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In this paper, we propose and study an energy-efficient trajectory optimization scheme for unmanned aerial vehicle (UAV) assisted Internet of Things (IoT) networks. In such networks, a single UAV is powered by both solar energy and charging stations (CSs), resulting in sustainable communication services, while avoiding energy outage. In particular, we optimize the trajectory design of UAV by jointly considering the average data rate, the total energy consumption, and the fairness of coverage for the IoT terminals. A dynamic spatial-temporal configuration scheme is operated for terminals working in the discontinuous reception (DRX) mode. The module-free, action-confined on-policy and off-policy reinforcement learning (RL) approaches are proposed and jointly applied to solve the formulated optimization problem in this paper. We evaluate the effectiveness of the proposed strategy by comparing it with other dynamic benchmark algorithms. The extensive simulation results provided in this paper reveal that the proposed scheme outperforms the benchmarks in terms of data transmission, energy efficiency and adaptivity of avoiding battery depletion. By deploying the proposed trajectory scheme, the UAV is able to adapt itself according to the temporal and dynamic conditions of communication networks. [ABSTRACT FROM AUTHOR]

This paper is the first to investigate both communication and control in traffic channel (TCH) and control channel (CCH) respectively when considering leader-follower formation keeping in UAV communication networks. In this paper, we analyze the relationship between the mutual interference and information exchange cost, and then formulate the joint channel and link selection problem as a two-way consensus game between CCH and TCH. To characterize the two-way choice of link selection, we creatively propose the generalized two-way consensus equilibrium (GTCE) to capture the stable state. Then, we prove that the formulated game has at least one pure-strategy GTCE which can maximize the UAV communication network utility. A distributed better reply based joint channel and link selection (BRJCLS) algorithm as well as two-dimensional minimum spanning tree (MST) based initialization (TMSTI) algorithm is proposed to achieve the GTCE. Simulation results are presented to show the convergence and effectiveness of the formulated two-way consensus game and proposed algorithms. [ABSTRACT FROM AUTHOR]

Miniature radar has demonstrated its great potential in smart homes, such as understanding the wellness of the residents and providing ubiquitous interactions. While it has many promising applications, it also results in congested RF (radio frequency) environments as there is an unprecedented amount of traffic in a smart home. To ease the strain on the limited spectrum, we ask the question that, can we reuse the sensing signals for data communication? With such a capability, we can improve the spectrum utilization by sharing the spectrum between sensing and communication systems. However, radar signals are customized for the sensing purpose and are incompatible with legacy communication standards. To address this challenge, we have an observation that, non-linearity effect in RF circuits can convert wideband radar signals into a LoRa signal. Based on this observation, in this paper, we present LoRadar, which enables an FMCW (Frequency-Modulated Continuous Wave) radar to carry LoRa signals in sensing waves. We present both the downlink and uplink design, enabling a LoRadar device to communicate with LoRa nodes in a bi-directional way. We implement LoRadar and evaluation results show that LoRadar can achieve home-level coverage with 3.4kbps data rate while it preserves the sensing resolution of the radar. [ABSTRACT FROM AUTHOR]

In this paper, we propose a reinforcement learning approach of collision avoidance and investigate optimal trajectory planning for unmanned aerial vehicle (UAV) communication networks. Specifically, each UAV takes charge of delivering objects in the forward path and collecting data from heterogeneous ground IoT devices in the backward path. We adopt reinforcement learning for assisting UAVs to learn collision avoidance without knowing the trajectories of other UAVs in advance. In addition, for each UAV, we use optimization theory to find out a shortest backward path that assures data collection from all associated IoT devices. To obtain an optimal visiting order for IoT devices, we formulate and solve a no-return traveling salesman problem. Given a visiting order, we formulate and solve a sequence of convex optimization problems to obtain line segments of an optimal backward path for heterogeneous ground IoT devices. We use analytical results and simulation results to justify the usage of the proposed approach. Simulation results show that the proposed approach is superior to a number of alternative approaches. [ABSTRACT FROM AUTHOR]

To support the increasing data traffic demand in wireless communications networks, a multi-tier architecture that consists of multiple small cells is adopted in traditional (macro) cellular networks. Nevertheless, due to the expansion of various wireless devices and services, there is still a need to increase the network capacity in new generation networks such as 5G. Hence, the integration of Device-to-Device (D2D) communication as a promising technology with heterogeneous networks has been proposed. This integration not only increases network capacity but also improves spectral efficiency and alleviates the traffic load of base stations. However, the co/cross-tier interferences between D2D and cellular communications caused by resource sharing is a significant challenge. In this paper, we propose a distributed resource allocation algorithm based on matching theory to minimize these interferences and optimize the network performance. It is shown in this paper that the proposed algorithm converges to a stable matching and terminates after finite iterations. Simulation results show that the proposed algorithm is able to achieve more than 90 percent of the optimum network performance with much lower overhead and complexity. [ABSTRACT FROM AUTHOR]

The maximum capacity of fractal D2D (device-to-device) social networks with both direct and hierarchical communications is studied in this paper. Specifically, the fractal networks are characterized by the direct social connection and the self-similarity. First, for a fractal D2D social network with direct social communications, it is proved that the maximum capacity is Θ(1/n log n) if a user communicates with one of his/her direct contacts randomly, where n denotes the total number of users in the network, and it can reach up to Θ (1/log n) if any pair of social contacts with distance d communicate according to the probability in proportion to d−β. Second, since users might get in touch with others without direct social connections through the inter-connected multiple users, the fractal D2D social network with these hierarchical communications is studied as well, and the related capacity is further derived. Our results show that this capacity is mainly affected by the correlation exponent ε of the fractal structure. The capacity is reduced in proportional to 1/log n if 2 < ε < 3 , while the reduction coefficient is 1/n if ε > 3 . [ABSTRACT FROM AUTHOR]

In this paper, we study the co-design of full-duplex (FD) radio with joint communication and radar sensing (JCAS) techniques in millimeter-wave (mmWave) heterogeneous networks (HetNets). Spectral co-existence of radar and communication systems causes mutual interference between the two systems, compromising both the data exchange and sensing capabilities. Focusing on the detection performance, we propose a cooperative detection technique, which exploits the sensing information from multiple base stations (BSs), aiming at enhancing the probability of successfully detecting an object. Three combining rules are considered, namely the OR, the Majority and the AND rule. In real-world network scenarios, the locations of the BSs are spatially correlated, exhibiting a repulsive behavior. Therefore, we model the spatial distribution of the BSs as a $\beta$ β -Ginibre point process ($\beta$ β -GPP), which can characterize the repulsion among the BSs. By using stochastic geometry tools, analytical expressions for the detection performance of $\beta$ β -GPP-based FD-JCAS systems are expressed for each of the considered combining rule. Furthermore, by considering temporal interference correlation, we evaluate the probability of successfully detecting an object over two different time slots. Our results demonstrate that our proposed technique can significantly improve the detection performance when compared to the conventional non-cooperative technique. [ABSTRACT FROM AUTHOR]

