Random Waypoint Model Research Articles

Performance Analysis of Non-Realistic Routing Protocol using Random Waypoint Model in MANET

A mobile ad hoc network (MANET) is a collection of wireless nodes connected via wireless networks and has no set structure. MANETs feature a self-organized routing topology in which mobile nodes are free to move, making it difficult and crucial to construct a stable and reliable network. Thus, failure of the route is also regarded as a prime factor affecting the efficiency of any MANET routing protocol. The breaking of the connection between two routes or more nodes will cause the failure of the route specifically in the non-realistic routing protocol. In a network of mobile nodes, the link break is mainly based on the mobility of individual nodes. Therefore, the objective of this research is to investigate the performance of proactive DSDV and reactive AODV routing protocol using the Random Waypoint(RWP) mobility model in MANET. NS-2 network simulator is used to simulate the MANET environment and BonnMotion is to create a movement of mobile nodes that integrate with the routing protocol. The network performance metrics used are throughput, packet delivery ratio, and average end-to-end delay. In addition, three simulation scenarios have been conducted to compare AODV and DSDV routing protocols with varying numbers of nodes, a comparison of AODV and DSDV routing protocols with varying pause time, and a comparison of AODV and DSDV routing protocols with varying mobility speed. The result from the three scenarios analysed and concluded that the RWP mobility model with AODV gives a better performance of throughput with 869.69 kbps and Packet Delivery Ratio (PDR) with 83.00% meanwhile, RWP with DSDV is better for the average end-to-end delay(EED) with 212.970 bps.

Mobile-IRS assisted next generation UAV communication networks

Prior research on intelligent reflection surface (IRS)-assisted unmanned aerial vehicle (UAV) communications has focused on a fixed location for the IRS or mounted on a UAV. The assumption that the IRS is located at a fixed position will prohibit mobile users from maximizing many wireless network benefits, such as data rate and coverage. Furthermore, assuming that the IRS is placed on a UAV is impractical for various reasons, including the IRS’s weight and size and wind speed in severe weather. Unlike previous studies, this study assumes a single UAV and an IRS mounted on a mobile ground vehicle (M-IRS) to be deployed in an Internet-of-Things (IoT) 6G wireless network to maximize the average data rate. Such a methodology for providing wireless coverage using an M-IRS assisted UAV system is expected in smart cities. In this paper, we formulate an optimization problem to find an efficient trajectory for the UAV, an efficient path for the M-IRS, and users’ power allocation coefficients that maximize the average data rate for mobile ground users. Due to its intractability, we propose efficient techniques to help find the optimization problem’s solution. First, we show that our dynamic power allocation technique outperforms the fixed power allocation technique in the network average sum rate. Then we employ the individual movement model (Random Waypoint Model) in order to represent the users’ movements inside the coverage area. Finally, we propose an efficient approach using a Genetic Algorithm (GA) to find an efficient trajectory for the UAV and an efficient path for the M-IRS to provide wireless connectivity for mobile users during their movement. We demonstrate through simulations that our methodology can enhance the average data rate by 15% on average compared with the static IRS and by 25% on average compared to without the IRS system.

Intelligent Connectivity Through RIS-Assisted Wireless Communication: Exact Performance Analysis With Phase Errors and Mobility

