Random Mobility Model Research Articles

GMMR: A Gaussian mixture model based unsupervised machine learning approach for optimal routing in opportunistic IoT networks

Opportunistic IoT (OppIoT) network is a subclass of Internet of Things network, in which connections between the source and destination devices are intermittent. This infrequent connectivity is due to lack of network infrastructure and random mobility models followed by devices. These attributes of the network make routing in OppIoT, an increasingly complex problem. Moreover OppIoT shares its unique network characteristics with another class of networks called Opportunistic Networks (OppNets). This commonality enables the same routing designs to be applicable to both OppNets and OppIoT. Increased research interest in Machine Learning (ML) has led to its successful application in routing solutions for OppNets through protocols like KNNR and MLPROPH. In this paper we pursue utilizing ML to automate routing decisions in OppIoT. To this end we use Gaussian Mixture Models, an ML based soft clustering mechanism, to develop the proposed routing protocol called GMMR. The design of GMMR is such that it combines the advantages of both context-aware and context-free routing protocols. We compare the performance of GMMR with that of KNNR, HBPR, MLPROPH, and PROPHET using simulations run on Opportunistic Network Environment (ONE) simulator. The performance criteria for this comparison includes delivery probability, network overhead ratio, average hop count and number of messages dropped. We will show through the results of the simulations, that GMMR outperforms all of the aforementioned routing protocols in terms of every performance parameter.

Impact of Mobility on Physical Layer Security Over Wireless Fading Channels

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.

Optimizing MDS Coded Caching in Wireless Networks With Device-to-Device Communication

We consider the caching of content in the mobile devices in a dense wireless network using maximum distance separable (MDS) codes. We focus on an area, served by a base station (BS), where mobile devices move around according to a random mobility model. Users requesting a particular file download the coded packets from caching devices within a communication range using device-to-device communication. If additional packets are required to decode the file, these are downloaded from the BS. We analyze the device mobility and derive a good approximation of the distribution of caching devices within the communication range of mobile devices at any given time. We then optimize the MDS codes to minimize the network load under a cache size constraint and show that using optimized MDS codes results in significantly lower network load compared to when caching the most popular files. We further show, numerically, that caching coded packets of each file on all mobile devices, i.e., maximal spreading, is optimal.

On the Distribution of the Received Signal Power in Mobile Networks: A Moment-Based Approach

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.

A Simple and Enriched Closed-Form Formula for Cell Residence Time in 5G Heterogeneous Networks

Cell residence time is a key system parameter for the performance analysis of cellular mobile systems and their related applications. In order to save cost and time before wide implementation and deployment of a mobile system, various network performance metrics, such as network resource occupancy probabilities, should be calculated through analytical results of the mean cell residence time. However, this is difficult to estimate in 5G heterogeneous networks, due to irregular-shaped multi-tier heterogeneous network topologies introduced by a diverse set of small cells. In order to find an efficient way of calculating the cell residence time for 5G heterogeneous networks, we first examine the well-known conventional formula. Then we propose an enhanced closed-form formula for cell residence time by considering more generalized cellular mobile systems, as well as more generic mobility models. The proposed closed-form formula can be directly applied to various complex and reliable network scenarios. It can be adapted to multi-tier heterogeneous networks with randomly positioned irregular-shaped small cells, even though they overlap with each other. Our simulation results show that the proposed formula provides excellent estimation accuracy for general random mobility models, including the Levy walk, which is known to realistically reflect human mobility.

A Comprehensive 3-Dimensional Random Mobility Modeling Framework for Airborne Networks

To design and evaluate airborne networks (ANs), it is crucial to utilize random mobility models (RMMs) that capture the physical movement patterns of different aerial vehicles in real scenarios. Compared to expensive flight field tests, RMM-based modeling, simulation, and emulation is cost-effective with a large set of RMM-generated flight trajectories. Despite the importance of RMMs, we notice that most existing models focus on the 2-D movement, and do not consider the temporal and 3-D spatial correlation of aerial mobility patterns. In this paper, we propose a comprehensive 3-D smooth turn (ST) modeling framework for fixed-wing aircraft, which can serve as a design and evaluation foundation for future ANs. In the proposed framework, we develop two realistic 3-D ST RMMs that capture the diverse mobility patterns of fixed-wing aircraft, through coupling stochastic forcing with physical laws that govern the 3-D aerial maneuvers. We also develop two boundary models to determine the movement of aerial vehicles when they approach simulation boundaries. Moreover, we propose an approach to estimate the optimal 3-D ST RMMs, with which we can produce rich trajectory ensembles with statistical mobility patterns that match with the real trajectory data.

