Showing papers on "Mobility model published in 2019"

Routing in Flying Ad Hoc Networks: Survey, Constraints, and Future Challenge Perspectives

Abstract: Owing to the explosive expansion of wireless communication and networking technologies, cost-effective unmanned aerial vehicles (UAVs) have recently emerged and soon they will occupy the major part of our sky. UAVs can be exploited to efficiently accomplish complex missions when cooperatively organized as an ad hoc network, thus creating the well-known flying ad hoc networks (FANETs). The establishment of such networks is not feasible without deploying an efficient networking model allowing a reliable exchange of information between UAVs. FANET inherits common features and characteristics from mobile ad hoc networks (MANETs) and their sub-classes, such as vehicular ad hoc networks (VANETs) and wireless sensor networks (WSNs). Unfortunately, UAVs are often deployed in the sky adopting a mobility model dictated by the nature of missions that they are expected to handle, and therefore, differentiate themselves from any traditional networks. Moreover, several flying constraints and the highly dynamic topology of FANETs make the design of routing protocols a complicated task. In this paper, a comprehensive survey is presented covering the architecture, the constraints, the mobility models, the routing techniques, and the simulation tools dedicated to FANETs. A classification, descriptions, and comparative studies of an important number of existing routing protocols dedicated to FANETs are detailed. Furthermore, the paper depicts future challenge perspectives, helping scientific researchers to discover some themes that have been addressed only ostensibly in the literature and need more investigation. The novelty of this survey is its uniqueness to provide a complete analysis of the major FANET routing protocols and to critically compare them according to different constraints based on crucial parameters, thus better presenting the state of the art of this specific area of research.

Modeling the Random Orientation of Mobile Devices: Measurement, Analysis and LiFi Use Case

Abstract: Light-fidelity (LiFi) is a networked optical wireless communication (OWC) solution for high-speed indoor connectivity for fixed and mobile optical communications. Unlike conventional radio frequency wireless systems, the OWC channel is not isotropic, meaning that the device orientation affects the channel gain significantly, particularly for mobile users. However, due to the lack of a proper model for device orientation, many studies have assumed that the receiver is vertically upward and fixed. In this paper, a novel model for device orientation based on experimental measurements of 40 participants has been proposed. It is shown that the probability density function (PDF) of the polar angle can be modeled either based on a Laplace (for static users) or a Gaussian (for mobile users) distribution. In addition, a closed-form expression is obtained for the PDF of the cosine of the incidence angle based on which the line-of-sight (LOS) channel gain is described in OWC channels. An approximation of this PDF based on the truncated Laplace is proposed and the accuracy of this approximation is confirmed by the Kolmogorov–Smirnov distance. Moreover, the statistics of the LOS channel gain are calculated and the random orientation of a user equipment (UE) is modeled as a random process. The influence of the random orientation on signal-to-noise-ratio performance of OWC systems has been evaluated. Finally, an orientation-based random waypoint (ORWP) mobility model is proposed by considering the random orientation of the UE during the user’s movement. The performance of ORWP is assessed on the handover rate and it is shown that it is important to take the random orientation into account.

Contract Mechanism and Performance Analysis for Data Transaction in Mobile Social Networks

Abstract: In this paper, a novel mobile data offloading method is proposed based on an external-infrastructure-free approach. Specifically, through the hotspot function of smartphones, data demands from some mobile users, who have used out the data with their monthly data plans, can be offloaded by some other mobile users who still have redundant unused data. In order to model this data transaction among mobile users, which can be realized with assistance of current mobile social platforms, we introduce an auction-based contract mechanism, and then we further analyze the system performance. To improve the efficiency and performance of the system, a socially-aware mobility model is also designed. In this model, betweenness of the data auctioneers is introduced, according to which the number of data requesters in different auctions can be balanced and the performance of the system can be optimized. The proposed data transaction mechanisms and friendship-aware mobility model are then simulated as operating on Flickr, a real-world online social network database. Results show that the number of data bidders in different auctions can be balanced effectively through the proposed mobility model, and the income per unit time of sellers in the networked data transaction can also be increased.

