In the rapidly urbanizing world, efficient traffic prediction is essential for reducing congestion, optimizing travel times, and enhancing road safety. Traditional machine learning (ML) models have long been used for traffic forecasting but often struggle with unstructured data and capturing the complex temporal and spatio-temporal relationships inherent in traffic networks. Deep learning (DL) models, by contrast, can effectively handle large datasets and learn complex patterns, yet they still demand substantial human expertise for architecture design, hyperparameter tuning, and dataset-specific adaptation. This paper presents a comprehensive review of the evolution of traffic prediction models, highlighting the limitations of ML and DL approaches and introducing Automated Machine Learning (AutoML) as a promising solution. We discuss how AutoML can automate key stages of the ML pipeline—including data preprocessing, feature engineering, model learning, and model updating—reducing the need for human expertise, improving generalizability, and enabling model adaptation across datasets. While some studies have integrated AutoML components into traffic prediction tasks, a fully automated, end-to-end pipeline remains an open research challenge. This review identifies current gaps, explores AutoML’s potential to address these challenges, and outlines future directions for advancing traffic prediction through AutoML.

Indoor positioning systems (IPSs) allow the location and tracking of mobile devices in indoor environments where the global positioning system (GPS) does not provide satisfactory results. In model-based IPSs, it is common to use signal propagation models to estimate distances between anchor nodes and mobile devices using the received signal strength indicator (RSSI). However, using fixed parameters in the path loss model to characterize the signal in large-scale scenarios results in the degradation of the positioning accuracy. In this article, we propose the adaptive model (ADAM) positioning system, a model-based IPS that chooses the best anchor nodes to benefit the positioning computation and uses different parameters for the log-distance model to represent the signal in different regions and conditions of the scenario. Then, we estimate a single, more precise position using a data fusion technique. Our proposal does not require training nor prior knowledge of the best parameters for each region. We evaluated the performance of our proposed system in a real-world, large-scale environment using Bluetooth-based mobile devices. Our results clearly show that ADAM can locate mobile devices with an average error of 2.93 m in relation to the real position, which is 23% better than literature-based models using fixed parameters for the entire environment.

In today’s world, interconnected Vehicular ad-hoc networks (VANET) and intelligent transportation systems have become more popular. Although IoV can bring many benefits for the smart cities and provide comforts for the passengers, however, the increasing needs for keeping the QoS and QoE at an acceptable level in time sensitive applications seems crucial and needs to be investigated deeply. Also, allocating the right number of resources to avoid congestions and fill the deficiencies in a distributed manner is a challenging issue. So, with the increase in users, attention must be given to Quality of Service (QoS) and resource allocation. As the vehicle network provides information to provide safety, comfort, and entertainment to drivers and passengers, they are one of the most compelling research topics in intelligent transportation systems. TDMA protocol is used in this study to increase the efficiency of the network and the quality of service it provides. To solve the synchronization problem, the Markov method predicts the size of slots and frames. The scenario field is used in the Markov application section to better predict TDMA gaps on solving the synchronization problem. Accordingly, the higher the quality of service, the lower the latency of the network, and the better the allocation of resources. Optimizing allocation and quality of service is further motivated by reducing collision between packets. In terms of its implementation, this method is divided into two components, the first being the database proposal for constructing the Markov matrix and the second being the simulation on VanetMobisim and implementation of the network in NS2. The proposed method performed better in different scenarios in terms of computational complexity, PDF, latency, and overhead, as shown in the results section.

Hovering Information and Floating Content are two sub-domains of information dissemination which aim to keep information persistent in a region where vehicle to vehicle (V2V) communication is the only option. In this mutual goal to keep information alive, both sub-domains have sought to design algorithms that overcome the geographical and technological challenges while maintaining efficient resource management. Techniques have arising which stem from flooding and broadcasting techniques, probabilistic communication, and using machine learning to direct communication. This work will examine the state-of-the-art works within both sub-domains to bring the reader to a respectable level of knowledge, and offer insight into the future directions research in the area may take.

Traffic forecasting at appropriate times is vital for a variety of urban traffic control applications. There are a plethora of factors that can severely affect the performance of such forecasting models, especially those unpredictable events that cannot be learned through previous time steps in the model. One of the important factors that can change the traffic flow pattern abruptly, is accident occurrence. This issue affects more when the severity of the accident is high which would lead to a complete anomaly behavior in the traffic flow pattern. In this paper, we detected the approximate time that the accidents happen through anomaly detection around the accident record and then pulled out the ones that change the traffic pattern suddenly. To predict the traffic flow after a severe accident, we propose a hybrid CNN-LSTM model that takes spatio-temporal matrices as discrete time sequences for each accident. Furthermore, we leverage distances between neighboring nodes and accident location, coupled with static features that are pertained to the accidents. Moreover, we evaluate our model on PeMs dataset which is enhanced with the static features of the accidents from Moosavi’s accident data set [1] [2]. Despite recent trials that are not able to forecast the results when an anomaly event happens, our results demonstrate that our proposed model can learn traffic patterns after the accidents and predict the traffic flow more accurately compared to current models.

The use of contextual data to suggest distinct types of routes helps to understand new aspects of a city that may change the perception of drivers about routes. The impact of these aspects may differ from driver to driver requiring a way to change the suggestion according to the driver's point of view. Therefore, this paper presents an approach that identifies distinct situations in multiple types of contextual data and proposes a personalized and context-aware vehicle rerouting service called PONCHE. It considers common characteristics found in every dataset of spatiotemporal data to overcome the necessity of processing specific aspects of distinct data types. Regarding personalized service, each driver's profile is reflected into contextual data type weights considered by the system, i.e., the intensity he/she wants to avoid a contextual region. With that, a driver's profile may ignore a determined contextual data type. Performance evaluation results show that PONCHE identifies the best routes according to the weights given by a driver. It also improves the quality of contextual information obtained according to traffic, crime, and vehicle crashes. This study takes into consideration contextual data from Austin and Chicago in the USA, enabling comparison with two distinct cities.

