Location-based Routing Research Articles

Adaptive Location-based Routing Protocols for Dynamic Wireless Sensor Networks in Urban Cyber-physical Systems

This study investigates the development and enhancement of adaptive location-based routing protocols within dynamic wireless sensor networks (WSNs) in urban cyber-physical systems, recommending the implementation of the study’s innovative Urban Adaptive Location-based Routing Protocol (UALRP). This innovative protocol integrates real-time data analytics and adaptive machine learning models into its algorithmic framework to dynamically optimize routing decisions based on continuously changing urban conditions. Through the utilization of data-driven simulation models and machine learning techniques, the research sought to significantly improve the efficiency, reliability, and scalability of urban WSNs. Existing protocols such as Geographic Adaptive Fidelity (GAF), Greedy Perimeter Stateless Routing (GPSR), and Dynamic Source Routing (DSR) were critically assessed under urban settings using extensive datasets detailing New York City's traffic patterns and environmental variables. The analysis demonstrated that while GPSR showed superior performance in terms of latency, throughput, and energy efficiency among the traditional protocols, the introduction of UALRP, with its advanced predictive and adaptive capabilities, can further optimize these metrics. The study affirms the critical role of enhancing location accuracy and the ongoing advancement of machine learning models within urban routing protocols. These insights advocate for the broader implementation of adaptive strategies like UALRP to foster the development of more resilient and efficient urban cyber-physical systems.

RECAR: Robust and efficient collision-avoiding routing for 3D underwater named data networking

Internet of Underwater Things (IoUT) has important application prospects in fields of both scientific research and commercial business. As a future network architecture, Named Data Networking (NDN) is starting to be applied to IoUT. Although Underwater Named Data Networking (UNDN) has unique advantages in dealing with bandwidth usage, multi-path forwarding, and node mobility, there is still no specific routing protocol for UNDN. The existing underwater routing protocols are either difficult to combine with NDN, or are limited by channel collision and redundant forwarding, especially broadcast suppression routing. In this paper, we propose a routing method named Robust and Efficient Collision-Avoiding Routing (RECAR) for 3D UNDN. RECAR consists of three combined forwarding modes: Directive Mode (DM), Directive Flooding Mode (DFM), and Flooding Mode (FM). In DFM, we propose Segmentation Suppression for Optimal Position (SSOP), an elaborate waiting time algorithm of broadcast suppression which can effectively reduce channel collisions and redundant forwarding. For DM, failure path recovery and unreliable path elimination are proposed to address failure paths. Additionally, several forwarding efficient mechanisms are designed including flexible mode shift, unified data forwarding and scope control. Simulation results show that RECAR has excellent and robust performance, even in the cases of node failure and void hole. Compared with a recent underwater routing method (adaptive location-based routing protocol), RECAR improves the average interest satisfied rate by 19.57% while reducing the request time, collisions, redundant forwarding, total traffic, and energy consumption by 19.5%, 91.7%, 71.4%, 78.4%, and 27.3%, respectively.

Environment-Aware Adaptive Reinforcement Learning-Based Routing for Vehicular Ad Hoc Networks.

With the rapid development of the intelligent transportation system (ITS), routing in vehicular ad hoc networks (VANETs) has become a popular research topic. The high mobility of vehicles in urban streets poses serious challenges to routing protocols and has a significant impact on network performance. Existing topology-based routing is not suitable for highly dynamic VANETs, thereby making location-based routing protocols the preferred choice due to their scalability. However, the working environment of VANETs is complex and interference-prone. In wireless-network communication, the channel contention introduced by the high density of vehicles, coupled with urban structures, significantly increases the difficulty of designing high-quality communication protocols. In this context, compared to topology-based routing protocols, location-based geographic routing is widely employed in VANETs due to its avoidance of the route construction and maintenance phases. Considering the characteristics of VANETs, this paper proposes a novel environment-aware adaptive reinforcement routing (EARR) protocol aimed at establishing reliable connections between source and destination nodes. The protocol adopts periodic beacons to perceive and explore the surrounding environment, thereby constructing a local topology. By applying reinforcement learning to the vehicle network's route selection, it adaptively adjusts the Q table through the perception of multiple metrics from beacons, including vehicle speed, available bandwidth, signal-reception strength, etc., thereby assisting the selection of relay vehicles and alleviating the challenges posed by the high dynamics, shadow fading, and limited bandwidth in VANETs. The combination of reinforcement learning and beacons accelerates the establishment of end-to-end routes, thereby guiding each vehicle to choose the optimal next hop and forming suboptimal routes throughout the entire communication process. The adaptive adjustment feature of the protocol enables it to address sudden link interruptions, thereby enhancing communication reliability. In experiments, the EARR protocol demonstrates significant improvements across various performance metrics compared to existing routing protocols. Throughout the simulation process, the EARR protocol maintains a consistently high packet-delivery rate and throughput compared to other protocols, as well as demonstrates stable performance across various scenarios. Finally, the proposed protocol demonstrates relatively consistent standardized latency and low overhead in all experiments.

