Random Walk Mobility Model Research Articles

Analyzing Distance-Based Registration with Two Location Areas: A Semi-Markov Process Approach

In order to connect an incoming call to the user equipment (UE) in a mobile communication network, the location information of the UE must be always kept in the network database. Therefore, the efficiency of the location registration method of reporting new location information to a mobile communication network whenever the location information of the UE changes directly affects the performance of the radio channel, which is a limited resource in a mobile communication network. This study deals with distance-based registration (DBR). DBR does not cause the ping-pong phenomenon known to be a main problem in zone-based registration. It shows good performance when assuming a random walk mobility model. To improve the performance of the original DBR with one location area (1D), a DBR with two location areas (2D) was proposed. It is known that 2D is better than 1D in most cases. However, unlike 1D, an accurate mathematical model for 2D has not been presented in previous studies, raising questions about whether an accurate performance comparison has been performed. In this study, we present an accurate mathematical model based on the semi-Markov process for performance analysis of 2D. We compared performances of 1D and 2D using the proposed mathematical model. Various numerical results showed that 2D with two-step paging was superior to 1D in most cases. However, when simultaneous paging was applied to 2D, 1D was better than 2D in most cases. In real situations, optimal performance can be achieved by reflecting the network situation in real time and dynamically changing the operating method using a better-performing model among these two methods.

Reinforcement Learning-Based Optimization Framework for Application Component Migration in NFV Cloud-Fog Environments

By decoupling network functions from the underlying hardware, Network Function Virtualization (NFV) allows application components to be implemented as sets of Virtual Network Functions (VNFs) chained in a specific order, represented by VNF-Forwarding Graphs (VNF-FG). Fog computing is instrumental to tap into the full potential of NFV by deploying VNFs in close proximity to end-users, thus decreasing the latency significantly. However, the mobility of end-users and the fog nodes, and the limited fog nodes coverage results in service discontinuity and may increase application delay. Application component migration offers great potential to address this issue. In this paper, we propose a component migration strategy in an NFV-based hybrid cloud/fog system considering the mobility of both end-users and fog nodes. We use the Gauss-Markov mobility model and a random walk mobility model for fog nodes and end-user devices, respectively. We modeled the problem mathematically, which minimizes the aggregated weighted function of application delay and cost. However, considering the mobility of both end-users and fog nodes makes the problem quite complex. Hence, we propose a Deep Reinforcement Learning (DRL) approach to decide where and when to migrate application components and to achieve rapid decision-making. Simulation results demonstrate that the proposed scheme performs well. It offers favorable convergence and outperforms existing algorithms in terms of application delay and migration costs.

Mobility prediction for random walk mobility model using ARIMA in mobile ad hoc networks

Mobility prediction for random walk mobility model using ARIMA in mobile ad hoc networks

Performance Analysis of Mobility Impact on IEEE 802.11ah Standard with Traffic Pattern Scheme

Internet of Things (IOT) offers a new dimension of technology and information where connectivity is available anywhere, anytime, and for any purpose. IEEE 802.11 Wireless Local Area Network group is a standard that developed to answer the needs of wireless communication technology (WI-Fi). Recently, IEEE 802.11 working group released the 802.11ah technology or Wi-Fi HaLow as a Wi-fi standard. This standard works on the 1 GHz frequency band with a broader coverage area, massive device and the energy efficiency issues. This research addresses, the influence of Random Walk, Gauss-Markov, and Random Waypoint mobility model on 802.11ah with different traffic pattern scheme are analyzed. The design of the simulation system is done by changing of node density. Based on the result, it can be concluded that the overall performance of the network with all of the parameter scenarios is decreasing along with increasing the Stations. In the node density scenario, the Random Waypoint mobility model has the best performance with an average delay is about 0.65805 s, throughput is about 0.53811Mbps, PDR is about 96.75%, and energy consumption is about 5.2530 Joule.

Mobility speed prediction using ARIMA and RNN for random walk mobility model in mobile ad hoc networks

AbstractIn this article, an auto‐regressive integrated moving average (ARIMA) modeling has been proposed to predict the mobility speed of the nodes in the mobile ad hoc networks (MANETs). The mobility speed prediction supports effective route discovery to enhance efficient and reliable routing. The random walk mobility model had been used to forecast the mobility of the nodes. Subsequently, various the recurrent neural network (RNN) model has been developed with different number hidden neurons, and the prediction results are compared with proposed ARIMA based results. The Akaike information criterion, auto‐correlation function metrics are evaluated to assess the dataset's quality. Several network scenarios are evaluated with various speeds and the number of nodes. The results of the proposed ARIMA model are compared with the RNN results. It demonstrates that the proposed model has higher prediction rates with reduced error rates of 0.1%–1.4% than RNN values. Such that the proposed methods facilitate the higher prediction rate of 10%–26% as compared with the RNN. Therefore, the proposed mobility speed prediction techniques support the effective routing in the MANETs.

