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Flexible mobility and random jitter are two unique features of UAV communication platforms. Although advantages of mobility have been extensively explored, the random jitter of UAV platforms, caused by airflow and body vibrations, has been rarely studied. This work aims to answer the two fundamental questions: i) how to analyze the secrecy performance when considering UAV jitter and ii) can this inherent characteristic of UAV be exploited to enhance secrecy? Detailed, we study the modeling and analysis of UAV jitter on the secrecy performance in an air-to-ground (A2G) wiretap system with multiple non-colluding eavesdroppers, where a UAV-mounted transmitter equipped with directional antennas illuminates ground terminals in a finite area. Random waypoint model is applied to characterize the mobility of eavesdroppers. To be specific, by modeling UAV jitter in both horizontal azimuth and vertical elevation, distortion and shift of UAV illumination area are analyzed. Further, beam-illumination probability of a randomly located ground terminal is obtained. Following which, a tractable framework for analyzing the secrecy coverage probability (SCP) and ergodic secrecy capacity (ESC) is developed. Expressions for SCP and ESC are derived with characterizations for the signal-to-noise ratio received at legitimate receiver and eavesdroppers. Finally, extensive simulations are provided to validate the theoretical analysis. This is the first work to find that UAV jitter can be exploited to enhanced secrecy performance of A2G wiretap system with appropriate UAV height and beamwidth.

Radio frequency energy harvesting can prolong the battery life and improve energy efficiency of device-to-device (D2D) communication. In this paper, we analyze the performance of a mobile D2D device powered by EH from the transmissions of underlying cellular base stations (BSs), whose locations are modeled as a homogeneous Poisson point process. We model the movements of D2D nodes via a modified random waypoint model. Log-distance path loss and Rayleigh fading are considered, and EH takes place solely within harvesting zones surrounding each BS and each D2D user harvests energy for a fixed number of charging time slots before attempting to transmit. We derive the probability of a D2D device being within an EH region surrounding BSs after multiple movements, and the probability of being within the fully charged state using a Markov-chain approach taking into account temporal effects. Moreover, the statistics of the harvested energy are characterized, and subsequently, the outage probability of a D2D transmission utilizing the harvested energy is derived. We show that the number of movements required to be within a harvesting region increases significantly when the harvesting threshold power increases, and that the number of harvesting time slots should be selected judiciously.

The present paper features results on global survival and extinction of an infection in a multi-layer network of mobile agents. Expanding on a model first presented in [CHJW22], 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 that is able to transmit a patch to neighboring infected agents that in turn can further distribute the patch, leading to a 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., Comment: 20 pages, 5 figures

In this article we setup a dynamic device-to-device communication system where devices, given as a Poisson point process, move in an environment, given by a street system of random planar-tessellation type, via a random-waypoint model. Every device independently picks a target location on the street system using a general waypoint kernel, and travels to the target along the shortest path on the streets with an individual velocity. Then, any pair of devices becomes connected whenever they are on the same street in sufficiently close proximity, for a sufficiently long time. After presenting some general properties of the multi-parameter system, we focus on an analysis of the clustering behavior of the random connectivity graph. In our main results we isolate regimes for the almost-sure absence of percolation if, for example, the device intensity is too small, or the connectivity time is too large. On the other hand, we exhibit parameter regimes of sufficiently large intensities of devices, under favorable choices of the other parameters, such that percolation is possible with positive probability. Most interestingly, we also show an in-and-out of percolation as the velocity increases. The rigorous analysis of the system mainly rests on comparison arguments with simplified models via spatial coarse graining and thinning approaches. Here we also make contact to geostatistical percolation models with infinite-range dependencies., Comment: 24 pages, 8 figures

In this letter, we emulate real-world statistics for mobility patterns on road systems. We then propose modifications to the assumptions of the random waypoint (RWP) model to better represent high-mobility profiles. We call the model under our new framework as RWP+. Specifically, we show that the lengths of the transitions which constitute a trip, are best represented by a lognormal distribution, and that the velocities are best described by a linear combination of normal distributions with different mean values. Compared to the assumptions used in the literature for mobile cellular networks, our modeling provides mobility metrics, such as handoff rates, that better characterize actual emulated trips from the collected statistics., To appear in IEEE Communications Letters