Performance Evaluation of ERGR-EMHC Routing Protocol using LSWTS and 3DUL Localization Schemes in UWSNs

This paper studies the impact of different localization schemes on the performance of location-based routing for UWSNs. Particularly, LSWTS and 3DUL localization schemes available in the literature are used to study their effects on the performance of the ERGR-EMHC routing protocol. First, we assess the performance of two localization schemes by measuring their localization coverage, accuracy, control packets overhead, and required localization time. We then study the performance of the ERGR-EMHC protocol using location information provided by the selected localization schemes. The results are compared with the performance of the routing protocol when using exact nodes’ locations. The obtained results show that LSWTS outperforms 3DUL in terms of localization accuracy by 83% and localization overhead by 70%. In addition, the results indicate that the localization error has a significant impact on the performance of the routing protocol. For instance, ERGR-EMHC with LSWTS is better in delivering data packets by an average of 175% compared to 3DUL.

An Efficient Grid-Based Geocasting Scheme for Wireless Sensor Networks

In a wireless sensor network (WSN), geocasting is a location-based routing protocol used for data collection or information delivery. In geocasting, a target region usually contains many sensor nodes with limited battery capacity, and sensor nodes in multiple target regions need to transmit data to the sink. Therefore, how to use location information to construct an energy efficient geocasting path is a very important issue. FERMA is a geocasting scheme for WSNs based on Fermat points. In this paper, an efficient grid-based geocasting scheme for WSNs, which is called GB-FERMA, is proposed. The scheme uses the Fermat point theorem to search for the specific nodes as Fermat points in a grid-based WSN, and it selects the optimal relay nodes (gateways) in the grid structure to realize energy-aware forwarding. In the simulations, when the initial power 0.25 J, the average energy consumption of GB-FERMA is about 53% of FERMA-QL, 37% of FERMA, and 23% of GEAR; however, when with the initial power 0.5 J, the average energy consumption of GB-FERMA is about 77% of FERMA-QL, 65% of FERMA, and 43% of GEAR. The proposed GB-FERMA can effectively reduce the energy consumption and thus prolong the lifetime of the WSN.

ARPLR: An All-Round and Highly Privacy-Preserving Location-Based Routing Scheme for VANETs

Location-based routing is a widely adopted message transmission mechanism in Vehicular Ad Hoc Networks (VANETs). While the existing location-based routing schemes of VANETs ignore the location privacy protection of vehicles, leading that the drivers to be tracked, and further threaten the safety of their life and property. To address the above issue, we propose an All-Round and Highly Privacy-Preserving Location-Based Routing for VANETs (called ARPLR). Specifically, ARPLR first proposes a road side unit assisted location management with location privacy protection that prevents the destination vehicle’s location from being leaked by the arbitrary query. Then, a message routing based on location ciphertext with highly privacy protection is designed by order revealing encryption, in which a multi-hop routing between the source and destination vehicle is established only by comparing the encrypted locations between intermediate vehicles. Security analysis shows that, ARPLR can not only effectively provide location privacy protection for the intermediate and the destination vehicles in the whole routing process, but also ensure end-to-end secure communication between the source and destination vehicles. Extensive experiments based on real-road map indicate that, compared with two state-of-the-art solutions, the average transmission delay of ARPLR is respectively reduced by about 18% and 60%, meanwhile the average packet delivery rate also increases about 30% and 2%, respectively.

Localization in wireless sensor network using machine learning optimal trained deep neural network by parametric analysis

Sensor nodes (SNs), which are a component of wireless sensor devices, have several uses in monitoring and surveillance. To perform location-based routing, the sensor nodes must be aware of their location reference (LR). The field of localization is the subject of several studies. Future developments in mobility, 3-D localization, energy preservation, and security are yet largely neglected. Here, optimization aided DNN trained with the measured distance based features like “Angle of Arrival (AoA) and Received Signal Strength Indicator (RSSI)” gives the predicted results on location of unknown nodes. To enhance the accuracy on localization, a hybrid model termed as Lion Assisted Firefly Algorithm (LAFA) model has been introduced. In this conference, a parametric analysis is made on the proposed algorithm by varying the parameter in LAFA. This includes the performance analysis of the model under each variation.

