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International audience; Delay Tolerant networks (DTNs) are one type of wireless networks where the number of nodes per unit area is small and hence the connectivity between the nodes is intermittent. In this case, the performance in terms of transport of information from source to destination relies on the mobility of the nodes which would cause their encounters and hence the relay of information from one node to another as well as on the routing protocol that is deployed. There exists several mobility patterns, each yielding a different performance of the network. In this work, we show first that the Manhattan mobility pattern performs worse than other widely-used ones, such as Random WayPoint. In the second part of this work, our aim is to propose and evaluate a new proposal, based on the deployment of fixed relays, so as to enhance the performance of Manhattan

This thesis focuses on developing methods and models making it possible to evaluate quantitative measures characterizing the dependability of mobile services as perceived by the users. These models and measures are aimed at providing support to the designers during the selection and analysis of candidate architectures that are well suited to fulfill the dependability requirements. We consider the case of vehicular applications using inter-vehicle communications based on ad-hoc networks and may have access to services located on fixed infrastructure. We propose an approach combining: 1) dependability models based on stochastic activity networks, in order to describe the system failure modes and associated recovery mechanisms, and 2) simulation and analytical models allowing the estimation of connectivity characteristics, taking into account different mobility scenarios and environment. This approach is illustrated on three case studies including a virtual black box based on cooperative data replication and backup, and an automated highway system (Platooning application).; Cette thèse porte sur le développement de méthodes et de modèles permettant de quantifier la sûreté de fonctionnement d'applications embarquées sur des systèmes mobiles. L'objectif est de fournir des indicateurs pour l'analyse et la sélection des architectures les plus adaptées pour satisfaire les exigences de sûreté de fonctionnement. Nous considérons le cas des applications véhiculaires utilisant des communications inter-véhicules basées sur des réseaux ad-hoc et pouvant avoir accès à des services situés sur des infrastructures fixes. Nous proposons une approche combinant: 1) des modèles de sûreté de fonctionnement utilisant des réseaux d'activités stochastiques permettant de décrire les modes défaillances et de restauration des systèmes considérés et 2) des simulations et des modèles analytiques de scénarios de mobilité permettant d'estimer des caractéristiques de connectivité de ces systèmes. Cette approche est illustrée sur trois cas d'études dont un système d'autoroute automatisée, et une boîte noire virtuelle basée sur la réplication et la sauvegarde coopérative des données.

The study on performance of On-demand Ant Routing Algorithm for Mobile Ad Hoc Network is done. An ant routing algorithm based on swarm intelligence and especially on Ant Colony Optimization (ACO). It describes a noval on demand Ant colony algorithm for MANETs. This algorithm tries to minimize complexity at nodes and this is achived at exoences of optimality of routing path. Inextensive set of simulation experiment, We try to set parameter of ant routing algorithms and compare Proposed algorithm with DAR,a pre existing on demand ant routing algorithms and with AODV,a reference algorithm in MANETs. The comparition base on optimal path length with respect to control overhead.