Fundamentals of Mobility-Aware Performance Characterization of Cellular Networks: A Tutorial

Abstract: This paper provides a tutorial on mobility-aware performance analysis of cellular networks considering both the spatially random [where base stations (BSs) are deployed according to a homogeneous point process] and deterministic grid-based network deployment topologies. We first provide a summary of users’ mobility models with no spatiotemporal correlations (e.g., random walk, random way point, and random direction), with spatial correlations (e.g., pursue mobility and column mobility), and with temporal correlations (e.g., Gauss–Markov and Levy flight). The differences among various mobility models, their statistical properties, and their pros and cons are presented. We then describe two primary approaches (referred to as trajectory-based and association-based approaches) for mobility-aware performance analysis of both random and deterministic cellular networks. For the first approach (which is more general but less tractable than the other approach), we describe a general methodology and present several case studies for different cellular network tessellations, such as square lattice, hexagon lattice, single-tier, and multi-tier models in which BSs follow a homogeneous Poisson point process (PPP). For the second approach, we also outline the general methodology and highlight some limitations/imperfections of the existing techniques and provide corrections to these imperfections. For both of these approaches, we present selected numerical and simulation results to calibrate the achievable handoff rate and coverage probability in various network settings. Finally, we point out specific emerging fifth generation (5G) cellular wireless applications where the impact of mobility would be significant and outline the challenges associated with mobility-aware analysis of those network applications.

Urban Human Mobility: Data-Driven Modeling and Prediction

Abstract: Human mobility is a multidisciplinary field of physics and computer science and has drawn a lot of attentions in recent years. Some representative models and prediction approaches have been proposed for modeling and predicting human mobility. However, multi-source heterogeneous data from handheld terminals, GPS, and social media, provides a new driving force for exploring urban human mobility patterns from a quantitative and microscopic perspective. The studies of human mobility modeling and prediction play a vital role in a series of applications such as urban planning, epidemic control, location-based services, and intelligent transportation management. In this survey, we review human mobility models based on a human-centric angle in a datadriven context. Specifically, we characterize human mobility patterns from individual, collective, and hybrid levels. Meanwhile, we survey human mobility prediction methods from four aspects and then describe recent development respectively. Finally, we discuss some open issues that provide a helpful reference for researchers' future direction. This review not only lays a solid foundation for beginners who want to acquire a quick understanding of human mobility but also provides helpful information for researchers on how to develop a unified human mobility model.

Application Component Placement in NFV-Based Hybrid Cloud/Fog Systems With Mobile Fog Nodes

Abstract: Fog computing reduces the latency induced by distant clouds by enabling the deployment of some application components at the edge of the network, on fog nodes, while keeping others in the cloud. Application components can be implemented as Virtual Network Functions (VNFs) and their execution sequences can be modeled by a combination of sub-structures like sequence, parallel, selection, and loops. Efficient placement algorithms are required to map the application components onto the infrastructure nodes. Current solutions do not consider the mobility of fog nodes, a phenomenon which may happen in real systems. In this paper, we use the random waypoint mobility model for fog nodes to calculate the expected makespan and application execution cost. We then model the problem as an Integer Linear Programming (ILP) formulation which minimizes an aggregated weighted function of the makespan and cost. We propose a Tabu Search-based Component Placement (TSCP) algorithm to find sub-optimal placements. The results show that the proposed algorithm improves the makespan and the application execution cost.