Driving simulators play an important role in vehicle research. However, existing virtual reality simulators do not give users a true sense of presence. UniNet is our driving simulator, designed to allow users to interact with and visualize simulated traffic in mixed reality. It is powered by SUMO and Unity. UniNet's modular architecture allows us to investigate interdisciplinary research topics such as vehicular ad-hoc networks, human-computer interaction, and traffic management. We accomplish this by giving users the ability to observe and interact with simulated traffic in a high fidelity driving simulator. We present a user study that subjectively measures user's sense of presence in UniNet. Our findings suggest that our novel mixed reality system does increase this sensation.

An increasing number of users have been adopting route recommendation systems, mostly motivated by the convenience that those systems bring to their traffic experiences. Usually, those systems observe the historical and current traffic conditions in order to evaluate and recommend the fastest routes. However, besides mobility aspects, more contextual information such as unplanned street events and neighborhood safety, are not taken into account in the recommendation process. With this in mind, we propose a platform to support context-aware route recommendation systems. The proposed platform aims to improve existing recommendation algorithms or enable the proposal of new ones. To assess it, we use datasets of routes suggested by Google Maps in the city of Curitiba, Brazil, official open data provided by the city and also data generated voluntarily by citizens in a participatory sensing fashion. Our results show the existence of an opportunity for route planners to provide personalized services to users, which is an important step towards the development of context- aware vehicular networks. Besides, these results illustrate how publicly available big data can be explored to improve context-aware route recommendations.

The constant sharing of information among vehicles is of vital importance to provide different types of service in Intelligent Transportation Systems (ITS). Typically, ITS apply the sharing benefit to carrying out tasks such as extracting knowledge of vehicle traffic conditions and its distribution. The ITS that use this approach are able to perform the knowledge distribution, however, they lack of mechanisms to select the most appropriate vehicles to do so. It is common, in these systems, such tasks are performed by all vehicles. Consequently, it could easily cause a network overhead because of the highly redundant knowledge about the traffic that is being transmitted. With this in mind, we propose a system for information management and knowledge distribution named TRUSTed. The proposed system applies the egocentric betweenness measure to select the most relevant vehicle to carry out such tasks. Simulation results have shown that TRUSTed outperforms other systems found in the literature in several requirements.

Greedy Forwarding technique is an attractive approach used by most geographic routing algorithms to forward packets to the node that is geographically closer to the destination node. However, this strategy requires all sensor nodes to know their physical location which is not always possible in forest scenarios and in most cases is not able to overcome routing holes. In this work, we propose a Novel RSSI-based Algorithm that performs data aggregation and is able to overcome routing holes in WSNs called LRS (Long-Range SINK). Our algorithm considers the existence of a long-range sink so that in a single hop it is possible to reach the whole network. Our algorithm takes advantage of the Received Signal Strength Indicator (RSSI) of the nodes to enable the construction of routing path toward the sink. Our results clearly show that the proposal has high delivery rates in scenarios with routing holes with all of the benefits of a greedy forwarding technique.

Urban mobility becomes one of the most challenging issues in large urban centers, since traffic congestion is a daily problem. In order to address this issue, a number of researchers, from both academia and industry, have studied several Traffic Management Systems (TMS) approaches to improve urban mobility. However, the existing approaches do not consider an essential factor: the population information. Within this context, this work proposes a new approach, called APOLO, that employs historical knowledge of mobility patterns of the drivers to obtain a global view of the road network. APOLO is different from others research approaches that need constant information exchange among the vehicles and the central server in order to obtain a global view of road traffic condition. These existing approaches can lead to network overload and have a high data processing cost in real-time. Results show that APOLO improves vehicles' mobility compared to well-known approaches, which indicates that APOLO could be a potential alternative for providing TMS services with valuable mobility knowledge.

Location-awareness plays an important role in Wireless Sensor Networks (WSNs) by aiding in tasks such as packet routing, event mapping, and energy savings. The use of Global Positioning System (GPS) on sensor nodes is not always viable due to a number of issues, e.g., power constraints. Location estimation solves the problem of computing sensor node positions by using information from devices that can house a GPS module, e.g., a mobile sink. However, GPS error may affect the accuracy of position estimations. In this paper, we propose a range-based scheme that uses trilateration and also handles GPS error. The proposed approach takes advantage of sink beacons used in packet routing. These beacons are used as position packets in order to estimate the position of nodes while reducing network overhead. However, a mobile sink poses issues when used as a source of position packets. Therefore, we propose Position Distance, Circle Limit and a Hybrid version of the algorithms in order to decide on the best position packets from the sink to be used in trilateration. An extensive set of performance evaluation experiments is conducted and results show that the proposed algorithms can improve position estimation accuracy, while sustaining acceptable packet delivery ratio and reducing network overhead.

Efficient and reliable data dissemination is crucial to most of the vehicular network applications. However, the inherent vehicular network characteristics make data dissemination a challenging task. Typically, the existing algorithms generate too many redundant packets that saturate the network, thus causing frequent channel contention and packet collisions. To tackle these problems we propose an Efficient Encounter-based Event Dissemination Protocol. By exploiting the distance and the encountering probability of the vehicles to the event, the proposed protocol is capable of performing an efficient data dissemination in both urban and highway scenarios. An extensive set of simulation experiments was conducted to evaluate the performance of the proposed algorithms. Results showed that the proposed protocol outperforms the selected approaches in terms of retransmission packets and delivery ratio.

Ego-network concept has been systematically studied, since this kind of network employs only locally available information to analyze its structure. Degree, closeness, and betweenness are widely studied centrality measures. Among the three measures presented, betweenness centrality in ego-networks is the most used in several fields such as Wireless Mesh Networks, Wireless Sensor Networks, and Delay Tolerant Networks. However, surprisingly, that measure has not been largely investigated in Vehicular ad hoc Networks (VANETs). In this paper, we contribute to filling this gap by designing and implementing the egocentric betweenness measure in VANETs, besides we compare it to the sociocentric betweenness measure.