Light fidelity (LiFi) is an emerging communication technology, which utilizes the light-emitting diodes (LEDs) for high-speed wireless communications. Due to its huge unlicensed bandwidth, LiFi is capable of supporting high data rates. The quality of the LiFi channel fluctuates across the room due to interference, reflection from walls or blockage. On the other hand, WiFi is another wireless communication technology that is capable of providing moderate data rates with ubiquitous coverage. As the electromagnetic spectrum of LiFi does not overlap with WiFi, both of them can coexist to form a hybrid LiFi and WiFi network for seamless and high-throughput connectivity. The performance of a hybrid system significantly depends upon the access point (AP) assignment and resource allocation strategies. In this paper, a downlink hybrid system with one WiFi AP and four LiFi APs is considered, and a reinforcement learning (RL) algorithm is implemented in order to determine an optimal AP assignment strategy, which maximizes the long-term system throughput while ensuring the required users fairness and satisfaction. Furthermore, two different scenarios based on the random waypoint model with uniform and non-uniform distribution of users have been studied. The performance of the proposed system is compared against state-of-the-art benchmark approaches e.g., signal strength strategy (SSS), exhaustive search, and an iterative optimization method. The results are reported in terms of the average system throughput, user satisfaction, fairness, and capacity outage probability. It is shown that the proposed RL method performs closer to the exhaustive search scheme at fairly low complexity. The RL method also outperforms the SSS scheme and the iterative algorithm in most scenarios.

A mobile ad hoc network is collection of self configuring and adaption of wireless link between communicating devices (mobile devices) to form an arbitrary topology and multihop wireless connectivity without the use of existing infrastructure. It requires efficient dynamic routing protocol to determine the routes subsequent to a set of rules that enables two or more devices to communicate with each others. This paper basically classifies and evaluates the mobility metrics into two categories- direct mobility metrics and derived mobility metrics. These two mobility metrics has been used to measure different mobility models, this paper considers some of mobility models i.e Random Waypoint Model, Reference Point Group Mobility Model, Random Direction Mobility Model, Random Walk Mobility Model, Probabilistic Random Walk, Gauss Markov, Column Mobility Model, Nomadic Community Mobility Model and Manhattan Grid Model.

Many wireless networks operate in a mobile environment with randomly moving user terminals. This letter analytically characterizes the impact of ground user mobility, propagation environment and channel fading on the outage performance of unmanned aerial vehicle (UAV) communications. Closed-form expressions for the outage probability using the random waypoint model for ground user mobility, UAV channel models for different propagation environments and the Nakagami- ${m}$ model for fading channels are derived. Furthermore, the outage analysis takes into account the effect of co-channel interference by both the stationary and mobile users. Numerical results are presented to demonstrate the interplay between the communication performance and the system parameters.

Wireless physical layer security has attracted great attention in recent years. Although mobility is an intrinsic property of wireless networks, most of the existing works only consider static scenarios and the impact of mobility on wireless physical layer security is not well understood. To fill this gap, in this paper, we investigate physical layer security in the scenario with a random mobile receiver under Rayleigh fading channel. We consider a common scenario where a base station or access point communicates to a random mobile receiver with a passive eavesdropper in a circular region. The secrecy performances under three typical random mobility models are studied: random waypoint model (RWP); random direction model (RD); and border move model. We investigate the secrecy characteristics of the mobile user under steady-state running and provide a general analytical framework for computing the ergodic secrecy capacity. We derive tractable closed-form expressions of positive secrecy capacity probability and secrecy outage probability for RWP and RD mobility users, respectively. By comparing the secrecy performance of mobility with static case, we find that the RWP mobile user can achieve much better secrecy performance than the others. We then investigate the secrecy performance of RWP mobile user with pause time. Furthermore, the two types of secrecy improvement strategies for random mobile users are proposed. In the first strategy, a transmit subcell for RWP users is bounded. We allow the transmitter to communicate with the mobile user only when he is moving within the subcell. In the other strategy, the transmitter is turned on only when the evaluated secrecy performance reaches to a required level. We strike a good trade-off between the secrecy improvements and transmit outage probability. Extensive simulation results validate our theoretical analysis. Finally, we extend our framework to other realistic scenarios, including nodes moving in other shapes of areas, and multiple non-cooperative and cooperative eavesdroppers.

In this paper, we characterize the wireless interference of a mobile ad hoc network, where the nodes move according to the random waypoint model. The interferers are assumed to be located within an interference region that is defined as a circular region centered in a fixed node located at a given point of the mobility scenario. The main contribution of this paper is the characterization of the aggregate interference caused to the fixed node by mobile interferers located within the interference region. The distribution of the interference is analyzed taking into account the stochastic nature of the path loss due to the mobility of the nodes, as well as fast fading and shadowing effects. The derivation of the characteristic function of the aggregate interference is used in two different estimators, which successfully characterize the interference using only a small set of samples. The theoretical approach is validated through simulations, which confirm its effectiveness. Finally, we assess the accuracy of the proposed estimators, demonstrating the practical value of this paper.

