Random Mobility Model Research Articles

Estimation of Random Mobility Models with Application to Unmanned Aerial Vehicles

Random mobility models (RMMs) capture the statistical movement characteristics of mobile agents and play an important role in the evaluation and design of mobile wireless networks. Particularly, RMMs are used to model the movement of unmanned aerial vehicles (UAVs) as the platforms for airborne communication networks. In many RMMs, the movement characteristics are captured as stochastic processes constructed using two types of independent random variables. The first type describes the movement characteristics for each maneuver and the second type describes how often the maneuvers are switched. We develop a generic method to estimate RMMs that are composed of these two types of random variables. Specifically, we formulate the dynamics of movement characteristics generated by the two types of random variables as a special Jump Markov System and develop an estimation method based on the Expectation–Maximization principle. Both off-line and on-line variants of the method are developed. We apply the estimation method to the Smooth–Turn RMM developed for fixed-wing UAVs. The simulation study validates the performance of the proposed estimation method. We further conduct a UAV experimental study and apply the estimation methods to real UAV trajectories.

Markov Chain-based Mobility Prediction and Relay-node Selection for QoS Provisioned Routing in Opportunistic Wireless Network

In the fields of networking and communication, wireless sensor networks are a commonly used technology. Although Mobility in Wireless Networks or Mobile Ad hoc Networks (MANETs) were developed to solve most critical problems in a disaster scenario. However, data transmission in a disaster area is a difficult operation due to irregular connections between sensing devices and the sink. Opportunistic network-based MANETs are utilized to overcome this problem. There are many routing issues such as communication overhead ratio, packet loss, and packet delivery ratio at mobile nodes. There are several traditional approaches used in opportunistic networks for node localization and routing. The drawback of these traditional routing methods is their poor reliability. A Markov chain-based opportunistic routing protocol is proposed in this paper. A Markov chain model is used to predict the node mobility for the random mobility model, and a neighbor table-based relay node selection procedure is proposed. A Markov prediction model uses the history of a node’s movement without requiring additional information. By analyzing simulation metrics including delay, overhead rate, packet drop, and packet delivery rate, the proposed routing protocol is evaluated and verified based on the Packet Delivery Ratio (PDR) in an opportunistic network environment (ONE) simulator. In addition, existing routing protocols such as Spray and Wait (SNW), Epidemic, Prophet, and MaxPro differ from the proposed routing protocol in terms of buffer size, node count, and message generation rate. Corresponding result analysis demonstrates the superior performance of the proposed routing protocol over existing protocols.

Mobility Prediction of Mobile Wireless Nodes

Artificial intelligence (AI) is a fundamental part of improving information technology systems. Essential AI techniques have revolutionized communication technology, such as mobility models and machine learning classification. Mobility models use a virtual testing methodology to evaluate new or updated products at a reasonable cost. Classifiers can be used with these models to achieve acceptable predictive accuracy. In this study, we analyzed the behavior of machine learning classification algorithms—more specifically decision tree (DT), logistic regression (LR), k-nearest neighbors (K-NN), latent Dirichlet allocation (LDA), Gaussian naive Bayes (GNB), and support vector machine (SVM)—when using different mobility models, such as random walk, random direction, Gauss–Markov, and recurrent self-similar Gauss–Markov (RSSGM). Subsequently, classifiers were applied in order to detect the most efficient mobility model over wireless nodes. Random mobility models (i.e., random direction and random walk) provided fluctuating accuracy values when machine learning classifiers were applied—resulting values ranged from 39% to 81%. The Gauss–Markov and RSSGM models achieved good prediction accuracy in scenarios using a different number of access points in a defined area. Gauss–Markov reached 89% with the LDA classifier, whereas RSSGM showed the greatest accuracy with all classifiers and through various samples (i.e., 2000, 5000, and 10,000 steps during the whole experiment). Finally, the decision tree classifier obtained better overall results, achieving 98% predictive accuracy for 5000 steps.