A model that realistically imitates real pedestrian movement can be used for numerous applications such as infrastructure design, evacuation planning, architecture, robot-human interaction or navigation. Within the scope of this paper, the purpose of such models is to quantitatively represent both the stochastic and deterministic nature of 3D pedestrian movement in order to generate a movement model for sequential Bayesian filtering techniques, such as particle-filtering. The prediction stage of sequential Bayesian positioning estimators depends entirely on the movement model to determine the probability density function of the pedestrian’s location and motion at each time step. A movement model that accurately represents the pedestrian’s motion ensures that measurement data used for positioning is consistent with how a normal pedestrian might move. Furthermore, the model has to be efficiently implemented to that it can be employed in realizations such as Particle Filters. We note that the model does not need to predict the motion of a single pedestrian accurately in any singular experiment; but it needs to correctly model the expected motion in a probabilistic sense. In this paper, a three-dimensional movement model that is suitable for pedestrian navigation will be illustrated. Specifically, the knowledge of maps and floor-plans is used in our movement model and the performance gain on the overall positioning will be investigated. A combination of three-dimensional movement models will be used to model the pedestrian motion. The constituents are a three dimensional Stochastic Behavioral Movement Model and a three dimensional Targeted Movement Model. Some specific constraints are applied on the pedestrian movement while moving on stairs to have a realistic stairs movement. 3D Stochastic Behavioral Movement Model: Human movement is parameterized by physical parameters such as speed, direction and as a result the position. Building layouts are obviously amongst the main parameters that affect the movement of the pedestrian. In order to add the third dimension, the model of [KKRA08] was extended to be able to predict the elevation of the pedestrian at each time step. A linear speed function is used for modeling the elevation. This vertical speed is designed to be a function of time, steepness of the stairs and "activeness" of the pedestrian. Accordingly, the probability distribution of the distance moved in the Z-direction can be calculated. The direction of vertical movement could also be modeled, but in order to have a more realistic movement in the stairs area, the direction is predicted using a targeted movement model described below. Outside the stairs area, the elevation is assumed to be constant. 3D Target Driven Movement Model: To represent target driven human motion, a so-called "diffusion movement" model [KKRA08] is applied. It is derived from "gas diffusion" in space studied in thermodynamics and is a standard solution for path finding of robots [ScA93]: The idea is to have a source continuously effusing gas that disperses in free space and which gets absorbed by walls and other obstacles. A path towards this source is computed by following the steepest gradient, starting at the current position. To model the stochastic nature of a human´s motion, the destination points are chosen randomly, and a Markov process models the fact that the destination may change. In order to add the third dimension, the set of destinations can be distributed over all the floors. The stairs area is projected into a 2D area that can be included in the respective floor plan of each floor. Accordingly, the diffusion matrix calculation can be started at any of the floors. The diffusion matrix at the stairs area of the destination floor is calculated for the stairs going up and down and then copied to the stairs areas of the respective neighboring floors. The diffusion matrix is then calculated from the stairs area to the rest of the respective floor. The stairs diffusion matrix of the next upper or lower stairs is calculated using the values of the current floor and so on. Paths to the destinations are found in the same 2D manner but continuing to the upper or lower floors until the destination is reached. Combined Model: If the pedestrian is outside the stairs area a top-level Markov process is used to determine whether to use the stochastic behavioral or the diffusion model; therefore, the model switches between motion that is more goal oriented or stochastic. The destination point for the diffusion model is kept until the destination is reached or until the top-level Markov process determines that the stochastic behavioral movement model is again used. When applying the diffusion model the path is computed in two steps: the direction is chosen to follow the gradient of the gas diffusion towards the target while the speed of the pedestrian is predicted with the stochastic behavioral movement model. If the pedestrian enters the stairs area then the three dimensional Stochastic Movement Model will be used to predict distances moved in X, Y, Z directions. These distances are passed to the Targeted Movement Model to be combined with the paths and obtain the new positions. Maps and Floor-Plans: The effect of the advance knowledge of specific maps and floor-plans will be tested in an already available distributed simulation and demonstration system for mobility, and location estimation. The system allows us to integrate several types of sensors, Bayesian Filters, movement models, maps and floor plans. We will discuss quantitative performance improvements that our 3D movement model allows when combined with maps and floor-plans in the overall estimation process in pedestrian indoor/outdoor navigation applications.