Understanding traffic conditions, in an urban environment, by means monitoring or/and predicting is not an easy task. In Intelligent Transportation Systems, the reliable vehicle route prediction has meaningful application value. Vehicle route prediction can increase the variety of VANETs applications such as predicting traffic situation ahead, optimal route recommendation, driver assistant, and automatic vehicle behaviors. Due to the challenge imposed by the vehicle route prediction and its wide application, researchers in both industry and academia have focused their efforts on this area. In order to explore this area, this paper describes an approach to predict the vehicle's future path in a realistic urban scenario. For that, it employs a hidden Markov model along with the outcome of the Viterbi algorithm to make a probabilistic prediction. The parameters modeling is estimated based on information extracted from the travel route dataset and computed in an offline manner. In the online phase, the routes prediction is carried out. Our approach has high accuracy rate according to the numerical simulations results. Moreover, we believe that the VANETs applications previously mentioned can take advantage of our approach.

Several Intelligent Transportation Systems (ITS) rely on localization to enable services ranging from comfort to safety applications. Following this same idea, the use of Dedicated Short Range Communications (DSRC) devices based on the IEEE 802.11p standard, and the Vehicular Ad Hoc Networks (VANETs) paradigm, have resulted in the deployment of several protocols, services and applications that need different localization accuracy levels. The most common solution for localization is based on Global Navigation Satellite Systems (GNSS). GNSSs have problems of unavailability in dense urban areas, tunnels and multilevel roads. Moreover, GNSS have errors in the range of 5-15 meters. These unavailability and error problems are not acceptable for several VANET and ITS safety applications. In this work, we investigate and characterize the GNSS problems of error and unavailability based on datasets of real GNSS devices installed in vehicles and develop a Geodesic Dead Reckoning solution to overcome the GNSS unavailability issue.

Some Inherent Vehicular Ad Hoc Networks (VANETs) characteristics, such as intermittent connectivity, highly dynamic topology, and hard delay constraints, make data communication a challenging task in these networks. Due to such peculiarities, in this work we study the impact of using vehicles predicted locations as a metric for data communication in VANETs. In our proposal, called LPRV (Localization Prediction-based Routing for VANETs), packet forwarding is performed by nodes with predicted future localization closer to the delivery destination, without the need for exchanging additional control message. The proposed algorithm also explores the knowledge of a digital map to limit the scope of message exchanges in the shortest path for vehicles between source and destination. We compared our proposal to both classic Flooding and SIFT (Simple Forwarding over Trajectory) algorithms. Our results clearly demonstrate the efficiency of the proposed solution in different scenarios, especially in terms of delivery rate, number of hops and delay, with a reduced number of message transmissions.

Localization systems play a major role in many applications for Vehicular Ad Hoc Networks (VANets). Although Data Fusion techniques can provide reliable localization information for most of the application requirements in VANets, enhancements on the localization systems are required and desirable. Unique characteristics of VANets such as mobility constraints, driver behavior, and high speed displacement nature of vehicles cause rapid and constant changes in the network topology, leading to the dissemination of outdated localization information. To circumvent this problem, an alternative is the use of predicted future locations of vehicles. The main idea of this approach is to use the localization prediction as an extension of a Data Fusion localization system. In such approach, a future position of a car is predicted for a given future time step and used to take advantage of a future time-space window of a vectorial trajectory rather than a static localization point. Thus, in this paper we further discuss this subject by analyzing the use of localization prediction as natural way to improve applications for VANets. We present a set of experiments that shows the results of such techniques when applied to a realistic VANet scenario.

In recent years, the consumption of electricity has increased considerably in the industrial, commercial and residential sectors. This has prompted a branch of research which attempts to overcome this problem by applying different information and communication technologies, turning houses and buildings into smart environments. In this paper, we propose and design an energy saving technique based on the relationship between the user's activities and electrical appliances in smart home environments. The proposed method utilizes machine learning techniques to automatically recognize the user's activities, and then a ranking algorithm is applied to relate activities and existing home appliances. Finally, the system gives recommendations to the user whenever it detects a waste of energy. Tests on a real database show that the proposed method can to save up to 35% of electricity in a smart home.

This work proposes an intelligent decision system for a residential infrastructure based on wireless sensors and actuator networks, called ResiDI. ResiDI is equipped with battery-powered nodes to ensure that they are deployable anywhere in the house without the need for wiring, drilling or any pre-existing infrastructure. The key intelligence of ResiDI is distributed in the decider nodes, which are able to make decisions locally without the need to send traffic from the sensor nodes to the sink. The network intelligence core is based on a neural network that seeks to improve the accuracy of the decision-making, together with a temporal correlation mechanism that is targeted at reducing the energy consumption. When compared with an approach adopted in the literature, the results show that ResiDI is efficient in different scenarios in all evaluations performed.

An addition to the target tracking application is the presence of a tracker that aims to intercept the target. The WSN provides the position of the target to the tracker, so that it can move towards the target. The objective is to reach the target in the shortest possible time, using the fewest number of nodes to save energy. In this paper, we propose and evaluate a Tracking Algorithm for Target Interception in face-structured sensor networks (TATI). TATI reduces the number of active nodes, activating only the faces that are feasible to be achieved by the target until the next sampling. Furthermore, the algorithm uses the nominal communication range of the nodes to shorten the route of the tracker. Simulation results show that TATI can save up to 15% in energy consumption, and it can keep the tracker around 10 meters closer to the target compared to the baseline.

In recent years, we have witnessed a growing interest in Vehicular Networks from both the research community and industry. Several potential applications of Vehicular Networks are envisioned such as road safety and security, streaming services, traffic monitoring and driving comfort, just to mention a few. It is critical that the existence of convenience or driving comfort services do not negatively affect the performance of safety services. In essence, the dissemination of safety services or the discovery of convenience applications require the communication among service providers and service requesters through constrained bandwidth resources. Therefore, service discovery techniques for vehicular networks must efficiently use the available common resources. In this paper, we present a bandwidth-efficient and scalable hybrid adaptive service discovery protocol (VSDP) for Vehicular Networks. VSDP aims at providing high success ratio while guaranteeing low response time and good scalability when the number of requests increases. Our proposed protocol finds the service provider and its routing information simultaneously which results in overall bandwidth savings. It uses diverse channels to exchange discovery and routing packets, thereby decreasing the congestion on single channels and decreasing the delay of service discovery. Our proposed service discovery protocol adapts the advertisement zone size of service providers based on an efficient adaptation mechanism that takes into consideration network condition and application requirements. The adaptation process is based on an adjustment technique and a prediction technique. We discuss the implementation of our protocol, present its proof of correctness as well as the performance evaluation through an extensive set of simulation experiments and using different mobility models. Our results show the scalability of our protocol. They indicate that our techniques can achieve significant success rate (more than 90 percent), while guaranteeing low response time (in the order of milliseconds) and low bandwidth usage when compared to existing service discovery techniques.