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.

Hierarchical Cooperation Improves Delay in Cognitive Radio Networks with Heterogeneous Mobile Secondary Nodes

This paper characterizes the throughput and delay performance of Cognitive Radio Networks (CRNs), where both primary and secondary networks coexist in a unit torus. Specifically, the primary network consists of static primary nodes (PNs) of density $n$ n , which have a higher priority to access the spectrum. In contrast, the secondary network consists of mobile secondary nodes (SNs) of density $m=n^{\beta }$ m = n β with $\beta \geq 1$ β ≥ 1 , which move according to a hybrid random walk mobility model and have opportunistic access to the spectrum without affecting primary packet transmissions. Motivated by the fact that cooperation between primary and secondary nodes leads to possible improvement on the performance of CRNs, as well as the fact that the heterogeneous moving regions of secondary nodes will bring about further improvement, we propose a novel hierarchical cooperative scheduling mechanism, where secondary nodes serve as relays for primary packet transmissions by exploiting their mobility heterogeneity and geographic information. Our findings include: (i) For the primary network, stronger mobility heterogeneity of secondary nodes leads to better delay performance of the primary network, and meanwhile the delay scaling can be significantly reduced to $\Theta (n^{\sqrt{\beta /{(4\;\log n)}}}\log ^{3/2}n)$ Θ ( n β / ( 4 log n ) log 3 / 2 n ) when a near-optimal per-node throughput of $\Theta ({1}/{\log n})$ Θ ( 1 / log n ) is obtained. (ii) For the secondary network, we also adopt a similar hierarchical cooperative scheduling mechanism, and obtain a near-optimal per-node throughput of $\Theta {(1/{\log m})}$ Θ ( 1 / log m ) with the delay scaling of $\Theta ({m^{1-(1/\sqrt{\log m})}})$ Θ ( m 1 - ( 1 / log m ) ) . (iii) The delay of secondary source-destination pairs is determined by the moving region of destinations and has no relation with sources. Our work provides deeper understandings of the cooperation, heterogeneous mobility, and geographic information on the performance of CRNs, and sheds light on designing more efficient CRNs.

Low-Mean Hitting Time for Random Walks on Heterogeneous Networks

Mean hitting time for random walks on a network, defined as the average of hitting times over all possible pairs of nodes, has found a large variety of applications in many areas. In this paper, we first prove that among all $N$ -node networks, the complete graph has the minimum mean hitting time $N-1$ , which scales linearly with network size. We then study a random walk mobility model with location heterogeneity, modeled by scale-free networks, which are ubiquitous in realistic systems such as P2P networks. For this purpose, we consider random walks on two sparse scale-free small-world networks. By using the connection between random walks and electrical networks, we derive explicit formulas about mean hitting time for both networks, the dominant scaling of which exhibits the same behavior as that of complete graphs. This paper demonstrates that heterogeneous sparse networks can have low-mean hitting time with a behavior similar to that of dense complete graphs, which is instrumental in designing networks, where search is fast between any pair of nodes.

Context-Awareness Enhances 5G Multi-Access Edge Computing Reliability

The fifth generation (5G) mobile telecommunication network is expected to support Multi- Access Edge Computing (MEC), which intends to distribute computation tasks and services from the central cloud to the edge clouds. Towards ultra-responsive, ultra-reliable and ultra-low-latency MEC services, the current mobile network security architecture should enable a more decentralized approach for authentication and authorization processes. This paper proposes a novel decentralized authentication architecture that supports flexible and low-cost local authentication with the awareness of context information of network elements such as user equipment and virtual network functions. Based on a Markov model for backhaul link quality, as well as a random walk mobility model with mixed mobility classes and traffic scenarios, numerical simulations have demonstrated that the proposed approach is able to achieve a flexible balance between the network operating cost and the MEC reliability.

