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Journal articles on the topic 'Random Waypoint Mobility Models'

Author: Grafiati

Published: 4 June 2021

Last updated: 6 February 2022

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1

Singh, Alok, Saurabh Sharma, and Rajneesh K. Srivastava. "Investigation of random waypoint and steady state random waypoint mobility models in NS-3 using AODV." Journal of High Speed Networks 26, no. 4 (December 23, 2020): 267–74. http://dx.doi.org/10.3233/jhs-200643.

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NS-3 has been one of the popular network simulator software for many years especially in research related to Mobile Adhoc Networks (MANETs). In NS-3, there is provision of several mobility models including Random Waypoint (RWP) mobility model and Steady State Random Waypoint (SSRWP) mobility model. RWP mobility model suffers from the transition phase related imperfection. SSRWP mobility model overcomes this limitation of RWP mobility by allowing the steady state initialization states of nodes in terms of position, speed and pause time of mobile nodes right from the beginning of the simulation. As SSRWP mobility model avoids any requirement of warm-up (cut-off) phase of RWP mobility model, it saves a significant amount of time of warm-up (cut-off) phase as well as establishes a high level of confidence in results obtained due to absence of any subjective guess. In the present work, RWP and SSRWP mobility models have been investigated using AODV routing protocol and it has been found that a way to mitigate the misleading effect of the transition phase of RWP mobility model is to have a sufficiently large simulation time which results, to a good extent, in convergence of performance of RWP mobility model toward that of SSRWP mobility model.

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2

Laqtib, Safaa, Khalid El Yassini, and Moulay Lahcen Hasnaoui. "Link-state QoS routing protocol under various mobility models." Indonesian Journal of Electrical Engineering and Computer Science 16, no. 2 (November 1, 2019): 906. http://dx.doi.org/10.11591/ijeecs.v16.i2.pp906-916.

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<p>Mobile Ad Hoc Network (MANET) consists of a group of mobile or wireless nodes that are placed randomly and dynamically that causes the continual change between nodes. A mobility model attempts to mimic the movement of real mobile nodes that change the speed and direction with time. The mobility model that accurately represents the characteristics of the mobile nodes in an ad hoc network is the key to examine whether a given protocol. The aim of this paper is to compare the performance of four different mobility models (i.e. Random Waypoint, Random Direction, Random walk, and Steady-State Random Waypoint) in MANET. These models were configured with Optimized Link State Routing (OLSR) protocol under three QoS (Quality of Service) <a title="Learn more about Metrics" href="https://www.sciencedirect.com/topics/engineering/metrics">metrics</a> such as the Packet Delivery Ratio (PDR), Throughput, End-to-End delay. The simulation results show the effectiveness of Steady-State Random Waypoint Mobility Models and encourage further investigations to extend it in order to guarantee other QoS requirements.</p>

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3

Kraaier, Jan, and Ulrich Killat. "Random direction or random waypoint? A comparison of mobility models for urban environments." European Transactions on Telecommunications 19, no. 8 (December 2008): 879–94. http://dx.doi.org/10.1002/ett.1219.

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4

Nadhum kadhum, Aseil, and Aseel Nadhum kadhum. "The effect of random waypoint mobility infrastructure for wireless networks." Journal of Al-Qadisiyah for computer science and mathematics 9, no. 2 (August 20, 2017): 10–18. http://dx.doi.org/10.29304/jqcm.2017.9.2.145.

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Mobile wireless sensor networks (mwsns) have as of late propelled a developing well known class of wsn in which portability assumes a key part in the execution of the application. As of late, portability has turned into an imperative zone of research for the wsn group. The expanding abilities and the diminishing expenses of portable sensors make versatile sensor systems conceivable and viable. In spite of the fact that wsn organizations were never imagined to be completely static, portability was at first viewed as having a few difficulties that should have been defeat, including availability, scope, and vitality utilization, among others. be that as it may, late studies have been indicating versatility in a more ideal light. In this article, an outline of proposition that assess portable correspondence in wsns is exhibited. Accordingly ,an assortment of versatility were proposed by analysts throughout the years where every portability display has its own particular properties that may influence the execution of the system in a way that varies from different models entitled with various properties. In this paper we give a study of versatility models that can be utilized as a part of remote sensor systems since it is imperative to give an arrangement of the accessible models along these lines a few portability models were looked into in the proposed work.

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Sornil, Ohm. "Addressed Query Gossip Resource Discovery Protocol for Mobile P2P Networks and Its Performance in Diverse Mobility Models." International Journal of Business Data Communications and Networking 14, no. 2 (July 2018): 33–43. http://dx.doi.org/10.4018/ijbdcn.2018070103.