WIRELESS LAN FOR IOT 5G APPLICATIONS IN A CONGESTED INDOOR ENVIRONMENT: IMPROVED PRIMARY SIGNAL SENSING AT MILLIMETER-WAVE V-BAND [40 – 75 GHZ

Abstract. Presently, the IEEE 802.11ad wireless network standard supports the communication capability within the V band of millimeter-Waves (or mm-Waves) [40 – 75 GHz] for Internet of Things (or IoT) technology. This paper presents an algorithm to improve the Primary Signal 5G (or PS5G) sensing at 60 GHz in WLANIoT-5G (or Wireless Local Area Network for IoT-5G). To achieve that, we aim at investigating and assessing the sensing performances of the PS5G from the Access Point of WLANIoT-5G (or APWLANIoT-5G) by the Secondary User IoT-5G (or SUIoT-5G) in a congested environment using a simple energy detector (or SED) algorithm and a simple recursive estimator (or SRE). In addition, the SUIoT-5G is regarded as a mobile user in WLANIoT-5G by employing the Gauss-Markov Random Mobility Model (or GMRMM). Through various scenario simulations, the performances and the robustness of the proposed algorithm are proved.

Performance Investigation of Routing Protocol with the velocity of 30 m/s for Random Mobility Model

Performance Investigation of Routing Protocol with the velocity of 30 m/s for Random Mobility Model

Performance characterization of modified random direction mobility model in UAVs cellular network

Performance characterization of modified random direction mobility model in UAVs cellular network

Mobile Ad Hoc networks intrusion detection system against packet dropping attacks

<span>Due to the extreme lack of a stable infrastructure, also self-organization of network components, unpredictable network topologies, and the lack of a central authority for routing, security assurance in mobile ad hoc networks (MANETs) is an important and difficult challenge. Among the famous threat that MANETs suffer from: blackhole, grayhole, and selfishness attacks, because the target of these attacks is to drop packets and disturb the routing operation of the network. A scalable, reliable, and robust network intrusion detection system (NIDS) should be created to effectively combat these families of network layer routing assaults in order to offer high availability for MANETs. In this paper, we present a MANETs-IDS based on machine learning algorithm against blackhole, grayhole, and selfishness attacks with Ad Hoc on-demand distance vector (AODV) routing protocol (RFC 3561) and optimized link state routing (OLSR) potocol (RFC 3626), using ns-3 simulation platform. Our simulation took into consideration the density of the network and a random mobility model of nodes. The obtained experimental results show that the proposed detection algorithm reached very promoting performances (in term of accuracy, processing time, time to build the model, precision, recall, F-measure).</span>

Group Mobility Model for Complex Multimission Cooperation of UAV Swarm

In the unmanned aerial vehicle (UAV) swarm combat system, multiple UAVs’ collaborative operations can solve the bottleneck of the limited capability of a single UAV when they carry out complicated missions in complex combat scenarios. As one of the critical technologies of UAV collaborative operation, the mobility model is the basic infrastructure that plays an important role for UAV networking, routing, and task scheduling, especially in high dynamic and real-time scenarios. Focused on real-time guarantee and complex mission cooperative execution, a multilevel reference node mobility model based on the reference node strategy, namely, the ML-RNGM model, is proposed. In this model, the task decomposition and task correlation of UAV cluster execution are realized by using the multilayer task scheduling model. Based on the gravity model of spatial interaction and the correlation between tasks, the reference node selection algorithm is proposed to select the appropriate reference node in the process of node movement. This model can improve the real-time performance of individual tasks and the overall mission group carried out by UAVs. Meanwhile, this model can enhance the connectivity between UAVs when they are performing the same mission group. Finally, OMNeT++ is used to simulate the ML-RNGM model with three experiments, including the different number of nodes and clusters. Within the three experiments, the ML-RNGM model is compared with the random class mobility model, the reference class mobility model, and the associated class mobility model for the network connectivity rate, the average end-to-end delay, and the overhead caused by algorithms. The experimental results show that the ML-RNGM model achieves an obvious improvement in network connectivity and real-time performance for missions and tasks.

