Greedy Perimeter Stateless Routing Research Articles

Performance Evaluation of Routing Algorithm in Satellite Self-Organizing Network on OMNeT++ Platform

Self-organizing networks of small satellites have gradually gained attention in recent years. However, self-organizing networks of small satellites have high topological change frequency, large transmission delay, and complex communication environments, which require appropriate networking and routing methods. Therefore, this paper, considering the characteristics of satellite networks, proposes the shortest queue length-cluster-based routing protocol (SQL-CBRP) and has built a satellite self-organizing network simulation platform based on OMNeT++. In this platform, functions such as the initial establishment of satellite self-organizing networks and cluster maintenance have been implemented. The platform was used to verify the latency and packet loss rate of SQL-CBRP and to compare it with Dijkstra and Greedy Perimeter Stateless Routing (GPSR). The results show that under high load conditions, the delay of SQL-CBRP is reduced by up to 4.1%, and the packet loss rate is reduced by up to 7.1% compared to GPSR. When the communication load is imbalanced among clusters, the delay of SQL-CBRP is reduced by up to 12.7%, and the packet loss rate is reduced by up to 16.7% compared to GPSR. Therefore, SQL-CBRP performs better in networks with high loads and imbalance loads.

An adaptive and multi-path greedy perimeter stateless routing protocol in flying ad hoc networks

In recent years, flying ad hoc networks (FANET), formed from unmanned aerial vehicles (UAVs), have absorbed the attention of academic and industrial research communities due to their many applications in military and civilian fields. FANETs benefit from unique features, including highly moving UAVs and dynamic topological structure. Therefore, most existing routing protocols, such as the greedy perimeter stateless routing (GPSR), are not compatible with the FANET environment and its specific features. To improve the performance of GPSR in FANET, it is important to address several challenges, namely the selection of the right period for broadcasting hello messages in the network, the selection of the right criteria for selecting the next-hop node, and the improvement of reliability in the data transfer process. In this paper, an adaptive and multi-path greedy perimeter stateless routing (AM-GPSR) protocol is suggested in FANETs. It includes two new strategies, namely adaptive hello strategy and multi-path greedy forwarding strategy. The adaptive hello strategy defines a special hello broadcast period for each UAV according to its speed and error between two estimated and actual positions. Furthermore, the greedy forwarding strategy carries out a filtering operation on candidate nodes and eliminates border UAVs and those that are far from the destination. Then, candidate UAVs are prioritized based on the time to reach the destination and buffer capacity, and UAVs with higher priorities are chosen to send data packets. Finally, AM-GPSR applies a greedy multi-path forwarding strategy to increase reliability in the data transmission process. Lastly, the simulation of AM-GPSR is done via the network simulator version 2 (NS2) to evaluate its performance. This evaluation process includes two different scenarios, i.e. change in the speed of UAVs and change in their communication range. In this process, AM-GPSR is compared with three other methods, namely the aerial greedy geographic routing (AGGR) protocol, the geolocation assisted aeronautical routing protocol (AeroRP), and GPSR. This comparison shows the successful performance of AM-GPSR in terms of delivery success rate, throughput, and delay. Although the control overhead of the proposed method is more than that of AGGR.

Multi-Objective Optimized GPSR Intelligent Routing Protocol for UAV Clusters

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.

SD-GPSR: A Software-Defined Greedy Perimeter Stateless Routing Method Based on Geographic Location Information

To mitigate the control overhead of Software-Defined Mobile Ad Hoc Networks (SD-MANETs), this paper proposes a novel approach, termed Software-Defined Greedy Perimeter Stateless Routing (SD-GPSR), which integrates geographical location information. SD-GPSR optimizes routing functions by decentralizing them within the data plane of SD-MANET, utilizing the geographic location information of nodes to enhance routing efficiency. The controller is primarily responsible for providing location services and facilitating partial centralized decision-making. Within the data plane, nodes employ an enhanced distance and angle-based greedy forwarding algorithm, denoted as GPSR_DA, to efficiently forward data. Additionally, to address the issue of routing voids in the data plane, we employ the A* algorithm to compute an optimal routing path that circumvents such voids. Finally, we conducted a comparative analysis with several state-of-the-art approaches. The evaluation experiments demonstrate that SD-GPSR significantly reduces the control overhead of the network. Simultaneously, there is a notable improvement in both end-to-end latency and packet loss rate across the network.