We study the distribution of the received signal power in wireless networks subject to fading, path loss, and user mobility. We show that this distribution is fully characterized by a finite number of the incomplete moments of the underlying channel fading (static) distribution, when imposing mild restrictions on the random user mobility patterns. This general approach is used to determine the effect of different random mobility models such as the random waypoint model, when assuming state-of-the-art generalized line-of-sight fading models combined with multislope path-loss scenarios.

Mobile crowdsensing can facilitate environmental surveys by leveraging sensor-equipped mobile devices that carry out measurements covering a wide area in a short time without bearing the costs of traditional field work. In this article, we examine statistical methods to perform an accurate estimate of the mean value of an environmental parameter in a region based on such measurements. The main focus is on estimates produced by considering the mobile device readings at a random instant in time. We compare stratified sampling with different stratification weights to sampling without stratification as well as an appropriately modified version of systematic sampling. Our main result is that stratification with weights proportional to stratum areas can produce significantly smaller bias for a moderate number of strata and gets arbitrarily close to the true area average as the number of mobiles increases. The performance of the methods is evaluated for an application scenario where we estimate the mean area temperature in a linear region that exhibits the so-called Urban Heat Island effect, with mobile users moving in the region according to the Random Waypoint Model.

In this paper, a hybrid adaptive MCB-PSO node localization algorithm is proposed for three-dimensional mobile wireless sensor networks (MWSNs), which considers the random mobility of both anchor and unknown nodes. An improved particle swarm optimization (PSO) approach is presented with Monte Carlo localization boxed (MCB) to locate mobile nodes. It solves the particle degeneracy problem that appeared in traditional MCB. In the proposed algorithm, a random waypoint model is incorporated to describe random movements of anchor and unknown nodes based on different time units. An adaptive anchor selection operator is designed to improve the performance of standard PSO for each particle based on time units and generations, to maintain the searching ability in the last few time units and particle generations. The objective function of standard PSO is then reformed to make it obtain a better rate of convergence and more accurate cost value for the global optimum position. Furthermore, the moving scope of each particle is constrained in a specified space to improve the searching efficiency as well as to save calculation time. Experiments are made in MATLAB software, and it is compared with DV-Hop, Centroid, MCL, and MCB. Three evaluation indexes are introduced, namely, normalized average localization error, average localization time, and localization rate. The simulation results show that the proposed algorithm works well in every situation with the highest localization accuracy, least time consumptions, and highest localization rates.

In an RFID network, readers simultaneously querying tags may interfere with each other, generating a reader collision that prevents the tag identification. The reader-to-reader interference can occur among readers closer than a given distance, called interference range. Readers within the interference range are called neighbors. Many protocols designed to tackle reader collisions are based on a TDMA scheme. The performance of an anti-collision protocol can be measured in terms of throughput, i.e., the number of times readers can successfully query tags. This paper quantifies the size of the neighborhood and then analyzes its impact on the throughput of TDMA anti-collision protocols. The average number of neighbors is shown to depend not only on the number of readers in the RFID network, but also on the mobility of the readers. Thus, both static and mobile RFID systems are investigated. By simulating two state-of-the-art protocols, it is shown how properly setting the configuration parameters of the TDMA protocols according to the average amount of the neighborhood in order to achieve the highest throughput.

Mobility model characterize node movement patterns in opportunistic networks, it is usually used for simulation purposes when new communication or navigation techniques are proposed. There are two kinds of mobility model at present. One is the mobility model based on the theory, and other is the mobility model based on the realistic networks. But they cannot characterize the inherent property of opportunistic networks well. We try to tradeoff their two extreme cases, and put forward an opportunistic networks model with restricted time-space (RTSM), which cannot only describe the community characteristic and activity scheduling of nodes on the macro, but also obey the node mobility rules of Random waypoint model (RWP) in the micro. The simulation results show that we set the different parameters (such as, and ) to get the different simulating scenarios which is closer the realistic network scenarios than the classical mobility models (such as, Random waypoint, Community movement and Map based movement), and the proposed mobility model has good encounter duration time distribution and flexible parameter controllability.

The VANETs carry several security considerations. One in every of the popular and dangerous attacks is launched within the variety of Sybil, connectivity holes or cut-up attack, wherever associated in Nursing assaulter inserts a faux position inside within the cluster. The inserted faux node data is used by the hackers within the case of inconsiderate driver, traffic jams, selective collisions and different similar dangerous things. To avoid such things the VANETs should be protected against such attacks. During this paper, a completely unique answer has been projected to beat the Sybil and cut-up attacks on the VANETs. The new answer is capable of police work the faux data injections by confirmatory the VANET node behavior within the cluster. The behavior of the node includes the direction, speed and pattern. The projected model has been developed mistreatment the random waypoint model. The random waypoint model has been compared against the point of reference cluster model. The experimental results have shown the effectiveness of the projected model and also shows that RWPM is better than RPGM.