Social Based Mobility Model with Metrics for Evaluation of Social Behaviour in Mobility Models for MANET-DTN Networks

In this paper, are described the basics of Social Based Mobility Model inspired by mobility of students alongside with Metrics for Evaluation of Social Behaviour in Mobility Models for MANET-DTN networks. These networks are mobile networks, where mobile devices are carried by humans. For simulation purposes, it is useful if mobility models designed to evaluate and tests performance of routing protocols are using mobility patterns and behaviour of humans. For these reasons, Students Social Based Mobility Model (SSBMM) was proposed as simulation tool with social mobility of nodes. To prove that SSBMM is really using social behaviour of nodes, Metrics for Evaluation of Social Behaviour in Mobility Models was designed. These metrics were adapted to the mobility of nodes in order to be able to reveal if the mobility of nodes in used mobility models is social. The performed simulations prove deviation of SSBMM from random mobility models. Described metrics reveal that SSBMM has strong social ties among nodes in comparison with random mobility models.

Tools for evaluation of social relations in mobility models

In MANET-DTN, the main idea is to detect the social relations between nodes in mobility models because the wireless mobile devices are carried by humans and the network uses the social relations to transport messages between isolated islands of the mobile terminals in order to increase the network performance. Today there are a lot of social and non-social mobility models. The problem is how to use these models in MANET-DTN. Therefore, proper evaluation method is needed, that is able to reveal the social aspect of investigated mobility model. Since there are a lot of methods that do not directly exhibit the social aspect of mobility models, in this paper the new evaluation method was proposed based on Louvain method for community detection and the other network graph parameter (average weighted degree). Simulations of evaluation method were made as a comparison between two random mobility models and one social based mobility model in order to point out differences between social and non-social mobility models. All models were evaluated by proposed method and other existing protocol dependent and independent methods. The main idea of the simulations was to analyse how the mobility models with social and non-social mobility models can affect the network performance and provide new and reliable tool, which enables analysis of the mobility models from social behaviour point of view.

Coverage Analysis of Mobile Network in Nakagami Fading Channel

Analysis of coverage and bit error rate (BER) for Wireless systems in a Nakagami fading channel have been reported in the literature. Most of the analysis considers the nodes to be static and the received power follows Gamma distribution. However, the nodes in Mobile Ad hoc Networks are mostly mobile. The mobility pattern of nodes is depicted using mobility models. In this paper, we consider the Random Direction mobility model to represent the mobility of mobile nodes. Due to mobility of nodes, the received power at the nodes does not follow Gamma distribution in a Nakagami fading environment. The probability density function and cumulative distribution function of the received power at the mobile nodes are derived in this paper. Subsequently, the coverage probability and average BER are derived. Furthermore, the effects of interference due to the presence of neighboring nodes on the coverage probability and average BER are investigated.

Impact of Random Mobility Models for Reactive Routing Protocols over MANET

Impact of Random Mobility Models for Reactive Routing Protocols over MANET

Hierarchical Coloured Petri Net based Random Direction Mobility Model for Wireless Communications

Most of the research in the area of wireless communications exclusively relies on simulations. Further, it is essential that the mobility management strategies and routing protocols should be validated under realistic conditions. Most appropriate mobility models play a pivotal role to determine, whether there is any subtle error or flaw in a proposed model. Simulators are the standard tool to evaluate the performance of mobility models however sometimes they suffer from numerous documented problems. To accomplish the widely acknowledged lack of formalization in this domain, a Coloured Petri nets (CPNs) based random direction mobility model for specification, analysis and validation is presented in this paper for wireless communications. The proposed model does not suffer from any border effect or speed decay issues. It is important to mention that capturing the mobility patterns through CPN is challenging task in this type of the research. Further, an appropriate formalism of CPNs supported to analyze the future system dynamic status. Finally the formal model is evaluated with the state space analysis to show how predefined behavioral properties can be applied. In addition, proposed model is evaluated based on generated simulations to track origins of errors during debugging.

Analysis of Cell Sojourn Time in Heterogeneous Networks With Small Cells

Recently, heterogeneous networks with small cells have been widely used to increase the capacity of mobile systems. In such environments, accurate estimation of the mean cell sojourn time is critical for evaluating the performance of the network and its applications. It is especially important to analyze the cell sojourn times of mobile users as they reside in different network tiers: either macro-cell-only or small-cell-covered areas. But because small cells are deployed in an irregular manner, it is difficult to derive the analytical mean cell sojourn time in a macro-cell-only area. In this letter, we propose a novel approach to resolve this difficulty. We developed a simple but effective trick that approximates the heterogeneous network to a discrete grid so that it becomes tractable, making it possible to derive the analytical mean sojourn time in the macro-cell-only area. Simulation results confirm that the proposed method has excellent accuracy for general random walk mobility models including random waypoint, Brownian motion, tailored Brownian motion, and truncated Levy walk.