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.

Trust and Energy Effective Framework for Wireless Sensor Networks

Sensor nodes have been manufactured from an enormous amount of very thick sensor systems. To a large extent, wireless sensor networks were powered by electricity. The sensor connection has to work under really uncertain conditions. The nodes are powerless to various types of dynamic attacks especially specific outbound and well attacks under such conditions. These attacks inject malicious packages by trading the knot. Topographical conventions of direction of wireless sensor connections were created by thinking about the safety and power angle aspects of these assaults. In this article, a directing convention named energy-efficient and confidence implanted greedy perimeter stateless routing algorithm (EETGPSR) suggested for wireless sensor connections to join confidence systems in power-aware greedy perimeter stateless routing algorithm (EGPSR). The results show that EETGPSR beats EGPSR by reducing maintenance and improving the connection delivery ratio.

A Novel Optimized Link-State Routing Scheme with Greedy and Perimeter Forwarding Capability in Flying Ad Hoc Networks

A flying ad hoc network (FANET) is formed from a swarm of drones also known as unmanned aerial vehicles (UAVs) and is currently a popular research subject because of its ability to carry out complicated missions. However, the specific features of UAVs such as mobility, restricted energy, and dynamic topology have led to vital challenges for making reliable communications between drones, especially when designing routing methods. In this paper, a novel optimized link-state routing scheme with a greedy and perimeter forwarding capability called OLSR+GPSR is proposed in flying ad hoc networks. In OLSR+GPSR, optimized link-state routing (OLSR) and greedy perimeter stateless routing (GPSR) are merged together. The proposed method employs a fuzzy system to regulate the broadcast period of hello messages based on two inputs, namely the velocity of UAVs and position prediction error so that high-speed UAVs have a shorter hello broadcast period than low-speed UAVs. In OLSR+GPSR, unlike OLSR, MPR nodes are determined based on several metrics, especially neighbor degree, node stability (based on velocity, direction, and distance), the occupied buffer capacity, and residual energy. In the last step, the proposed method deletes two phases in OLSR, i.e., the TC message dissemination and the calculation of all routing paths to reduce routing overhead. Finally, OLSR+GPSR is run on an NS3 simulator, and its performance is evaluated in terms of delay, packet delivery ratio, throughput, and overhead in comparison with Gangopadhyay et al., P-OLSR, and OLSR-ETX. This evaluation shows the superiority of OLSR+GPSR.

RC-LAHR: Road-Side-Unit-Assisted Cloud-Based Location-Aware Hybrid Routing for Software-Defined Vehicular Ad Hoc Networks.

The reliability of the communication link is quite common and challenging to handle as the topology changes frequently in vehicular ad hoc networks (VANETs). Another problem with VANETs is that the vehicles are from different manufacturers. Hence, the heterogeneity of hardware is obvious. These heterogeneity and reliability problems affect the message dissemination in VANETs. This paper aims to address these challenges by proposing a robust routing protocol capable of ensuring reliable, scalable, and heterogeneity-tolerant message dissemination in VANETs. We first introduced a hybrid hierarchical architecture based on software-defined networking (SDN) principles for VANETs, leveraging SDN's inherent scalability and adaptability to heterogeneity. Further, a road-side unit (RSU)-assisted cloud-based location-aware hybrid routing for software-defined VANETs (SD-VANETs) that we call RC-LAHR was proposed. RC-LAHR was rigorously tested and analyzed for its performance in terms of packet delivery ratio (PDR) and end-to-end delay (EED), along with a comprehensive assessment of network traffic and load impacts on cloud infrastructure and RSUs. The routing protocol is compared with state-of-the-art protocols, Greedy Perimeter Stateless Routing (GPSR) and Opportunistic and Position-Based Routing (OPBR). The proposed routing protocol performs well as compared to GPSR and OPBR. The result shows that the EED is reduced to 20% and the PDR is increased to 30%. The network reliability is also increased up to 5% as compared to the OPBR and GPSR.