A movement model that realistically imitates real pedestrian movement can be used for numerous applications such as transport infrastructure design, evacuation planning, architecture, human like robot movement or indoor/outdoor navigation. Within the scope of this paper, the purpose of such models is to quantitatively represent the stochastic nature of pedestrian movement in order to generate a pedestrian movement model for sequential Bayesian filtering techniques, such as particle-filtering. Within the work that has led to this paper we have been particularly interested in finding suitable movement models for further use in a sequential Bayesian estimation algorithm for navigation purposes in 2D and 3D. A movement model in the sense of a first order Markov process can, therefore, be used to represent and predict the current set of human motion and behavioral parameters as a function of previous parameters and other affecting states. The prediction stage of sequential Bayesian estimation depends entirely on the movement model to determine the probability density function of the pedestrian’s location and motion at each time step. A movement model that accurately models the pedestrian’s motion strongly determines the performance of the sequential Bayesian estimation algorithm, and ensures that measurement data used for positioning is correctly weighted with the movement model prediction. Furthermore, the model has to be efficiently implemented to that it can be employed in realizations such as Particle Filters. We note that the model does not need to predict the motion of a single pedestrian accurately in any singular experiment; it needs to correctly model the expected motion in a probabilistic sense. In this paper, a three dimensional movement model at the microscopic level that is suitable for pedestrian navigation will be illustrated. A combination of three dimensional movement models will be used to model the pedestrian movement. The constituents are a three dimensional Stochastic Behavioral Movement Model and a three dimensional Targeted Movement Model. Some specific constraints are applied on the pedestrian movement while moving on stairs to have a realistic stairs movement. A three dimensional Stochastic Behavioral Movement Model Human movement is parameterized by physical parameters such as speed, direction and as a result the position. Building layouts are obviously amongst the main parameters that affect the movement of the pedestrian. For instance, the pedestrian cannot penetrate a wall under any normal circumstances. In order to add the third dimension, the model was extended to be able to predict the height of the pedestrian at each time step. A linear speed function is used for modeling the height. This speed is designed to be a function of time, steepness of the stairs and activeness of the pedestrian. Accordingly, the distance moved in the Z-direction could be predicted in addition to the distances in X and Y. The direction of vertical movement could also be modeled, but in order to have a more realistic movement in the stairs area, the direction is predicted using the Targeted Movement Model. Outside the stairs area, the height is assumed to be constant. A three dimensional Target Driven Movement Model To overcome the problem of tending to stay too long in rooms or displaying motion that is not goal orientated, the diffusion movement model is applied. This model is derived from the gas diffusion in space studied in thermodynamics and is a standard solution for path finding of robots: The idea is to have a source continuously effusing gas that disperses in free space and which gets absorbed by walls and other obstacles. A path towards this source is computed by following the steepest gradient, starting at the current position. To model the stochastic nature of a human’s motion, the destination points are chosen randomly, and a Markov process models the fact that the destination may change more or less frequently. In order to add the third dimension, the set of destinations are spread over all the floors. The stairs area is projected into a 2D area that can be included in the respective floor plan of each floor. Accordingly, the diffusion matrix calculation could be started at any of the floors. The diffusion matrix at the stairs area of the destination floor is calculated for the stairs going up and down and then copied to the stairs areas of the respective neighboring floors. The diffusion matrix is then calculated from the stairs area to the rest of the respective floor. The stairs diffusion matrix of the next upper or lower stairs is calculated using the values of the current floor and so on. Paths to the destinations are found in the same 2D manner but continuing to the upper or lower floors until the destination is reached. Combined Model If the pedestrian is outside the stairs area a top-level Markov process is used to determine whether to use the stochastic behavioral or the diffusion model; therefore, the model switches between motion that is more goal oriented or stochastic. The destination point for the diffusion model is kept until the destination is reached or until the top-level Markov process determines that the stochastic behavioral movement model is again used. When applying the diffusion model the path is computed in two steps: the direction is chosen to follow the gradient of the gas diffusion towards the target while the speed of the pedestrian is predicted with the stochastic behavioral movement model. If the pedestrian enters the stairs area then the three dimensional Stochastic Movement Model will be used to predict distance moved in the Z-direction. This distance is passed to the Targeted Movement Model to calculate distances moved in X, and Y and additionally the directions. A realistic pedestrian movement in the stairs is more target driven and that is why we are more biased toward the Targeted Movement Model while being in the stairs area.