Satellite-based communication technology has gained much attention in the past few years, where satellites play mainly the supplementary roles as relay devices to terrestrial communication networks. Unlike previous work, we treat the low-earth-orbit (LEO) satellites as secure data storage mediums. We focus on data acquisition from a LEO satellite based data storage system (also referred to as the LEO based datacenters), which has been considered as a promising and secure paradigm on data storage. Under the LEO based datacenter architecture, one fundamental challenge is to deal with energy-efficient downloading from space to ground while maintaining the system stability. In this paper, we aim to maximize the amount of data admitted while minimizing the energy consumption, when downloading files from LEO based datacenters to meet user demands. To this end, we first formulate a novel optimization problem and develop an online scheduling framework. We then devise a novel coflow-like “Join the first $K$ K -shortest Queues (JKQ)” based job-dispatch strategy, which can significantly lower backlogs of queues residing in LEO satellites, thereby improving the system stability. We also analyze the optimality of the proposed approach and system stability. We finally evaluate the performance of the proposed algorithm through conducting emulator based simulations, based on real-world LEO constellation and user demand traces. The simulation results show that the proposed algorithm can dramatically lower the queue backlogs and achieve high energy efficiency. [ABSTRACT FROM AUTHOR]

The use of Bluetooth Low Energy (BLE) beacons enhanced further for connectionless services such as location-specific information and navigation. With BLE 5.0, the way beacons deliver more information can move away from the current model of app-paired-to-device to a connectionless IoT. When users pass areas with installed BLE beacons, their mobile devices can receive specials, promotional contents, and discount coupons. However, the beacons are only broadcasting. This means that beacons are not able to collect information from the users with mobile devices. In this paper, we propose responsive advertising with the wait-slot scheme (RAWS) based on advertising extensions to improve the performance of the discovery process before further communications in BLE networks. Besides, we consider the energy consumption and investigate the latency-energy tradeoff with our proposed scheme. The theoretical lower bounds for both latency and energy of the discovery process as well as their tradeoff are presented. In addition, we formulate the state transition diagram for analyzing the performance of our proposed scheme. Simulation results validated by analysis results show that RAWS indeed improves the latency and the energy consumption of the discovery process in BLE networks. [ABSTRACT FROM AUTHOR]

In this paper, an analytical model for the coverage analysis of multiuser visible light communication (VLC) networks is presented, taking into account the cooperation among access points (APs). Specifically, the cooperation is realized through joint transmission (JT), where the coordinated APs jointly transmit data to users in a noncoherent or coherent manner to reduce the inter-cell interference and enhance the useful signal power. Using a second-order moment matching approach, we find approximate distribution functions of the signal power and interference, and derive tractable results for the network coverage probability based on the signal-to-interference-plus-noise ratio (SINR). For both noncoherent and coherent JT, the derived coverage probabiklity are further simplified into closed forms when the communication link is interference-limited. We validate the derived results through Monte Carlo simulations and apply them to study behaviors and trends of the network under various parameter settings. Results show that JT can improve the coverage performance of the network and coherent JT can provide higher performance gains than its noncoherent counterpart, at the cost of higher implementation complexities. [ABSTRACT FROM AUTHOR]

Deploying small cell base stations (SBS) under the coverage area of a macro base station (MBS), and caching popular contents at the SBSs in advance, are effective means to provide high-speed and low-latency services in next generation mobile communication networks. In this paper, we investigate the problem of content caching (CC) and user association (UA) for edge computing. A joint CC and UA optimization problem is formulated to minimize the content download latency. We prove that the joint CC and UA optimization problem is NP-hard. Then, we propose a CC and UA algorithm (JCC-UA) to reduce the content download latency. JCC-UA includes a smart content caching policy (SCCP) and dynamic user association (DUA). SCCP utilizes the exponential smoothing method to predict content popularity and cache contents according to prediction results. DUA includes a rapid association (RA) method and a delayed association (DA) method. Simulation results demonstrate that the proposed JCC-UA algorithm can effectively reduce the latency of user content downloading and improve the hit rates of contents cached at the BSs as compared to several baseline schemes. [ABSTRACT FROM AUTHOR]

With significantly dynamic characteristics of the new aerial users, the emerging cellular-enabled unmanned aerial vehicle (UAV) communication paradigm raises great challenges to current research of UAV applications. As far as the robust channel allocation is concerned, the high mobility of UAV nodes and the unexpected disturbance of external environment would render most existing methods which rely on definite information and are vulnerable to dynamic environment, become less attractive or even invalid. In this paper, we particularly investigate a cellular-enabled mesh UAV network exploiting partially overlapping channels (POCs), and propose a distributed fuzzy space based learning scheme for POCs allocation to combat the dynamic environment. Rather than the perfect channel state information (CSI) assumption, the dynamic and uncertain CSI of UAVs is characterized by fuzzy number. On this basis, the allocation process can be implemented in a mapped fuzzy space. Integrating fuzzy-logic and game based learning, we formulate the problem of POCs assignment as a fuzzy payoffs game (FPG), and demonstrate the existence of fuzzy Nash equilibrium for our designed FPG. Then, with the derived priority vector in the fuzzy space, the equilibrium solution can be achieved by the proposed algorithm. Numerical simulations demonstrate the advantages of our new scheme. [ABSTRACT FROM AUTHOR]

This paper investigates the delay minimization problem for instantly decodable network coding (IDNC) based device-to-device (D2D) communications. In D2D enabled systems, users cooperate to recover all their missing packets. The paper proposes a game theoretic framework as a tool for improving the distributed solution by overcoming the need for a central controller or additional signaling in the system. The session is modeled by self-interested players in a non-cooperative potential game. The utility functions are designed so as increasing individual payoff results in a collective behavior which achieves both a desirable system performance in a shared network environment and the Nash equilibrium. Three games are developed whose first reduces the completion time, the second the maximum decoding delay and the third the sum decoding delay. The paper, further, improves the formulations by including a punishment policy upon collision occurrence so as to achieve the Nash bargaining solution. Learning algorithms are proposed for systems with complete and incomplete information, and for the imperfect feedback scenario. Numerical results suggest that the proposed game-theoretical formulation provides appreciable performance gain against the conventional point-to-multipoint (PMP), especially for reliable user-to-user channels. [ABSTRACT FROM AUTHOR]