Implementation of Network Security for Intrusion Detection & Prevention System in IoT Networks: Challenges & Approach

EPSO-GPSR (Enhanced Particle Swarm Optimization-based Load Balancing with Geographic Routing using Greedy Perimeter Stateless Routing), a unique strategy designed specifically for WSNs, is presented in this work. Using Enhanced Particle Swarm Optimization (EPSO) to provide load balancing across sensor nodes, the proposed EPSO-GPSR technique reduces energy disparities and increases the operational lifetime of the network. Additionally, it interfaces with the geographic routing protocol Greedy Perimeter Stateless Routing (GPSR) to enable effective data forwarding based on geographic locations, minimizing communication overhead and improving scalability. EPSO-GPSR's efficacy is shown against traditional load balancing and routing methods via comprehensive simulations and performance assessments. The network lifetime, energy efficiency, throughput, packet delivery ratio, and delay have all significantly showed better performance, according to the results. Additionally, the EPSO-GPSR algorithm demonstrates robustness against node failures and issues related to scalability, indicating a significant potential for real-world implementation in various WSN scenarios.

KOGPSR: A 3D GPSR algorithm using adaptive Kalman prediction for FANETs with omnidirectional antenna

Nowadays, flying ad hoc network (FANET) has captured great attention for its huge potential in military and civilian applications. However, the high-speed movement of unmanned aerial vehicles (UAVs) in three-dimensional (3D) space leads to fast topology change in FANET and brings new challenges to traditional routing mechanisms. To improve the performance of packet transmission in the 3D high dynamic FANETs, we propose a 3D greedy perimeter stateless routing (GPSR) algorithm using adaptive Kalman prediction for FANETs with omnidirectional antenna (KOGPSR). Especially, in data forwarding part of the KOGPSR, we propose a new link metric for greedy forwarding based on a torus-shaped radiation pattern of the omnidirectional antenna of UAVs, and a restricted flooding strategy is introduced to solve the 3D void node problem in geographic routing. In addition, in order to enhance the accuracy of the location information of high dynamic UAVs, we design an adaptive Kalman algorithm to track and predict the motion of UAVs. Finally, a FANET simulation platform based on OPNET is built to depict the performance of the KOGPSR algorithm. The simulation results show that the proposed KOGPSR algorithm is more suitable for the actual 3D high dynamic FANET.

A Novel Secure Routing Design Based on Physical Layer Security in Millimeter-Wave VANET

With the continuous development of millimeter-wave communication technology, new requirements such as ultra-reliability and higher data rates pose new challenges to the security issues of traditional cryptographic encryption in vehicular ad hoc networks (VANET). Physical layer security uses the characteristics of different wireless channels to protect the information security. In this paper, we propose a novel VANET routing mechanism that utilizes physical layer security to improve the secrecy performance, which is compatible with the millimeter-wave vehicular network. Specifically, we design a new secure routing selection factor, the utility function, that takes into account the effects of both secrecy rate and single-hop transmission distance to achieve the hop selection. In addition, we propose a novel routing mechanism and design a waiting mechanism based on the utility function. Compared with the traditional routing algorithms, the greedy perimeter stateless routing (GPSR) and Dijkstra simulation results illustrate that our design achieves superior performance in secrecy performance and dynamic adaptability.

AFB-GPSR: Adaptive Beaconing Strategy Based on Fuzzy Logic Scheme for Geographical Routing in a Mobile Ad Hoc Network (MANET)

In mobile ad hoc networks (MANETs), geographical routing provides a robust and scalable solution for the randomly distributed and unrestricted movement of nodes. Each node broadcasts beacon packets periodically to exchange its position with neighboring nodes. However, reliable beacons can negatively affect routing performance in dynamic environments, particularly when there is a sudden and rapid change in the nodes’ mobility. Therefore, this paper suggests an improved Greedy Perimeter Stateless Routing Protocol, namely AFB-GPSR, to reduce routing overhead and increase network reliability by maintaining correct route selection. To this end, an adaptive beaconing strategy based on a fuzzy logic scheme (AFB) is utilized to choose more optimal routes for data forwarding. Instead of constant periodic beaconing, the AFB strategy can dynamically adjust beacon interval time with the variation of three network parameters: node speed, one-hop neighbors’ density, and link quality of nodes. The routing evaluation of the proposed protocol is carried out using OMNeT++ simulation experiments. The results show that the AFB strategy within the GPSR protocol can effectively reduce the routing overhead and improve the packet-delivery ratio, throughput, average end-to-end delay, and normalized routing load as compared to traditional routing protocols (AODV and GPSR with fixed beaconing). An enhancement of the packet-delivery ratio of up to 14% is achieved, and the routing cost is reduced by 35%. Moreover, the AFB-GPSR protocol exhibits good performance versus the state-of-the-art protocols in MANET.