Modeling and Performance Analysis of UAV-Assisted Vehicular Networks

Abstract: Vehicular networks’ connectivity and data delivery delay performance is highly affected by the vehicular traffic's spatio-temporal dynamics whose variations are subject to a multitude of random factors. Under the stringent and inevitable limitations imposed by free-flow vehicular traffic conditions (i.e., low-to-medium vehicular densities, elevated degree of mobility, high speeds, etc), these networks suffer from considerably rapid topology variations leading to severe connectivity intermittence and, hence, delayed data delivery. This motivates the study presented in this paper, which aims at investigating the capability of external elements that are independent of the vehicular traffic flow and its inherent limitations (e.g., airborne unmanned aerial vehicles (UAVs), a.k.a., drones) to serve as possible adjuvant relays; thus, contributing to strengthening/healing weak/broken communication links among ground-bound vehicular entities (i.e., RoadSide Units (RSUs) and vehicles) and uplifting the vehicular connectivity and delay performance. Particularly, in the context of a vehicular sub-networking scenario, a UAV mobility model is proposed as a first step in analytically capturing macroscopic dynamics for UAVs exhibiting waypoint mobility patterns and plying over a considered roadway segment. Then, a stochastic analytical model is formulated for the purpose of mathematically characterizing the path availability and achieved data delivery delays in the presence of these UAVs. A simulation framework is established to verify the validity and accuracy of the proposed models and gauge the merit of UAV assistance in improving the vehicular connectivity and data delivery delay performance.

Aeronautical $Ad~Hoc$ Networking for the Internet-Above-the-Clouds

Abstract: The engineering vision of relying on the “smart sky” for supporting air traffic and the “internet-above-the-clouds” for in-flight entertainment has become imperative for the future aircraft industry. Aeronautical ad hoc networking (AANET) constitutes a compelling concept for providing broadband communications above clouds by extending the coverage of air-to-ground (A2G) networks to oceanic and remote airspace via autonomous and self-configured wireless networking among commercial passenger airplanes. The AANET concept may be viewed as a new member of the family of mobile ad hoc networks (MANETs) in action above the clouds. However, AANETs have more dynamic topologies, larger and more variable geographical network size, stricter security requirements, and more hostile transmission conditions. These specific characteristics lead to more grave challenges in aircraft mobility modeling, aeronautical channel modeling, and interference mitigation as well as in network scheduling and routing. This paper provides an overview of AANET solutions by characterizing the associated scenarios, requirements, and challenges. Explicitly, the research addressing the key techniques of AANETs, such as their mobility models, network scheduling and routing, security, and interference, is reviewed. Furthermore, we also identify the remaining challenges associated with developing AANETs and present their prospective solutions as well as open issues. The design framework of AANETs and the key technical issues are investigated along with some recent research results. Furthermore, a range of performance metrics optimized in designing AANETs and a number of representative multiobjective optimization algorithms are outlined.

Bidirectional Optical Spatial Modulation for Mobile Users: Toward a Practical Design for LiFi Systems

Abstract: Among the challenges of realizing the full potential of light-fidelity (LiFi) cellular networks are user mobility, random device orientation, and blockage. In this paper, we study the impact of those challenges on the performance of LiFi networks in an indoor environment using measurement-based channel models, unlike existing studies that rely on theoretical channel models. In our paper, we adopt spatial modulation (SM) and consider two configurations for the user equipment (TIE). A multidirectional receiver (MDR) structure is proposed, in which the PDs are located on different sides of the TIE, e.g., a smartphone. This configuration is motivated by the fact that conventional structures exhibit poor performance in the presence of random device orientation and blockage. In fact, we show that the MDR outperforms the benchmark structure by over 10 dB at bit-error ratio (BER) of 3.8 × 10 -3 . Moreover, an adaptive access point (AP) selection scheme for the SM is considered, where the number of APs is chosen adaptively in an effort to achieve the lowest energy requirement for a target BER and spectral efficiency. The user performance with random orientation and blockage in the entire room is evaluated for sitting and walking activities, for which the orientation-based random waypoint (ORWP) mobility model is invoked. Furthermore, we demonstrate that the proposed adaptive technique with SM outperforms the conventional spatial multiplexing system. We also study the performance of the underlying system on the uplink channel where we apply the same techniques used for the downlink channel. It is shown analytically that the multidirectional transmitter (MDT) with adaptive SM is highly energy efficient.