This paper presents the generic layered architecture for mobility models (LEMMA), which can be used to construct a wide variety of mobility models, including the majority of models used in wireless network simulations. The fundamental components of the architecture are described and analyzed, in addition to its benefits. One of the core principles stipulates that each mobility model is divided in five distinct layers that communicate via interfaces. This allows their easy replacement and recombination, which we support by reviewing 19 layers that can form 480 different mobility models. Some of the advanced features provided by the architecture are also discussed, such as layer aggregation, and creation of hybrid and group mobility models. Finally, some of the numerous existing studies of the different layers are presented.

Ubiquitous Computing promises to enrich our everyday lives by enabling the environment to be enhanced via computational elements. These elements are designed to augment and support our lives, thus allowing us to perform our tasks and goals. The main facet of Ubiquitous Computing is that computational devices are embedded in the environment, and interact with users and themselves to provide novel and unique applications. Ubiquitous Computing requires an underlying architecture that helps to promote and control the dynamic properties and structures that the applications require. In this thesis, the Networking package of Communicating Sequential Processes for Java (JCSP) is examined to analyse its suitability as the underlying architecture for Ubiquitous Computing. The reason to use JCSP Networking as a case study is that one of the proposed models for Ubiquitous Computing, the ?-Calculus, has the potential to have its abstractions implemented within JCSP Networking. This thesis examines some of the underlying properties of JCSP Networking and examines them within the context of Ubiquitous Computing. There is also an examination into the possibility of implementing the mobility constructs of the ?-Calculus and similar mobility models within JCSP Networking. It has been found that some of the inherent properties of Java and JCSP Networking do cause limitations, and hence a generalisation of the architecture has been made that should provide greater suitability of the ideas behind JCSP Networking to support Ubiquitous Computing. The generalisation has resulted in the creation of a verified communication protocol that can be applied to any Communicating Process Architecture.

Mobile Ad Hoc networks are subject to some unique security issues that could delay their diffusion. Several solutions have already been proposed to enforce specific security properties. However, mobility pattern nodes obey to can, on one hand, severely affect the quality of the security solutions that have been tested over "synthesized" mobility pattern. On the other hand, specific mobility patterns could be leveraged to design specific protocols that could outperform existing solutions. In this work, we investigate the influence of a realistic mobility scenario over a benchmark mobility model (Random Waypoint Mobility Model), using as underlying protocol a recent solution introduced for the detection of compromised nodes. Extensive simulations show the quality of the underlying protocol. However, the main contribution is to show the relevance of the mobility model over the achieved performances, stressing out that in mobile ad-hoc networks the quality of the solution provided is satisfactory only when it can be adapted to the nodes underlying mobility model.

In this paper, we investigate the impact of mobility on the performance of multi-hop wireless ad hoc and sensor networks. We introduced some models of mobility in these networks and studied their behavior in realistic situations. It concerns the basic relationship between link length and message transmission. Additionally, we take into consideration the probability of successful transmission in an interference limited channel when fading is modeled as Rayleigh block fading. Our mobility models are verified by an accurate description and simulation of the behavior of mobile sensor and ad hoc networks., Studia Informatica, Vol 29, No 4B (2008)

According to different kinds of connectivity, we can distinguish three types of mobile ad-hoc networks: dense, sparse and clustered networks. This paper is about modeling mobility in clustered networks, where nodes are concentrated into clusters of dense connectivity, and in between there exists sparse connectivity. The dense and sparse networks are extensively studied and modeled, but not much attention is paid to the clustered networks. In the sparse and clustered networks, an inherently important aspect is the mobility model, both for the design and evaluation of routing protocols. We propose a new mobility model for clustered networks, called Heterogeneous Random Walk. This model is simple, mathematically tractable and most importantly it captures the phenomenon of emerging clusters, observed in real partitioned networks, in an elegant way. We provide a closed-form expression for the stationary distribution of node position and we give a recipe for the "perfect simulation". Moreover, based on the real mobility trace we provide strong evidence for the main macroscopic characteristics of clustered networks captured by the proposed mobility model. For the very first time in the literature we show evidence for the correlation between the spatial speed distribution and the cluster formation. We also present the results of the analysis of real cluster dynamics caused by nodes' mobility.

