Greedy Perimeter Stateless Routing Research Articles

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.

PERFORMANCE ANALYSIS ON GPSR PROTOCOL IN VANETS ENVIRONMENT OF OVERLAY NETWORK AND FORWARDING NODE SELECTION METHODS

VANETs are technology in Intelligent Transport Systems (ITS) in driving safety and convenient network services for vehicle users. However, the high mobility of VANETs makes the topology change frequently, resulting in the unavailability of routes and causing communication failures between nodes. Greedy Perimeter Stateless Routing (GPSR) is a routing protocol that solves communication problems in the VANETs environment. GPSR is a geographic routing protocol that uses information on the location of neighbouring nodes and the transmission range to the nearest destination node. But, GPSR does not always find the optimal route because not all nearby nodes can forward packets to their destination during heavy traffic and many intersections.
 In this research, the overlay network and forwarding node selection methods will be used to solve problems in the GPSR routing protocol related to communication instability because of changing node positions. Based on the results of testing and analysis that has been carried out on a grid scenario with 50 nodes, the Packet Delivery Ratio results are 32.60. In contrast, the results for the real scenario with the same nodes produce a value of 64. The analysis of End to End Delay in the 50-node grid scenario produces 5.64, while the real scenario results with 50 nodes yield the value of 24.11. The analysis Routing Overhead in the grid scenario with 50 nodes produces a value of 39,978, while the results of the real scenario with 50 nodes get a value of 10,239. With the result of these two analysis methods, it is expected to increase the average value of package delivery.

Topology-Aware Resilient Routing Protocol for FANETs: An Adaptive Q-Learning Approach

Flying ad hoc networks (FANETs) play a crucial role in numerous military and civil applications since it shortens mission duration and enhances coverage significantly compared with a single unmanned aerial vehicle (UAV). Whereas, designing an energy-efficient FANETs routing protocol with a high packet delivery rate (PDR) and low delay is challenging owing to the dynamic topology changes. In this article, we propose a topology-aware resilient routing strategy based on adaptive <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 (TARRAQ) to accurately capture topology changes with low overhead and make routing decisions in a distributed and autonomous way. First, we analyze the dynamic behavior of UAVs nodes via the queuing theory, and then the closed-form solutions of neighbors’ change rate (NCR) and neighbors’ change interarrival time (NCIT) distribution are derived. Based on the real-time NCR and NCIT, a resilient sensing interval (SI) is determined by defining the expected sensing delay of network events. Besides, we also present an adaptive <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 approach that enables UAVs to make distributed, autonomous, and adaptive routing decisions, where the above SI ensures that the action space can be updated in time with low cost. The simulation results verify the accuracy of the topology dynamic analysis model, and also prove that our TARRAQ outperforms 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-based topology-aware routing (QTAR), mobility prediction-based virtual routing (MPVR), and greedy perimeter stateless routing based on energy-efficient hello (EE-Hello) in terms of 25.23%, 20.24%, and 13.73% lower overhead, 9.41%, 14.77%, and 16.70% higher PDR, and 5.12%, 15.65%, and 11.31% lower energy consumption, respectively.

A novel extended Kalman filter-based optimized routing approach for IoV environment

The development of intelligent transportation system has divulged towards traffic management, planning and control that requires precise neighboring vehicle location anticipation for information transmission. The crucial problem is to maintain QoS parameters in high speed and varying vehicular topology environment. The paper presents a novel EK-PGRP (Extended Kalman filter- Predictive Geographic Routing Protocol) routing approach to anticipate neighbor location and to select the propitious neighbor for advancing packets from source to destination vehicle using extended Kalman filter for real-time V2V communication in both urban and highway vehicular environment. This is acquired according to spatial and temporal movement attributes; every vehicle has an anticipation model to anticipate its own and neighboring vehicle mobility. Moreover, if LMP (Local Maximum Problem) state is encountered, i.e., where a vehicle is unable to locate any neighbor nearer to destination than itself to forward an information packet; then it uses predictive prediction algorithm to overcome that state. The precision, robustness and coherence attributes of the proposed routing approach are illustrated via extensive simulations. EK-PGRP is contrasted with K-PGRP (Kalman filter- Predictive Geographic Routing Protocol), PGRP (Predictive Geographic Routing Protocol) and GPSR (Greedy Perimeter Stateless Routing) routing protocols and results demonstrate that EK-PGRP outperformed most of the simulation cases and attained the minimum location error while ameliorating prediction accuracy of the vehicles in vehicular environment. The simulations were performed on MATLAB R2018a along with traffic simulator SUMO.