Discovering Mobile Applications in Cellular Device-to-Device Communications: Hash Function and Bloom Filter-Based Approach

We propose a code-based discovery protocol for cellular device-to-device (D2D) communications. To realize proximity-based services such as mobile social networks and mobile marketing using D2D communications, each device should first discover nearby devices, which have mobile applications of interest, by using a discovery protocol. The proposed discovery protocol makes use of a short discovery code that contains compressed information of mobile applications in a device. A discovery code is generated by using either a hash function or a Bloom filter. When a device receives a discovery code broadcast by another device, the device can approximately find out the mobile applications in the other device. The proposed protocol is capable of quickly discovering massive number of devices while consuming a relatively small amount of radio resources. We analyze the performance of the proposed protocol under the random direction mobility model and a real mobility trace. By simulations, we show that the analytical results well match the simulation results and that the proposed protocol greatly outperforms a simple non-filtering protocol.

Detection of Intelligent Intruders in Wireless Sensor Networks

Most of the existing research works on the intrusion detection problem in a wireless sensor network (WSN) assume linear or random mobility patterns in abstracting intruders’ models in traversing the WSN field. However, in real-life WSN applications, an intruder is usually an intelligent mobile robot with environment learning and detection avoidance capability (i.e., the capability to avoid surrounding sensors). Due to this, the literature results based on the linear or random mobility models may not be applied to the real-life WSN design and deployment for efficient and effective intrusion detection in practice. This motivates us to investigate the impact of intruder’s intelligence on the intrusion detection problem in a WSN for various applications. To be specific, we propose two intrusion algorithms, the pinball and flood-fill algorithms, to mimic the intelligent motion and behaviors of a mobile intruder in detecting and circumventing nearby sensors for detection avoidance while heading for its destination. The two proposed algorithms are integrated into a WSN framework for intrusion detection analysis in various circumstances. Monte Carlo simulations are conducted, and the results indicate that: (1) the performance of a WSN drastically changes as a result of the intruder’s intelligence in avoiding sensor detections and intrusion algorithms; (2) network parameters, including node density, sensing range and communication range, play a crucial part in the effectiveness of the intruder’s intrusion algorithms; and (3) it is imperative to integrate intruder’s intelligence in the WSN research for intruder detection problems under various application circumstances.

The Mobile Version of the Predicted Energy Efficient Bee-Inspired Routing (PEEBR)

In this paper, the previously proposed Predictive Energy Efficient Bee-inspired Routing (PEEBR) family of routing optimization algorithms based on the Artificial Bees Colony (ABC) Optimization model is extended from a random static mobility model, as employed by its first version (PEEBR-1), into a random mobility model in its second version (PEEBR-2). This random mobility model used by PEEBR-2 algorithm is proposed and described. Then, PEEBR-2’s was simulated in order to compare its performance relative to the first version (PEEBR-1) in terms of predicted optimal path energy consumption, nodes batteries residual power and fitness. The simulation results have shown that PEEBR-2’s optimal path is predicted to consume less energy and realizing higher fitness. On the other hand, PEEBR-1’s optimal paths nodes possess higher batteries residual power. At last, the impact of mobile nodes speeds was studied for PEEBR-2 in terms of optimal path’s predicted energy consumption and path nodes batteries residual power showing its performance stability relative to nodes mobility speed.

Mobility Issue on Octagonal Structured ZigBee Network Using Riverbed

Wireless Sensor Network (WSN) is a special type of communication medium through distributed sensor nodes. Popular wireless sensor nodes like ZigBee have splendid interoperability after IEEE 802.15.4 standardization in the domain of wireless personal area network (WPAN). ZigBee has another great feature mobility that makes the ZigBee network more versatile. The mobility feature of ZigBee mobile nodes has a greater impact on network performance than fixed nodes. This impact sometimes turns into more severe because of network structure and mobility model. This study mainly focuses on the performance analysis of the ZigBee mobile node under Random and Octagonal mobility management model with the Tree routing method. The Riverbed academic modeler is used to design, implement and simulate the ZigBee network under certain conditions. This study also presents a competitive performance analysis based on ZigBee mobile nodes transmitter and receiver characteristics under the observation of the mobility model. This indicates that Octagonal mobility model exhibits better performance than the Random mobility model. This study will constitute a new way for further designing and planning a reliable and efficient ZigBee network.