The current research offers only approximations for evaluating the performance of wireless systems that use reconfigurable intelligent surfaces (RIS) over generalized fading channels with phase error caused by imperfect phase compensation at the RIS. This paper presents an exact analysis of RIS-assisted vehicular communication considering uniformly distributed phase error and generalized fading channels with a coherent combining of received signals reflected by RIS elements and direct transmissions from the source terminal. We use a generalized- <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$K$</tex-math></inline-formula> shadowed distribution for the direct link and asymmetrical channels for the RIS-assisted transmission with <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\kappa$</tex-math></inline-formula> - <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\mu$</tex-math></inline-formula> distribution for the first link and double generalized Gamma (dGG) distribution for the second link, combined with a statistical random waypoint (RWP) model for the moving vehicle. We employ a novel approach to represent the probability density function (PDF) and cumulative distribution function (CDF) of the resultant channel in terms of a single univariate Fox-H function and use the multivariate Fox-H approach to develop an exact statistical analysis of the end-to-end signal-to-noise ratio (SNR) for the RIS-assisted system. We also use the inequality between the arithmetic and geometric means to simplify the statistical results of the considered system in terms of the univariate Fox-H function. Our analysis also provides exact, upper bound, and asymptotic expressions of the outage probability and average bit-error-rate (BER) performance using the derived density and distribution functions. We conduct computer simulations in various practically relevant scenarios to assert that mitigating phase errors is achievable by augmenting the number of elements in the RIS module and employing a higher quantization level.

Improved physical layer secrecy fairness in a realistic indoor NOMA VLC network under users’ mobility

This paper investigates the improvement of the secrecy rate fairness in a cellular non-orthogonal multiple access (NOMA) visible light communication (VLC) network. We formulate the users’ secrecy rate by taking into account the users (legitimate and illegitimate) mobility according to the random way-point (RWP) model. We propose an optimization problem to maximize the minimum secrecy rate for two legitimate users per cell, and then we generalize it for an arbitrary number of users. Moreover, utilizing secrecy considerations, we customize two well-known power allocation methods of fixed power allocation (FPA) and gain ratio power allocation (GRPA) as benchmarks for comparison of the proposed maximization power allocation method. Our numerical results demonstrate the superiority of the proposed power allocation algorithm compared with FPA and GRPA methods. Moreover, for the higher number of users, our results indicate the advantages of the proposed algorithm over modified FPA and GRPA methods. Finally, we investigate the effect of the optical receiver’s field of view fluctuations on the performance of the VLC network.

Performance analysis of intelligent reflecting surface‐assisted mobile wireless networks subjected to generalized Gaussian noise

SummaryDifferent from the prior works, this paper presents the performance analysis of an intelligent reflecting surface (IRS)‐assisted communication link in a static and mobile scenario impaired by Rayleigh fading and additive white generalized Gaussian noise (AWGGN). Precisely, the IRS is configured as an intelligent access point, and the mobile behavior of the nodes is characterized by the random waypoint (RWP) model. To this end, closed‐form expressions of average bit error rate (BER), average channel capacity (ACC), and outage probability (OP) in both static and mobile scenarios are obtained. To gain further insight into the system performance at high signal‐to‐noise ratio (SNR), asymptotic expressions are obtained. Moreover, the effect of the number of reflective elements ( ) and the shaping parameter ( ) on the system performance is thoroughly studied. The results indicate that introduction of IRS leads to significant improvement in the overall system performance. The derived results are corroborated with Monte Carlo simulations.

Chase–escape in dynamic device-to-device networks

AbstractWe feature results on global survival and extinction of an infection in a multi-layer network of mobile agents. Expanding on a model first presented in Cali et al. (2022), we consider an urban environment, represented by line segments in the plane, in which agents move according to a random waypoint model based on a Poisson point process. Whenever two agents are at sufficiently close proximity for a sufficiently long time the infection can be transmitted and then propagates into the system according to the same rule starting from a typical device. Inspired by wireless network architectures, the network is additionally equipped with a second class of agents able to transmit a patch to neighboring infected agents that in turn can further distribute the patch, leading to chase–escape dynamics. We give conditions for parameter configurations that guarantee existence and absence of global survival as well as an in-and-out of the survival regime, depending on the speed of the devices. We also provide complementary results for the setting in which the chase–escape dynamics is defined as an independent process on the connectivity graph. The proofs mainly rest on percolation arguments via discretization and multiscale analysis.