Sensor-System-Based Network with Low-Power Communication Using Multi-Hop Routing Protocol Integrated with a Data Transmission Model

Wireless sensor networks (WSNs) comprise several cooperating sensor nodes capable of sensing, computing, and transmitting sensed signals to a central server. This research proposes a sensor system-based network with low power communication using swarm intelligence integrated with multi-hop communication (SIMHC). This routing protocol selects the optimal route based on link distance, transmission power, and residual energy to optimize the network lifetime and node energy efficiency. Moreover, adaptive clustering-based locative data transmission (ACLDT) is applied for optimizing data transmission. The proposed approach combines clustering with data transfer via location-based routing and low-power communication in two phases to calculate the ideal cluster heads (CHs). First, a CH seeks the next hop from the nearest CH. Then, a path to the base station is formed by developing CH chains. The results reveal that the proposed sensor system based on data transmission and low-power consumption achieved a network lifetime of 96%, an average delay of 53 ms, a coverage rate (CR) of 83%, a throughput of 97%, and energy efficiency of 95%.

A Q-Learning-Based Topology-Aware Routing Protocol for Flying Ad Hoc Networks

Flying <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">ad hoc</i> networks (FANETs) have emanated over the last few years for numerous civil and military applications. Owing to underlying attributes, such as a dynamic topology, node mobility in 3-D space, and the limited energy of unmanned aerial vehicles (UAVs), a routing protocol for FANETs is challenging to design. Exiting topology-based routing is unsuitable for highly dynamic FANETs. Location-based routing protocols can be preferred for FANETs owing to their scalability, but are based on one-hop neighbor information and do not contemplate the reachability of further appropriate nodes for forwarding. Owing to the rapid mobility of UAVs, the topology frequently changes; thus, some route entries in the routing table can become invalid and the next-hop nodes may be unavailable before a timeout. That is, the routing decision based on one-hop neighbors cannot assure a successful delivery. In this study, we propose a novel <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$Q$ </tex-math></inline-formula> -learning-based topology-aware routing (QTAR) protocol for FANETs to provide reliable combinations between the source and destination. The proposed QTAR improves the routing decision by considering two-hop neighbor nodes, extending the local view of the network topology. With the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${Q}$ </tex-math></inline-formula> -learning technique, QTAR adaptively adjusts the routing decision according to the network condition. Our simulation results reveal that QTAR outstrips the existing routing protocols in respect of various performance metrics under distinct scenarios.

A Deep Reinforcement Learning-Based Geographic Packet Routing Optimization

Packet routing is a fundamental problem in wireless networks in which routers decide the next hop for each packet in order to deliver it to its destination as quickly as possible. In order to overcome the shortcoming of non optimal forwarding path caused by fixed forwarding mode in geographic location-based routing algorithm, we investigated a new efficient packet routing strategy which combined with Deep Reinforcement Learning (DRL) algorithm (Proximal Policy Optimization: PPO) to minimize the hops and reduce the probability of encountering “routing hole” during the forwarding of the packets in complex networks. Each node in our network can make routing decisions to learn a routing policy that can not only use the greedy mode to maintain the efficiency of routing policy but also reduce the use of peripheral forwarding mode. The learning process of the DRL agent is based on the status information of the packet being transmitted and information of neighbor nodes within the communication range. Extensive simulations over dynamic network topologies and the number of nodes have shown that our packets routing agent can learn the optimal policy in terms of average packets delivery rate and the number of hops compared with Greedy Perimeter Stateless Routing (GPSR) protocol. The performance of PPO in large-scale action space is also verified, which provides a basis for the future researches to combine PPO technique with packet routing optimization.

Impact of Network Topology on Energy Efficiency in WSN

&lt;p class="0abstractCxSpFirst"&gt;&lt;span lang="EN-US"&gt;Wireless communication network has a significant success in scientific and industrial communities. Due to its various advantages, this technology is considered as a key element in current network architectures. It represents the architecture that allows to group a large number of sensors to collect information about a physical process in different environments. The gathered data is transmitted to base station which communicates the information to the end user.&lt;/span&gt;&lt;/p&gt;&lt;p class="0abstractCxSpFirst"&gt;Several protocols are proposed for WSNs routing, by considering the limited capacities of sensor nodes according to a specific topology that allows to organize the nodes within the network. However, the performance of each routing protocol mainly depends on the application requirements and its results in terms of the lifetime of WSN and satisfaction of objectives defined.&lt;/p&gt;&lt;p class="0abstractCxSpLast"&gt;&lt;span lang="EN-US"&gt;According of the structure of WSN, the routing techniques can be divided in three types hierarchical, location-based flat routing. This paper, present the different routing techniques in WSN, based on the organization of nodes in sensor area. We focus specially to study the three types, cluster-based, chain-based and location-based routing techniques. These techniques will be simulated in order to compared their performances with our protocol Location-Based LEACH (LOC-LEACH).&lt;/span&gt;&lt;/p&gt;