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This article describes how P2P resource discovery protocols perform poorly over mobile ad hoc networks mainly due to the frequent network dynamics. Peer-to-Peer search techniques including structured and unstructured can be employed over MANETs. Empirical studies indicate that searching in such resultant networks are not efficient and effective due to peer discovery, connectivity and mobility issues. The author proposes Addressed Query Gossip Resource Discovery algorithm, a lightweight resource discovery designed to suit the mobility requirements of ad hoc networks to optimize the search performance while at the same time minimize the extra usage of mobile and network resources. Mobility models represent the movements of mobile nodes. Such models are used to represent how the location, velocity and acceleration change over time. The author conducts performance analyses of the proposed protocol and widely used unstructured search techniques over MANET under 2 realistic mobility models, i.e., Random Waypoint and Reference Point Group Mobility models. The results show that the proposed protocol has the best performance in almost every measured metrics. In addition, the protocol consumes less energy, has less message overhead and good success ratio for random waypoint movement as compared to the reference group mobility model. After extensive evaluations, the simulation results clarify that the mobility models have a significant impact on the performance of peer-to-peer content discovery protocols over mobile ad hoc networks.

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6

Wang, Yong, Qiang Dou, Wei Peng, and Zheng Hu Gong. "DTN Routing Performance Evaluation under Random Waypoint with Base Point Mobility Model." Applied Mechanics and Materials 411-414 (September 2013): 676–79. http://dx.doi.org/10.4028/www.scientific.net/amm.411-414.676.

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Mobility models are drawing increasing attention since it plays an indispensable role in delay tolerant networks performance evaluation (e.g., routing performance evaluation). Random Waypoint with Base Point (RWPBP) mobility model aims to model the movement characteristics in catastrophe rescue scenario. RWPBP mobility model can represent different movement styles according to different parameters. In this paper, we consider the traffic scenario that all the data generated by the nodes need to be sent to the base point, and evaluate the performance of the five DTN routing protocols (i.e., DirectDelivery, Epidemic, PROPHET, SpayAndWait and FirstContact) under the RWPBP mobility model with different parameters. Epidemic performs best in our experiment, since the traffic is not heavy in catastrophe rescue scenario.

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7

Nyangaresi, Vincent Omollo, Silvance O. Abeka, and Anthony J. Rodrigues. "Tracking Area Boundary-aware Protocol for Pseudo Stochastic Mobility Prediction in LTE Networks." International Journal of Information Technology and Computer Science 12, no. 5 (October 8, 2020): 52–62. http://dx.doi.org/10.5815/ijitcs.2020.05.04.

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Accurate mobility prediction enables efficient and faster paging services in these networks. This in turn facilitates the attainment of higher bandwidths and execution of activities such as handovers at low latencies. The conventional mobility prediction models operate on unrealistic assumptions that make them unsuitable for cellular network mobile station tracking. For instance, the Feynman-Verlet, first order kinetic model and Random Waypoint assume that mobile phones move with constant velocity while Manhattan, Freeway, city area, street unit, obstacle mobility, and pathway mobility postulate that mobile station movement is restricted along certain paths. In addition, obstacle mobility model speculate that the mobile station signal is completely absorbed by an obstacle while random walk, random waypoint, Markovian random walk, random direction, shortest path model, normal walk, and smooth random assume that a mobile station can move in any direction. Moreover, the greatest challenge of the random direction model is the requirement that a border behavior model be specified for the reaction of mobile stations reaching the simulation area boundary. In this paper, a protocol that addresses the border behavior problem is developed. This protocol is shown to detect when the subscriber has moved out of the current tracking area, which is crucial during handovers.

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8

Jayakumar, Geetha, and Gopinath Ganapathi. "Reference Point Group Mobility and Random Waypoint Models in Performance Evaluation of MANET Routing Protocols." Journal of Computer Systems, Networks, and Communications 2008 (2008): 1–10. http://dx.doi.org/10.1155/2008/860364.

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Ad hoc networks are characterized by multihop wireless connectivity, frequently changing network topology and the need for efficient dynamic routing protocols plays an important role. We compare the performance of two prominent on-demand routing protocols for mobile ad hoc networks: dynamic source routing (DSR), ad hoc on-demand distance vector routing (AODV). A detailed simulation model with medium access control (MAC) and physical layer models is used to study the interlayer interactions and their performance implications. We demonstrate that even though DSR and AODV share similar on-demand behavior, the differences in the protocol mechanisms can lead to significant performance differentials. In this paper, we examine both on-demand routing protocols AODV and DSR based on packet delivery ratio, normalized routing load, normalized MAC load, average end-to-end delay by varying the node density, network loading, and mobility variations for reference point group mobility and random waypoint models. This framework aims to evaluate the effect of mobility models on the performance of mobile ad hoc networks (MANETs) routing protocols. Our results show that the protocol performance may vary drastically across mobility models and performance rankings of protocols may vary with the mobility models used. This effect can be explained by the interaction of the mobility characteristics with the connectivity graph properties.

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9

Kumar, Subodh, G. S. Agrawal, and Sudhir Kumar Sharma. "Impact of Node Mobility on MANETs Routing Protocols under Random Waypoint, Group and File Mobility Models." INROADS- An International Journal of Jaipur National University 5, no. 1s (2016): 229. http://dx.doi.org/10.5958/2277-4912.2016.00044.8.

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10

Nagaraju, M., K. Raghava Rao, and K. Vijayalakshmi. "Efficient way of implementing the random and GM (Gauss-Markov) mobility model in MANET." International Journal of Engineering & Technology 7, no. 2.7 (March 18, 2018): 270. http://dx.doi.org/10.14419/ijet.v7i2.7.10595.