In this paper, we address the optimization of the energy efficiency of underlay multicast device-to-device (D2MD) communications on cellular networks. In particular, we maximize the energy efficiency of both the global network and the individual users considering various fairness factors such as maximum power and minimum rate constraints. For this, we employ a canonical mixed-integer non-linear formulation of the joint power control and resource allocation problem. To cope with its NP-hard nature, we propose a two-stage semi-distributed solution. In the first stage, we find a stable, yet sub-optimal, channel allocation for D2MD groups using a cooperative coalitional game framework that allows co-channel transmission over a set of shared resource blocks and/or transmission over several different channels per D2MD group. In the second stage, a central entity determines the optimal transmission power for each user in the system via fractional programming. We performed extensive simulations to analyze the resulting energy efficiency and attainable transmission rates. The results show that the performance of our semi-distributed approach is very close to that obtained with a pure optimal centralized one. [ABSTRACT FROM AUTHOR]

Transmit antenna selection (TAS) at base station has been widely studied and employed in many communication networks (such as those using massive multiple-input multiple-output (MIMO) systems). Thanks to the small size of microstrip antenna elements applicable to millimeter-wave (mmWave) frequencies, the implementation of TAS in small user equipments (UEs) employing switchable directional antennas is recently becoming popular. In this paper, we consider device-to-device (D2D) communications underlaying a cellular network wherein each D2D UE is equipped with switchable transmit antennas. By employing Generalized Bender’s Decomposition (GBD) algorithm, we obtained the solution to the problem of globally optimal transmit antenna selection and channel allocation to D2D UEs together with transmit powers of cellular and D2D UEs. Although we reformulated the non-convex primal subproblem of the proposed GBD-based method into convex form, we further managed to obtain the corresponding closed-form solution through analytical manipulations; this extensively increased (at least 60 times) the execution speed of the proposed method as shown in the simulation results. [ABSTRACT FROM AUTHOR]

In this paper, we study the critical transmitting range (CTR) for connectivity in mobile ad hoc networks. We prove that rM = c√ln n/πn for some constant c > 1, where rM is the CTR in the presence of M-like node mobility and n is the number of network nodes. Our result holds for an arbitrary mobility model M such that: 1) M is obstacle free and 2) nodes are allowed to move only within a certain bounded area. We also investigate in detail the case of random waypoint mobility, which is the most common mobility model used in the simulation of ad hoc networks. Denoting with rpw the CTR with random waypoint mobility when the pause time is set to p and node velocity is set to v, we prove that rpw = p+0.521405/v/p √ln n/πn if p > 0 and that r0w ≫ √ ln n/n. The results of our simulations also suggest that if n is large enough (n > 50), r0w is well approximated by r/4 ln n, where r is the critical range in case of uniformly distributed nodes. The results presented in this paper provide a better understanding of the behavior of a fundamental network parameter in the presence of mobility and can be used to improve the accuracy of mobile ad hoc network simulations. [ABSTRACT FROM AUTHOR]

While traffic modeling and prediction are at the heart of providing high-quality telecommunication services in cellular networks and attract much attention, they have been approved as an extremely challenging task. Due to the diverse network demand of Internet-based apps, the cellular traffic from an individual user can have a wide dynamic range. Most existing methods, on the other hand, model traffic patterns as probabilistic distributions or stochastic processes and impose stringent assumptions over these models. Such assumptions may be beneficial at providing closed-form formula in evaluating prediction performances, but fall short for practice use. In this paper we propose STEP, a spatio-temporal fine-granular user traffic prediction mechanism for cellular networks. A deep graph convolution network, called GCGRN, is constructed. It is a novel combination of the graph convolution network (GCN) and gated recurrent units (GRU), which exploits graph neural network to learn an efficient spatio-temporal model from a user’s massive dataset for traffic prediction. The prototype of STEP has been implemented. Extensive experimental results demonstrate that our model outperforms the state-of-the-art time-series based approaches. Besides, STEP merely incurs mild energy consumption, communication overhead and system resource occupancy to mobile devices. Moreover, NS-3 based simulations validate the efficacy of STEP in reducing session dropping ratio in cellular networks. [ABSTRACT FROM AUTHOR]

Multipath TCP (MPTCP) is a promising solution that can provide high end-to-end throughput in fifth generation (5G) mobile networks. Many next-generation applications will require high throughput and low latency simultaneously, but the current MPTCP congestion control algorithms cannot reliably satisfy this requirement. In this paper, a novel MPTCP congestion control scheme named delay-equalized FAST (DEFT) is proposed to achieve high throughput and low end-to-end (E2E) delay in 5G networks. First, in order to achieve high throughput, DEFT includes a novel window control algorithm that shows fast responsiveness when the state of the millimeter-wave (mmWave) link changes from line-of-sight (LOS) to non-LOS (NLOS) and vice versa. Second, in order to achieve low E2E delay, DEFT includes a delay-equalizing algorithm which minimizes additional reordering delay in the receive buffer. The performance of DEFT was evaluated based on ns-3 simulation and was compared with wVegas, Balia, and delay-adapted LIA. Simulation results show that DEFT can provide a significant goodput gain and application-level E2E delay reduction for the range of interest. [ABSTRACT FROM AUTHOR]

In modern distributed cyber-physical systems (CPS), information fusion often plays a key role in automate and self-adaptive decision making process. However, given the heterogeneous and distributed nature of modern CPSs, it is a great challenge to operate CPSs with the compromised data integrity and unreliable communication links. In this paper, we study the distributed state estimation problem under the false data injection attack (FDIA) with probabilistic communication networks. We propose an integrated ”detection + fusion” solution, which is based on the Kullback-Leibler divergences (KLD) between local posteriors and therefore does not require the exchange of raw sensor data. For the FDIA detection step, the KLDs are used to cluster nodes in the probability space and to partition the space into secure and insecure subspaces. By approximating the distribution of the KLDs with a general χ2 distribution and calculating its tail probability, we provide an analysis of the detection error rate. For the information fusion step, we discuss the potential risk of double counting the shared prior information in the KLD-based consensus formulation method. We show that if the local posteriors are updated from the shared prior, the increased number of neighbouring nodes will lead to the diminished information gain. To overcome this problem, we propose a near-optimal distributed information fusion solution with properly weighted prior and data likelihood. Finally, we present simulation results for the integrated solution. We discuss the impact of network connectivity on the empirical detection error rate and the accuracy of state estimation. [ABSTRACT FROM AUTHOR]