Improving Mobility-aware Routing in Vehicular Ad hoc Networks Considering Two Level Architecture

In VANET, moving vehicles each act as one moving node. Because of the large mobility of vehicles, the topology of the network is unstable. This instability of the network and its rapid changes have created a major challenge with regard to mobility management. Optimizing routing across automotive networks improves network node mobility management and minimizes clustering changes. As a result, in this study, the node clustering method was used for greater stability in node mobility. This study aims to significantly reduce changes in network topology, which means a decrease in clusters, as well as a significant increase in cluster survival. A random mobility model was considered in NS-3 and the speed of the nodes was randomized between 0 and 30 m/s. The simulation results showed that the proposed protocol has a high rate of accepted packages and the average survival of nodes and at the same time low cluster changes, which has a significant effect on improving mobility.

Bottom-Up Model of Random Daily Electrical Load Curve for Office Building

In the design stage of energy systems in buildings, accurate load boundary conditions are the key to achieving energy supply and demand balance. Compared with the building cold and heat load, the generation of building electrical load has stronger randomness, and the current standard electrical load calculation method cannot reflect this feature. Therefore, this paper proposes a bottom-up high time resolution power load generation method for office buildings. Firstly, the non-homogeneous Markov chain is used to establish the random mobility model of personnel in office buildings, and the building electrical appliances are divided into four categories according to the different driving modes of personnel to electrical appliances in office buildings. Then, based on the personnel mobility model, the correlation between the use of electrical appliances in office buildings and the personnel in the room is established to construct the random power simulation model of different types of electrical appliances. Finally, the electric load of different types of electrical appliances is superimposed hourly to generate a random daily load curve. In order to verify the validity of the model, an office building is simulated and compared with the measured electrical load value. The verification results show that the model well reflects the daily distribution characteristics of electric load. The simulation value and the measured value are used for statistical analysis. The evaluation results show that the correlation between the simulation value and the measured value is high, which further illustrates the validity and accuracy of the model.

3D Non-Stationary Wideband UAV-to-Ground MIMO Channel Models Based on Aeronautic Random Mobility Model

A commonly used assumption in the existing unmanned aerial vehicle (UAV) channel models is that the UAV flies along linear trajectories. However, this assumption does not always hold in realistic UAV communication scenarios. In this paper, we relax the linear trajectory restriction and present a temporally non-stationary channel model for UAV-to-ground communication scenario. The temporal non-stationarity of the channel stemming from time-varying heading directions of the UAV is properly modeled. This is achieved by combining a geometry-based stochastic model (GBSM) and an aeronautic random mobility model (RMM), which is introduced to characterize the movement pattern of UAVs. Based on UAV and ground station (GS) trajectories, time-varying model parameters and statistics including space-time-frequency correlation function (STF-CF), Doppler power spectrum density (PSD), delay PSD, and stationary interval are derived. The influences of the RMM-related parameters on the statistics are presented and analyzed. Some of those statistics are verified by measurements, showing the practicability of the model. The work presented in this paper is helpful in designing UAV communication system considering realistic UAV trajectories.

Improvement and Performance Evaluation When Implementing a Distance-Based Registration

An efficient location registration scheme is essential to continuously accommodate the increasing number of mobile subscribers and to offer a variety of multimedia services with good quality. The objective of this study was to analyze the optimal size for the location area of a distance-based registration (DBR) scheme by varying the number of location areas on a cell-by-cell basis, not on a ring-by-ring basis. Using our proposed cell-by-cell distance-based registration scheme with a random walk mobility model, a variety of circumstances were analyzed to obtain the optimal number of cells for location area for minimizing the total signaling cost on radio channels. Analysis results showed that the optimal number of cells for location area was between 4 and 7 in most cases. Our cell-by-cell distance-based location registration scheme had less signaling cost than an optimal ring-by-ring distance-based location registration scheme with an optimal distance threshold of 2 (the optimal number of cells for location area was 7). Therefore, when DBR is adopted, it must be implemented with an LA increasing on a cell-by-cell basis to achieve optimal performance.