Research on optimal intelligent routing algorithm for IoV with machine learning and smart contract

The huge increase in the communication network rate has made the application fields and scenarios for vehicular ad hoc networks more abundant and diversified and proposed more requirements for the efficiency and quality of data transmission. To improve the limited communication distance and poor communication quality of the Internet of Vehicles (IoV), an optimal intelligent routing algorithm is proposed in this paper. Combined multi-weight decision algorithm with the greedy perimeter stateless routing protocol, designed and evaluated standardized function for link stability. Linear additive weighting is used to optimize link stability and distance to improve the packet delivery rate of the IoV. The blockchain system is used as the storage structure for relay data, and the smart contract incentive algorithm based on machine learning is used to encourage relay vehicles to provide more communication bandwidth for data packet transmission. The proposed scheme is simulated and analyzed under different scenarios and different parameters. The experimental results demonstrate that the proposed scheme can effectively reduce the packet loss rate and improve system performance.

LDAB-GPSR: Location PreDiction with Adaptive Beaconing – Greedy Perimeter Stateless Routing Protocol for Mobile Ad Hoc Networks

In mobile ad-hoc networks (MANET), nodes are randomly distributed and move freely, and hence the network may face rapid and unexpected topological changes. In this paper, an improved greedy perimeter stateless routing protocol, called “LDAB-GPSR”, is proposed. LDAB-GPSR mainly focuses on maximizing the packet delivery ratio while minimizing the control overhead. In order to accomplish this, two techniques are introduced, the first one is the location prediction technique in which the greedy forwarding strategy is improved by choosing more stable routes for data forwarding. The second one is the adaptive beaconing technique in which the slow start algorithm is employed to adapt the beacon packet interval time based on the mobility of nodes and the data traffic load instead of using the periodic beaconing strategy. These two strategies together improve the overall performance of the GPSR routing protocol. The performance of the new proposed protocol is evaluated by carrying out several NS-2.35 simulation experiments. The simulation results show that LDAB-GPSR protocol outperforms the GPSR+Predict protocol in terms of packet delivery ratio, control traffic overhead, end to end delay, and throughput. The ratios of enhancement approaches 40%.

Coalitional Dynamic Graph Game for Aeronautical Ad Hoc Network Formation

Aeronautical <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">ad hoc</i> networking (AANET) of the air vehicles is envisioned to support future enhanced applications, such as free flight and in-flight Internet, and AANET serves as the middle layer of the air–space–ground integrated network, bridging the space and the ground components. However, intermittent connectivity is the greatest challenge to an AANET. To deal with the intermittence, the air vehicle acts as a relay in an AANET using the buffer onboard to temporally cache the data when an interruption occurs, known as opportunistic transmission. For the highly dynamic topology of an AANET, we use a sampled dynamic graph to capture significant variations while ignoring trivial changes for avoiding extra complexity. And thus we formulate a coalitional game incorporating with the dynamic graph for the AANET to obtain the optimal transmission schedule in terms of the effective throughput with limited transmission delay. The corresponding coalitional dynamic graph game algorithm will then generate an approximately optimal AANET formation, which converges to Nash equilibrium within finite iterations. The simulations conducted with the real flight data show that 700 Mb of buffer size onboard and 1400 Mb of buffer in the Internet gateway station (IGS) are the optimal settings for the opportunistic transmission, and the coalitional dynamic graph game algorithm outperforms the geographic location-based greedy perimeter stateless routing algorithm in terms of the total received data amounts.