Analysis of Random Walk Mobility Models with Location Heterogeneity

This paper investigates random walk mobility models with location heterogeneity, where different locations may have different neighboring regions. We consider $n$ locations in a one-dimension network and investigate two cases, i.e., full-range locations where nodes situated have the capability to shuffle throughout the network and long-range locations where nodes are allowed to move to positions nearby within a certain range. In the former situation, with the exact expressions derived, we find location heterogeneity has a critical impact on the first hitting time of random walk, varying from $\Theta (n)$ to $\Theta \left(n^3\right)$ according to different extent of heterogeneity. The result covers, as two special cases, both the classic independent and identically distributed (i.i.d) mobility and traditional random walk when varying the number of full-range locations. In the latter one, our asymptotic results on both the first crossing time and cover time suggest that they are inversely proportional to the range of neighboring region $r$ ( $\propto r^{-2}$ and $\propto r^{-1}$ , respectively). Furthermore, with multiple concurrent random walks introduced, the first hitting time can be drastically decreased and the effect is strengthened if combined with location heterogeneity. In addition, our investigation into the stationary distribution of nodes indicates that the uniformity no longer holds due to different transition probabilities, as a result of location heterogeneity. We also conduct extensive simulation results to verify our observations and enhance the understanding on the impact of network parameters. Based on the insights obtained, we move forward to investigate the impact of location heterogeneity in two-dimension networks.

A 2-D random walk mobility model for WiMAX location update

Mobile Worldwide Interoperability for Microwave Access (WiMAX) network is increasingly popular, and upcoming deployments can be expected with the development of intelligent transport systems (ITS) and the advent of smart cities. However, both applications will demand an efficient management of high mobility. Therefore, optimizing the cost of mobility signaling procedures of the network is key. In this work we study the location update procedure in WiMAX networks. Whilst previous works consider 1-D layouts of base stations (BSs), corresponding to ITS-based scenarios, we focus on extending that scenario to develop an analytical model for 2-D layouts, which fit better for cities. Our model consider the two cases in which the logical entity in charge of handling the location tracking and paging operations, known as anchor paging controller (APC), is assigned for a mobile station (MS) during a location update: when the old APC is reassigned (no relocation), and when a new APC is assigned (relocation). The comparison is made by calculating the cost (as the number of exchanged messages) of the location update procedure in each case. We validate our model through simulations, and discuss the impact on the final cost of several parameters, such as type and frequency of the movements. Finally, we provide some guidelines on how to assign the APC depending on the network parameters.

SHER: a colored petri net based random mobility model for wireless communications.

In wireless network research, simulation is the most imperative technique to investigate the network’s behavior and validation. Wireless networks typically consist of mobile hosts; therefore, the degree of validation is influenced by the underlying mobility model, and synthetic models are implemented in simulators because real life traces are not widely available. In wireless communications, mobility is an integral part while the key role of a mobility model is to mimic the real life traveling patterns to study. The performance of routing protocols and mobility management strategies e.g. paging, registration and handoff is highly dependent to the selected mobility model. In this paper, we devise and evaluate the Show Home and Exclusive Regions (SHER), a novel two-dimensional (2-D) Colored Petri net (CPN) based formal random mobility model, which exhibits sociological behavior of a user. The model captures hotspots where a user frequently visits and spends time. Our solution eliminates six key issues of the random mobility models, i.e., sudden stops, memoryless movements, border effect, temporal dependency of velocity, pause time dependency, and speed decay in a single model. The proposed model is able to predict the future location of a mobile user and ultimately improves the performance of wireless communication networks. The model follows a uniform nodal distribution and is a mini simulator, which exhibits interesting mobility patterns. The model is also helpful to those who are not familiar with the formal modeling, and users can extract meaningful information with a single mouse-click. It is noteworthy that capturing dynamic mobility patterns through CPN is the most challenging and virulent activity of the presented research. Statistical and reachability analysis techniques are presented to elucidate and validate the performance of our proposed mobility model. The state space methods allow us to algorithmically derive the system behavior and rectify the errors of our proposed model.

이동 방향 정보를 이용한 DTN 라우팅: TAILWIND

In base station based networks, traffic overload at the base station is inevitable. Peer-to-peer DTN which disperses the traffic overhead to each node can relieve the traffic overload at the base station. To increase the message delivery ratio and reduce the message overhead, we present novel routing using mobility information which can be obtained from each node, unlike the existing flooding based routings. In the proposed routing scheme, the routing decision metric, which is defined based on the node mobility information, is computed by using the expected distance between each node to the destination. The message is copied to other nodes that have lower expected distance to the destination than the value for the node willing to copy the message. We conducted simulations by using both a random mobility model and a real mobility trace to compare the performance of the proposed routing scheme to the existing routing scheme that does not utilize the mobility information. The performance evaluation showed the proposed routing successfully delivers messages with 10% to 30% less copies compared to previously proposed routing schemes.