In this paper, a link-layer synchronization and medium access control (MAC) protocol for very-high-speed wireless communication networks in the Terahertz (THz) band is presented. The protocol relies on a receiver-initiated handshake to guarantee synchronization between transmitter and receiver. Two scenarios are considered, namely, a macroscale scenario, where nodes utilize rotating directional antennas to periodically sweep the space while overcoming the distance problem at THz frequencies, and a nanoscale scenario, where nano-devices require energy harvesting systems to operate. Both scenarios are implemented on a centralized and an ad-hoc network architecture. A carrier-based physical layer is considered for the macro-scenario, whereas the physical layer for the nano-scenario is based on a femtosecond-long pulse-based modulation scheme with packet interleaving. The performance of the proposed MAC protocol is analytically investigated in terms of delay, throughput and probability of successful packet delivery, and compared to that of an adapted Carrier Sense Multiple Access with Collision Avoidance (CSMA/CA) with and without handshake. The results are validated by means of extensive simulations with ns-3, in which all the necessary THz elements have been implemented. The results show that the proposed protocol can maximize the successful packet delivery probability without compromising the achievable throughput in THz-band communication networks. [ABSTRACT FROM AUTHOR]

Due to the fact that Carrier Sense Multiple Access with Collision Avoidance (CSMA/CA) protocols are extensively used in commercial wireless networks, the analysis of this family of medium access control protocols has been a topic of great interest for the wireless networking community. In this paper, we present a mean field analysis for the throughput of a slotted CSMA/CA scheme in single-hop networks. The concept of mean field approximation originates in statistical mechanics and it is a widely used approximation method employed to address systems of many interacting particles that cannot be solved exactly. The idea is to simplify the treatment of a many-body system by describing the interaction of one particle with the other interacting particles by an average potential, the so-called mean field. In our analysis, the nodes of a wireless network constitute a set of interacting particles; the interaction of a certain node with the other nodes in the network is reduced to an averaged channel condition. We estimate the amount of busy slots and the network throughput with respect to the offered traffic. Our analysis is of a recursive form, in which at each step the amount of traffic is increased by a specific amount. Also, our model takes into accounts retransmissions of collided packets. [ABSTRACT FROM AUTHOR]

In this paper, we study the phase transition behavior of k-connectivity (k = 1,2,…) in wireless multihop networks where a total of n nodes are randomly and independently distributed following a uniform distribution in the unit cube [0, 1]d (d = 1,2,3), and each node has a uniform transmission range r(n). It has been shown that the phase transition of k-connectivity becomes sharper as the total number of nodes n increases. In this paper, we investigate how fast such phase transition happens and derive a generic analytical formula for the phase transition width of k-connectivity for large enough n and for any fixed positive integer k in d-dimensional space by resorting to a Poisson approximation for the node placement. This result also applies to mobile networks where nodes always move randomly and independently. Our simulations show that to achieve a good accuracy, n should be larger than 200 when k = 1 and d = 1; and n should be larger than 600 when k < 3 and d = 2, 3. The results in this paper are important for understanding the phase transition phenomenon; and it also provides valuable insight into the design of wireless multihop networks and the understanding of its characteristics. [ABSTRACT FROM AUTHOR]

LED-to-camera communication allows LEDs deployed for illumination purposes to modulate and transmit data which can be received by camera sensors available in mobile devices like smartphones, wearable smart-glasses, etc. Such communication has a unique property that a user can visually identify a transmitter (i.e., LED) and specifically receive information from the transmitter. It can support a variety of novel applications such as augmented reality through mobile devices, navigation using smart signs, fine-grained location specific advertisement, etc. However, the achievable data rate in current LED-to-camera communication techniques remains very low to support any practical application. In this paper, we present $\mathsf {ColorBars}$ ColorBars , an LED-to-camera communication system that utilizes Color Shift Keying (CSK) to modulate data using different colors transmitted by the LED. It exploits the increasing popularity of Tri-LEDs (RGB) that can emit a wide range of colors. We show that commodity cameras can efficiently and accurately demodulate the color symbols. $\mathsf {ColorBars}$ ColorBars ensures flicker-free and reliable communication even in the presence of inter-frame loss and diversity of rolling shutter cameras. We implement $\mathsf {ColorBars}$ ColorBars on embedded platform and evaluate it with Android and iOS smartphones as receivers. Our evaluation shows that $\mathsf {ColorBars}$ ColorBars can achieve a data rate of 7.7 Kbps on Nexus 5, 3.7 Kbps on iPhone 5S, and 2.9 Kbps on Samsung Note8. It is also shown that lower CSK modulations (e.g., four and eight CSK) provide extremely low symbol error rates ($<10^{-3}$ < 10 - 3 ), making them a desirable choice for reliable LED-to-camera communication. [ABSTRACT FROM AUTHOR]

With the emerging Internet-of-Things services, massive machine-to-machine (M2M) communication will be deployed on top of human-to-human (H2H) communication in the near future. Due to the coexistence of M2M and H2H communications, the performance of M2M (i.e., secondary) networks depends largely on the H2H (i.e., primary) network. In this paper, we propose ambient backscatter communication for the M2M networks which exploits the energy (signal) sources of the H2H network, referring to its traffic applications and popularity. In order to maximize the harvesting and transmission opportunities offered by varying traffic sources of the H2H network, we adopt a Bayesian nonparametric (BNP) learning algorithm to classify traffic applications (patterns) for secondary transmitters (STs). We then analyze the performance of STs using the stochastic geometric approach, based on a criterion for optimal traffic selection. Because of the mathematical intractability of the optimal criterion, we have attained a suboptimal traffic selection criterion which provides more tractable analysis. Results are presented to validate the performance of the proposed BNP classification algorithm and the criterion, as well as the impact of traffic sources and popularity. [ABSTRACT FROM AUTHOR]