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In Mobile Adhoc Network (MANET) nodes are communicating each other with the help of routing protocol. In Adhoc networks, a node having high mobility, with that node’s moving randomly from node to node. For observing the movement mobility, we are studying different forms of mobility. These models can deploy the mobility of the network condition, including the various parameters such as the size of the network, traffic models of data, throughput and the PDR (Packet Delivery Ratio) are used as performance Parameters. We are investigating the RWP (Random Waypoint) and GM (Gauss-Markov) mobility model to express efficiency of Adhoc routing protocol by using the OMNET++ simulator .The result of the simulator shows that the mobility has more influence upon MANET protocol with the increasing node density. Here, we evaluated RWP and GM mobility model with AODV protocol. The study of these models illustrates dissimilar outcomes related inputs with the increasing performance of the pause time rises among the speed and number of nodes.

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Shriramoju, Suman Kumar, and Dr N. Satyanarayana. "Survey of Routing Protocols under Realistic Mobility and Traffic." International Journal Of Engineering And Computer Science 7, no. 03 (March 16, 2018): 23737–41. http://dx.doi.org/10.18535/ijecs/v7i3.14.

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Mobile ad hoc networks are a dynamic and unpredictable community topology. There are numerous routing protocols that have been proposed for MANETs. Maximum pervious research centered on improving the present routing protocols or designing new routing algorithms. In our work, we investigated and compared the effect of mobility models on routing protocols for various site visitors instructions in MANETs. There have been many factors that affected the overall performance of routing protocols which include mobility and visitors styles. We designed several simulation models that added these factors together and measured the software performance in terms of end -to-end throughput (bit rate), latency, and jitter. three instructions of MANET routing algorithms (Proactive, Reactive, and Hybrid), mobility models (Random Waypoint and group), and three instructions of visitors styles (constant bit rate, variable bit rate, and random) have been used.

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12

Sreerama Murty, M., and M. Venkat Das. "Performance Evalution of MANET Routing Protocols using Reference Point Group Mobility and Random WayPoint Models." International Journal of Ad hoc, Sensor & Ubiquitous Computing 2, no. 1 (March 24, 2011): 33–43. http://dx.doi.org/10.5121/ijasuc.2011.2104.

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13

Viswanath, Kumar, Katia Obraczka, Athanasios Kottas, and Bruno Sansó. "Statistical Equivalent Models for Computer Simulators with an Application to the Random Waypoint Mobility Model." SIMULATION 83, no. 2 (February 2007): 157–72. http://dx.doi.org/10.1177/0037549707080610.

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14

Ahmed, Muhammed Zaharadeen, Aisha Hassan Abdalla Hashim, Othman O. Khalifa, Abdulkadir H. Alkali, Nur Shahida Bt Midi, and Faridah Bt Abd. Rahman. "Evaluating Mobility Management Models for Content Forwarding in Named Data Networking Environments." International Journal of Interactive Mobile Technologies (iJIM) 13, no. 04 (April 10, 2019): 47. http://dx.doi.org/10.3991/ijim.v13i04.10519.

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<span>Named Data Networking (NDN) performs its routing and forwarding decisions using name prefixes. This removes some of the issues affecting addresses in our traditional IP architecture such as limitation in address allocation and management, and even NAT translations etcetera. Another positivity of NDN is its ability to use the conventional routing like the link state and distance vector algorithm. In route announcement, NDN node broadcasts its name prefix which consists of the knowledge of the next communicating node. In this paper, we evaluate the performance of mobility management models used in forwarding NDN contents to a next hop. This makes it crucial to select an approach of mobility model that translates the nature of movement of the NDN mobile routers. A detailed analysis of the famous mobility model such as the Random Waypoint mobility and Constant Velocity were computed to determine the mobility rate of the NDN mobile router. Simulation analysis was carried out using ndnSIM 2.1 on Linux Version 16.1. we build and compile with modules and libraries in NS-3.29. The sample of movement of the mobile router is illustrated and our result present the viability of the Constant Velocity model as compared with the Random Way point.</span>

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15

Wang, Yong, Qiang Dou, Wei Peng, and Zheng Hu Gong. "Simulation Based Study on the Node Spatial Distribution of the RWPBP Mobility Model." Applied Mechanics and Materials 411-414 (September 2013): 667–70. http://dx.doi.org/10.4028/www.scientific.net/amm.411-414.667.

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Mobility Model has drawn more and more attentions since its critical role in Mobile Wireless Networks performance evaluation. In the simulation of the mobile scenario using mobility models, the distribution of the node’s location will converge to the stationary distribution after a long time running. Random Waypoint with Base Point (RWPBP) mobility model proposed in [1] aims to model the movement characteristics in catastrophe rescue scenario. In this paper, we study the Node Spatial Distribution of the RWPBP mobility model using simulation to estimate the convergence time. The simulation results show that, when we use the two dimensional RWPBP mobility model for simulation, the results of more than 21000 seconds of the initial simulation time should be discarded to guarantee the stationary distribution.