Technology has reached a point where it has become feasible to develop unmanned aerial vehicles (UAVs), that is aircraft without a human pilot on board. Given that future UAVs can be autonomous and cheap, applications of swarming UAVs are possible. In this thesis we have studied a reconnaissance application using swarming UAVs and how these UAVs can communicate the reconnaissance data. To guide the UAVs in their reconnaissance mission we have proposed a pheromone based mobility model that in a distributed manner guides the UAVs to areas not recently visited. Each UAV has a local pheromone map that it updates based on its reconnaissance scans. The information in the local map is regularly shared with a UAV’s neighbors. Evaluations have shown that the pheromone logic is very good at guiding the UAVs in their cooperative reconnaissance mission in a distributed manner. Analyzing the connectivity of the UAVs we found that they were heavily partitioned which meant that contemporaneous communication paths generally were not possible to establish. This means that traditional mobile ad hoc network (MANET) routing protocols like AODV, DSR and GPSR will generally fail. By using node mobility and the store-carry-forward principle of delay-tolerant routing the transfer of messages between nodes is still possible. In this thesis we propose location aware routing for delay-tolerant networks (LAROD). LAROD is a beacon-less geographical routing protocol for intermittently connected mobile ad hoc networks. Using static destinations we have shown by a comparative study that LAROD has almost as good delivery rate as an epidemic routing scheme, but at a substantially lower overhead. Report code: LiU-Tek-Lic-2008:14

Carme Miralles-Guasch i Laia Oliver-Frauca analitzen els hàbits de mobilitat de la regió metropolitana de Barcelona, on el patró de mobilitat no només és determinat per les característiques territorials i l’oferta d’infraestructures i serveis de transport existent, sinó que també és fortament condicionat pels trets personals de cada individu i de cada col·lectiu., Carme Miralles-Guasch y Laia Oliver-Frauca analizan los hábitos de movilidad de la Regió Metropolitana de Barcelona, donde el patrón no viene determinado solamente por las características territoriales y por la oferta de infraestructuras y servicios de transporte existente, sino que también está muy condicionado por los rasgos personales de cada individuo y de cada colectivo.

The thesis investigates the process of modeling and simulation of the mobile ad-hoc networks. It provides a overview of the actual state of art together with a literature survey. Basic ideas of both security issues in mobile ad-hoc networks as well as intrusion detection systems are presented. Additionally some new ideas for improvements - like the AGM mobility model - are proposed, and tested during the simulation proces. As an addition a set of applications designer for automating the simulation processes were created.

We examine the fundamental properties that determine the basic performance metrics for opportunistic communications. We first consider the distribution of intercontact times between mobile devices. Using a diverse set of measured mobility traces, we find as an invariant property that there is a characteristic time, order of half a day, beyond which the distribution decays exponentially. Up to this value, the distribution in many cases follows a power law, as shown in recent work. This power law finding was previously used to support the hypothesis that inter-contact time has a power law tail, and that common mobility models are not adequate. However, we observe that the time scale of interest for opportunistic forwarding may be of the same order as the characteristic time, and thus the exponential tail is important. We further show that already simple models such as random walk and random waypoint can exhibit the same dichotomy in the distribution of inter-contact times as in empirical traces. Finally, we perform an extensive analysis of several properties of human mobility patterns across several dimensions, and we present empirical evidence that the return time of a mobile device to its favorite location site may already explain the observed dichotomy. Our findings suggest that existing results on the performance of forwarding schemes based on power-law tails might be overly pessimistic.