In the vision of the Internet of Things (IoT), objects become smart by aggregating in a network and exchanging information. Thanks to this shared knowledge, the objects can interact for performing advanced tasks. The obtrusiveness of the services is guaranteed by the mobility of the smart objects. For example, mobile sensors are used to follow dynamic phenomena, whereas smartphones and wearable devices are always accessible to the user. The interaction among the smart devices can be described by means of a graph, where nodes, representing IoT objects, are linked if they can communicate. This paper studies the node degree (i.e., the number of links of the node) in a graph developed for describing heterogeneous wireless networks. With respect to previous work, the mobility of the network, which can change the degree of every node, is considered for the first time. Formulas for the degree distribution and the average degree are theoretically computed and then validated with simulations. In particular, as a case study the proposed formulas are applied considering IoT objects following the random waypoint model, one of the most common mobility models.

The VANETs carry many security concerns. One of the popular and dangerous attacks can be launched in the form of Sybil or Prankster attack, where an attacker inserts a fake position within in the cluster. The inserted fake node information can be utilized by the hackers in the case of selfish driver, traffic jams, selective collisions and other similar hazardous situations. To avoid such things the VANETs must be protected against such attacks. In this paper, a novel solution has been proposed to overcome the Sybil and prankster attacks on the VANETs. The new solution is capable of detecting the fake information injections by verifying the VANET node behaviour in the cluster. The behaviour of the node includes the direction, speed, pattern, etc. In case a node is found malicious, the whole cluster is reported against that node, and node is ordered to stop by the central control system. The proposed model has been developed using the random waypoint model. The random way point model is much closer to the real time VANETs. The random waypoint model has been compared against the reference point group model. The experimental results have shown the effectiveness of the proposed model.

With the popularity of portable wireless devices it is important to model and predict how information or contagions spread by natural human mobility -- for understanding the spreading of deadly infectious diseases and for improving delay tolerant communication schemes. Formally, we model this problem by considering $M$ moving agents, where each agent initially carries a \emph{distinct} bit of information. When two agents are at the same location or in close proximity to one another, they share all their information with each other. We would like to know the time it takes until all bits of information reach all agents, called the \textit{flood time}, and how it depends on the way agents move, the size and shape of the network and the number of agents moving in the network. We provide rigorous analysis for the \MRWP model (which takes paths with minimum number of turns), a convenient model used previously to analyze mobile agents, and find that with high probability the flood time is bounded by $O\big(N\log M\lceil(N/M) \log(NM)\rceil\big)$, where $M$ agents move on an $N\times N$ grid. In addition to extensive simulations, we use a data set of taxi trajectories to show that our method can successfully predict flood times in both experimental settings and the real world., Comment: 10 pages, ACM SIGSPATIAL 2018, Seattle, US

An infinite number of nodes move in $\mathbb{R}^{2}$ according to a random waypoint model; a single packet is traveling towards a destination (located at an infinite distance away) using combinations of wireless transmissions and physical transport on the buffers of nodes. In earlier work [1] we defined two performance metrics, namely, the long-term average speed with which the packet travels towards its destination, and the rate with which transmission cost accumulates with distance covered. Explicit expressions were derived for these metrics, under specific ergodicity assumptions. In this paper we give a precise description of the induced Markov process, we show that it is indeed (uniformly) geometrically ergodic, and that the law of large numbers holds for the random variables of interest. In particular, we show that the two performance metrics are well-defined and asymptotically constant with probability one.

In an RFID network, the signal transmitted by a reader to query tags may interfere with the communication of other surrounding readers. As a consequence, the readers are not able to detect the weak reply from tags. The reader-to-reader interference affects readers located within a given distance, called interference range. This phenomenon can be estimated when deploying an RFID system, because the initial positions of the readers are known. It is also possible to completely avoid it by placing the readers far enough each other. However, if the readers are mobile, the distances among readers change and the probability of reader-to-reader interference dramatically increases. A theoretical analysis is conducted in this paper in order to estimate the probability of interference among static and mobile readers. The random waypoint model, one of the most common mobility models, is adopted to describe the movements of the readers. The theoretical results are validated with simulations.

The mobility of the node plays a crucial role in the route discovery process for Mobile Ad hoc networks (MANET). The high-speed node affects the routing process by packet relaying, packet delivery. This paper proposes a mobility prediction model FMPM using Auto-Regressive Integrated Moving Average (ARIMA) method to estimate the futuristic speed values of the nodes in MANET. It uses the autocorrelations of previous data by time series forecasting approach. The ARIMA model applied to mobile nodes for predicting its future speeds in the network. This mobility prediction supports the route discovery process to select the moderate mobility nodes for the reliable routing in the network. The nodes are trained by ARIMA model using neural network time-series tool of Matlab. Roughly, it trains each node with ten iterations. Simulation results show that the forecasted values almost match with the simulated node speed values. Performance analysis of the predicted mobility values exhibits the improved results compared to existing works on performance metrics such as mean square error, covariance, and computation overhead. The proposed FMPM produces more perfection in the speed prediction of a mobile node with a maximum of 80-100 % throughout the time series and has the lowest error values as 0.1085. But, the neural based prediction has the lowest MSE as 0.852. Therefore, the ARIMA prediction has approximately 0.75 reduced error values.