Image-Based Rendering (IBR) has become widely known by its relatively low requirements for generating new scenes based on a sequence of reference images. This characteristic of IBR shows a remarkable potential impact in rendering complex 3D virtual environments on graphics-constrained devices, such as head-mounted displays, set-top boxes, media streaming devices, and so on. If well exploited, IBR coupled with remote rendering would enable the exploration of complex virtual environments on these devices. However, remote rendering requires the transmission of a large volume of images. In addition, existing solutions consider limited and/or deterministic navigation schemes as a means of decreasing the volume of streamed data. This article proposes the PRO gressive PAN orama Str E aming protocol (PROPANE) to offer users a smoother virtual navigation experience by prestreaming the imagery data required to generate new views as the user wanders within a 3D environment. PROPANE is based on a very simple yet effective trigonometry model and uses a strafe (lateral movement) technique to minimize the delay between image updates at the client end. This article introduces the concept of key partial panoramas, namely panorama segments that cover movements in any direction by simply strafing from an appropriate key partial panorama and streaming the amount of lost pixels. Therefore, PROPANE can provide a constrained device with sufficient imagery data to cover a future user's viewpoints, thereby minimizing the impact of transmission delay and jitter. PROPANE has been implemented and compared to two baseline remote rendering schemes. The evaluation results show that the proposed technique outperforms the selected and closely related existing schemes by minimizing the response time while not limiting the user to predefined paths as opposed to previous protocols.

It is crucial to achieve Quality of Service (QoS) on IEEE802.11 in order to provide stable and reliable communication for real time and multimedia applications. Most of the recent QoS techniques for Ad Hoc Networks rely on basic QoS classifications such as Enhanced Distributed Channel Access (EDCA) and Hybrid Coordination Function Channel Access (HCCA) with stationary backoff range for specific services, without considering overall resource consumption and the external correlation among terminals. In this paper, a novel contention window adjustment QoS scheme, as a special case of QoS classification, is proposed for achieving QoS-fairness on Ad Hoc Networks. It applies dynamic automatic QoS assignment with low complexity by considering the restriction among various terminal requirements. Throughput estimation with a proportional relation between throughput and backoff parameters is discussed based on a Markov chain model of a saturated Ad Hoc Networks. We measure the performance of different QoS algorithms theoretically and verify improvements of our algorithm on QoS-fairness with detailed simulations.

Transmission Control Protocol (TCP) is well-known for its poor performance over wireless networks. The main reason is the unstable condition of wireless networks. Previous attempts to improve TCP performance have been centered on techniques such as queue management, congestion window adjustment, delayed acknowledgement, and etc., because lower layers are hidden in the layered Open Systems Interconnection (OSI) model. With cross layer techniques, more precise data can be retrieved from lower layers for network condition estimation. In this paper, we analyze and model the factors that affect the TCP throughput in the lower layers. Consequently, to solve the TCP optimization problem, we formulate TCP performance as a Markov Decision Process (MDP). An extensive set of simulation experiments has been performed on NS-2 in order to illustrate that TCP performance can be enhanced by cooperatively adjusting lower layer factors.

One of the most challenging issues facing vehicular networks lies in the design of an efficient MAC protocol adaptable to different traffic scenarios (urban and suburban environments). While each environment has its own characteristics leading to different challenges, the merit of this paper lies in developing a MAC protocol suitable for both. In this work, we propose an efficient Multichannel QoS Cognitive MAC solely dedicated for Vehicular Environments (MQOG). MQOG incorporates efficient channel negotiation on the dedicated control channel whereas data is transmitted on other channel without contention. Since vehicular environments are widely known to suffer from interference and multipath, MQOG assesses the quality of channel prior to transmission employing a dynamic channel allocation and negotiation algorithm to achieve significant increase in channel reliability and throughput. The channel assignment problem was solved in an integrated manner while taking into account the QoS of different frames(Safety and NonSafety. The uniqueness of this protocol lies in making use of the ISM Band and UNII-3 in case all available channels in DSRC were considered unreliable. The proposed protocol was implemented in OMNET++ 4.1 and extensive experiments demonstrated that the proposed MAC ensures the reception of safety messages much faster, more efficient and reliable than other existing VANet MAC Protocols.

Video streaming capabilities over Vehicular Ad Hoc Networks (VANETs) are crucial to the development of interesting and valuable services. However, VANETs are a challenging environment to this kind of communication due to the dispersion and movement of vehicles. In this work, we present a feasible solution to this problem. The VIdeo Reactive Tracking-based UnicaSt protocol (VIRTUS) is a receiving-based solution that uses vehicles' current and future location for a selection policy of relaying nodes. It fulfills video streaming requirements without incurring into an excessive number of transmissions. Besides that, it outperforms other baseline solutions.

Transmitting video content over Vehicular Ad Hoc Networks (VANETs) faces a great number of challenges caused by strict QoS (Quality of Service) requirements and highly dynamic network topology. In order to tackle these challenges, multipath forwarding schemes can be regarded as potential solutions. However, route coupling will severely impair the performance of multipath schemes. In this work, we present a LocatIon-Aware multIpaTH videO streamiNg (LIAITHON) scheme to address video streaming over urban VANETs. LIAITHON uses location information to discover two relatively short paths with minimum route coupling effect. The performance results have shown it outperforms the underlying single path solution as well as the node-disjoint multipath solution.