Coverage Probability of 3-D Mobile UAV Networks

Abstract: In this letter, we consider a network of multiple unmanned aerial vehicles (UAVs) where a given number of UAVs are placed at 3-D locations in a finite circular disk shaped region to serve a reference ground user equipment (UE) located at its center. Herein, a serving UAV is assumed to be located at fixed altitude which communicates with the reference UE. All the other UAVs in the network are designated as interfering UAVs to the UE and are assumed to have 3-D mobility. To characterize the 3-D UAV movement process, we hereby propose an effective 3-D mobility model based on the mixed random waypoint mobility and uniform mobility models in the vertical and spatial directions. Further, considering the proposed 3-D mobility model, we first characterize the interference received at reference UE, and then evaluate its coverage probability under Nakagami- ${m}$ fading. We quantify the achievable performance gains for the ground UE under various system and channel conditions. Moreover, we corroborate our analytical results through simulations.

Collision Avoidance Effects on the Mobility of a UAV Swarm Using Chaotic Ant Colony with Model Predictive Control

Abstract: The recent development of compact and economic small Unmanned Aerial Vehicles (UAVs) permits the development of new UAV swarm applications. In order to enhance the area coverage of such UAV swarms, a novel mobility model has been presented in previous work, combining an Ant Colony algorithm with chaotic dynamics (CACOC). This work is extending CACOC by a Collision Avoidance (CA) mechanism and testing its efficiency in terms of area coverage by the UAV swarm. For this purpose, CACOC is used to compute UAV target waypoints which are tracked by model predictively controlled UAVs. The UAVs are represented by realistic motion models within the virtual robot experimentation platform (V-Rep). This environment is used to evaluate the performance of the proposed CACOC with CA algorithm in an area exploration scenario with 3 UAVs. Finally, its performance is analyzed using metrics.

Aeronautical Ad Hoc Networking for the Internet-Above-The-Clouds

Abstract: The engineering vision of relying on the ``smart sky" for supporting air traffic and the ``Internet above the clouds" for in-flight entertainment has become imperative for the future aircraft industry. Aeronautical ad hoc Networking (AANET) constitutes a compelling concept for providing broadband communications above clouds by extending the coverage of Air-to-Ground (A2G) networks to oceanic and remote airspace via autonomous and self-configured wireless networking amongst commercial passenger airplanes. The AANET concept may be viewed as a new member of the family of Mobile ad hoc Networks (MANETs) in action above the clouds. However, AANETs have more dynamic topologies, larger and more variable geographical network size, stricter security requirements and more hostile transmission conditions. These specific characteristics lead to more grave challenges in aircraft mobility modeling, aeronautical channel modeling and interference mitigation as well as in network scheduling and routing. This paper provides an overview of AANET solutions by characterizing the associated scenarios, requirements and challenges. Explicitly, the research addressing the key techniques of AANETs, such as their mobility models, network scheduling and routing, security and interference are reviewed. Furthermore, we also identify the remaining challenges associated with developing AANETs and present their prospective solutions as well as open issues. The design framework of AANETs and the key technical issues are investigated along with some recent research results. Furthermore, a range of performance metrics optimized in designing AANETs and a number of representative multi-objective optimization algorithms are outlined.

Data Collection in Underwater Sensor Networks based on Mobile Edge Computing

Abstract: With the rapid developments in edge devices and wireless technologies, the underwater wireless sensor networks (UWSNs) are in the process of vigorous development. In UWSNs, the traditional multi-hop data collection methods have some disadvantages such as high power consumption, severe unbalance in power consumption, and so on. In recent years, mobile edge elements (such as an autonomous underwater vehicle, AUV) are widely used in underwater data collection to solve energy consumption imbalance problems. However, the existing methods do not fully consider the efficient mobile edge computing and the real mobility model of AUV in the underwater environment. In this paper, we propose a data collection scheme based on a mobility model of mobile edge elements under water. In this model, the mobility direction and velocity are fully considered, which are close to the mobility characteristic of AUVs in the stable 3D environment. By using computing, storage, and mobility abilities of AUVs, a target selection algorithm is designed to calculate the mobility path of data collection for AUV. The theoretical analysis and experimental results show that the proposed method improves the efficiency of data collection, reduces the power consumption of nodes, and extends the network lifetime.