The emergence of vehicular networking enables distributed cooperative computation among nearby vehicles and infrastructures to achieve various applications that may need to handle mass data by a short deadline. In this paper, we investigate the fundamental problems of a cooperative vehicle-infrastructure system (CVIS): how does vehicular communication and networking affect the benefit gained from cooperative computation in the CVIS and what should a reliability-optimal cooperation be? We develop an analytical framework of reliability-oriented cooperative computation optimization, considering the dynamics of vehicular communication and computation. To be specific, we propose stochastic modeling of V2V and V2I communications, incorporating effects of the vehicle mobility, channel contentions, and fading, and theoretically derive the probability of successful data transmission. We also formulate and solve an execution time minimization model to obtain the success probability of application completion with the constrained computation capacity and application requirements. By combining these models, we develop constrained optimizations to maximize the coupled reliability of communication and computation by optimizing the data partitions among different cooperators. Numerical results confirm that vehicular applications with a short deadline and large processing data size can better benefit from the cooperative computation rather than non-cooperative solutions. [ABSTRACT FROM AUTHOR]

Control of conventional transportation networks aims at bringing the state of the network (e.g., the traffic flows in the network) to the system optimal (SO) state. This optimum is characterized by the minimality of the social cost function, i.e., the total cost of travel (e.g., travel time) of all drivers. On the other hand, drivers are assumed to be rational and selfish, and make their travel decisions (e.g., route choices) to optimize their own travel costs, bringing the state of the network to a user equilibrium (UE). A classic approach to influence users’ route choice is using congestion tolls. In this paper, we study the SO and UE of future connected vehicular transportation networks, where users consider both the travel cost and the utility from data communication, when making their travel decisions. We leverage the data communication aspect of the decision making to influence the user route choices, driving the UE state to the SO state. We assume the cache-enabled vehicles can communicate with other vehicles via vehicle-to-vehicle (V2V) connections. We propose an algorithm for calculating the values of the data communication utility that drive the UE to the SO. This result provides a guideline on how the system operator can adjust the parameters of the communication network (e.g., data pricing and bandwidth) to achieve the optimal social cost. We discuss the insights that the results shed on a secondary optimization that the operator can conduct to maximize its own utility without deviating the transportation network state from the SO. We validate the proposed communication model via Veins simulation. The simulation results also show that the system cost can be lowered even if the bandwidth allocation does not exactly match the optimal allocation policy under 802.11p protocol. [ABSTRACT FROM AUTHOR]

In the near future, several radio access technologies will coexist in Beyond 3G mobile networks (B3G), and they will be eventually transformed into one seamless global communication infrastructure. Self-managing systems (i.e., those that self-configure, self-protect, self-heal, and self-optimize) are the solution to tackle the high complexity inherent to these networks. In this context, this paper proposes a system for autodiagnosis in the Radio Access Network (RAN) of wireless systems. The malfunction of the RAN may be due not only to a hardware fault but also (and more difficult to identify) to a bad configuration. The proposed system is based on the analysis of Key Performance Indicators (KPIs) in order to isolate the cause of the network malfunction. In this paper, two alternative probabilistic systems are compared, which differ on how KPIs are modeled (continuous or discrete variables). Experimental results are examined in order to support the theoretical concepts, based on data from a live network. The drawbacks and benefits of both systems are studied, and some conclusions on the scenarios under which each model should be used are presented. [ABSTRACT FROM AUTHOR]

In this paper, we investigate the impact of variable-range transmission power control on the physical and network connectivity, on network capacity, and on power savings in wireless multihop networks. First, using previous work by Steele [18], we show that, for a path attenuation factor α = 2, the average range of links in a planar random network of A m² having n nodes (Multiple line equation(s) cannot be represented in ASCII text). We show that this average range is approximately half the range obtained when common-range transmission control is used. Combining this result and previous work by Gupta and Kumar [8], we derive an expression for the average traffic carrying capacity of variable-range-based multihop networks. For α = 2, we show that this capacity remains constant even when more nodes are added to the network. Second, we derive a model that approximates the signaling overhead of a routing protocol as a function of the transmission range and node mobility for both route discovery and route maintenance. We show that there is an optimum setting for the transmission range, not necessarily the minimum, which maximizes the capacity available to nodes in the presence of node mobility. The results presented in this paper highlight the need to design future MAC and routing protocols for wireless ad hoc and sensor networks based, not on common-range which is prevalent today, but on variable-range power control. [ABSTRACT FROM AUTHOR]

Simulation has become an indispensable tool in the design and evaluation of mobile systems. By using mobility models that describe constituent movement, one can explore large systems, producing repeatable results for comparison between alternatives. In this paper, we show that a large class of mobility models—including all those in which nodal speed and distance or destination are chosen independently—have a transient period in which the average node speed decreases until converging to some long-term average. This speed decay provides an unsound basis for simulation studies that collect results averaged over time, complicating the experimental process. In this paper, we derive a general framework for describing this decay and apply it to a number of cases. Furthermore, this framework allows us to transform a given mobility model into a stationary one by initializing the simulation using the steady-state speed distribution and using the original speed distribution subsequently. This transformation completely eliminates the transient period and the decay in average node speed and, thus, provides sound models for the simulation of mobile systems. [ABSTRACT FROM AUTHOR]

In this paper, we consider wireless ad hoc networks that use adaptive antennas and have limited energy resources. To explore the advantages of power saving offered by the use of adaptive antennas, we consider the case of source initiated multicast traffic. We present a constraint formulation for the MEM (Minimum-Energy Multicast) problem in terms of MILP (Mixed Integer Linear Programming) for wireless ad hoc networks. An optimal solution to the MEM problem using our MILP model can always be obtained in a timely manner for moderately sized networks. In addition to the theoretical effort, we also present two polynomial-time heuristic algorithms called RB-MIDP and D-MIDP to handle larger networks for which the MILP model may not be computationally efficient. The experimental results show that our algorithms compare well with other proposals discussed in this paper. [ABSTRACT FROM AUTHOR]

In distributed multiple access control protocols, two categories of overhead are usually associated with contention resolution. One is channel idle overhead, where all contending stations are waiting to transmit. Another is collision overhead, which occurs when multiple contending stations attempt to transmit simultaneously. Either idle overhead or collision overhead being large, contention resolution algorithm would be inefficient. Prior research work tries to minimize both the idle and the collision overheads using various methods. In this paper, we propose to apply ‘pipelining’ techniques to the design of multiple access control protocol so that channel idle overhead could be (partially) hidden and the collision overhead could be reduced. While the concept of pipelined scheduling can be applied to various MAC protocol designs in general, in this paper, we focus on its application to IEEE 802.11 DCF. In particular, an implicitly pipelined dual-stage contention resolution MAC protocol (named DSCR) is proposed. With IEEE 802.11, the efficiency of contention resolution degrades dramatically with the increasing load due to high probability of collision. Using the implicit pipelining technique, DSCR hides the majority of channel idle time and reduces the collision probability, hence, improves channel utilization, average access delay, and access energy cost over 802.11 significantly both in wireless LANs and in multihop networks. The simulation results, as well as some analysis, are presented to demonstrate the effectiveness of DSCR. [ABSTRACT FROM AUTHOR]