Network Routing Issues in Global Geographic Information System

Research background: A geographic information system (GIS) is a computer-based information system that gathers, manages, and disseminates different geographic (related to earth) information to provide intelligent analytics necessary for prompt decisions and actions. A GIS can aggregate data from several different streams and turn it into a smart dashboard for different users to enhance productivity. The use of intelligent technologies, remote sensing, and ad-hoc wireless networks has significantly improved GIS. In GIS, utilization of sensed data from different sources depends upon the use of efficient sensing equipment, smart mobile nodes, and network gateways and relays that can efficiently route traffic towards the sink or base station. GIS achieve attention in emergency response scenarios for their capability to collect, analyze, and process spatial-referred. Purpose of the article: Article is focused on studying and identifying suitable routing issues of wireless mobile nodes, which are the main transponders for smooth and errorless data transmission. Methods: We performed a simulation-based comparative study of three different routing protocols used in ad-hoc wireless networks, namely is to identify suitable routing protocols that can aid the GIS to improve its overall performance. We calculated and compared our results with different routing protocols. We were able, with the Random mobility model, to estimate the performance of various network parameters. Findings & Value added: We proposed a study in this work that includes geo-information services overall of routing protocols to support a team in stressful situations. The study shows that the AODV routing protocol performed better than the other two routing protocols (OLSR & TORA) under the given topology.

Statistical Properties and Airspace Capacity for Unmanned Aerial Vehicle Networks Subject to Sense-and-Avoid Safety Protocols

Random mobility models (RMMs) capture the random mobility patterns of mobile agents, and have been widely used as the modeling framework for the evaluation and design of mobile networks. All existing RMMs in the literature assume independent movements of mobile agents, which does not hold for unmanned aircraft systems (UASs). In particular, UASs must maintain a safe separation distance to avoid collision. In this paper, we propose a new modeling framework of random mobility models equipped with physical sense-and-avoid protocols to capture the flexible, variable, and uncertain movement patterns of UASs subject to separation safety constraints. For the random direction (RD) RMM equipped with a commonly used sense-and-avoid (S&A) protocol, named sense-and-stop (S&S), we provide its statistical properties including stationary location distribution and stationary inter-vehicle distance distribution, using the Markov analysis. This study provides knowledge on the impact of S&A protocols to critical UAS networking statistics. In addition, we define collision probabilities and airspace capacity concepts for UASs based on the inter-vehicle distance distribution, and derive their closed-form expressions. This analytical framework mathematically bridges local autonomy with global airspace capacity, and allows the impact analysis of local autonomy configurations for effective UAS airspace capacity management.

A Medium-Term Disruption Tolerant SDN for Wireless TCP/IP Networks

A novel framework, Medium-Term Disruption Tolerant Software Defined Network (MDT-SDN), is proposed to handle medium-term disruptions of the order 10 seconds to 6 minutes. Such medium-term disruptions are crucial for the next generation wireless networks that use TCP/IP protocol stack, where the existing disruption tolerant approaches may under-perform due to resource constraints. MDT-SDN enables network control with an additional STORE action which exploits the nodes’ memory for buffering packets within the TCP/IP stack during link disruptions and forwards them as the links become alive. First, we model the network with medium-term disruptions using temporal graphs and design an Earliest Arrival Path with Minimal Storage Time (EAPMST) controller algorithm to demonstrate the MDT-SDN framework. The framework is realized in a software defined wireless mesh network testbed, using in-band control, involving mobile nodes with three mobility models: ( ${i}$ ) stationary nodes, ( ii ) group mobility, and ( iii ) random mobility. Experimental results with four application protocols justify the efficacy of MDT-SDN in providing storage control and additional performance benefits. MDT-SDN along with EAPMST improves the throughput beyond 25% with random mobility model and is capable of carrying packets and maintaining sessions during medium-term disruptions using the existing TCP/IP stack. The use of EAPMST reduces packets’ buffering time by 24.45% in group mobility while the buffering time increases in random mobility by 5.82%. However, EAPMST significantly reduces the buffer occupancy by 60.28% and 44.49% for group and random mobility, respectively.

Overlap Avoidance of Mobility Models for Multi-UAVs Reconnaissance

As avionics technologies have advanced, it is possible to perform many aerial applications which demand cooperative work with multiple Unmanned Aerial Vehicles (UAVs). Since one of the basic applications is reconnaissance, we focus on efficient cooperative reconnaissance. While random mobility models are useful for multi-UAVs reconnaissance, they suffer from overlapped reconnaissance problem that two or more UAVs reconnoiter a region at the same time. The overlapped reconnaissance also leads to imbalanced reconnaissance in which an area scanned by one UAV may be re-visited soon by the other UAV. Thus, we provide overlap avoidance schemes for the existing reconnaissance mobility models and enhance their performance. Throughout the simulations, we evaluate the effect of applying overlap avoidance in the existing models. The simulation results show that overlapped area is reduced by up to 20 times and 90%-coverage reaching time is improved by up to 19%.