The Impact of Mobility on Physical Layer Security of 5G IoT Networks

Internet of Things (IoT) is rapidly spreading and reaching a multitude of different domains, since the fifth generation (5G) wireless technologies are the key enablers of many IoT applications. It is hence apparent that the broadcast nature of IoT devices makes data security unprecedentedly critical. Compared with traditional cryptography algorithms, which cannot cater for the features of IoT devices characterized by the severe limits in terms of energy, computation and storage capabilities, physical layer security (PLS) has been regarded as a promising solution to facilitate secure communications by exploiting the intrinsic randomness of the wireless medium. However, most of previous works assumed that all devices are static, and the impact of mobility on PLS deserves further investigation. In this paper, applying two types of random mobile models, i.e., the models of Random WayPoint (RWP) and Random Direction (RD), we study the impact of mobility on PLS in a scenario with three types of wireless devices (i.e., a destination, multiple interferers and an eavesdropper). Specifically, we establish an analytical framework for secrecy transmission capacity (STC), a fundamental metric in the study of PLS, under RWP and RD models. To the best of our knowledge, this is the first paper to derive STC and present the condition to achieve a positive STC with the consideration of mobility. We conclude that the RWP mobile destination can achieve a higher STC than that achievable in RD mobile and static scenarios, while RWP mobile eavesdropper is a challenging scenario to obtain a positive STC. Therefore, we propose an effective secrecy improvement strategy for the latter. Simulation validates the theoretical analyses.

Heterogeneous Ultradense Networks With Traffic Hotspots: A Unified Handover Analysis

With the ever-growing communication demands and the unceasing miniaturization of mobile devices, the Internet of Things is expanding the amount of mobile terminals to an enormous level. To deal with such numbers of communication data, plenty of base stations (BSs) need to be deployed. However, denser deployments of heterogeneous networks (HetNets) lead to more frequent handovers, which could increase network burden and degrade the users experience, especially in traffic hotspot areas. In this paper, we develop a unified framework to investigate the handover performance of wireless networks with traffic hotspots. Using the stochastic geometry, we derive the theoretical expressions of average distances and handover metrics in HetNets, where the correlations between users and BSs in hotspots are captured. Specifically, the distributions of macro cells are modeled as independent Poisson point processes (PPPs), and the two tiers of small cells outside and inside the hotspots are modeled as PPP and Poisson cluster process (PCP) separately. A modified random waypoint (MRWP) model is also proposed to eliminate the density wave phenomenon in traditional models and to increase the accuracy of handover decision. By combining the PCP and MRWP model, the distributions of distances from a typical terminal to the BSs in different tiers are derived. Afterwards, we derive the expressions of average distances from a typical terminal to different BSs, and reveal that the handover rate, handover failure rate, and ping-pong rate are deduced as the functions of BS density, scattering variance of clustered small cell, user velocity, and threshold of triggered time. Simulation results verify the accuracy of the proposed analytical model and closed-form theoretical expressions.

A New Objective Function for RPL Based on Combined Metrics in Mobile IoT

To satisfy the quality of service requirements for some applications in the Internet of Things (IoT) network with mobile nodes, routing protocols must be adaptable to make better routing decisions. Routing Protocol for Lowpower and Lossy Networks (RPL) is one of the routing protocols that support metrics and constraints while building a Destination Oriented Directed Acyclic Graphs (DODAG) using a specific Objective Function (OF). However, RPL metrics that use standard OFs do not guarantee the performance criteria for a specific mobile IoT in terms of received and lost packets, overhead, throughput and power consumption. In this paper, we propose a new version of mrhof based on a combination of metrics such as total energy, the number of neighbors, and expected transmission count (ETX) to evaluate RPL performances in a mobile context. Then, we compare the assessment of this function to existing OFs based on various mobility models (Random Waypoint (RWP), Reference Point Group Mobility (RPGM), Nomadic) and node densities. The results show that this new function is more efficient than the standards OF in terms of packets received and packets lost with Random Way Point and RPGM models. Regardless of the number of nodes, it also reduces ETX and traffic overhead for all mobility models, as well as convergence time in the Random Waypoint environment. Furthermore, this new function contributes to the improvement of Rtmetric, the enhancement of throughput at low density only in favor of RWP and RPGM models, and an effective power consumption reduction through all densities and mobility models.