A greedy perimeter stateless routing method based on a position prediction mechanism for flying ad hoc networks

Today, unmanned aerial vehicles (UAVs) are very popular in military and commercial applications as well as academic research. Flying ad hoc network (FANET) is a new type of ad hoc network that organizes small drones in an ad hoc form. The movement in 3D space, high mobility, frequent topological changes, restricted resources, and low density are the features of these networks. These features cause serious challenges in designing an appropriate routing approach for these networks. In this paper, a greedy perimeter stateless routing method based on a position prediction mechanism called GPSR+ is proposed for FANETs. This scheme employs a position forecast strategy to approximate the future position of UAVs and modifies the propagation period of hello messages based on this strategy to achieve better adaptability to the dynamic network. In addition, GPSR+ chooses a set of candidate UAVs using a new method called the spherical removal technique to decide on the next-hop UAVs in the routing process. Finally, the most stable UAV toward the destination will be chosen from the candidate set to act as the next-hop. The simulation results show that GPSR+ grows the packet delivery ratio in FANET and extends network longevity because it increases path stability and improves energy consumption. However, the delay in GPSR+ is high.

Weight-Based PA-GPSR Protocol Improvement Method in VANET.

Vehicle Ad-hoc network (VANET) can provide technical support and solutions for the construction of intelligent and efficient transportation systems, and the routing protocol directly affects the efficiency of VANET. The rapid movement of nodes and uneven density distribution affect the routing stability and data transmission efficiency in VANET. To improve the local optimality and routing loops of the path-aware greedy perimeter stateless routing protocol (PA-GPSR) in urban sparse networks, a weight-based path-aware greedy perimeter stateless routing protocol (W-PAGPSR) is proposed. The protocol is divided into two stages. Firstly, in the routing establishment stage, the node distance, reliable node density, cumulative communication duration, and node movement direction are integrated to indicate the communication reliability of the node, and the next hop node is selected using the weight greedy forwarding strategy to achieve reliable transmission of data packets. Secondly, in the routing maintenance stage, based on the data packet delivery angle and reliable node density, the next hop node is selected for forwarding using the weight perimeter forwarding strategy to achieve routing repair. The simulation results show that compared to the greedy peripheral stateless routing protocol (GPSR), for the maximum distance-minimum angle greedy peripheral stateless routing (MM-GPSR) and PA-GPSR protocols, the packet loss rate of the protocol is reduced by an average of 24.47%, 25.02%, and 14.12%, respectively; the average end-to-end delay is reduced by an average of 48.34%, 79.96%, and 21.45%, respectively; and the network throughput is increased by an average of 47.68%, 58.39%, and 20.33%, respectively. This protocol improves network throughput while reducing the average end-to-end delay and packet loss rate.

UF‐GPSR: Modified geographical routing protocol for flying ad‐hoc networks

AbstractFlying Ad‐hoc Networks (FANETs) has recently gained significant exposure for their emerging military, civil, and commercial applications. In FANETs, all Unmanned Aerial Vehicles (UAVs) can communicate within a restricted wireless communication range without fixed infrastructure. However, the highly dynamic nature of UAVs imposes a significant issue in FANET's communications. Therefore, designing an effective routing strategy is always necessary for sustaining appropriate network performance in FANETs. This paper is interested in modifying Greedy Perimeter Stateless Routing (GPSR) protocol named Utility Function based Greedy Perimeter Stateless Routing (UF‐GPSR) protocol for FANETs. The proposed approach optimizes the greedy forwarding strategy by considering multiple vital parameters of UAVs: residual energy ratio, distance degree, movement direction, link risk degree, and speed, respectively. The proposed UF‐GPSR applies the utility function on these parameters to enhance the routing performance by selecting optimal next‐hop within the communication range. The effectiveness of the proposed work is mathematically evaluated and then simulated through the NS‐3.23 simulator. The experimental outcomes verify that the proposed routing approach enhances the packet delivery ratio and throughput while decreasing packet drop ratio and delay compared to the other routing approaches: GPSR and GPSR‐PPU.