Ad hoc localization of wireless sensor nodes is a fundamental problem in wireless sensor networks. Despite the recent proposals for the development of ad hoc localization algorithms, the fundamental behavior in systems using measurements has not been characterized. In this paper, we take a first step toward such a characterization by examining the behavior of error inducing parameters in multihop localization systems in an algorithm independent manner. We first derive the Cramé Rao Bound for Gaussian measurement error for multihop localization systems using distance and angular measurements. Later on, we use these bounds on a carefully controlled set of scenarios to study the trends in the error induced by the measurement technology accuracy, network density, beacon node concentration, and beacon uncertainty. By exposing these trends, the goal of this paper is to develop a fundamental understanding of the error behavior that can provide a set of guidelines to be considered during the design and deployment of multihop localization systems. [ABSTRACT FROM AUTHOR]

In this paper, we address the problem of how to make the wireless service provider (WSP) earn profits in a wireless video broadcast network with consideration of advertisement insertion. At the beginning, this study examines the profit components by analyzing traffic provision and advertisement insertion. This study considers using two components for profit maximization—one is the function for allocating video rates, and the other is the function for inserting advertisement duration. The maximum achievable profit depends on joint optimization of optimal video-rate vectors and advertisement-duration vectors, which are usually computationally intensive. To resolve such a complexity problem, this work also proposes an effective algorithm for joint optimization. First, the overall profit is formulated as the solution of four local optimization problems through horizontal and vertical decomposition. Second, a theoretic polymatroidal framework is introduced in our work for optimization as this framework is proved effective in profit maximization of multiuser systems. Third, this study shows that the overall profit can be maximized by finding the optimal profit points on the boundary of the rate and duration regions. As a result, the optimum points and the total profit can be obtained through a hierarchical greedy algorithm. Experimental results demonstrate that the proposed method is capable of making maximum profits for WSPs in a wide range of broadcasting rates. [ABSTRACT FROM AUTHOR]

Bufferbloat has drawn much attention in the network community for its negative impact on TCP delay performance and user QoE. Recently, it has been more commonly noted in wireless access networks, in part, due to over-provisioned buffer space. Previous works that focused only on bufferbloat prevention have suffered from either deployment or fairness problems when coexisting with conventional TCP flows. In this paper, we address the bufferbloat problem in resource-competitive environments such as Wi-Fi, and design a receiver-side countermeasure for easy deployment that does not require any modification at the sender or intermediate routers. Exploiting TCP and AQM dynamics, our scheme competes for shared resource in a fair manner with conventional TCP flow control methods and prevents bufferbloat. We implement our proposed scheme in commercial smart devices and verify its performance through real experiments in LTE and Wi-Fi networks. [ABSTRACT FROM AUTHOR]

With the increasing availability of flexible wireless 802.11 devices, the potential exists for users to selfishly manipulate their channel access parameters and gain a performance advantage. Such practices can have a severe negative impact on compliant stations. To enable access points to counteract these selfish behaviours and preserve fairness in wireless networks, in this paper we propose a policing mechanism that drives misbehaving users into compliant operation without requiring any cooperation from clients. This approach is demonstrably effective against a broad class of misbehaviours, soundly-based, i.e., provably hard to circumvent and amenable to practical implementation on existing commodity hardware. [ABSTRACT FROM PUBLISHER]

Detecting node failures in mobile wireless networks is very challenging because the network topology can be highly dynamic, the network may not be always connected, and the resources are limited. In this paper, we take a probabilistic approach and propose two node failure detection schemes that systematically combine localized monitoring, location estimation and node collaboration. Extensive simulation results in both connected and disconnected networks demonstrate that our schemes achieve high failure detection rates (close to an upper bound) and low false positive rates, and incur low communication overhead. Compared to approaches that use centralized monitoring, our approach has up to 80 percent lower communication overhead, and only slightly lower detection rates and slightly higher false positive rates. In addition, our approach has the advantage that it is applicable to both connected and disconnected networks while centralized monitoring is only applicable to connected networks. Compared to other approaches that use localized monitoring, our approach has similar failure detection rates, up to 57 percent lower communication overhead and much lower false positive rates (e.g., 0.01 versus 0.27 in some settings). [ABSTRACT FROM PUBLISHER]

In this paper, a novel framework for optimizing the caching of popular user content at the level of wireless user equipments (UEs) is proposed. The goal is to improve content offloading over wireless device-to-device (D2D) communication links. In the considered network, users belong to different social communities while their UEs form a single multi-hop D2D network. The proposed framework allows us to exploit the multi-community social context of users for improving the local offloading of cached content in a multi-hop D2D network. To model the collaborative effect of a set of UEs on content offloading, a cooperative game between the UEs is formulated. For this game, it is shown that the Shapley value (SV) of each UE effectively captures the impact of this UE on the overall content offloading process. To capture the presence of multiple social communities that connect the UEs, a hypergraph model is proposed. Two line graphs, an influence-weighted graph, and a connectivity-weighted graph, are developed for analyzing the proposed hypergaph model. Using the developed line graphs along with the SV of the cooperative game, a precise offloading power metric is derived for each UE within a multi-community, multi-hop D2D network. Then, UEs with high offloading power are chosen as the optimal locations for caching the popular content. Simulation results show that, on the average, the proposed cache placement framework achieves 12, 19, and 21 percent improvements in terms of the number of UEs that received offloaded popular content compared to the schemes based on betweenness, degree, and closeness centrality, respectively. [ABSTRACT FROM AUTHOR]