Caching on the Move: A User Interest-Driven Caching Strategy for D2D Content Sharing

Abstract: Device-to-device (D2D) content sharing helps to accommodate the exponentially surge in mobile data traffic. However, how to cache in mobile users is crucial to ensure the above advantages. There are three issues that have not been fully considered in the previous works. First, the ignorance of mobility cannot depict the random connectivity of mobile users in D2D content sharing. Second, the lack of the diverse and complete information on user interest leads to unsatisfied demands of users. Third, caching a complete content will be wasteful due to the limited cache capacity, which is also not likely to be obtained in one connection. Regarding the three issues, we construct not only a user mobility model, which helps to provide the contact opportunity for the users sharing contents, but also a user interest prediction model, which combines the social proximity and the dynamic content popularity. Moreover, we exploit the maximum distance separable code to encode the contents into smaller partitions. Accordingly, we formulate a mobility-aware and user interest-driven caching problem as a 0–1 multiple knapsack problem. Due to its NP-hard property, we prove that this problem falls into the category of monotone submodular function over one matroid and multiple knapsack constraints. Then, we develop a corresponding algorithm based on a greedy approach, which approximates the optimum within a constant factor in polynomial time. Numerical results demonstrate the performance and the effectiveness of our proposed algorithm.

A Survey of Human Mobility Models

Abstract: Human mobility models are key components of various research fields including transportation, mobile networks, disaster management, urban planning, and epidemic modeling. Understanding human mobility has a major role in the realistic evaluation of new approaches to challenges in these fields. For the perspective of networked systems, simulations of the networks with human participants such as opportunistic social networks are highly dependent on human mobility. In this article, we summarize the state of the art for scientific research on human mobility and survey the currently used human mobility models. We discuss the commonly used metrics and data collection techniques. Furthermore, we include a taxonomy of the mobility models according to their main characteristics and classify them. We lastly discuss the general trends, applicability, further research directions and open problems of human mobility modeling.

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

Abstract: The fifth-generation 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. Toward 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.

Middleware Implementation in Cloud-MANET Mobility Model for Internet of Smart Devices

Abstract: The smart devices are extremely useful devices that are making our lives easier than before. A smart device is facilitated us to establish a connection with another smart device in a wireless network with a decentralized approach. The mobile ad hoc network (MANET) is a novel methodology that discovers neighborhood devices and establishes connection among them without centralized infrastructure. Cloud provides service to the MANET users to access cloud and communicates with another MANET users. In this article, I integrated MANET and cloud together and formed a new mobility model named Cloud-MANET. In this Mobility model, if one smart device of MANET is able to connect to the internet then all smart devices are enabled to use cloud service and can be interacted with another smart device in the Cloud-MANET framework. A middleware acts as an interface between MANET and cloud. The objective of this article is to implement a middleware in Cloud-MANET mobility model for communication on internet of smart devices.

Data-driven activity scheduler for agent-based mobility models

Abstract: Activity-based modelling is a modern agent-based approach to travel demand modelling, in which the transport demand is derived from the agent’s needs to perform certain activities at specific places and times. The agent’s mobility is considered in a broader context, which allows the activity-based models to produce more realistic trip chains, compared to traditional trip-based models. The core of any activity-based model is an activity scheduler – a software component producing sequences of agent’s daily activities interconnected by trips, called activity schedules. Traditionally, activity schedulers used to rely heavily on hard-coded knowledge of transport behaviour experts. We introduce the concept of a Data-Driven Activity Scheduler (DDAS), which replaces numerous expert-designed components and their intricately engineered interactions with a collection of machine learning models. Its architecture is significantly simpler, making it easier to deploy and maintain. This shift towards data-driven, machine learning based approach is possible due to increased availability of mobility-related data. We demonstrate DDAS concept using our own proof-of-concept implementation, perform a rigorous analysis and compare the validity of the resulting model to one of the rule-based alternatives using the Validation Framework for Activity-Based Models (VALFRAM).