PERFORMANCE ANALYSIS OF ROUTING PROTOCOL IN MOBILE AD-HOC NETWORKS

Routing in a mobile ad hoc network (MANET) is a difficult task due to the constantly changing network topology and the absence of a fixed infrastructure. In such a scenario, mobile hosts can act as both hosts and routers, forwarding packets for other mobile nodes in the network. Routing protocols used in MANETs must be able to adapt to frequent changes in topology, while minimizing the impact on wireless resources. The AODV, DSR, ZRP and DYMO protocol are specifically designed for mobile nodes in wireless multihop ad hoc networks. It is capable of adapting to the changing network topology and determining unicast routes between nodes within the network. This paper presents a comparative analysis of commonly used routing protocols in terms of key performance metrics, including Broadcast sent packets, CTS packets sent, Packet drops due to re-transmission,RTS re-transmission the timeout , Unicast packet received ,RTS packets sent,Packet due to ACK timeout, ACK packet sent, Unicast sent packet and Broadcast Packet Received. The study's findings demonstrate that the routing protocols' performance is influenced by the network's size, node density, and mobility patterns. These routing protocols showing the simulation performance using random waypoint model on qualnet simulator.

IoT-Enabled Precision Agriculture: Developing an Ecosystem for Optimized Crop Management

The Internet of Things (IoT) has the potential to revolutionize agriculture by providing real-time data on crop and livestock conditions. This study aims to evaluate the performance scalability of wireless sensor networks (WSNs) in agriculture, specifically in two scenarios: monitoring olive tree farms and stables for horse training. The study proposes a new classification approach of IoT in agriculture based on several factors and introduces performance assessment metrics for stationary and mobile scenarios in 6LowPAN networks. The study utilizes COOJA, a realistic WSN simulator, to model and simulate the performance of the 6LowPAN and Routing protocol for low-power and lossy networks (RPL) in the two farming scenarios. The simulation settings for both fixed and mobile nodes are shared, with the main difference being node mobility. The study characterizes different aspects of the performance requirements in the two farming scenarios by comparing the average power consumption, radio duty cycle, and sensor network graph connectivity degrees. A new approach is proposed to model and simulate moving animals within the COOJA simulator, adopting the random waypoint model (RWP) to represent horse movements. The results show the advantages of using the RPL protocol for routing in mobile and fixed sensor networks, which supports dynamic topologies and improves the overall network performance. The proposed framework is experimentally validated and tested through simulation, demonstrating the suitability of the proposed framework for both fixed and mobile scenarios, providing efficient communication performance and low latency. The results have several practical implications for precision agriculture by providing an efficient monitoring and management solution for agricultural and livestock farms. Overall, this study provides a comprehensive evaluation of the performance scalability of WSNs in the agriculture sector, offering a new classification approach and performance assessment metrics for stationary and mobile scenarios in 6LowPAN networks. The results demonstrate the suitability of the proposed framework for precision agriculture, providing efficient communication performance and low latency.

RANDOM WAYPOINT MOBILITY ROUTING ALGORITHM FOR MOBILE SENSOR NETWORKS

Mobile Sensor Network an emerging trend in recent network platform. Random waypoint mobility routing proposed on virtual infrastructure based mobile sensor network. Routing is highly challenging task in mobile sensor network, in which the random waypoint model used to ascertain through put and energy depletion. Sensor network classified into multiple regions. Scheduled time slot is assigned for data transmission in between source to sink. Routing table is periodically updated with its neighborhood information. In order to discovers sink node random waypoint mobility routing algorithm checks either clockwise or anti clockwise in the region to find an optimal route for reliable data transmission. In comparison to other cutting-edge cluster-based routing protocols, the effectiveness of the suggested technique assessed using the essential network characteristics. In addition proposed algorithm reduces normalized routing overhead and reselection of region head by varying the node density in the network.