Mobile Ad-hoc Networks (MANETs) are a cluster of self-organizing and self-governing wireless nodes without any backbone infrastructure and centralized administration. The various nodes in MANET move randomly, and this node mobility may pose challenges on the performance of routing protocols. In this paper, an Intra and intergroup performance review of various MANET routing protocols are performed under varying speed of nodes. The routing protocols included in this study are reactive, proactive, and hybrid protocols. This performance review is done using the NS2 simulator and random waypoint model. The routing protocols performance is assessed through standard performance measure metrics including packet delivery ratio, throughput, routing overhead and end to end delivery with varying speed of nodes. The simulations result shows that there is no significant impact of varying speed of nodes on standard performance evaluation metrics.

In order to optimize the utilization of limited resources, the operators have already addressed to deploy their services in heterogeneous networks integrated different Radio Access Technologies (RAT), e.g. WLAN/WiMAX/WCDMA. Vertical handoffs (VHO) as a key problem should be overcome while mobile users are moving in heterogeneous networks. In existing works, resource assignment depends on the packet’s size, which is usually defined a fix length. This paper proposes an analytical model for evaluating the VHO performance. In the model, resources are proportionally assigned to real-time services (RS) and to non realtime services (NRS) by a resource factor m, which can be defined as any value. The performances on blocking probability and on throughput are derived and evaluated with different values of m under the restriction of resources. For enhancing the effect of VHO, the Random Waypoint Model on the border (RWPB) is implemented in the simulation, which enforces the mobile users residing near the border of networks. Simulation results demonstrate that with a greater value of m, the blocking probability slightly increases while the total throughput is significantly improved.

We present a general approach to study the flooding time (a measure of how fast information spreads) in dynamic graphs (graphs whose topology changes with time according to a random process). We consider arbitrary ergodic Markovian dynamic graph processes, that is, processes in which the topology of the graph at time $$t$$ t depends only on its topology at time $$t-1$$ t - 1 and which have a unique stationary distribution. The most well studied models of dynamic graphs are all Markovian and ergodic. Under general conditions, we bound the flooding time in terms of the mixing time of the dynamic graph process. We recover, as special cases of our result, bounds on the flooding time for the random trip model and the random path one; previous analysis techniques provided bounds only in restricted settings for such models. Our result also provides the first bound for the random waypoint model whose analysis had been an important open question. The bound is tight for the most realistic ranges of the network parameters.

Mobile ad-hoc networks are widely used these days as in smart phones but energy efficiency is a major issue when discovering neighbor nodes to maintain connectivity as periodically exchanging hello messages are used for it. Overhead goes high due to neighbor discovery messages in the MANET routing protocols, such as in AODV, DYMO. In an attempt to enhance the scheme, this paper proposes a new approach to solve the problem by reducing unnecessary hello messages. In this paper we consider MANET under random waypoint model and investigated the relationship between the hello interval and event intervals. Finally we evaluate our study through simulations, the proposed scheme reduces the energy consumption and overhead of neighbor discovery processes.

The rapid change of topology is one of the most important factors affecting the performance of the routing protocols of flying ad hoc networks (FANETs). A routing scheme suitable for highly dynamic mobile ad hoc networks is proposed for the rapid change of topology in complex scenarios. In the scheme moving nodes sense changes of the surrounding network topology periodically, and the current mobile scenario is confirmed according to the perceived result. Furthermore, a suitable routing protocol is selected for maintaining network performances at a high level. The concerned performance metrics are packet delivery ratio, network throughput, average end-to-end delay and average jitter. The experiments combine the random waypoint model, the reference point group mobility model and the pursue model to a chain scenario, and simulate the large changes of the network topology. Results show that an appropriate routing scheme can adapt to rapid changes in network topology and effectively improve network performance.