With an increasing number of machine-type communication devices (MTCDs), machine-to-machine (M2M) communications have attracted great attentions from both academia and industry. Different from traditional communication networks, the data connections with M2M communications are typically small-sized but with high frequency, necessitating the efficiency optimization of both energy consumption and computation. In this paper, we introduce mobile edge computing (MEC) into virtualized cellular networks with M2M communications, to decrease the energy consumption and optimize the computing resource allocation as well as improve computing capability. Moreover, based on different functions and quality of service (QoS) requirements, the physical network can be virtualized into several virtual networks, and then each MTCD selects the corresponding virtual network to access through the embedded-SIM (eSIM) technology. Meanwhile, the random access process of MTCDs is formulated as a partially observable Markov decision process (POMDP) to minimize the system cost, which consists of both the energy consumption and execution time of computing tasks. Furthermore, to facilitate the network architecture integration, software-defined networking (SDN) is introduced to deal with the diverse protocols and standards in the networks. Extensive simulation results with different system parameters reveal that the proposed scheme could significantly improve the system performance compared to the existing schemes. [ABSTRACT FROM AUTHOR]

This paper presents StrLight, the first practical VLC system that leverages widely-deployed string lights to transmit data. The data transmission is imperceptible to human eyes. Users can decode the data by mobile devices (e.g., smartphones) equipped with cameras. StrLight primarily differs from existing VLC systems in using string lights which are composed of a large number of small LEDs and thus the unique design to address practical issues including a special data modulation/encoding scheme, a data representation with unstructured/unknown topologies of LEDs in the string light, and a fault tolerance against broken and blocked LEDs. To the best of our knowledge, StrLight is the first practical VLC system of its kind. We build several prototypes of string light transmitters and test with different smartphone models and a customized mobile device as receivers. The experiment results show that StrLight provides an efficient and robust data broadcasting. A string light of 100 LEDs working in $450 \;\mathrm{Hz}$450 Hz and a camera with a capture rate of $30 \;\mathrm{Hz}$30 Hz and an image resolution of as low as $320 \times 240$320×240 pixels, delivers data rate of $\sim\!1\;\mathrm{kbps}$∼1 kbps , without observable light flickers. [ABSTRACT FROM AUTHOR]

RFID and Wireless Sensor Networks exemplify computationally constrained environments, where the compact nature of the components cannot support complex computations or high communication overhead. On the other hand, such components should support security applications such as message integrity, authentication, and time stamping. The latter are efficiently implemented by Hash Message Authentication Codes (HMAC). As clearly stated in the literature, current approved implementations of HMAC require resources that cannot be supported in constrained components. An approach to implement a compact HMAC by the use of stream ciphering is presented in this paper. [ABSTRACT FROM AUTHOR]

The unreachability problem (i.e., the so-called void problem) that exists in the greedy routing algorithms has been studied for the wireless sensor networks. Some of the current research work cannot fully resolve the void problem, while there exist other schemes that can guarantee the delivery of packets with the excessive consumption of control overheads. In this paper, a greedy anti- void routing (GAR) protocol is proposed to solve the void problem with increased routing efficiency by exploiting the boundary finding technique for the unit disk graph (UDG). The proposed rolling-ball UDG boundary traversal (RUT) is employed to completely guarantee the delivery of packets from the source to the destination node under the UDG network. The boundary map (BM) and the indirect map searching (IMS) scheme are proposed as efficient algorithms for the realization of the RUT technique. Moreover, the hop count reduction (HCR) scheme is utilized as a short-cutting technique to reduce the routing hops by listening to the neighbor's traffic, while the intersection navigation (IN) mechanism is proposed to obtain the best rolling direction for boundary traversal with the adoption of shortest path criterion. In order to maintain the network requirement of the proposed RUT scheme under the non-UDG networks, the partial UDG construction (PUC) mechanism is proposed to transform the non-UDG into UDG setting for a portion of nodes that facilitate boundary traversal. These three schemes are incorporated within the GAR protocol to further enhance the routing performance with reduced communication overhead. The proofs of correctness for the GAR scheme are also given in this paper. Comparing with the existing localized routing algorithms, the simulation results show that the proposed GAR-based protocols can provide better routing efficiency. [ABSTRACT FROM AUTHOR]

How to simultaneously achieve fairness and quality-of-service (QoS) guarantee in QoS-oriented wireless local area networks (LANs) is an important and challenging issue. Targeting at this goal and jointly taking priority setting, fairness, and cross-layer design into account, four scheduling schemes designed for the QoS-oriented wireless LAN mainly based on concepts of deficit count and allowance are proposed in this paper to provide better QoS and fairness. Using multiple deficit count to intertrame space (IFS) and allowance to IFS mappings for different priorities, enhanced distributed deficit round robin (EDDRR) and enhanced distributed elastic round robin (EDERR) schemes are designed to reduce (or even eliminate) possible collisions, while EDDRR with backoff interval and EDERR with backoff interval schemes still keep the backoff procedure but dynamically adjust backoff intervals for non failure events (the events excluding collisions and failed transmissions) depending on the priority setting and deficit count or allowance with a cross-layer design. Through extensive numerical examples, we show that the proposed schemes outperform the closest scheduling schemes in the literature and exhibit much better QoS as well as station-level and flow-level fairness. [ABSTRACT FROM AUTHOR]

The main challenge in wireless sensor network deployment pertains to optimizing energy consumption when collecting data from sensor nodes. This paper proposes a new centralized clustering method for a data collection mechanism in wireless sensor networks, which is based on network energy maps and Quality-of-Service (QoS) requirements. The clustering problem is modeled as a hypergraph partitioning and its resolution is based on a tabu search heuristic. Our approach defines moves using largest size cliques in a feasibility cluster graph. Compared to other methods (CPLEX-based method, distributed method, simulated annealing-based method), the results show that our tabu search-based approach returns high-quality solutions in terms of cluster cost and execution time. As a result, this approach is suitable for handling network extensibility in a satisfactory manner. [ABSTRACT FROM AUTHOR]

A large body of work has theoretically analyzed the performance of mobility-assisted routing schemes for intermittently connected mobile networks, However, the vast majority of these prior studies have ignored wireless contention. Recent papers have shown through simulations that ignoring contention leads to inaccurate and misleading results, even for sparse networks. In this paper, we analyze the performance of routing schemes under contention. First, we introduce a mathematical framework to model contention. This framework can be used to analyze any routing scheme with any mobility and channel model. Then, we use this framework to compute the expected delays for different representative mobility-assisted routing schemes under random direction, random waypoint, and community-based mobility models. Finally, we use these delay expressions to optimize the design of routing schemes while demonstrating that designing and optimizing routing schemes using analytical expressions that ignore contention can lead to suboptimal or even erroneous behavior. [ABSTRACT FROM AUTHOR]