Multi-Scale Fusion Localization Based on Magnetic Trajectory Sequence

Magnetic fingerprint has a multitude of advantages in the application of indoor positioning, but as a weak magnetic field, the dynamic range of the data is limited, which exerts direct influence on the positioning accuracy. Aiming at resolving the problem wherein the indoor magnetic positioning results tremendously rest with the magnetic characteristics, this paper puts forward a method based on deep learning to fuse the temporal and spatial characteristics of magnetic fingerprints, to fully explore the magnetic characteristics and to obtain stable and trustworthy positioning results. First and foremost, the trajectory of the acquisition area is extracted by adopting the ameliorated random waypoint model, and the simulation of pedestrian trajectory is completed. Then, the magnetic sequence is obtained by mapping the magnetic data. Aside from that, considering the scale characteristics of the sequence, a scale transformation unit is designed to obtain multi-scale features. At length, the neural network self-attention mechanism is adopted to fuse multiple features and output the positioning results. By probing into the positioning results of dissimilar indoor scenes, this method can adapt to diverse scenes. The average positioning error in a corridor, open area and complex area reaches 0.65 m, 0.93 m and 1.38 m respectively. The addition of multi-scale features has certain reference value for ameliorating the positioning performance.

Temporal Correlation and Joint Coverage for Finite 3-D UAV Networks With Blockage Effects

When serving urban hotspots, UAVs are distributed in finite three-dimensional (3D) area and the building blockage further aggravates signal and topology fluctuation, which has not been modeled and analyzed in current works. In this letter, considering the fluctuation of the topology and channel, the exact expressions of temporal correlation and joint coverage are derived, where all UAVs move independently in spatial and vertical directions according to random waypoint (RWP) mobility process within finite 3D area and the impact of building blockage effect is theoretically characterized. Specifically, the distance distribution between the UAV and user is derived based on the steady-state non-uniform distribution of the RWP model instead of simplifying with uniform distribution. In addition, since the flexibility of UAV in height, an air-to-ground channel considering the actual 3D blockage effect is applied and the blockage is not only angle-dependent but also distance-dependent. The numerical results analyze the effects of buildings’ geometrical parameters and finite 3D area size parameters on temporal correlation and joint coverage.

A Random Waypoint Model for Route Avoidance with Zone Routing Protocol in Wireless Sensor Network

A Random Waypoint Model for Route Avoidance with Zone Routing Protocol in Wireless Sensor Network

The impact of mobility on physical layer security in 5G uRLLC

Due to the openness nature of wireless medium, security issues have increasingly become a bottleneck that restricts the development of ultra-reliable and low-latency communications (uRLLCs). Physical layer security (PLS) technique has been proposed to fulfill the security and confidentiality of information transmission by exploiting the characteristics of the wireless channel, which caters to the features of uRLLC. Furthermore, PLS also shows great practicality in artificial intelligence field, especially in wireless intelligent networks. However, the previous works on the study of PLS ignored the significance of mobility and limited packet length constraint required by uRLLC for satisfying low latency, in this paper, we investigate the impact of mobility on the secrecy performance of uRLLC by using the Random WayPoint (RWP) model and the Random Direction (RD) model. Specifically, with the tools of stochastic geometry, to observe the impact of key system parameters on the secrecy performance, we establish the closed-form expression of connection outage probability, secrecy outage probability, and decoding error probability-based secrecy transmission capacity (DEP-STC). Furthermore, we derive the condition that achieves a positive DEP-STC under two moving models, which can offer the network designer some greatly significant insights into achieving perfect secrecy. Simulations validate our derived theoretical results, and indicate that RWP moving receiver can obtain a higher security level than RD moving one, while RWP eavesdropper can lead to a lower security.