International audience; User mobility is of critical importance when designing mobile networks. In particular, "waypoint" mobility has been widely used as a simple way to describe how humans move. This paper introduces the first modeling framework to model waypoint-based mobility. The proposed framework is simple, yet general enough to model any waypoint-based mobility regimes. It employs first order ordinary differential equations to model the spatial density of participating nodes as a function of (1) the probability of moving between two locations within the geographic region under consideration, and (2) the rate at which nodes leave their current location. We validate our models against real user mobility recorded in GPS traces collected in three different scenarios. Moreover, we show that our modeling framework can be used to analyze the steady-state behavior of spatial node density resulting from a number of synthetic waypoint-based mobility regimes, including the widely used Random Waypoint (RWP) model. Another contribution of the proposed framework is to show that using the well-known preferential attachment principle to model human mobility exhibits behavior similar to random mobility, where the original spatial node density distribution is not preserved. Finally, as an example application of our framework, we discuss using it to generate steady-state node density distributions to prime mobile network simulations.

Wireless networks are increasing in popularity with current advances in technology, The architecture of such networks is not based on a centralized base station but on each node which acts as a router and forwards data packets to other nodes in the network. The technologies have driven into new era with the introduction of ad hoc networks and the concept behind the ad hoc networks is it works without the access points. It has features like adaptive, self organizing and decentralized in nature. Due to these specialized features, it has become a popular technology. So, there has been an inevitable need of a good routing protocol in order to establish the connection between the nodes since the mobile nodes can change their topology frequently. The movement of the mobile node is one of the important characteristics because it can affect the performance of the ad hoc network protocol. This paper has analyzed the mobility of the random waypoint model for different routing protocols in mobile ad-hoc network.

The high-level contribution of this paper is to establish benchmarks for the minimum hop count per source-receiver path and the minimum number of edges per tree for multicast routing in mobile ad hoc networks (MANETs) under different mobility models. In this pursuit, we explore the tradeoffs between these two routing strategies with respect to hop count, number of edges and lifetime per multicast tree with respect to the Random Waypoint, City Section and Manhattan mobility models. We employ the Breadth First Search algorithm and the Minimum Steiner Tree heuristic for determining a sequence of minimum hop and minimum edge trees respectively. While both the minimum hop and minimum edge trees exist for a relatively longer time under the Manhattan mobility model; the number of edges per tree and the hop count per source-receiver path are relatively low under the Random Waypoint model. For all the three mobility models, the minimum edge trees have a longer lifetime compared to the minimum hop trees and the difference in lifetime increases with increase in network density and/or the multicast group size. Multicast trees determined under the City Section model incur fewer edges and lower hop count compared to the Manhattan mobility model.

In wireless network simulation analysis, researchers tweak mobility metrics, such as the speed or the pause time of the nodes, to get different stability levels of the network. Meanwhile, in theoretical analysis, link failure rate is widely used to model the stability of a wireless network. This paper presents an analysis of a simplified mobility model and shows that the link failure rate is positively correlated with the average speed of nodes in this model. Though this result is based on a mobility model with many restrictions, a simulation evaluation suggests that the result still holds in the popular random waypoint model and random direction model. Based on this observation, this paper also encourages the use of link failure rate as mobility metric instead of the problematic pause time in future practice.

Ensuring the consistency and the availability of replicated data in highly mobile ad hoc networks is a challenging task because of the lack of a backbone infrastructure. Previous work provides strong data guarantees by limiting the motion and the speed of the mobile nodes during the entire system lifetime, and by relying on assumptions that are not realistic for most mobile applications. We provide a small set of mobility constraints that are sufficient to ensure strong data guarantees and that can be applied when nodes move along unknown paths and speed, and are sparsely distributed. In the second part of the paper, we analyze the problem of conserving energy while ensuring strong data guarantees, using quorum system techniques. We devise a condition necessary for a quorum system to guarantee data consistency and data availability under our mobility model. This condition shows the unsuitability of previous quorum systems and is the basis for a novel class of quorum systems suitable for highly mobile networks, called mobile dissemination quorum (MDQ) systems. We also show a MDQ system that is provably optimal in terms of communication cost by proposing an efficient implementation of a read/write atomic shared memory. The suitability of our mobility model and MDQ systems is validated through simulations using the random waypoint model and the restricted random waypoint on a city section. Finally, we apply our results to assist routing and coordinate the low duty cycle of mobile nodes while maintaining network connectivity.

The simulation of mobility models such as the random waypoint often cause subtle problems, for example the decay of average speed as the simulation progresses, a difference between the long term distribution of nodes and the initial one, and sometimes the instability of the model. All of this has to do with time averages versus event averages. This is a well understood, but little known topic, called Palm calculus. In this paper we first give a very short primer on Palm calculus. Then we apply it to the random waypoint model and variants (with pause time, random walk). We show how to simply obtain the stationary distribution of nodes and speeds, on a connected (possibly non convex) area. We derive a closed form for the density of node location on a square or a disk. We also show how to perform a perfect (i.e. transient free) simulation without computing complicated integrals. Last, we analyze decay and explain it as either convergence to steady state or lack of convergence.