The paper presents mobility framework for Wireless Sensor Networks (WSNs), which identifies mobility issues and requirements for mobility management within the Hybrid Hierarchical Architecture (HHA) proposed by CRUISE, and provides a methodology for evaluation of mobility-management solutions including mobility classifications, mobility models and performance metrics. The proposed mobility framework is a tool for evaluation of diverse set of scenarios and applications, in terms of mobility impact and mobility-enabled functionality. The paper briefly summarises the aspects of the mobility framework and provides examples of how the proposed methodology could be applied in a logistics scenario and a road-traffic scenario.

The paper presents mobility framework for Wireless Sensor Networks (WSNs), which identifies mobility issues and requirements for mobility management within the Hybrid Hierarchical Architecture (HHA) proposed by CRUISE, and provides a methodology for evaluation of mobility-management solutions including mobility classifications, mobility models and performance metrics. The proposed mobility framework is a tool for evaluation of diverse set of scenarios and applications, in terms of mobility impact and mobility-enabled functionality. The paper briefly summarises the aspects of the mobility framework and provides examples of how the proposed methodology could be applied in a logistics scenario and a road-traffic scenario.

A compact model of the low-field effective carrier mobility is developed for n- and p-type MOSFETs with either polySi or TiN gate, ultrathin SiO2/HfO2 gate stacks, and silicon under biaxial or uniaxial stress conditions. Physical insights, theoretical analyses and experimental investigations are used to develop and accurately calibrate the model.

This paper presents a new system level simulator that has been developed to evaluate Radio Resource Management (RRM) techniques in UMTS (Universal Mobile Telecommunication Systems) and enhanced-UMTS networks. The simulator includes new implementations for the User Equipment, Node B, Radio Network Controller nodes and can evaluate parameters associated with UMTS or enhanced-UMTS performance, related to the introduction of RRM functions. The RRM functions implemented deal with admission control, packet scheduling, handover control, load control, and power control. The evaluation of RRM mechanisms is supported by the provision of appropriate radio propagation, traffic generation, and mobility models. 2005 396 403 Sponsors: IEEE Computer Society CREATE-NET INRIA ICST Intel Conference code: 67373 Cited By :2

Ad hoc networks present the next great challenge for distributed systems research. Protocols that support communication in ad hoc networks have to take into account the mobility of the participants and the variation in the connectivity between associated parties. In fact, most research on routing algorithms in an ad hoc network is mainly based on algorithms dedicated to completely connected networks in which the node mobility is not used. In this thesis, we are interested on solutions which use mobility to improve routing performances. Some critical issues of routing in a large size ad hoc network are: inaccurate routing information about remote nodes, the connectivity and the protocol overhead. This thesis proposes a control mobility architecture to improve performances of the routing protocols in a large scale ad hoc network. We think that the node mobility represents an opportunity: if nodes move in an appropriate fashion, then routing algorithms can take advantage. Thus, our architecture with its rendez-vous mechanism try to reduce mobility and routing overhead. The use of the rendez-vous mechanism reduces energy consuption and node bandwidth, because the node transmission range can be reduced. We also present two algorithms, one fault tolerant in conjuction with simulations, tests and performances mesures. We also proved the feasibility of our solution by an implementation using real rebots., Un réseau ad hoc peut se voir comme une généralisation ultime d'un réseau sans fil. Les protocoles qui assurent la communication dans un réseau ad hoc doivent également prendre en compte la mobilité et la variation de la connectivité des noeuds. En fait, la recherche sur les algorithmes de routage dans les réseaux ad hoc s'est principalement concentrée sur des réseaux totalement connectés dans lesquels la mobilité des noeuds n'est pas utilisée. Dans cette thèse, nous nous sommes intéressés à des techniques qui mettent la mobilité au service du routage dans un réseau ad hoc de grande taille. Certains inconvénients du routage dans ces réseaux sont l'information imprécise sur le routage des noeuds à longue distance, la variation de la connectivité et le surcoût généré par les protocoles de routage. Cette thèse offre une solution basée sur le contrôle de la mobilité des noeuds pour amléiorer les performances des protocoles de routage d'un réseau ad hoc de grande taille. Nous pensons que le mouvement des noeuds présente une opportunité: si les noeuds se déplacent d'une manière appropriée, alors les algorithmes de routage peuvent en tirer profit. Ainsi, notre solution met en oeuvre un mécanisme de rendez-vous qui réduit, les effets de la mobilité, le surcoût dû aux mises à jour et assure une communication en temps borné dans le réseau. Une autre conséquence de ce mécanisme est la réduction de la consommation de l'énergie et de la bande passante car la zone de transmission des noeuds peut être réduite. Nous présentons deux algorithmes, dont un tolérant aux pannes et développé un simulateur pour faire des tests et des mesures de performances. De plus, nous avons montré la faisabilité de la solution par une implantation sur des robots.