3GPP-Inspired Stochastic Geometry-Based Mobility Model for a Drone Cellular Network

Abstract: This paper deals with the stochastic geometry- based characterization of the time-varying performance of a drone cellular network in which the initial locations of drone base stations (DBSs) are modeled as a Poisson point process (PPP) and each DBS is assumed to move on a straight line in a random direction. This drone placement and trajectory model closely emulates the one used by the third generation partnership project (3GPP) for drone-related studies. Assuming the nearest neighbor association policy for a typical user equipment (UE) on the ground, we consider two models for the mobility of the serving DBS: (i) UE independent model, and (ii) UE dependent model. Using displacement theorem from stochastic geometry, we characterize the time- varying interference field as seen by the typical UE, using which we derive the time-varying coverage probability and data rate at the typical UE. We also compare our model with more sophisticated mobility models where the DBSs may move in nonlinear trajectories and demonstrate that the coverage probability and rate estimated by our model act as lower bounds to these more general models. To the best of our knowledge, this is the first work to perform a rigorous analysis of the 3GPP-inspired drone mobility model and establish connection between this model and the more general non-linear mobility models.

TARCS: A Topology Change Aware-Based Routing Protocol Choosing Scheme of FANETs

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

What Machine Learning Predictor Performs Best for Mobility Prediction in Cellular Networks

Abstract: It is envisaged that the future cellular networks (5G) will be able to meet the promising capacity and quality of experience requirements through extreme network densification and conglomeration of diverse technologies. It is easy to fathom that efficient management of such a convoluted network will be one of the big challenges faced by 5G. To cope with this challenge, Self-Organizing Networks (SONs) that were originally designed for legacy networks with reactive approach needs to be transformed to proactive paradigm. This radical transformation is possible only if the future network state can be predicted beforehand by harnessing historical network data. Mobility prediction is one of the key enablers of Proactive SON which enables efficient resource management. In this paper, we perform comparative analysis of four mobility predictors: Deep Neural Network (DNN), Extreme Gradient Boosting Trees (XGBoost), Semi-Markov, and Support Vector Machine (SVM). Our investigation is based on realistic synthetic dataset of eighty-four mobile users generated through realistic Self-similar Least Action Walk (SLAW) mobility model. We evaluate the effectiveness of each model not only based on the model's ability to predict the future location of mobile users but also the time each algorithm takes to be fully trained and perform such prediction. XGBoost stands out as clear winner among all predictors considered with high accuracy of 90%. Its high prediction accuracy enables high energy saving gain of above 80% when it is employed for driving proactive energy saving SON solution.

IoT System Integrating Unmanned Aerial Vehicles and LoRa Technology: A Performance Evaluation Study

Abstract: Nowadays, the popularity of the unmanned aerial vehicles (UAVs) is high, and it is expected that, in the next years, the implementation of UAVs in day-to-day service will be even greater. These new implementations make use of novel technologies encompassed under the term Internet of Things (IoT). One example of these technologies is Long-Range (LoRa), classified as a Low-Power Wide-Area Network (LPWAN) with low-cost, low-power consumption, large coverage area, and the possibility of a high number of connected devices. One fundamental part of a proper UAV-based IoT service deployment is performance evaluation. However, there is no standardized methodology for assessing the performance in these scenarios. This article presents a case study of an integrated UAV-LoRa system employed for air-quality monitoring. Each UAV is equipped with a set of sensors to measure several indicators of air pollution. In addition, each UAV also incorporates an embedded LoRa node for communication purposes. Given that mobility is key when evaluating the performance of these types of systems, we study eight different mobility models, focusing on the effect that the number of UAVs and their flying speed have on system performance. Through extensive simulations, performance is evaluated via multiple quality dimensions, encompassing the whole process from data acquisition to user experience. Results show that our performance evaluation methodology allows a complete understanding of the operation, and for this specific case study, the mobility model with the best performance is Pathway because the LoRa nodes are distributed and move orderly throughout the coverage area.