Efficient Producer Mobility Management Model in Information-Centric Networking

Information centric networking is a clean-slate Internet architecture designed as a future Internet to supplement and completely replace the current Internet architecture. The future Internet information-centric networking was proposed in different kind of approaches to offered vast advantages ranging from security, catching, and content mobility support. However, some of the approaches support only content consumer, while content producer mobility faces many challenges, such as unnecessary Interest packet losses, high handoff latency, scalability issues, and high signaling overhead. Therefore, many approaches, protocols, and schemes were proposed to address the problem. The schemes such as indirection-based approach, locator-based approach, rendezvous-based, forwarding-based, and control/data plane-based, and mapping-based approach were investigated using either analytical or simulation investigation. However, in many cases of the formulation of an analytical investigation for information-centric networking mobility support management, the determination and incorporation of producers' movement behavior are neglected, whereas the movement pattern of mobile content producer plays a vital role in mobility performance analysis of the wireless mobile network. This paper proposed a producer mobility management model for information-centric networking with a random waypoint and random walk mobility model incorporated, to measure the movement pattern effect and proved the uniformity of the proposed model to support any kind of mobility support approaches or schemes. The performance analysis result of our proposed model revealed that movement pattern does affect the mobile producer handoff performance. Hence, for the accuracy of handoff latency, handoff signaling cost, and data packets delivery cost investigation, mobility models must be selected carefully based on the application domain.

How to Cache in Mobile Hybrid IoT Networks?

Content-centric mobile hybrid Internet-of-Things (IoT) networks consisting of mobile devices and static femto access points (FAPs) are studied, where each device moves according to the random walk mobility model and requests a content object from the library independently at random according to a Zipf popularity distribution. Instead of allowing access to content objects at macro base stations via costly backhaul providing connection to the core network, we consider a more practical scenario where mobile devices and static FAPs, each having a finite-size cache space, are able to cache a subset of content objects so that each request is served by other mobile devices or static FAPs. Under a general multihop-based content delivery protocol, we analyze the order-optimal throughput--delay trade-off by presenting a new cache allocation strategy. In particular, under a given caching strategy, we first characterize a throughput--delay trade-off in terms of scaling laws along with the general content delivery multihop routing protocol. Then, the order-optimal throughput--delay trade-off is characterized by presenting the order-optimal cache allocation strategy, which jointly finds the replication sets at mobile devices and static FAPs via a novel variable decoupling approach. In our mobile IoT network, an interesting observation is that highly popular content objects are mainly served by mobile devices while the rest of content objects are served by static FAPs. We perform numerical evaluation to validate our analytical results. We also show that the order-optimal strategy strictly outperforms a baseline approach, where the replication sets at mobile devices and static FAPs are optimized separately.

Analysis of Coverage Under Border Effects in Three-Dimensional Mobile Sensor Networks

Recent advances in robotics and low-power embedded systems made three-dimensional (3D) mobile wireless sensor networks (MSNs) an effective solution for monitoring a field of interest (FoI). From a cost perspective, it is often important to ensure the desired coverage ratio for the FoI within a maximum allowable response (MAR) time, by using a minimum number of sensors in MSNs. The literature on determining the minimum number of sensors for the desired coverage ratio assumes that the FoI is unbounded to overcome the border effects. Since the entire sensing sphere of the sensors near the boundary may not be useful for the coverage, the number of sensors estimated without the border effects is lower than the actual value. In this paper, we estimate the minimum number of sensors required to achieve a desired coverage ratio in a given MAR time for a 3D FoI. We term this problem (α; V; T)-coverage problem, where a, V , and T are the desired coverage ratio, average speed of sensors, and MAR time, respectively. We assume straight line mobility model for the sensors and consider the border effects while deriving the expected sensing volume of a sensor useful in coverage. We also consider the restriction of sampling rate of the sensors in this analysis. We discuss the application of our analysis for a non-hyper-rectangle shaped FoI, random walk, and waypoint mobility models, and also the impact of neglecting the border effects. Our numerical and simulation results demonstrate the significance of border effects on the number of sensors and also the relationship between the coverage ratio, MAR time, sampling period, and the sensing range.

Multicast Capacity for VANETs With Directional Antenna and Delay Constraint Under Random Walk Mobility Model

In this paper, we investigate the multicast capacity for vehicular ad hoc networks with directional antennas and the end-to-end delay constraint. We consider a torus of unit area with $n$ vehicles (nodes), there are $n_{s}$ multicast sessions and each session contains one source vehicle which is associated with $p$ destinations. We study the 2D and 1D random walk mobility models with two different time scales, i.e., fast and slow mobility. Given a delay constraint $D$ and assuming that each vehicle is equipped with a directional antenna, we obtain the multicast capacity of the two mobility models with two different time scales in the order of magnitude, respectively. We then characterize the impact of the network parameters (i.e., the end-to-end delay constraint $D$ , the beamwidth of directional antenna $\theta$ , and the number of destinations $p$ in each session) on the multicast capacity. Moreover, we find that the unicast capacity can be considered as a special case of our multicast results when the beamwidth of directional antenna $\theta$ tends to $2\pi$ and the number of destinations $p$ tends to 1 in the sense of probability.