Mobile ad hoc networks are characterized by a lack of a fixed infrastructure and by node mobility. In these networks data transfer can be improved by using mobile nodes as relay nodes. As a result, transmission power and the movement pattern of the nodes have a key impact on the performance. In this work we focus on the impact of node mobility through the analysis of a simple one-dimensional ad hoc network topology. Nodes move in adjacent segments with reflecting boundaries according to Brownian motions. Communications (or relays) between nodes can occur only when they are within transmission range of each other. We determine the expected time to relay a message and compute the probability density function of relaying locations. We also provide an approximation formula for the expected relay time between any pair of mobiles.

A number of mobility models have been proposed for the purpose of either analyzing or simulating the movement of users in a mobile wireless network. Two of the more popular are the random waypoint and the random direction models. The random waypoint model is physically appealing but difficult to understand. Although the random direction model is less appealing physically, it is much easier to understand. User speeds are easily calculated, unlike for the waypoint model, and, as we will observe, user positions and directions are uniformly distributed. The contribution of this paper is to establish this last property for a rich class of random direction models that allow future movements to depend on past movements. To this end, we consider finite one- and two-dimensional spaces. We consider two variations, the random direction model with wrap around and with reflection. We establish a simple relationship between these two models and, for both, show that positions and directions are uniformly distributed in steady-state for a class of Markov movement models regardless of initial position. In addition, we establish a sample path property for both models, namely that any piecewise linear movement applied to a user preserves the uniform distribution of position and direction provided that users were initially uniformly throughout the space with equal likelihood of being pointed in any direction.

The distribution of the dwell time, which represents a higher level of abstraction than the use of mobility models, is often required for the performance evaluation of mobile communication systems. This contribution investigates the problem of the dwell time modeling. Using the often employed model for a constant movement, it is shown that a suitable choice of the velocity distribution is very important. Thus, a condition for the probability density function (PDF) of the velocity is derived, which prevents an unbounded mean dwell time. Since an infinite mean dwell time causes some problems for the estimation of the mobility-related signaling traffic, it is important that the mean dwell time is finite. Furthermore, some basic models for the PDF of the travel length of a subscriber within a radio cell are introduced and the relation with realistic mobility patterns are shown.

A Monte Carlo Simulation based evaluation of mobile ad hoc network reliability is proposed which considers different mobility models along with the effect of different scenario metrics and different values of tuning parameter. Through our approach we show that the mobility considerations have no significant impact on reliability as the same results are obtained by just implicitly simulating the node locations. Considering no mobility models reduces computational burden, number of random variables involved making the algorithm more efficient is the added advantage. A comparative study of the results of the network reliability estimate considering with and without mobility is provided.