Energy-efficient location-based routing algorithms for three dimensional mobile ad hoc networks

Wireless ad hoc network nodes suffer from limited energy supply. In the current location-based topology control algorithms a node discovers its neighbors by exchanging periodic hello messages between neighbors using the maximum transmission power of each node. This could be a source of extreme power consumption. This paper suggests several new location-based routing algorithms for mobile ad hoc networks that try to increase a network lifetime by decreasing the average power consumption of the network nodes. In the newly proposed algorithms, if the node is not moving it uses less frequent hello messages. During the movement of the node, the hello messages frequency increases. The new algorithms use adjusted transmission power for routing messages as well. We compare by simulation the power consumption of the new algorithm with the current location-based routing algorithms to show a substantial improvement in the overall network lifetime.

Wireless Sensor Network (WSN) Configuration Method to Increase Node Energy Efficiency through Clustering and Location Information

Wireless Sensor Network (WSN) technology, for services that are difficult to access or which need to be continuously monitored regardless of location, needs further research and development due to an expansion of fields where it can be applied and due to increases in efficiency. In particular, in the field of defense, research on the latest IT technologies including sensor networks is being actively conducted as an alternative to the risky use of personnel in areas such as surveillance and surveillance reconnaissance. This paper experimented with analyzing the conditions necessary for increasing the energy efficiency of the nodes constituting a sensor network using a clustering routing technique and a location-based routing technique. The derived factors include a method for selecting a cluster head (CH), a method for establishing a path from each channel to a base station (BS), and a method for transmitting collected data. We experimented with the derived factors and proposed a WSN configuration method that increases the energy efficiency of each node by applying optimal results and methods that were verified experimentally.

A Robust Netrosophic Clustering Based Raven Routing Optimization to Alleviate Void Hole and Energy Depletion in IoT WSN

Wireless Sensor Networks (WSNs) find extensive utilisation in diverse domains, including but not limited to environmental monitoring, industrial control, and healthcare. Wireless Sensor Networks (WSNs) have a crucial function in gathering and relaying information from sensor nodes to a central node or sink in various applications. Wireless Sensor Networks (WSNs) encounter various obstacles that can have a significant impact on their performance and lifespan. These challenges include but are not limited to limited battery life, void holes, and energy depletion.&#x0D; Several routing algorithms have been suggested in scholarly works to tackle these concerns, such as clustering-based routing, data-centric routing, and location-based routing. Nonetheless, a majority of these algorithms possess constraints and may not be appropriate for every situation.&#x0D; The present study introduces a methodology called Rncrro (Robust Netrosophic Clustering Based Raven Routing Optimisation) that aims to mitigate the issues of void holes and energy depletion in Wireless Sensor Networks (WSNs). The proposed approach utilises Netrosophic Clustering and Raven Optimisation algorithms in tandem to enhance the efficacy and resilience of the routing mechanism.&#x0D; The significance of this study is rooted in its capacity to surmount the constraints of current routing algorithms and furnish a superior and dependable resolution for Wireless Sensor Networks (WSNs). The proposed methodology has the potential to enhance the performance and longevity of Wireless Sensor Networks (WSNs) by mitigating void holes and energy depletion. This, in turn, can result in more efficient and dependable data collection and transmission across diverse applications.

A Survey on Geographic location routing and forwarding strategies of VANET and WSN based on NDN

Named-data Network (NDN) is a new network architecture, and its purpose is to achieve network architecture from the host-centric to the data-centric. NDN uses the data name of the application to communicate directly. Since the data name is defined by the application and unrelated to the connection, it relieves the need for IP address configuration, so as long as the physical connection exists, data exchange can occur. The NDN-based forwarding mechanism is very important for effective communication in Vechicle Ad-hoc Network (VANET) and Wireless Sensor Network (WSN). Location-based routing and forwarding utilizes the location information of neighboring nodes or destination nodes to improve the efficiency of routing search. The paper mainly discusses the geographical routing and forwarding strategies of NDN-based VANET and WSN and the existing problems, and proposes future challenges for NDN routing and forwarding.

