end delay, packet delivery rate, route stability, and energy consumption. However, it has slightly increased the routing overhead.

Research on Distributed In‐Vehicle Wireless Self‐Organized Routing Protocol Distribution Mechanism

In recent years, the application of intelligent transportation systems has gradually made the transportation industry safe, efficient, and environmentally friendly and has led to a broader research prospect of vehicle wireless communication technology. Distributed vehicular self‐organizing networks are mobile self‐organizing networks in realistic traffic situations. Data interaction and transmission between nodes are achieved through the establishment of a vehicular self‐organizing network. In this paper, a multipath routing protocol considering path stability and load balancing is proposed to address the shortcomings of existing distributed vehicular wireless self‐organizing routing protocols. This protocol establishes three loop‐free paths in the route discovery phase and uses the path stability parameter and load level parameter together to measure the total transmission cost. The one with the lowest total transmission cost is selected as the highest priority path for data transmission in the route selection phase, and the other two are used as alternate paths, and when the primary path breaks, the higher priority of the remaining path will continue to transmit data as the primary route. In this paper, to improve the content distribution performance of target vehicles in scenarios where communication blind zones exist between adjacent roadside units, an assisted download distribution mechanism for video‐like large file content is designed in the V2V and V2I cooperative communication regime. That is, considering a two‐way lane scenario, we use the same direction driving vehicles to build clusters, reverse driving vehicles to carry prefetched data, and build clusters to forward prefetched data to improve the data download volume of target vehicles in nonhot scenarios such as highways with the sparse deployment of roadside units, to meet the data volume download demand of in‐vehicle users for large files and give guidance for efficient distribution of large file content in highway scenarios.

Ecologically Friendly Full-Duplex Data Transmission Scheme for Underwater Acoustic Sensor Networks

Underwater acoustic sensor networks (UASNs) have been proposed as a promising way in supporting the Underwater-Internet-of-Things (UIoT) applications. However, to guarantee and improve Quality of Service (QoS), they are still facing great challenges especially when it comes to enabling reliable data communication for the UIoT applications and meanwhile protecting the marine ecosystems for sustainable underwater monitoring and exploration; this is because the acoustic signals used by UASNs can do harmful interference to vocalizing marine mammals. Therefore, the article proposed an ecologically friendly data transmission scheme for UASNs, which adopts an interference-aware opportunistic route discovery method and a frequency-division multiplexing (FDM)-based full-duplex communication scheme. First, in the route discovery phase, a virtual-void zone scheme, an FDM-based channel allocation approach and a Bayesian network-based mammal avoidance strategy is introduced to establish interference-free routing paths for enabling reliable and environmentally friendly data transmissions. Then during the data transmission phase, an FDM-based full-duplex communication technique is adopted to enable high-speed data flow from the seabed to the surface. Extensive simulations indicate that the proposed scheme has excellent advantages in terms of QoS while also taking marine mammals into account since the signal interference to both underwater nodes and nearby vocalizing mammals is significantly mitigated.

FractWhale-DSR: Fractional Whale Optimization Based Secure Dynamic Source Routing Algorithm for Mobile Ad-hoc Network

Background: Nodes in the mobile Ad-hoc network (MANET) have the dynamic nature due to their vast separation distance. The dynamic nature of the MANET nodes changes the routing path established for the communication. The dynamic secured routing (DSR) has gained popularity since they provide the routing path based on the demand provided by the source and destination nodes. Various literature works have discussed the DSR strategy for routing path establishment, but faces challenges since it consumes high energy during the route discovery phase. Objective: To overcome the challenges in the existing works, a DSR strategy based on the Fractional Whale optimization algorithm (FWOA) is introduced in this work. Methods: The proposed algorithm uses the C 2 TE based selection criteria which depend on the connectivity, congestion, trust, and energy for selecting the suitable nodes for the communication. The proposed FractWhale-DSR algorithm finds the secured routing path in three phases. Results: The parameters, such as throughput, delay, Packet Delivery Ratio (PDR), and the energy define the performance of the proposed model. From the simulation results, the proposed FractWhale- DSR algorithm has an overall better performance with the values of 0.57265, 0.005118, 0.786325, and 75.88636% for throughput, delay, PDR, and energy respectively at the round of 25 for the MANET with 100 nodes. Conclusion: The proposed DSR strategy has the advantage of adaptability and scalability. Also, the router selects the alternate paths, when there is a link failure in the current network.

A Secure Data Dissemination in a DHT-Based Routing Paradigm for Wireless Ad Hoc Network

Over the past decade, distributed hash table- (DHT-) based routing protocols have been adopted in wireless ad hoc networks (WANETs) to achieve scalability in the route discovery phase by avoiding the flooding mechanism. The security aspects of the routing protocols based on the DHT mechanism are crucial to address and have not been discussed in the existing literature. Therefore, addressing the security issues in DHT-based routing protocols would prevent the service disruption, decrease the traffic overhead, and reduce the packet loss in the network. In this paper, several security issues are identified and elaborated through an example scenario. Moreover, a novel DHT-based routing protocol is proposed that uses a digital signature and the user’s trust in order to swap securely the logical identifiers (LIDs). Trust between nodes is established by the user’s acquaintance and the first visual contact. The proposed protocol vindicates its effectiveness via simulation results in terms of computation time, normalized overhead, percent improvement, and packet delivery ratio.

An Anti-Gray Hole Attack Scheme in Mobile Ad Hoc Network

Dynamic variation of network topology in mobile ad hoc networks (MANET) forces network nodes to work together and rely on each other for routing. Considering the lack of a central control node, some nodes appear maliciously and selectively drop the data packets instead of transmitting to the next hop node, which is known as the gray hole attack. In order to prevent and identify the gray hole attack, an intrusion detection system (IDS) is proposed on nodes to maintain network efficiency. In addition to establishing security, the proposed anti gray hole attack mechanism extracts abnormal differences between routing packets in the route discovery phase of the ad hoc on-demand distance vector (AODV) routing protocol. It then assigns a suspicious value to each participating node and monitors the exchange of data packets between neighboring nodes in the data transfer phase using a data transmission information table. If the suspicious value reaches a predetermined threshold, IDS nodes send an alert message to other nodes about the identity of the malicious node, in order to prevent its activity on the network. Simulation results indicate that the performance of the proposed scheme in terms of packet delivery rate, packet loss rate, and routing overhead outperforms those in the literature.

ENERGY CONSUMPTION SOLUTION IN MOBILE AD-HOC NETWORK

The current study was motivated because of higher energy consumption in the current mobile-ad hoc network especially the dynamic system routing. A solution was proposed consisted of nodes energy and traffic load and distance during the route discovery phase. Later, a simulation was performed to make comparison between DSR and MP-DSR. The results states that the proposed MP-DSR outperformed the DSR in all three tests including packet delivery fraction, end-to-end delay, and average energy consumption.