In this paper we revisit two classes of mobility models which are widely used to represent users' mobility in wireless networks: Random Waypoint (RWP) and Random Direction (RD). For both models we obtain systems of partial differential equations which describe the evolution of the users' distribution. For the RD model, we show how the equations can be solved analytically both in the stationary and transient regime adopting standard mathematical techniques. Our main contributions are i) simple expressions which relate the transient duration to the model parameters; ii) the definition of a generalized random direction model whose stationary distribution of mobiles in the physical space corresponds to an assigned distribution.

We define "random trip", a generic mobility model for random, independent node motions, which contains as special cases: the random waypoint on convex or nonconvex domains, random walk on torus, billiards, city section, space graph, intercity and other models. We show that, for this model, a necessary and sufficient condition for a time-stationary regime to exist is that the mean trip duration (sampled at trip endpoints) is finite. When this holds, we show that the distribution of node mobility state converges to the time-stationary distribution, starting from the origin of an arbitrary trip. For the special case of random waypoint, we provide for the first time a proof and a sufficient and necessary condition of the existence of a stationary regime, thus closing a long standing issue. We show that random walk on torus and billiards belong to the random trip class of models, and establish that the time-limit distribution of node location for these two models is uniform, for any initial distribution, even in cases where the speed vector does not have circular symmetry. Using Palm calculus, we establish properties of the time-stationary regime, when the condition for its existence holds. We provide an algorithm to sample the simulation state from a time-stationary distribution at time 0 ("perfect simulation"), without computing geometric constants. For random waypoint on the sphere, random walk on torus and billiards, we show that, in the time-stationary regime, the node location is uniform. Our perfect sampling algorithm is implemented to use with ns-2, and is available to download from http://ica1www.epfl.ch/RandomTrip

In "Stationary distributions for the random waypoint mobility model" (TMC, Vol. 3, No, 1), Navidi and Camp find the stationary distribution of the random waypoint model, with or without pause on a rectangular area. In this short note, we show that, under the stationary regime, speed and location are independent.

We define "random trip", a generic mobility model for random, independent node motions, which contains as special cases: the random waypoint on convex or nonconvex domains, random walk on torus, billiards, city section, space graph, intercity and other models. We show that, for this model, a necessary and sufficient condition for a time-stationary regime to exist is that the mean trip duration (sampled at trip endpoints) is finite. When this holds, we show that the distribution of node mobility state converges to the time-stationary distribution, starting from the origin of an arbitrary trip. For the special case of random waypoint, we provide for the first time a proof and a sufficient and necessary condition of the existence of a stationary regime, thus closing a long standing issue. We show that random walk on torus and billiards belong to the random trip class of models, and establish that the time-limit distribution of node location for these two models is uniform, for any initial distribution, even in cases where the speed vector does not have circular symmetry. Using Palm calculus, we establish properties of the time-stationary regime, when the condition for its existence holds. We provide an algorithm to sample the simulation state from a time-stationary distribution at time 0 ("perfect simulation"), without computing geometric constants. For random waypoint on the sphere, random walk on torus and billiards, we show that, in the time-stationary regime, the node location is uniform. Our perfect sampling algorithm is implemented to use with ns-2, and is available to download from http://ica1www.epfl.ch/RandomTrip.

Wireless ad hoc sensor networks differ from wireless ad hoc networks from the following perspectives: low energy, lightweight routing protocols, and adaptive communication patterns. This paper proposes an energy-aware routing protocol (EARP) suitable for ad hoc wireless sensor networks and presents an analysis for its energy consumption in various phases of route discovery and maintenance. Based on the energy consumption associated with route request processing, EARP advocates the minimization of route requests by allocating dynamic route expiry times. This paper introduces a unique mechanism for estimation of route expiry time based on the probability of route validity, which is a function of time, number of hops, and mobility parameters. In contrast to AODV, EARP reduces the repeated flooding of route requests by maintaining valid routes for longer durations.