Adaptive clustering in energy efficient routing protocol for mobile nodes in WSNs

Introduction: Wireless Sensor Networks (WSN) is a collection of large number of small sensor nodes which communicate sensed data over a radio channel covering wide geographical region. Problem statement: A number of algorithms have been developed to enhance the network lifetime of WSN by efficiently utilizing the sources of energy. The most commonly used approach is clustering that is prone to uneven load balancing and instability issues. Furthermore, topological changes in WSN structure especially with mobile nodes significantly effect network lifetime. Methodology: In this study, we have proposed an Adaptive-Cluster-based Energy Efficient Routing Protocol (A-EECBRP), which employs a novel geometrical Voronoi-based configuration to solve load balancing and mobility issues while maintaining network stability and coverage. Furthermore, energy cost function and Energy Harvesters (EH) devices were implemented to reduce energy consumption and increase network life. Moreover, the concept of handshaking and random waypoint model for nodes movement between cluster groups was examined to define mobile nodes. Results: Simulation results obtained from network analysis performed on MATLAB® showed that A-EECBRP reduced energy consumption by almost 1500 rounds as compared to LEACH-M. This significantly improved the network lifetime of WSN as compared to the LEACH-M routing protocol. Therefore, our proposed scheme provides a huge potential for implementing energy-efficient routing protocols in mobile wireless sensor networks.

Retraction Note to: Congestion control load balancing adaptive routing protocols for random waypoint model in mobile ad-hoc networks

Retraction Note to: Congestion control load balancing adaptive routing protocols for random waypoint model in mobile ad-hoc networks

Joint Information and Energy Transfer of SWIPT-Enabled Mobile Users in Wireless Networks

Extremely high reliability and energy efficiency are crucial in sixth generation (6G) mobile networks to accommodate the diverse range of end-user devices in the era of the Internet of Everything. The concept of simultaneous wireless information and power transfer (SWIPT) has been emerged as a promising solution to boost the reliability of wireless communication systems through prolonging the battery lifetime by harvesting energy from the received radio-frequency signals. In this paper, we propose a low complexity threshold-based pair switching (TbPS) technique for SWIPT in the context of large-scale cellular networks, where the multiple-antenna mobile users (MUs) employ maximum ratio combining technique and adopt the random waypoint model. Under the TbPS technique, a subset of MU’s antennas is allocated for information decoding (ID), only when their post-combiner signal-to-interference ratio, exceeds a certain threshold, while the remaining antennas are allocated for energy harvesting (EH). Contrary to traditional approaches which assume the existence of either uncorrelated or fully correlated interference, our proposed technique takes into consideration the interference correlation between nearby antennas. In order to further alleviate the inter-cell interference and energy consumption, we propose a traffic load-based sleeping (TLbS) technique in the context of finite-area network deployments, where lightly-loaded cells switch into sleep mode. By leveraging tools from stochastic geometry, we derive analytical expressions for the ID, EH as well as joint ID and EH success probability of MUs based on the proposed techniques. Our results demonstrate the optimal parameters (i.e., antenna selection and traffic load threshold) of our proposed techniques, that maximize the joint ID and EH success probability. Finally, it is shown that, by properly selecting the threshold values, both the proposed TbPS scheme and TLbS mechanism outperform the conventional techniques in terms of the SWIPT capability of the MUs.

Multipoint Relay Selection based on Stability of Spatial Relation in Mobile Ad hoc Networks

Increasing stability is one of the main objectives in designing routing protocols for Mobile Ad-Hoc Network (MANETS). Various research schemes have been addressed to this challenge and to support it. In fact, some papers have considered modifications to MPRs selection mechanism in OLSR. In this paper, the author proposes a new mechanism to elect stable and sustainable nodes relay between all nodes in MANETs. In this mechanism, a mobility function is used as the main selection criterion based on the calculation of the spatial relation of a node relative to its neighbor. This mechanism is applied in OLSR protocol to choose stable and supportable MPRs nodes. This mechanism significantly finds more stable MPRs and it promises QoS metrics such as lost packets and delay. Simulation results reveals a significant performance gains and it motivates further examinations to develop the mechanism in order to improve the routing protocol requirements. Performances are evaluated based on Random Waypoint model and network simulator ns3.