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16

Singh, Rajnesh, and Neeta Singh. "Performance Analysis of TCP Newreno Over Mobility Models Using Routing Protocols in MANETs." International Journal of Wireless Networks and Broadband Technologies 10, no. 2 (July 2021): 1–15. http://dx.doi.org/10.4018/ijwnbt.2021070101.

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A MANET is a collection of nodes connected wirelessly that try to converse with each other with no need for any central control or infrastructure establishment. The model of mobility depicts the poignant nature of every node which is mobile in MANETs that is considered to be realistic. It plays a vital role in measuring the performance of MANETs. Mobility is considered to be the prime motive in simulation, because it is a huge influence over the design and network's performance due to limitation in resources and it lead to packet delivery ratio (PDR), varying velocity node energy (NE). Lots of work has been done to improve the above problems. Therefore, there is a requirement of more improvement in this area to enhance overall performance of mobility models. This paper presents a comparative simulation-based analysis of Gauss Markov, Manhattan, and random waypoint mobility models over TCP Newreno that uses a DSDV and AODV routing protocols. Moreover, experiment results and performance analysis have been performed with PDR and NE of the varying number of mobile nodes.

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17

Ibadah, Nisrine, Khalid Minaoui, Mohammed Rziza, Mohammed Oumsis, and César Benavente-Peces. "Deep Validation of Spatial Temporal Features of Synthetic Mobility Models." Computers 7, no. 4 (December 16, 2018): 71. http://dx.doi.org/10.3390/computers7040071.

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This paper analyzes the most relevant spatial-temporal stochastic properties of benchmark synthetic mobility models. Each pattern suffers from various mobility flaws, as will be shown by the models’ validation. A set of metrics is used to describe mobility features, such as the speed decay problem, the density wave phenomenon, the spatial node distribution, and the average neighbor percentage. These metrics have already been validated for the random waypoint mobility model (RWPMM), but they have not yet been verified for other mobility patterns that are most frequently used. For this reason, this investigation attempts to deeply validate those metrics for other mobility models, namely the Manhattan Grid mobility, the Reference Point Group mobility, the Nomadic Community mobility, the Self-Similar Least Action Walk, and SMOOTH models. Moreover, we propose a novel mobility metric named the “node neighbors range”. The relevance of this new metric is that it proves at once the set of outcomes of previous metrics. It offers a global view of the overall range of mobile neighbors during the experimental time. The current research aims to more rigorously understand mobility features in order to conduct a precise assessment of each mobility flaw, given that this fact further impacts the performance of the whole network. These validations aim to summarize several parameters into 18,126 different scenarios with an average of 486 validated files. An exhaustive analysis with details like those found in this paper leads to a good understanding of the accurate behaviors of mobility models by displaying the ability of every pattern to deal with certain topology changes, as well as to ensure network performances. Validation results confirm the effectiveness and robustness of our novel metric.

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18

Bajaj, Shruti, Er Rajdeep Singh, and Er Parveen Kakkar. "Investigation of Mobility Model Against Reactive Routing Protocols in MANETs." INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY 8, no. 1 (June 20, 2013): 751–67. http://dx.doi.org/10.24297/ijct.v8i1.3436.

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Ad-hoc network is a collection of wireless mobile nodes which dynamically form a temporary network without the use of any existing network infrastructure or centralized administration. It may connect hundreds to thousands of mobile nodes. The mobile nodes communicate directly with each other without the aid of access points. They form an arbitrary topology, where the routers are free to move randomly and arrange themselves as required. In this paper, an attempt has been made to investigate the impact of mobility models on the performance of three MANET on-demand reactive routing protocols: AODV, DSR and DYMO. The mobility models that are used in this work are: Random Waypoint mobility model and Group mobility model. The performance differentials are analyzed using varying network size, varying pause time, and varying velocity. We used Qual-Net [18] from scalable networks for the simulation purpose. The performance analysis is based on different network metrics such as packet delivery ratio, throughput, average end â€“to â€“end delay and average jitter.

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19

Singh, Sohajdeep, and Parveen Kakkar. "Investigating the Impact of Random Waypoint AND Vector Mobility Models on AODV, OLSR and GRP Routing Protocols in MANET." International Journal of Computer Applications 63, no. 3 (February 15, 2013): 30–34. http://dx.doi.org/10.5120/10448-5148.

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20

Chaba, Yogesh, and Mridul Chaba. "Q-Learning Based Optimized Link State Routing Protocol for Different Mobility Pattern." Journal of Computational and Theoretical Nanoscience 17, no. 9 (July 1, 2020): 4683–87. http://dx.doi.org/10.1166/jctn.2020.9299.