An Energy-Efficient Protocol based on Recursive Geographic Forwarding Mechanisms for Improving Routing Performance in WSN

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

A self-adapting greedy forwarding algorithm for MANETs

As the population application of GPS, some greedy forwarding algorithms based on geographic information for MANETs (mobile ad hoc networks) are proposed in recent years. These algorithms have been well-designed from different aspects to improve its performance. On the basis of analysis of these algorithms, this paper presents modified methods to address some issues of GPSR (greedy perimeter stateless routing): dynamically adjusting the time interval of sending beacons according to the radio transmission; not only considering the distance between each neighbor and the destination, but also the neighbor node surviving ratio. Some relevant algorithms are described in the paper as well. The simulation results show the improved routing algorithm excels GPSR markedly in terms of delivery ratio and routing overhead while the transmission range is larger or the motion velocity of nodes is greater.

NOMA-Assisted Routing Algorithm Design for UAV Ad Hoc Relay Networks

Unmanned aerial vehicle (UAV) ad hoc networks can be deployed flexibly and rapidly without any infrastructure, so as to play an irreplaceable role in postdisaster relief. However, the dynamic topology and energy constraints of UAVs always bring new challenges to the design of effective network architectures and routing strategies. In this article, a three-layer UAV network architecture is constructed, and the UAV channel models for the different layers are discussed categorically. A greedy perimeter comprehensive evaluation routing (GCER) algorithm is designed on the basis of geographic routing greedy perimeter stateless routing (GPSR). By estimating the energy, link stability, and data throughput of the UAV neighboring nodes, the optimal next-hop UAV node is synthetically evaluated using the analytic hierarchy process (AHP). In particular, the use of nonorthogonal multiple access (NOMA) technology in ad hoc networks is considered, and a nonconvex optimization problem for maximizing the throughput estimation of UAV relay nodes based on NOMA is proposed to solve for the optimal allocation of UAV transmission power in routing. Numerical results show that the proposed GCER routing algorithm has significant advantages over GPSR in improving link stability. The use of NOMA access technology in UAV ad hoc networks has a significant increase in the throughput of the data links.

Multi-index joint node selection protocol in UAV ad hoc network

In the application scenario of a UAV ad hoc network, aiming at the problems of low packet forwarding success rate and premature death of some nodes in greedy perimeter stateless routing (GPSR) protocol, a multi-index joint node selection-GPSR protocol (MT-GPSR) is proposed. Based on greedy forwarding, MT-GPSR protocol comprehensively considers the link holding time of adjacent nodes, the residual energy of adjacent nodes, and the node degree to jointly select the next hop node, and proposes an AHP maximum entropy criterion weighting algorithm, which reasonably weights the node index value, adds the weighted index values to obtain the selection priority value, and selects the neighbor node whose priority value is the best under the weighting condition as the next hop node for data forwarding, so as to improve the efficiency of data forwarding. At the same time, the network life is prolonged. The simulation results show that compared with the GPSR algorithm and GPSR-NMP algorithm, this algorithm ensures stable communication between UAVs, improves the network communication quality, and improves the network lifetime.

Improved trustworthy, speed, and energy-efficient GPSR routing algorithm in large-scale WSN

Geographic routing networks broadcast their readiness to modify the routing protocol using the traditional methodology in wireless sensor network (WSN). These are effectively dealt with to preserve electricity. Researchers propose the Modified - Greedy Perimeter Stateless Routing (GPSR) system for efficient sensor network connection to determine the optimal path based on energy usage and avoids malicious activity. Depending on the limited memory nodes and battery power, rapid dynamic topology, and unpredictable equipment, the deployment of GPSR in sensor networks faces several challenges. The cost of communication across the network is close to ideal because of our Modified-GPSR method. The simulation results show that minimizing power and latency considerably increases the durability of the sensor node system. The study also focuses on estimating implementation costs and learning about design, implementation, and statistical practice.