Energy-efficient location-based routing algorithms for three dimensional mobile ad hoc networks

Energy-efficient location-based routing algorithms for three dimensional mobile ad hoc networks

DGA: Distributed geographic-sensing addressing method for linear-zone internet of things

Several applications of Internet of Things (IoT) have hundreds of nodes, and the expansibility and flexibility of the network can be greatly improved if the nodes can address themselves automatically and dynamically.Existing nodes addressing methods are mainly based on the logical relationships between nodes and routers. In this paper, the automatic geographic-sensing addressing method is studied for end-node (sensor/actuator) without satellite positioning device (such as global positioning system or Beidou system) for the application of IoT deployed in a linear area. The nodes ID is determined by its geographical location, which is very important for location-based routing and transmitting strategies. First, a sniffer method is designed to realize automatic addressing in an ideal state. Then, according to the actual application scenario, two distributed ID estimation algorithms based on received signal strength indicator(RSSI) and ranging are proposed. Through the deployment of LoRa-2.4 GHz wireless node for testing, results show that when the deployment distance between nodes is greater than twice the ranging error, the reliability of our algorithm can be guaranteed.

Research on Data Transmission Optimization Of Communication Network Based on Reliability Analysis

This paper briefly introduced the vehicular communication network, vehicular ad-hoc network (VANET), and the ant colony algorithm for path search in the network, improved the ant colony algorithm, carried out a simulation experiment on the improved ant colony algorithm on the simulation platform, and compared it with the traditional ant colony algorithm and the geographical location-based routing algorithm. The results showed that the network packet loss rate and time delay showed a tendency of increasing first and then decreasing under the three algorithms with the increase of vehicle nodes in VANET; with the increase of nodes, the network reliability under the improved ant colony algorithm showed a tendency of increasing first and then being stable, and the network reliability under the other two algorithms showed a tendency of increasing first and then decreasing; under the same number of nodes, the packet loss rate and average delay were lower, and the reliability was higher under the improved ant colony algorithm.

Movable Platform-Based Topology Detection for a Geographic Routing Wireless Sensor Network.

With the increasing adoption of the Internet-of-Things (IoT), the wireless sensors network (WSN), as an underlying application of IoT, has attracted increasing attention. Topology, the working structure used to observe WSN, is the most instinctive form in troubleshooting and has great significance to WSN management and safety. To this end, it is imperative to recover WSN topology for the purpose of network management and non-cooperative network detection. Traditional network topology recovery mainly relies on the monitoring modules installed in nodes, or an extra network attached. However, these two approaches have several limitations, such as high energy consumption for monitoring nodes, time synchronization problems, reuse failure, limitation to specific targeted networks and high cost. In this paper, we present a new approach to recover the topology of WSN that adopts location-based routing protocols, based on movable platforms. Our observation is that the network topology is consistent with the node routing, as the nodes choose the next hop according to the geological position of neighbor nodes. Hence, we calculate the cost parameters of choosing routing nodes for the targeted network according to the partial connection of the nodes. Based on those cost parameters, we can determine the topology of the whole network. More specifically, by collecting the geological position and data packets of the nodes from movable platforms, we are able to infer the topology of the WSN according to the recovered partial connection of nodes. Our approach can be easily adopted to many scenarios, especially for non-cooperative large-scale networks. The evaluation of 30 simulations shows that the accuracy of recovery is above 90%.

ENERGY EFFICIENT ROUTING PROTOCOL FOR INCREASING LIFETIME OF WIRELESS SENSOR NETWORK

In the recent years, an efficient design of a Wireless Sensor Network has become important in the area of research. The major challenges in the design of Wireless Sensor Network is to improve the network lifetime. The main difficulty for sensor node is to survive in that monitoring area for the longer time that means there is a need to increase the lifetime of the sensor nodes by optimizing the energy and distance.&#x0D; There are various existing routing protocols in which optimal routing can be achieved like Data-Centric, Hierarchical and Location-based routing protocols. In this paper, new power efficient routing protocol is being proposed that not only select the shortest path between the source node and sink node for data transmission but also maximizes the lifetime of the participating nodes by selecting the best path for sending the data packet across the network. The main objective of this research is to develop a faster algorithm to find the energy efficient route for Wireless Sensor Network. Simulation results shows that this strategy achieves long network lifetime when compared to the other standard protocols.