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Now days wireless networks have become popular as the mobile applications are increasing day by day and mobility of nodes has become an important feature. The desirable property which separates mobile network from wireless networks is the mobility of communication devices. Therefore, there is a need to design routing mechanism in such a way that they can easily adopt to the frequent changes in the mobility pattern of the network. In this paper, Optimized Link State Routing protocol has been modified by implementing Q-Learning concept, a reinforcement learning algorithm which guides network to select next node to which it should forward packets by first calculating the reward R and then calculation of Q-value with neighbors. Performance of this modified routing protocol has been evaluated for parameters like delay, throughput and delivery ratio. Two mobility models have been used, Random Waypoint and Walk. It is observed that performance in terms of above parameters improve considerably in both mobility patterns when intelligent Q-Learning algorithm is implemented in Optimized Link State Routing.

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21

Kaur, Parampreet, Ashima Singh, and Sukhpal Singh Gill. "RGIM: An Integrated Approach to Improve QoS in AODV, DSR and DSDV Routing Protocols for FANETS Using the Chain Mobility Model." Computer Journal 63, no. 10 (April 30, 2020): 1500–1512. http://dx.doi.org/10.1093/comjnl/bxaa040.

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Abstract Flying ad hoc networks (FANETs) are a collection of unmanned aerial vehicles that communicate without any predefined infrastructure. FANET, being one of the most researched topics nowadays, finds its scope in many complex applications like drones used for military applications, border surveillance systems and other systems like civil applications in traffic monitoring and disaster management. Quality of service (QoS) performance parameters for routing e.g. delay, packet delivery ratio, jitter and throughput in FANETs are quite difficult to improve. Mobility models play an important role in evaluating the performance of the routing protocols. In this paper, the integration of two selected mobility models, i.e. random waypoint and Gauss–Markov model, is implemented. As a result, the random Gauss integrated model is proposed for evaluating the performance of AODV (ad hoc on-demand distance vector), DSR (dynamic source routing) and DSDV (destination-Sequenced distance vector) routing protocols. The simulation is done with an NS2 simulator for various scenarios by varying the number of nodes and taking low- and high-node speeds of 50 and 500, respectively. The experimental results show that the proposed model improves the QoS performance parameters of AODV, DSR and DSDV protocol.

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Al-Quzwini, Mahmoud Mir Ali, and Zeinab R. Khaleel. "Mobility Impact on MANET Routing Protocols In Grid Networks." INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY 11, no. 6 (November 5, 2013): 2691–702. http://dx.doi.org/10.24297/ijct.v11i6.3044.

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Mobile Ad-Hoc Networks (MANETS) is a collection of wireless mobile nodes that are able to dynamically form a temporary network without any aid from fixed infrastructure or centralized administration due to no wired backbone.Ad Hoc networks are formed spontaneously and the nodes are highly mobile.Thispaper presents performance evaluations, comparisons, andanalysis for three routing protocols (AODV, DSR, and OLSR)to bring out their relative meritsundervarying network size and mobilitywith Â various speed and pause times. The simulation is carried out using OMNET++ simulator based on the quantitative basic parameters like throughput, Packet transmission Ratio (PTR),packet transmission time delay and protocol overhead .The Â nodes are distributed randomly in a grid network topology and mobile nodes moving using Random Waypoint mobility models. The results demonstrate that, undervarious node speeds and pause timesfor different network size, AODVoutperforms DSR and OLSR protocols, with respect to networkthroughput (by 0.9% and 4.4%, respectively). For protocoloverhead,DSR has lower overhead than both AODV and OLSR protocols (by 13.4% and 65.5%, respectively). In contrast, thepacket transmission time delay when using OLSR is shorter than whenusing both AODV (by 81.7%) and DSR (by 76.7%).Â

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Verma, Jyotsna, and Nishtha Kesswani. "AMIGM: Animal Migration Inspired Group Mobility Model for Mobile Ad hoc Networks." Scalable Computing: Practice and Experience 20, no. 3 (September 22, 2019): 577–90. http://dx.doi.org/10.12694/scpe.v20i3.1574.

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The most widespread notion of mobility model is the representation of mobile node’s movement pattern in the wireless ad hoc networks which has a significant impact on the performance of the network protocols. In this paper, we have proposed an Animal Migration Inspired Group Mobility (AMIGM) model for mobile ad hoc networks based on the migration behavior of animals like, insects, flock of birds, schools of fishes, reptiles, amphibians, etc. The propound model tries to overcome the limitations of the existing mobility models, such as temporal dependencies, spatial dependencies, geographical restrictions and migration of nodes between the group of nodes so that it can realistically model the real world application scenarios. The proposed AMIGM model is based on Animal Migration Optimization (AMO) algorithm, in which each group of nodes has two phases namely, Migration phase and Population updating phase. In the first phase, the model simulates the movement of nodes in the group from one position to another by obeying the swarming laws. In the second phase, the model simulates joining and leaving of the nodes in the group during migration. The protocol dependent and independent performance metrics of the proposed model are compared with Random Waypoint Mobility model (RWP) and Reference Point Group Mobility model (RPGM) through ns-2 simulator.

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Barrett, Chris, Martin Drozda, Madhav V. Marathe, S. S. Ravi, and James P. Smith. "A Mobility and Traffic Generation Framework for Modeling and Simulating Ad Hoc Communication Networks." Scientific Programming 12, no. 1 (2004): 1–23. http://dx.doi.org/10.1155/2004/921065.