Due to the mobile nature of nodes comprising the vehicular networks in addition to interference and congested network traffic, the design of an efficient MAC network becomes challenging. Moreover, the latency constraints underlying safety application add complexity to this design. The TXOP (Transmit Opportunity) mechanism defined in the IEEE 802.11e is optimized to meet the requirements of a Multimedia Network (voice and audio) but not a vehicular network thus making it unsuitable to be used in a VANet environment. On the other hand, existing MAC algorithms for VANets are designed to overcome some challenges overlooking others. Hence, the merit of this paper lies in developing a MAC mechanism that incorporates in an integrated manner various VANet's challenges while modifying the 802.11e TXOP to meet vehicular conditions. In this work, we propose MoByToP (Mobility Based Dynamic TXOP for VANets). MoByToP is an enhancement mechanism added to the MAC layer to extend the operation of the medium reservation phase. The uniqueness of MoByToP lies in designing a dynamic TXOP to incorporate mobility and QoS (Quality of Service) while considering the transmit data rate of the source vehicle. The proposed protocol was implemented in OMNET++4.1 and extensive experiments demonstrated that the proposed MAC with MoByToP mechanism ensures the reception of QoS messages much faster, more efficient and reliable than existing VANet MAC protocols.

Vehicular Ad Hoc Networks (VANETs) are challenging environments for video dissemination since stringent requirements have to be satisfied. We have designed a protocol that is reactive to the dynamic topology of VANETs, adaptive to the non-uniformity of vehicles density throughout a city or a highway and that deliver packets in time for the playback of video frames. The Reactive, Density-Aware and Timely Dissemination protocol (REACT-DIS) was able to achieve low end-to-end latency with an acceptable number of transmissions. In order to meet delivery ratio requirements, we have used Network Coding to implement an additional redundancy control aimed at handling packet loss. By this manner, lower rates of frame loss were achieved which fulfill delivery ratios requirements for video-streaming while maintaining suitable levels of end-to-end latency and overhead.

Reliable, fast and energy-efficient data dissemination is one of the essential features for several applications in wireless sensor networks (WSNs). In the dawn of WSNs, data delivery techniques considered only static data sinks. However, static sink approaches place a considerable burden on sensor nodes surrounding the sinks in terms of traffic and energy consumption. Eventually, data dissemination techniques for WSNs with mobile sinks have been proposed to alleviate the traffic issues of static sink approaches and improve network lifetime. In this paper, we propose a new data dissemination strategy that combines a simple but efficient sleep schedule technique with a trail generation mechanism. Simulation results show that the proposed E-TRAIL protocol significantly improves network lifetime while maintaining similar data delivery success performance when compared to the selected approaches.

Advancements in both on-board and wireless communication technologies provide the necessary backbone for the deployment of a network between vehicles. Most of the envisioned applications for these networks would be greatly favored by multimedia support provisioning. However, there are several issues to be handled in order to provide multimedia services with reasonable quality. In this work, we analyze a specific multimedia service that can be used by several interesting applications: video broadcasting. Particularly, we throughly discuss and evaluate the role of redundancy in improving this service. We have verified that although redundancy does increase the effectiveness in video broadcasting, coding techniques do not improve redundancy's efficiency.

The increasing number of potential applications related to intelligent transportation systems (ITSs) have attracted researchers to the area of vehicular networks (VNs). Two main classes of applications have lately gained popularity, i.e., security and safety, and traffic information and service location applications. However, several open research challenges are delaying the efficient and widespread deployment and management of such applications in VNs. One of these challenges comprises how vehicles and service providers could discover each other in VNs, which are well known for their large scale and high mobility. Most service discovery strategies available present high overhead and poor performance in a VN environment. Existing context-aware and location-based service discovery protocols (LocVSDPs) are either designed without considering the particularities of VNs or are not scalable with the increase in network density and the number of requests. In this paper, we propose a new context-aware and LocVSDP (EB-LocVSDP) for VNs and its variant (Naive-LocVSDP). Our protocols offer a scalable framework for the discovery of time-sensitive and location-based services in VNs. They rely on a cluster-based infrastructure. Furthermore, LocVSDPs are integrated into the network layer and use channel diversity to improve service discovery efficiency. We discuss the implementation of our protocols and techniques, report on performance evaluation experiments, and offer a comparison against an existing location-based discovery protocol [the Vehicular Information Transfer Protocol (VITP)]. Our simulation results indicate that our proposed LocVSDPs show a gain of 20% in terms of success rate. LocVSDPs use at least 90% less bandwidth than VITP, and their average response time is at least 10% lower than VITP for successful query transactions.

Recent studies on service discovery protocols in vehicular networks have shown promising results. However, very little work has been reported on how to integrate the fault tolerance feature into these mechanisms. This feature is vital for the success of the deployment of service discovery protocols in vehicular networks. Drivers on their cars should not have their requests dissatisfied or their connections dropped because a service provider or some components between the service provider and the service requester have failed. In this paper, we present a fault tolerant location based service discovery protocol for Vehicular Networks. The main advantages of our protocol is its ability to tolerate service providers failure, communication links failure and roadside routers failure. We present our fault tolerant protocol, and report on its performance evaluation. Our simulation experiments show that our proposed fault tolerant LocVSDP algorithm improves the success rate significantly over the basic LocVSDP. In fact, the success rate is improved in the roadside routers failures scenario and in the links failures scenarios by 50 percent and 30 percent respectively.

Though wireless networks provide great convenience to mobile users, they also give rise to non-trivial concerns about the security due to open channels and flexible mobility. An important concern is the securing of a communication link between any pair of nodes. Here, data encryption is deemed the primary solution to protect data confidentiality and integrity. However, the issue of traditional cryptographic techniques' application in wireless and mobile networks is significant to improve the performance of networks. In this article, we propose a hybrid encryption algorithm to deal with the applications of symmetric key and asymmetric key in wireless ad hoc networks. In particular, a public key is used as an authentication method to validate the identity of a legitimate node and to prevent unwanted parties from obtaining unauthorized data and resources. Our performance comparison shows that our proposed schemes have reasonable computational costs and communication overhead, provide reliable security, and at the same time, improve the efficiency of cryptographic techniques. In this way, our simulation results indicate that our algorithm is effective and practical for the data protection in wireless and mobile networks.