State-of-the-Art Clustering Schemes in Mobile Ad Hoc Networks: Objectives, Challenges, and Future Directions

Abstract: Mobile ad hoc networks (MANETs) are self-organized networks without any fixed infrastructure. The topology changes are very frequent in MANETs due to nodes’ mobility. The topology maintenance creates an extra overhead, as the mobility information of a single node is shared with all nodes in the network. To address the topology maintenance overhead problem in MANETs, the researchers proposed different cluster-based algorithms to reduce the size of a routing table. The clusters are formed to locally adjust the topology changes within the cluster. If a node wants to communicate with a node outside the cluster, it only communicates with its cluster head (CH). The CH communicates with other CHs to transmit data toward the destination. To efficiently utilize the clustering mechanism in MANETs, stable and balanced clusters are required. To form good quality and optimized clusters, some metrics, such as relative mobility (node speed and direction), node degree, residual energy, communication workload, and neighbor’s behavior, are required. In this paper, we present a comprehensive survey of recent CAs in MANETs. We also present the objectives, goals, and contributions of recent research. Similarly, the findings, challenges, and future directions are stated. The validation of each proposed work is analyzed critically in terms of the mobility model, the simulation tool used during simulation, simulation metrics, and the performance metrics used in the validation process.

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

Abstract: 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.

Coverage Analysis for 2D/3D Millimeter Wave Peer-to-Peer Networks

Abstract: This paper presents a theoretical analysis for estimating the coverage probability in two-dimensional (2D) and three-dimensional (3D) peer-to-peer (P2P) millimeter-wave (mmWave) wireless networks. The analysis is carried out by adopting suitable link state models and realistic propagation conditions, involving path-loss attenuation, angular dispersion, mid- and small-scale fading, which comply with recent channel measurements. The presented framework accounts in detail for the actual shape of the transmitting/receiving antenna patterns and for the spatial statistic that describes the node location, by considering the widely adopted Poisson point process, the uniform distribution, and the random waypoint mobility model. Analytical expressions for the statistic of the received power and simple integral formulas for the coverage probability in the presence of interference and noise are derived. The accuracy of the obtained estimations and of the introduced approximations is checked by independent Monte Carlo validations. As possible applications in the 3D mmWave context, the conceived mathematical theory is used to discuss the impact of the interference model on the reliability of the noise-limited approximation, and to estimate the average link capacity of an interfered P2P communication.

Mobility-Aware Relay Selection in 5G D2D Communication Using Stochastic Model

Abstract: Challenges in relay selection for device-to-device (D2D) communication arise due to the mobility of nodes, which brings uncertainty in various network parameters. We first developed a network-assisted stochastic integer programming (SIP) model to incorporate uncertainty that predicts the network parameters for upcoming time instance based on information available at current time instance. We converted the SIP model to an equivalent deterministic mixed integer non-linear program (MINLP) model and proved its hardness result. By exploiting the constraints of MINLP, we developed a distributed greedy metric, termed as connectivity factor (CF), which is calculated locally at each node on per-hop basis. It captures the nodes mobility and, hence, takes care of link reliability that in turn controls packet loss and delay. It can be computed in O ( n ) time, where n is the number of transmitters interfering with the given link. Our approach is applicable to any mobility model with relevant distributions of mobility parameters known. We constructed perceived graph based on CF values to devise network-assisted and device-controlled relay selection algorithms for given source-destination pairs. Extensive simulation results show significant improvements in packet loss and average end-to-end delay by our approach over a recent implementation of an ad-hoc on-demand distance vector (AODV) based algorithm.