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We present a generic mobility and traffic generation framework that can be incorporated into a tool for modeling and simulating large scale ad~hoc networks. Three components of this framework, namely a mobility data generator (MDG), a graph structure generator (GSG) and an occlusion modification tool (OMT) allow a variety of mobility models to be incorporated into the tool. The MDG module generates positions of transceivers at specified time instants. The GSG module constructs the graph corresponding to the ad hoc network from the mobility data provided by MDG. The OMT module modifies the connectivity of the graph produced by GSG to allow for occlusion effects. With two other modules, namely an activity data generator (ADG) which generates packet transmission activities for transceivers and a packet activity simulator (PAS) which simulates the movement and interaction of packets among the transceivers, the framework allows the modeling and simulation of ad hoc communication networks. The design of the framework allows a user to incorporate various realistic parameters crucial in the simulation. We illustrate the utility of our framework through a comparative study of three mobility models. Two of these are synthetic models (random waypoint and exponentially correlated mobility) proposed in the literature. The third model is based on an urban population mobility modeling tool (TRANSIMS) developed at the Los Alamos National Laboratory. This tool is capable of providing comprehensive information about the demographics, mobility and interactions of members of a large urban population. A comparison of these models is carried out by computing a variety of parameters associated with the graph structures generated by the models. There has recently been interest in the structural properties of graphs that arise in real world systems. We examine two aspects of this for the graphs created by the mobility models: change associated with power control (range of transceivers) and variation in time as transceivers move in space.

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Al-Rahayfeh, Amer, Abdul Razaque, Yaser Jararweh, and Muder Almiani. "Location-Based Lattice Mobility Model for Wireless Sensor Networks." Sensors 18, no. 12 (November 22, 2018): 4096. http://dx.doi.org/10.3390/s18124096.

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Significant research has been conducted for maintaining a high standard of communication and good coverage in wireless sensor networks (WSNs), but extra power consumption and mobility issues are not yet fully resolved. This paper introduces a memory-less location mobility-aware Lattice Mobility Model (LMM) for WSNs. LMM is capable of concurrently determining the node and sink mobility. LMM has a lower pause time, fewer control packets, and less node dependency (e.g., the energy consumed by each node in each cycle that is independent of the data traffic). LMM accurately determines a node’s moving location, the distance from its previous location to its current location, and the distance from its existing location to its destination. Many existing mobility models only provide a model how nodes move (e.g., to mimic pedestrian behavior), but do not actually control the next position based on properties of the underlying network topology. To determine the strength of LMM, OMNet++ was used to generate the realistic scenario to safeguard the affected area. The operation in affected area comprises searching for, detecting, and saving survivors. Currently, this process involves a time-consuming, manual search of the disaster area. This contribution aims to identify an energy efficient mobility model for a walking pattern in this particular scenario. LMM outperforms other mobility models, including the geographic-based circular mobility model (CMM), the random waypoint mobility model (RWMM) and the wind mobility model (WMM), The simulation results also demonstrate that the LMM requires the least time to change the location, has a lower drop rate, and has more residual energy savings than do the WMM, RWMM, and CMM.

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Aznar, Fidel, Mar Pujol, Ramon Rizo, Francisco Pujol, and Carlos Rizo. "Energy-Efficient Swarm Behavior for Indoor UAV Ad-Hoc Network Deployment." Symmetry 10, no. 11 (November 13, 2018): 632. http://dx.doi.org/10.3390/sym10110632.

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Building an ad-hoc network in emergency situations can be crucial as a primary tool or even when used prior to subsequent operations. The use of mini and micro Unmanned Aerial Vehicles (UAVs) is increasing because of the wide range of possibilities they offer. Moreover, they have been proven to bring sustainability to many applications, such as agriculture, deforestation and wildlife conservation, among others. Therefore, creating a UAV network for an unknown environment is an important task and an active research field. In this article, a mobility model for the creation of ad-hoc networks using UAVs will be presented. This model will be based on pheromones for robust navigation. We will focus mainly on developing energy-efficient behavior, which is essential for this type of vehicle. Although there are in the literature several models of mobility for ad-hoc network creation, we find that either they are not adapted to the specific energy requirements of UAVs or the proposed motion models are unrealistic or not sufficiently robust for final implantation. We will present and analyze the operation of a distributed swarm behavior able to create an ad-hoc network. Then, an analytical model of the swarm energy consumption will be proposed. This model will provide a mechanism to effectively predict the energy consumption needed for the deployment of the network prior to its implementation. Determining the use of the mobility behavior is a requirement to establish and maintain a communication channel for the required time. Finally, this analytical model will be experimentally validated and compared to the Random Waypoint (RWP) mobility strategy.

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Hyytiä, Esa, and Jorma Virtamo. "Random waypoint mobility model in cellular networks." Wireless Networks 13, no. 2 (June 7, 2006): 177–88. http://dx.doi.org/10.1007/s11276-006-4600-3.

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Navidi, W., and T. Camp. "Stationary distributions for the random waypoint mobility model." IEEE Transactions on Mobile Computing 3, no. 1 (January 2004): 99–108. http://dx.doi.org/10.1109/tmc.2004.1261820.