In recent years, vehicular networks have been widely studied because these networks become an important part of wireless metropolitan networks. This type of wireless network is different from other conventional wireless mobile networks since the mobile nodes in the networks usually have high speed, sufficient power and dynamic topology. In vehicular networks, vehicles can connect with access points, which are deployed on the roadside, to communicate with their correspondent nodes through Internet. However, the radio range of antennas which are installed in vehicles and access points are limited. As a result, to maintain connections during the trips, vehicles have to switch their access points frequently. The question of how to design an efficient mobility management solution for vehicular networks is still very important in such mobile environment. In this paper, a novel mobility management scheme for vehicular networks is proposed. Network mobility solution is adopted for vehicular networks and intra-cluster communications are used to improve the quality of the mobility.

A considerable number of Vehicular Network (VN) applications have been developed recently. These applications range from security and safety to traffic information and service location. However, several research challenges remain open concerning efficient service discovery in large scale VNs. Most of the existing service discovery strategies present high overhead and poor performance when applied to VNs. Furthermore, existing context-aware and location-based service discovery protocols are either designed without considering the particularities of VNs or are not scalable with the increase of network density and number of requests. In this paper, we present novel context-aware and location-based service discovery protocols (Election-Based LocVSDP and Naive LocVSDP) that offer a scalable framework for the discovery of time-sensitive and location based services in large scale VNs. We conduct a concrete set of simulation experiments to evaluate the performance of our techniques and compare the results with an existing location-based discovery protocol (VITP). Simulation results indicate that our techniques outperform the VITP protocol in terms of success rate, average response time and bandwidth usage. In essence, both LocVSDP protocols show a gain of 20 percent in terms of success rate, use at least 90 percent less bandwidth than VITP and their average response time is at least 10 percent lower than VITP for successful query transactions.

The recent advances and wide availability of wireless access technologies and inter-vehicle communication systems are expected to culminate in the integration of different wireless networks such as the IEEE 802.11, 3G/4G, and WiMax, multimedia and sensor networks in the next generation vehicular networks. However, due to high mobility of vehicles, several issues remain to be resolved before real-time multimedia based applications over VANETs become a reality. In this paper, we propose to study the provision of multimedia support in VANET, and present an efficient Path Stability Protocol, which we refer to as PASTA, as an additional module to MAC layer protocols that aims at preventing path breaks between vehicles that are frequently within reach of each other but not necessarily on a continuous basis. We discuss the implementation of our protocol, and report on its performance evaluation using a wide range of realistic scenarios. Our results indicate that our PASTA protocol decreases significantly the end-to-end latency as well as the network jitter.

Recent advances in Intelligent Transportation Systems (ITS) and the growing number of applications in Vehicular Networks (VN) have attracted many researchers. Applications in Vehicular Networks comprise but are not limited to safety applications and convenience applications. Deploying Vehicular Networks widely cannot be accomplished without overcoming the existing research challenges in such networks. Service discovery is one of the main challenges in Vehicular Networks which are characterized by their large scale and high mobility. Existing service discovery techniques for ad hoc networks cannot be applied directly to Vehicular Networks scenarios due to their poor performance and decreased efficiency in Vehicular Networks. In this paper, we present our location-based service discovery protocol for Vehicular Networks (LocVSDP). Our protocol permits the discovery of location-aware and time-sensitive services in Vehicular Networks. Moreover, our LocVSDP protocol improves service discovery efficiency by integrating service information into the network layer and using diverse channels. In our protocol, we present our efficient mechanism that permits to service requesters to find service providers and their routing information simultaneously, which results in overall bandwidth savings. We make use of diverse channels for the exchange of discovery and routing packets, which decreases the congestion on single channels and improves the delay of service discovery. Then, we present our efficient location-based request propagation and an efficient computation of the service reply, based on the specified location of the requested service in the drivers request. We discuss the implementation of our protocol and present its proof of correctness.

In next generation mobile heterogeneous networks, WiFi-based wireless networks are becoming important components, because WiFi devices are widely used in laptops, PDAs and other mobile computing machines. In a WiFi-based wireless network, handoff management is a key service, as the radio range of the WiFi device is limited. Moreover, providing seamless roaming in wireless networks is mandatory for supporting realtime applications in a mobile environment, such as VoIP, online games, and eConference. Recently, many solutions have been introduced to reduce MAC layer handoff latency; however, these solutions consider every mobile node separately, which would not be suitable for a large-scale environment. This paper proposes a novel MAC layer handoff protocol for large-scale WiFi-based wireless networks to support seamless real-time applications. In our scheme, before the mobile node starts initiating the MAC layer handoff process, it selects several neighboring nodes to help it scan available channels. All channels are divided into groups and scanned by these neighbors separately. Therefore, the number of scanning channels in each node is reduced, and scanning latency is minimized. According to simulation results in ns2, we conclude that our scheme can shorten MAC layer handoff latency greatly, and also achieve seamless handoff in terms of loss ratio of data packets.

Existing localization schemes in wireless ad hoc networks rely on redundant measurements from multiple devices with known positions in order to reduce error. However, when node density is high this can result in excessive localization messages with minimal improvement on position accuracy. In this work we present a scheduling algorithm to select a subset of active reference nodes to be used in localization, which has the effect of reducing message overhead, increasing network lifetime, and improving localization accuracy in dense mobile networks. We investigate the Cramer-Rao Lower Bound (CRLB) and existing single-hop localization techniques to determine the optimal average node density to ensure sufficient estimation accuracy. The correctness and effectiveness of the proposed scheme is evaluated through extensive simulation results, which show that in dense networks localization messages are greatly reduced and network lifetimes are more than doubled, while maintaining high estimation accuracy. Furthermore, computational time of localization algorithms is reduced, which effectively decreases accumulated error due to computation latency when locating a mobile device.