Delay Tolerant Network assisted flying Ad-Hoc network scenario: modeling and analytical perspective

Abstract: Flying Ad-Hoc networks (FANET) are the extended paradigm of the mobile Ad-Hoc networks and, perhaps, one of the most emerging research domains in the current era. A huge number of tangible applications have been developed in this domain. The main advantages of such networks are their easy deployment, scalability, and robustness. However, the sparseness of these networks is an inherent characteristic that is known to be a bottleneck. The main objective of this work was to provide an alternative solution for the intermittently connected FANET by considering the philosophy of the Delay Tolerant Network (DTN) approach. To realize the functionality of the DTN protocols in a three-dimensional (3D) space, a social FANET model is proposed. FANET nodes are supposed to have a sparse node density. Fundamentally, the proposed DTN assisted Flying Ad hoc Network exploits the DTN routing and mobility features. The new mobility modeling for 3D spaces was re-engineered and tested with well-known routing protocols to analyze the performance of the model based on node speed, density, buffer, latency, message overhead, and power consumption. The effectiveness of 3D mobility models has also been compared against the one of classical models. The obtained results reflect a significant enhanced performance of the suggested DTN protocol for sparse FANET in a social scenario.

Reinforcement Learning-Based Data Forwarding in Underwater Wireless Sensor Networks with Passive Mobility

Abstract: Data forwarding for underwater wireless sensor networks has drawn large attention in the past decade. Due to the harsh underwater environments for communication, a major challenge of Underwater Wireless Sensor Networks (UWSNs) is the timeliness. Furthermore, underwater sensor nodes are energy constrained, so network lifetime is another obstruction. Additionally, the passive mobility of underwater sensors causes dynamical topology change of underwater networks. It is significant to consider the timeliness and energy consumption of data forwarding in UWSNs, along with the passive mobility of sensor nodes. In this paper, we first formulate the problem of data forwarding, by jointly considering timeliness and energy consumption under a passive mobility model for underwater wireless sensor networks. We then propose a reinforcement learning-based method for the problem. We finally evaluate the performance of the proposed method through simulations. Simulation results demonstrate the validity of the proposed method. Our method outperforms the benchmark protocols in both timeliness and energy efficiency. More specifically, our method gains 83.35% more value of information and saves up to 75.21% energy compared with a classic lifetime-extended routing protocol (QELAR).

Tracking Area Update and Paging in 5G Networks: a Survey of Problems and Solutions

Abstract: The 5th Generation wireless systems (5G) is expected to accommodate exceptional services beyond current cellular systems. To achieve this goal, however, ongoing studies are still developing new schemes to provide seamless connections to the ever increasing density of high-mobility User Equipments (UEs). That means that the network needs to track all UEs while moving throughout the coverage area for the purpose of data-packet delivery. The two Mobility Management (MM) procedures that are essential to localize a specific UE and deliver data packets to that UE are known as Tracking Area Update (TAU) and Paging, which are burdensome to the system because of very high-volume traffic. Therefore, MM will become a crucial problem for 5G requirements; how to support real-time applications and provide close-to-zero latency for life-critical systems? This paper addresses a variety of problems that should be faced and discusses various solution schemes in terms of implementation complexity, latency, and computation overhead for both the TAU and Paging. Because 5G systems will work in conjunction with current Long Term Evolution (LTE) systems and the latter is retuned to use as a base design for future 5G, our discussion starts from current LTE solutions towards 5G MM improvements. In this context, this paper emphasizes a new key design for 5G and explains the challenges that impact both the network performance and UE experience (e.g., power saving). Next, we critically discuss the applicability of current LTE solution schemes (in terms of TAU and Paging costs) and evaluate them for 5G use cases. To the best of our knowledge, this paper is the first study that emphasizes and gives a critique on using of different types of UE mobility models (based on the given studies), which are used to analyze the network performance that interacts with the UE movements. In this context, some 5G improvement schemes are discussed.