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29

Sabah, Nasser, and Aykut Hocanin. "Gamma random waypoint mobility model for wirelessad hocnetworks." International Journal of Communication Systems 26, no. 11 (February 20, 2012): 1433–45. http://dx.doi.org/10.1002/dac.2319.

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30

Althunibat, Saud, Osamah S. Badarneh, and Raed Mesleh. "Random Waypoint Mobility Model in Space Modulation Systems." IEEE Communications Letters 23, no. 5 (May 2019): 884–87. http://dx.doi.org/10.1109/lcomm.2019.2907947.

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31

Bettstetter, Christian, Hannes Hartenstein, and Xavier Pérez-Costa. "Stochastic Properties of the Random Waypoint Mobility Model." Wireless Networks 10, no. 5 (September 2004): 555–67. http://dx.doi.org/10.1023/b:wine.0000036458.88990.e5.

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32

Silva, Rogerio T., Roberto R. Colletti, Cecilio Pimentel, and Renato M. de Moraes. "BETA random waypoint mobility model for wireless network simulation." Ad Hoc Networks 48 (September 2016): 93–100. http://dx.doi.org/10.1016/j.adhoc.2016.06.001.

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33

Crescenzi, Pilu, Miriam Di Ianni, Andrea Marino, Donatella Merlini, Gianluca Rossi, and Paola Vocca. "Smooth movement and Manhattan path based Random Waypoint mobility." Information Processing Letters 111, no. 5 (February 2011): 239–46. http://dx.doi.org/10.1016/j.ipl.2010.12.009.

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34

Pillay, Narushan, and Hongjun Xu. "Large intelligent surfaces: Random waypoint mobility and two-way relaying." International Journal of Communication Systems 33, no. 14 (July 7, 2020): e4505. http://dx.doi.org/10.1002/dac.4505.

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35

Bettstetter, Christian. "Topology properties of Ad hoc networks with random waypoint mobility." ACM SIGMOBILE Mobile Computing and Communications Review 7, no. 3 (July 2003): 50–52. http://dx.doi.org/10.1145/961268.961287.

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36

Pong, Dennis, and Tim Moors. "The Impact of Random Waypoint Mobility on Infrastructure Wireless Networks." International Journal of Wireless Information Networks 13, no. 2 (March 28, 2006): 99–114. http://dx.doi.org/10.1007/s10776-006-0028-z.

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37

Mitsche, Dieter, Giovanni Resta, and Paolo Santi. "The random waypoint mobility model with uniform node spatial distribution." Wireless Networks 20, no. 5 (November 8, 2013): 1053–66. http://dx.doi.org/10.1007/s11276-013-0661-2.

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Wang, Ting, and Chor Ping Low. "Evaluating inter-arrival time in general random waypoint mobility model." Ad Hoc Networks 11, no. 1 (January 2013): 124–37. http://dx.doi.org/10.1016/j.adhoc.2012.04.011.

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39

Hyytia, E., P. Lassila, and J. Virtamo. "Spatial node distribution of the random waypoint mobility model with applications." IEEE Transactions on Mobile Computing 5, no. 6 (June 2006): 680–94. http://dx.doi.org/10.1109/tmc.2006.86.

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40

Dak, Ahmad Yusri, Nurul Fazliana Samsudin, and Noor Elaiza Abdul Khalid. "Physical Layer Jamming Attack using Waypoint Mobility Model in WLAN." Journal of Computing Research and Innovation 3, no. 2 (November 8, 2018): 1–9. http://dx.doi.org/10.24191/jcrinn.v3i2.82.

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Sharing nature of wireless medium provides various challenging features among various group of users. This is one of various services offered by Wireless Local Area Network (WLAN). In addition, due to popularity of WLANs, user experience suffer from various security threats especially jamming based Denial-of-Service (DoS) attack. The attacks are focused on radio channels where the transmission channel interfere with jamming attacks by sending high frequency signal to disturb the communication between the users in network. Most of attack exists at physical layer are detected randomly movable and less static attack are found. Therefore, the objective of this research is to study the pattern of randomly movable node and performance of physical layer jamming attack using Waypoint Mobility Model. To address these evaluation, a simulation model consists of constant and random jammer will be developed using OPNET. The performance involved physical layer attack that will be evaluated using three performance metrics such as Bit Error Rate (BER), Signal-to-Noise Ratio (SNR), and throughput by using Random Waypoint Point. Outcome concluded that these three-performance metrics can be shows as a significant impact to a detection mechanism that will enable offer insights and the level for future research based on DoS.

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41

Younes, Osama S., and Umar A. Albalawi. "Analysis of Route Stability in Mobile Multihop Networks Under Random Waypoint Mobility." IEEE Access 8 (2020): 168121–36. http://dx.doi.org/10.1109/access.2020.3023142.

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42

Romsaiyud, Walisa, and Wichian Premchaiswadi. "Location Recommendation on a Street Random Waypoint Mobility Model Based on Predictive Model." Journal of Wireless Networking and Communications 2, no. 5 (December 1, 2012): 136–42. http://dx.doi.org/10.5923/j.jwnc.20120205.08.