In recent years, Worldwide Interoperability for Microwave Access (WiMAX) has become an important technology providing wireless connections for mobile terminals in a wireless Metropolitan Area Network (MAN), due to its large radio range. In a MAN environment, wireless clients always have high mobility; therefore, it is possible that the mobile clients will move away from the service coverage of serving base stations and change their associating base stations. The process of switching between different base stations is known as the handoff process. During the handoff process, the connection between the mobile terminal and the serving base station ceases. The quality of mobile wireless networks is significantly affected by handoff latency and packet loss ratio. In this paper, we propose a fast handoff scheme using mobility patterns for WiMAX networks. Mobility patterns are adopted to predict the next base station and therefore waive unnecessary scans, and the serving base station forwards the data packets received during the handoff process to the target base station for the minimizing of the packet loss ratio. Extensive simulation experiments are conducted to evaluate the performance of the proposed scheme. The results demonstrate that our scheme can shorten the handoff latency.

WiFi-based wireless networks are important components in next generation mobile heterogeneous networks, as WiFi devices are widely used in laptops, PDAs and other mobile computing machines. During the movement, mobile clients have to switch their associated access points because the wireless transmission range is limited in a WiFi network. The process of switching access points is called handoff. Handoff management is a key service in mobile networks, because providing seamless roaming in wireless networks is mandatory for supporting realtime applications in a mobile environment, such as VoIP, online games, and eConference. Many solutions have been introduced to reduce MAC layer handoff latency; however, these solutions do not consider secure authentications, which would not be suitable for real scenarios. During the handoff procedure, mobile clients should pass the authentication to prevent security attacks. In this paper, we propose a fast authentication scheme for WiFi networks to reduce authentication latency during the handoff. In the meanwhile, the packet loss ratio is also minimized to support seamless roaming.

Recent advances in wireless communications and the availability of Heterogeneous Wireless and Mobile Networks (HWMNs) have enabled the development of interesting applications. The main objective of HWMNs is the delivery of wireless services to potential applications in personal, local, campus, and metropolitan areas. However, in these networks, there is a need of gateway discovery mechanisms that will support several of these HWMN applications. It is essential that the deployment of a gateway discovery protocol in HWMNs does not degrade the performance of existing applications in terms of bandwidth usage. Any gateway discovery approach in HWMNs is highly susceptible to this issue, due to the limited bandwidth. In this paper, we present a novel gateway discovery technique for HWMNs. Our protocol aims at providing an efficient hybrid adaptive location-aided gateway advertisement and discovery mechanism for HWMNs. Essentially, the originality of ou technique lies in its unique and novel characteristics: (i) it is built on top of the network layer; (ii) it uses channel diversity; (iii) and it is based upon a location-aided adaptation of the advertisement zone of the gateway. Our proposed approach benefits from the routing information to find the gateway service and the routing information to the gateway at the same time, thereby saving the overall bandwidth. It uses diverse channels to exchange discovery and routing packets that decreases the congestion on single channels and also the delay of gateway discovery. Our proposed gateway discovery protocol adapts the advertisement zone of gateways based on the location information and the speed of requesting wireless and mobile nodes. We discuss the implementation of our technique, and report on its performance evaluation through an extensive set of simulation experiments. Our results indicate that significant success rate can be achieved by our technique in the worst case (more than 90 percent), while guaranteeing low response time and low message complexity when compared to the selected gateway discovery approaches.

Vehicular Ad Hoc Networks (VANETs) have been widely studied, and the deployment of such networks is likely to happen soon as the required technology and commercial opportunities are already available. Most of applications proposed for these networks require a localization mechanism with reasonable accuracy. In addition to applications, most protocols rely on the availability of a system that determines vehicles' positions. As many vehicles are (or are in the process of being) equipped with GPS, the accurate localization of vehicles in VANETs is achievable. However, one issue that has been ignored is the localization of neighboring vehicles. In VANETs, nodes usually move at high speeds; the information about the position of a neighbour vehicle is therefore fast outdated. The naive approach for handling this issue is to increase the frequency by which periodic messages containing a node's position are exchanged. This solution might lead an unfeasible overhead significantly dropping the bandwidth available for the exchange of services' data. In this paper, we study this problem further, and propose a solution where vehicles predict the position of a neighbor for the near future. Through extensive experiments, we show that a prediction model of low complexity was able to considerably increase the accuracy of neighbor localization. Our mechanism has achieved an accuracy of 50 centimeters with a frequency of exchange of beacons 75% smaller than the naive approach.

Image-based rendering (IBR) has attracted recent attention mainly due to its low requirements for generating new scenes based on a sequence of reference images. IBR has paved the way for a new class of application, the free viewpoint television (FTV), which allows the viewer to interactively control the camera and move freely within a scene. IBR can also be used to render complex 3D virtual environments on graphics-constrained devices, such as cellphones and PDAs. In this paper, we propose a new protocol that offers the user a richer virtual experience by pre-streaming the necessary imagery data to generate new views as the user wanders within a 3D environment. We introduce the idea of key partial panoramas, Le., panorama segments that cover movements in any direction by simply strafing from an appropriate key partial panorama and streaming the amount of lost pixels. We have implemented our protocols and evaluated them against two well-known approaches. Experimental results show that our solution outperforms the selected approaches, by minimizing the delay between image updates and by allowing for a more complex navigation scheme.

Vehicular Ad Hoc Networks are a promising technology that provides several interesting new functionalities to drivers and passengers. These services are spread through a wide variety of applications, each with specific requirements in terms of latency, jitter and bandwidth, among other metrics. For this reason, it is crucial to provide mechanisms that can be used to offer different levels of communication quality in order to achieve reasonable performance in all services. In this paper, we demonstrate how link reliability may be used to support Quality of Service policies for any protocol based on unicast packets relay. This article is divided into two parts, the first of which describes how we estimate link reliability and evaluates how these estimations can be used to classify links into different groups with distinct quality. In the second part, this link reliability estimation model is used to group links into queues with different levels of expected transmission success ratios, which can be used to provide different quality levels depending on the requirements of each individual service. We show that the proposed mechanism adds little-to-none overhead to the overall network and provides an effective mean of supporting QoS in VANETs.