While many interesting dynamic load-balancing schemes have been proposed for efficient use of limited bandwidth and to increase the capacity of congested or hot spots (or cells) in wireless networks, to date, a comprehensive mathematical theory or framework that encompasses all of these schemes does not exist. In this paper, we provide the mathematical theory of dynamic load balancing in cellular networks, which leads to closed-form performance expressions for evaluating the performance of some of the most important dynamic load-balancing strategies proposed in the literature. To the best of our knowledge, this is the first generic theoretical framework that can be used to evaluate the performance of many different dynamic load-balancing schemes with simple closed-form results. The accuracy of the results predicted by the theoretical framework was checked against the simulation results provided in the literature for well-known schemes and an excellent agreement was observed. [ABSTRACT FROM AUTHOR]

This paper addresses when and how to adjust bandwidth allocation on uplink and downlink in a multiservice mobile wireless network under dynamic traffic load conditions. Our design objective is to improve system bandwidth utilization while satisfying call level QoS requirements of various call classes. We develop a new threshold-based multiservice admission control scheme (DMS-AC) as a study base for bandwidth reallocation. When the traffic load brought by some specific classes under dynamic traffic conditions in a system exceeds the control range of DMS-AC, the QoS of some call classes may not be guaranteed. In such a situation, bandwidth reallocation process is activated and the admission control scheme will try to meet the QoS requirements under the adjusted bandwidth allocation. We explore the relationship between admission thresholds and bandwidth allocation by identifying certain constraints for verifying the feasibility of the adjusted bandwidth allocation. We conduct extensive simulation experiments to validate the effectiveness of the proposed bandwidth reallocation scheme. Numerical results show that when traffic pattern with certain bandwidth asymmetry between uplink and downlink changes, the system can reallocate the bandwidth on uplink and downlink adaptively. With the designed bandwidth reallocation scheme in conjunction with the distributed admission control scheme, the QoS requirements of various call classes can be guaranteed under dynamic traffic conditions, and in the meantime, the system bandwidth utilization is improved significantly. [ABSTRACT FROM AUTHOR]

In this paper, the indoor wireless localization problem is addressed both from the theoretical and application standpoints. The main result of this paper is on the theoretical side: the topological definition of regular and irregular nodes is introduced, and formal results are presented to support regularity as a desirable network property for the attainment of precise node localization. In force of this definition, a mixed convex/nonconvex optimization approach has been derived for the solution of the positioning problem. The two procedures, suitably combined, allow the achievement of better convergence toward the best positioning of a multitude of blind wireless nodes. A completely decentralized algorithm is presented, which proceeds locally on each node based on the sole knowledge of the distances measured from, and of the estimated positions of the connected nodes only. Its repeated asynchronous application on each node guarantees the convergence of the algorithm to the positioning of the whole network, even in the presence of a limited number of peripheral reference points, Indeed, no global information is required for the proper functioning of the algorithm. Simulations of relevant case studies have been performed to qualify the proposed scheme in realistic conditions, and the results are presented. [ABSTRACT FROM AUTHOR]

The convergence of heterogeneous wireless access technologies with diverse levels of performance has been envisioned to characterize the next-generation wireless networks. In heterogeneous wireless networks, handoff can be separated into two parts: horizontal handoff (HHO) and vertical handoff (VHO). VHO plays an important role in fulfilling seamless data transfer when mobile nodes cross wireless access networks with different link layer technologies. Current VHO algorithms mainly focus on when to trigger VHO to improve connection QoS but neglect the problem of how one can synthetically consider all currently available networks (homogeneous or heterogeneous) and choose the optimal network for HHO or VHO from all available candidates. In this paper, we present an analytical framework to evaluate VHO algorithms. This framework can be used to provide guidelines for the optimization of handoff in heterogeneous wireless networks. Subsequently, we extend the traditional hysteresis-based and dwelling-timer-based algorithms to support both VHO and HHO decisions and apply them to complex heterogeneous wireless environments. We refer to these enhanced algorithms as E-HY and E-DW, respectively. Based on the proposed analytical model, we provide a formalization definition of the handoff conditions in E-HY and E-DW and analyze their performance. Subsequently, we propose a novel general handoff decision algorithm GHO to trigger HHO and VHO in heterogeneous wireless networks at the appropriate time. Analysis shows that GHO can achieve better performance than E-HY and E-DW. Simulations validate the analytical results and verify that GHO outperforms traditional algorithms in terms of the matching ratio, TCP throughput, and UDP throughput. [ABSTRACT FROM AUTHOR]

Recently, wireless sensor networks featuring direct sink access have been studied as an efficient architecture to gather and process data for numerous applications. In this paper, we focus on the joint effect of clustering and data correlation on the performance of such networks. More specifically, we propose a novel cluster-based data collection scheme for sensor networks with direct sink access (CDC-DSA) and provide an analytical framework to evaluate its performance in terms of energy consumption, latency, and robustness. In our scheme, cluster heads use a low-overhead and simple medium access control (MAC) conceptually similar to ALOHA to contend for the reachback channel to the data sink. Since, in our model, data is collected periodically, packet arrival is not modeled by a continuous random process, and therefore, we base our framework on a transient analysis rather than a steady-state analysis. Using random geometry tools, we study how the optimal average cluster size and energy savings, under the proposed MAC, vary according to the level of data correlation in the network. Extensive simulations for various protocol parameters show that our analysis is fairly accurate for a wide range of parameters. Our results suggest that, despite the trade-off between energy consumption and latency, both can be substantially reduced by a proper clustering design. [ABSTRACT FROM AUTHOR]

This paper focuses on intervehicular networks providing warning delivery service. As soon as a danger is detected, the propagation of a warning message is triggered, with the aim of guaranteeing a safety area around the point in which the danger is located, Multiple broadcast cycles can be generated so that a given lifetime of the safety area is guaranteed, The service is based on multihop ad hoc intervehicular communications with a probabilistic choice of relay nodes, The scenario we consider consists of highspeed streets such as highways in which vehicles exhibit one-dimensional movements along the direction of the road. We propose some analytical models for the study of this service and derive performance indices such as the probability that a vehicle is informed, the average number of duplicate messages received by a vehicle, and the average delay. Moreover, we use the models to discuss system design issues which include the proper setting of the forwarding probability at each vehicle so that a given probability to receive the warning can be guaranteed to all vehicles in the safety area. The analytical results are validated against simulation results. By being very accurate, the models can be instrumental to the performance evaluation and design of broadcasting techniques in intervehicular networks. [ABSTRACT FROM AUTHOR]