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43

Vijayalakshmi, P., K. Selvi, K. Gowsic, and K. Muthumanickam. "A misdirected route avoidance using random waypoint mobility model in wireless sensor network." Wireless Networks 27, no. 6 (July 15, 2021): 3845–56. http://dx.doi.org/10.1007/s11276-021-02703-1.

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44

Akhtar Khan, Naeem, Farooq Ahmad, and Sher Afzal Khan. "Formal and Executable Specification of Random Waypoint Mobility Model Using Timed Coloured Petri Nets for WMN." Abstract and Applied Analysis 2014 (2014): 1–9. http://dx.doi.org/10.1155/2014/798927.

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The wireless mesh network (WMN) is an emerging and cost-effective alternative paradigm for the next generation wireless networks in many diverse applications. In the performance evaluation of routing protocol for the WMN, it is essential that it should be evaluated under realistic conditions. The usefulness of specific mobility protocol can be determined by selection of mobility model. This paper introduces a coloured Petri nets (CP-nets) based formal model for implementation, simulation, and analysis of most widely used random waypoint (RWP) mobility model for WMNs. The formal semantics of hierarchical timed CP-nets allow us to investigate the terminating behavior of the transitions using state space analysis techniques. The proposed implementation improves the RWP mobility model by removing the “border effect” and resolves the “speed decay” problem.

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Zidani, Abdelmadjid, Souheila Bouam, Kamel Barka, and Lyamine Guezouli. "A variant of Random WayPoint mobility model to improve routing in Wireless Sensor Networks." International Journal of Information and Communication Technology 13, no. 4 (2018): 1. http://dx.doi.org/10.1504/ijict.2018.10012666.

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46

Bettstetter, C., G. Resta, and P. Santi. "The node distribution of the random waypoint mobility model for wireless ad hoc networks." IEEE Transactions on Mobile Computing 2, no. 3 (July 2003): 257–69. http://dx.doi.org/10.1109/tmc.2003.1233531.

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47

Lee, Dong Myung, Tae Wan Kim, and Yun-Hae Kim. "Localization–compensation algorithm based on the Mean kShift and the Kalman filter." Modern Physics Letters B 29, no. 06n07 (March 20, 2015): 1540020. http://dx.doi.org/10.1142/s0217984915400205.

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In this paper, we propose a localization simulator based on the random walk/waypoint mobility model and a hybrid-type location–compensation algorithm using the Mean kShift/Kalman filter (MSKF) to enhance the precision of the estimated location value of mobile modules. From an analysis of our experimental results, the proposed algorithm using the MSKF can better compensate for the error rates, the average error rate per estimated distance moved by the mobile node ( Err _ Rate DV ) and the error rate per estimated trace value of the mobile node ( Err _ Rate TV ) than the Mean shift or Kalman filter up to a maximum of 29% in a random mobility environment for the three scenarios.

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48

Nanaji, Uppe, and S. Pallam Setty. "Investigation Misbehavior Configuration Nodes with Secure Neighborhood on Energy Consumption for DYMO Routing Protocol in MANETS." International Journal of Innovative Technology and Exploring Engineering 10, no. 3 (January 10, 2021): 22–28. http://dx.doi.org/10.35940/ijitee.c8331.0110321.

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We calculate misbehavior of energy consumption during configuration nodes between neighborhood nodes with specific investigation on secure environment with DYMP routing Protocol. An experimental analysis of DYMO, M-DYMO (misbehavior DYMO), S-DYMO (Secure-DYMO) has been carried out using QualNet 5.1 simulator. The simulation results have been derived using self-created network scenarios by incorporating secure neighborhood in de-facto DYMO by varying the network size as small, medium and large, Node Traversal Time, ART, Buffer Size. From the experiment results, it has been concluded that energy consumption increases as security is incorporated in the existing routing protocol. From the results, the variance of total energy consumed in all modes of energy (transmit, receive and idle) for nodes in DYMO,M-DYMO and S-DYMO under Random waypoint Mobility Model is maximum for larger network size which is 3.380037 mj , 3.363414 mj and 3.612123 mj. For random waypoint mobility model the variance of total energy consumed in all modes of energy is maximum at 0.2320866668 at 115 nodes. In this research paper, an effort has been made to investigate the impact of secure neighborhood on energy consumption and QoS metrics of Dynamic MANETs On-Demand (routing protocol) (DYMO) in MANETS.

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Arya, Shobha, Nipur Nipur, and Chandrakala Arya. "Performance Analysis of AODV, DSR and DYMO Protocols using Random Waypoint Mobility Model in MANET." International Journal of Computer Applications 67, no. 19 (April 18, 2013): 13–17. http://dx.doi.org/10.5120/11502-7219.

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Mittal, Poonam, and Sneha Kanchan. "Impact of Random Waypoint Mobility on Reactive Routing Protocols of Scalable Mobile Ad hoc Network." IOSR Journal of Computer Engineering 16, no. 4 (2014): 17–22. http://dx.doi.org/10.9790/0661-16451722.

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