The objective of the work is to analyze the impact of weather conditions on different types of MANET routing protocols. The influence of weather on the performances of MANET protocols such as AODV, STAR, RIP and ZRP are compared with and without considering weather conditions. Most of the works are not considering the effect of weather, when analysing the performances of MANET protocols. The simulations are carried out using Qualnet 5.0 with 100 nodes. The mobility model used for simulation is the Random waypoint model, where each node is moving independently to reach the destination with a random velocity. The velocity of each mobile node varies from 10 m/s to 50 m/s with the weather intensity of 1000 deg/m2. The performance metrics such as end to end delay, jitter, through put and packet delivery ratio are analysed and compared. The simulation results reveals that AODV provides better throughput and high packet delivery ratio compared to other protocols under with and without considering weather. STAR protocol yields good performance with respect to end to end delay and jitter under both conditions.

In this paper we study the so-called random waypoint (RWP) mobility model in the context of cellular networks. In the RWP model the nodes, i.e., mobile users, move along a zigzag path consisting of straight legs from one waypoint to the next. Each waypoint is assumed to be drawn from the uniform distribution over the given convex domain. In this paper we characterise the key performance measures, mean handover rate and mean sojourn time from the point of view of an arbitrary cell, as well as the mean handover rate in the network. To this end, we present an exact analytical formula for the mean arrival rate across an arbitrary curve. This result together with the pdf of the node location, allows us to compute all other interesting measures. The results are illustrated by several numerical examples. For instance, as a straightforward application of these results one can easily adjust the model parameters in a simulation so that the scenario matches well with, e.g., the measured sojourn times in a cell.

In the performance evaluation of a protocol for an ad hoc network, the protocol should be tested under realistic conditions including, but not limited to, a sensible transmission range, limited buffer space for the storage of messages, representative data traffic models, and realistic movements of the mobile users (i.e., a mobility model). This paper is a survey of mobility models that are used in the simulations of ad hoc networks. We describe several mobility models that represent mobile nodes whose movements are independent of each other (i.e., entity mobility models) and several mobility models that represent mobile nodes whose movements are dependent on each other (i.e., group mobility models). The goal of this paper is to present a number of mobility models in order to offer researchers more informed choices when they are deciding upon a mobility model to use in their performance evaluations. Lastly, we present simulation results that illustrate the importance of choosing a mobility model in the simulation of an ad hoc network protocol. Specifically, we illustrate how the performance results of an ad hoc network protocol drastically change as a result of changing the mobility model simulated.

In this paper, we derive the probability distribution of the epoch length for the random waypoint model in mobile ad hoc networks. An epoch here is referred to as the movement between two target locations in the mobility model. Such a study is important as the epoch length distribution may be required for the derivation of the link-duration distribution or node spatial distribution for mobile ad hoc networks. The analytical result is then verified via simulation.

International audience; In this paper, we tackle the problem of designing a random mobility model generating a target node spatial distribution. More specifically, we solve a long standing open problem by presenting two versions of the well-known random waypoint (RWP) mobility model in bounded regions generating a uniform steady-state node spatial distribution. In the first version, named temporal-RWP, we exploit the temporal dimension of node mobility and achieve uniformity by continuously changing the speed of a mobile node as a function of its location and of the density function of trajectories in the movement region R. In the second version, named spatial-RWP, we instead exploit the spatial dimension and achieve uniformity by selecting waypoints according to a suitably defined mix of probability density functions. Both proposed models can be easily incorporated in wireless network simulators, and are thus of practical use. The RWP models presented in this paper allow for the first time completely removing the well-known border effect causing possible inaccuracies in mobile network simulation, thus completing the picture of a "perfect" simulation methodology drawn in existing literature.

International audience; Simulating human-centered pervasive systems requires accurate assumptions on the behavior of human groups. Recent models consider this behavior as a combination of both social and spatial factors. Yet, establishing accurate traces of human groups is difficult: current techniques capture either positions, or contacts, with a limited accuracy. In this paper we introduce a new technique to capture such behaviors. The interest of this approach lies in the unprecedented accuracy at which both positions and orientations of humans, even gathered in a crowd, are captured. From the mobility to the topological connectivity, the open-source framework we developed offers a layered approach that can be tailored, allowing to compare and reason about models and traces. We introduce a new trace of 50 individuals on which the validity and accuracy of this approach is demonstrated. To showcase the interest of our software pipeline, we compare it against the random waypoint model. Our fine-grain analyses, that take into account social interactions between users, show that the random way point model is not a reasonable approximation of any of the phenomena we observed.