Analytical model for predictable contact in intermittently connected cognitive radio ad hoc networks

In this article, an analytical model for predictable contact between two cognitive users in the intermittently connected cognitive radio ad hoc networks is proposed. The salient feature of the model is that it establishes a relationship between contact availability and the intermittently connected cognitive radio ad hoc network design parameters including cognitive user transmission range, velocity of cognitive user, direction of cognitive user, velocity of primary user, direction of primary user, and interference radius of primary user. However, a detailed analytical model is not available in the literature up to now. In particular, the relationship between contact availability and interference radius of primary user has not been derived in previous models. To research the contact availability, the concept of contact degree is first proposed to quantify the probability of contact availability between two cognitive users. In addition, the formulation for the contact degree between two cognitive users from different cases is illustrated in detail in this article. Under the contact degree scenario, the continuous effective contact time is derived to examine the communication duration of cognitive users based on the modified random walk mobility model. Finally, the simulation results demonstrate the effectiveness of the proposed analytical model for predictable contact in the intermittently connected cognitive radio ad hoc networks.

The diameter of mobile ad hoc networks

AbstractWith the prevalence of mobile devices, it is of much interest to study the properties of mobile ad hoc networks. In this paper, we extend the concept of diameter from static ad hoc network to mobile ad hoc network, which is the expected number of rounds for one node to transmit a message to all other nodes in the network, reflecting the worst end‐to‐end delay between any two node. Specifically, we investigate the diameter of identically and independently mobility model in cell‐partitioned network and random walk mobility model in two‐dimensional torus network, achieving the boundary , when (k=Ω(n)), and O(k log2k), respectively, where n is the number of nodes and k is the number of cells of network and especially under random walk mobility model . A comparison is made among the diameter of mobile ad hoc networks under identically and independently mobility model, random walk mobility model and static ad hoc network, showing that mobility dramatically decreases the diameter of the network and speed is an essential and decisive factor of diameter. Copyright © 2016 John Wiley & Sons, Ltd.

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.

Content-Centric Wireless Networks With Limited Buffers: When Mobility Hurts

We analyze throughput-delay scaling laws of mobile ad hoc networks under a content-centric traffic scenario, where users are mainly interested in retrieving contents cached by other nodes. We assume limited buffer size available at each node and Zipf-like content popularity. We consider nodes uniformly visiting the network area according to a random-walk mobility model, whose flight size varies from the typical distance among the nodes (quasi-static case) up to the edge length of the network area (reshuffling mobility model). Our main findings are: 1) the best throughput-delay tradeoffs are achieved in the quasi-static case: increasing the mobility degree of nodes leads to worse and worse performance; ii) the best throughput-delay tradeoffs can be recovered by power control (i.e., by adapting the transmission range to the content) even in the complete reshuffling case.

Distance-Based Location Management Utilizing Initial Position for Mobile Communication Networks

This paper aims at improving the distance-based location management scheme for mobile communication networks. In location management, a mobile terminal (MT) is tracked based on its location-update area (LA). The improvement is brought about by joint optimization of LA center and LA size. For LA center optimization (LCO), we determine the optimal center position of the LA given the initial position of the MT upon each location update. The investigation of optimal LA center has eluded research to date. Based on the popular continuous-time random walk (CTRW) mobility model, we propose an analytical framework that uses a diffusion equation to determine the optimal LA center that minimizes the total cost of location management, consisting of the location update cost and terminal paging cost. This framework allows us to easily model the non-Markovian movement of the MT and evaluate the impact of various measurable physical parameters (such as length of road section, angle between road sections, and road section crossing time) and LA center. In particular, we show that proper LA center can significantly reduce the total cost. For example, for the circular LA and low Poisson call-arrival rate, optimizing the LA center alone has the potential of reducing the cost by up to 37 percent. Joint optimization of the LA center and terminal paging scheme can reduce the cost even further. Simulations results match the theoretical analysis to a gap within 3 percent, indicating that our theoretical model is very accurate.

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.