A Lattice Signcrypted Secured Localization in Wireless Sensor Networks

Confidentiality, authentication, and the integrity services of wireless sensor networks (WSNs) are the concerns at present in an era of Internet of Things (IoT) or Internet of Everything (IoE). In this context, a secured location estimation technique is developed for advanced WSN with lightweight lattice signcryption. The method inherently uses range-free DV-hop algorithm to ensure no extra burden on the hardware cost with low power consumption, low complexity (time and space), and desirable accuracy. The anchor nodes and unknown sensor nodes of the WSNs are considered mobile in nature and use the random mobility model. The evaluation and comparison of the developed “SECure LAttice based Signcryption for LOcalization (SECLASLO)” have been done in terms of location error analysis, memory, time, and energy consumption.

Analysis of Route Stability in Mobile Multihop Networks Under Random Waypoint Mobility

Analytical performance evaluation is crucial in designing mobile multihop networks under different operational conditions. It provides the best insight into the effects of various network parameters and their interactions. The route and link lifetime in mobile multihop networks under a random mobility environment have significant effects on network performance. Many analytical studies have been introduced to the body of work concerned with the link and route lifetime in mobile multihop networks. However, there is no closed-form analytical study for link and route stability in MANETs under any random mobility model. In addition, to simplify the analysis, one or more network characteristics were not considered in most of related studies. This work presents a closed-form analytical model for the link and route lifetime in mobile multihop networks, where nodes move according to the random waypoint mobility model. The proposed model can capture the effects of most network characteristics including the number of mobile nodes, the number of hops, the network area size, the transmission range, and the speed of nodes. In addition, we used the proposed model to derive expressions for the bounds of the link and route lifetime under different network characteristics. The proposed model can help characterize the network performance, analyze the network as to meet a certain level of quality-of-service, and design better routing protocols to cope with link breakage caused by node mobility. To verify the proposed model, extensive simulations were performed under different network characteristics.

An efficient energy aware link stable multipath routing protocol for mobile ad hoc networks in urban areas

Ad Hoc wireless mobile networks are characterized by a lack of central administration and the fact that any element of the network, being very mobile, is susceptible to disappear. In an Ad Hoc network, all the elements must cooperate in order to establish a temporary network to communicate. This communication is affected by the links stability mainly in a restricted environment such as a city and the depletion of the batteries energy of the nodes. These factors degrade the ad hoc networks performance. We propose in this paper a stable routing protocol with weak energy consumption for urban areas in order to improve these performances. The proposed solution is a multipath protocol named ESMRua (Efficient energy aware and Link Stable Multipath Routing Protocol in urban areas). ESMRua uses a path selection scheme based on energy constraint, signal quality and link stability. For the link stability, three calculation variants are used. ESMRua will be designed for realistic mobility, contrary to the main existing protocols which are designed to the random mobility models; these models have unrealistic behaviors such as a brusque acceleration and a sudden stop. Simulation results show that our multipath protocol enhances the performance of the ad hoc networks, mainly in terms of routing overhead, energy consumption and network reliability.

A New Mobility Model for Multi-UAVs Reconnaissance Based on Partitioned Zone

Activities on Unmanned Aerial Vehicle (UAV) have increased over the last years and there are many fields in which UAVs can be used. One of the basic applications is reconnaissance of a given area using multiple UAVs. To perform reconnaissance mission, there are two methods: (i) path planning to navigate the pre-determined route; and (ii) random mobility method to explore without prior knowledge. In this paper, we indicate the imbalance problem of existing random mobility models for reconnaissance and propose a new model considering reconnaissance balance based on the number of visits. We divide the scanning area into N zones and then select a zone stochastically in which the search is insufficient. We evaluated the performance of the model by focusing on the coverage rate and average inter-visiting time. The proposed model shows that the 90%-coverage reaching time is improved by about 25% and the average inter-visiting time is improved by up to 15% compared to the previous approach.