The high-level contributions of this paper are: (1) A generic algorithm to determine connected dominating sets (CDS) for mobile ad hoc networks and its use to find CDS of different categories: maximum density-based (MaxD-CDS), node ID-based (ID-CDS) and stability-based (minimum velocity-based, MinV-CDS); (2) Performance comparison of the above three categories of CDS algorithms with respect to two categories of mobility models: random node mobility models (Random Waypoint model) and the grid-based vehicular ad hoc network (VANET) mobility models (City Section and Manhattan mobility models), with respect to the CDS Node Size and Lifetime. The performance of a CDS is observed to depend on the criteria used to form the CDS (i.e., the node selection criteria of the underlying algorithm) and the mobility model driving the topological changes. For each category of CDS, we identify the mobility model under which one can simultaneously maximize the lifetime and node size, with minimal tradeoff. For the two VANET mobility models, we also evaluate the impact of the grid block length on the CDS lifetime and node size.

We study connectivity properties in a probabilistic model for a large mobile ad-hoc network. We consider a large number of participants of the system moving randomly, independently and identically distributed in a large domain, with a space-dependent population density of finite, positive order and with a fixed time horizon. Messages are instantly transmitted according to a relay principle, that is, they are iteratively forwarded from participant to participant over distances smaller than the communication radius until they reach the recipient. In mathematical terms, this is a dynamic continuum percolation model. We consider the connection time of two sample participants, the amount of time over which these two are connected with each other. In the above thermodynamic limit, we find that the connectivity induced by the system can be described in terms of the counterplay of a local, random and a global, deterministic mechanism, and we give a formula for the limiting behaviour. A prime example of the movement schemes that we consider is the well-known random waypoint model. Here, we give a negative upper bound for the decay rate, in the limit of large time horizons, of the probability of the event that the portion of the connection time is less than the expectation., Comment: Published at http://dx.doi.org/10.3150/15-BEJ724 in the Bernoulli (http://isi.cbs.nl/bernoulli/) by the International Statistical Institute/Bernoulli Society (http://isi.cbs.nl/BS/bshome.htm)

Link duration between two vehicles is considered an important quality of service metric in designing a network protocol for vehicular networks. There exist many works that study the probability density functions of link duration in a vehicular network given various vehicle mobility models, for example, the random waypoint model. None of them, however, provides a practical solution to estimating the link duration between two vehicles on the road. This is in part because link duration between vehicles is affected by many factors including the distance between vehicles, their turning directions at intersections, and the impact of traffic lights. Considering these factors, we propose the extended link duration prediction (ELDP) model which allows a vehicle to accurately estimate how long it will be connected to another vehicle. The ELDP model does not assume that vehicles follow certain mobility models; instead, it assumes that a vehicle's velocity follows the Normal distribution. We validate the ELDP model in both highway and city scenarios in simulations. Our detailed simulations illustrate that relative speed between vehicles plays a vital role in accurately predicting link duration in a vehicular network. On the other hand, we find that the turning directions of a vehicle at intersections have subtle impact on the prediction results.

In this paper, we analyze the mobility patterns of users of wireless hand-held PDAs in a campus wireless network using an eleven week trace of wireless network activity. Our study has two goals. First, we characterize the high-level mobility and access patterns of hand-held PDA users and compare these characteristics to previous workload mobility studies focused on laptop users. Second, we develop two wireless network topology models for use in wireless mobility studies: an evolutionary topology model based on user proximity and a campus waypoint model that serves as a trace-based complement to the random waypoint model. We use our evolutionary topology model as a case study for preliminary evaluation of three ad hoc routing algorithms on the network topologies created by the access and mobility patterns of users of modern wireless PDAs. Based upon the mobility characteristics of our trace-based campus waypoint model, we find that commonly parameterized synthetic mobility models have overly aggressive mobility characteristics for scenarios where user movement is limited to walking. Mobility characteristics based on realistic models can have significant implications for evaluating systems designed for mobility. When evaluated using our evolutionary topology model, for example, popular ad hoc routing protocols were very successful at adapting to user mobility, and user mobility was not a key factor in their performance.

Mobile ad hoc network is a collection of wireless nodes that communicate to each other without using any infrastructure, access point, or centralized network. Each nodes have own capability to receiving and forwarding packet each other device in mobile ad hoc network. In this article, showing the performance of dynamic source routing protocol based on the broadcasting data on nodes placement scenarios using random waypoint model (RWM). Broadcast packet on CBR that means constant bit rate data transfer constantly on random waypoint model and showing the effective performance of dynamic source routing protocol in mobile ad hoc network (MANET).The performance analysis is based on different network metrics such as Number of Hop Counts, Number of Routes Selected, Number of RREP Received, and Number of RREQ discarded for loop, Number of RREQ received, Number of Duplicate RREQ received, Number of RREQ Retried, and Number of Data Packets Dropped for no route, Number of RREQ Forwarded, Number of RREQ TTL expired and Residual Battery Capacity.