While the notion of reputation is proposed to enhance an entity's trustworthiness and improve the security of a network, the problems of trust and reputation themselves, such as fair evaluation, peer assistance, efficient computation, become an important challenge in such systems. This paper addresses the issues of adaptive trust calculation and efficient reputation evaluation in wireless and mobile networks via a distributed approach. We first present the trust relationship between two mutual trustworthy nodes and then an adaptive computational trust prototype is formulated to effectively prevent malicious nodes from entering the trusted community. Through the analysis of our model's security properties, our system is proved to show how it is able to offer security protections to a dynamic but agile environment and at the same time prevent improper behavior within a community.

The Internet access from vehicular networks is gaining great interest from the research community. In fact, vehicles should be able to connect to the Internet and communicate with different networks through gateways. Guaranteeing safety on the roads is the main objective of vehicular networks. Safety applications need to collaborate with other types of services for efficient safety assurance. Consequently, many services would coexist with safety applications, including the gateway discovery service, and share a limited bandwidth. Any solution to the gateway discovery problem in vehicular ad hoc networks (VANets) is subject to this limitation. In this work, we present a novel gateway discovery technique for VANets. Our protocol aims to provide an efficient hybrid adaptive location-aided gateway advertisement and discovery mechanism for VANets (LAGAD). It has the following unique and novel characteristics for gateway discovery in VANets: (i) it is built on top of the network layer; (ii) it uses channel diversity; (iii) and it is based upon a location-aided adaptation of the advertisement zone of the gateway. Our proposed protocol benefits from the routing information to find the gateway service and the routing information to the gateway at the same time saving the overall bandwidth. It uses diverse channels to exchange discovery and routing packets decreasing the congestion on single channels and decreasing the delay of gateway discovery. Our proposed gateway discovery protocol adapts the advertisement zone of gateways based on the location information and the velocity of requesting vehicles. We discuss the implementation of our algorithm, then present its proof of correctness and message and time complexities computations.

Recently, IEEE 802.11-based wireless networks have been widely adopted as the main access technology. This type of wireless network is know for its low cost, easy deployment and easy configuration. However, the radio range of access points in an IEEE 802.11-based wireless network is limited, thereby mobile nodes have to switch their access points frequently in order to maintain connections in a mobile environment. The question of how to minimize the handoff latency is still a research challenge in IEEE 802.11 wireless networks. In this paper, a self-configured MAC layer handoff scheme is proposed to shorten the handoff latency by adjusting the MinChannelTime and MaxChannelTime dynamically. Simulation results demonstrate that this scheme can significantly reduce the handoff latency and achieve successful handoff at a reasonable probability.

The many advantages of IEEE 802.11 wireless local networks(WLANs) such as low cost, high-speed and easiness of maintenance have enabled the rapid growth and wide deployment of real-time applications. However, due to the limited coverage range of the access points in such networks, frequent handoffs are inevitable for the mobile clients to keep network connections during their movement. High latency and packet loss ratio in the handoff process will cause long delay in the network and degrade the quality of time-critical applications, such as VoIP. To minimize the handoff latency is the key issue of achieving seamless real-time communications. In this paper, a fast handoff scheme with dynamic adaption in MAC layer is presented. Both of the waiting for available channels and the number of scanned channels are reduced to enable fast handoff. The simulation results demonstrate that our scheme meets the requirements of real-time applications.

The pervasive nature of wireless devices and the arbitrary organization of mobile networks attract growing interest in the design of wireless and mobile ad hoc networks. However, malicious nodes always exist due to the vulnerabilities of wireless and mobile nodes and thereby their misbehavior can weaken the utilization of ad hoc networks. Therefore, addressing security issues becomes extremely important in such networks. In this article, we first describe the problem of misbehavior in wireless networks and state its challenges. Moreover, we propose a novel node evaluation solution in which a node can detect nodes' misbehavior through evaluating their trustworthiness and respond to the detected misbehavior accordingly. Thus, our scheme allows a mobile node to more effectively evaluate its neighbors based on the additional trust information from selected neighboring nodes. Finally, by means of the proof of system correctness and discussion, our node evaluation strategy is analyzed to show how it offers provable security properties, so it can thus enhance the security of a network and improve the effectiveness of node evaluation.

In this paper, we investigate the integration of HLA/RTI with VRML/X3D in order to provide a training facility that can be accessed through a traditional web browser. We apply our proposed architecture on a test bed that consists of a cancer treatment scenario within a 3D virtual Radiology Department. We have incorporated the High Level Architecture HLA standard as an important corner stone in allowing the e-learning environment to be distributed and interactive. Combining Virtual Reality concepts with the real pivots of HLA/RTI can create a very strong foundation for such a valuable and required class of applications by utilizing all reliable technologies to make it as flexible as possible. We have ensured that any foreseen future optimizations could be incorporated easily without any overhead.

Recent advances in image sensing hardware have enabled the development of wireless image sensor networks. Similar to generic wireless sensor networks that collect information from surrounding physical environments as scalar variables, wireless image sensor networks can collect data to generate descriptions of interested targets as images or video streams that, in turn, enhance the userpsilas understanding. However, relaying images over wireless image sensor networks with certain QoS requirements is a challenging task due to the characteristics of wireless channels. In this paper, a novel transport protocol for wireless image sensor networks is presented. This protocol aims at the reliable and synchronous transmission of images from multiple sensor nodes to a sync point. The semantics of JPEG stream are exploited in order to improve the performance of the proposed protocol. We have conducted a series of simulation experiments and reported on their results. Our simulation results show that the proposed protocol performs well in error-prone wireless channels even under high packet loss rates.

The development of low-cost image/video sensors has enabled wireless multimedia sensor networks (WMSN). Equipped with the ability to collect images/video streams from surrounding environments, many interesting applications will emerge through the use of WMSN. One of the key targets of a WMSN application is reconstructing the Plenoptic function by using collected images. However, due to the characteristics of wireless channels, this task is challenging. In this paper, a reliable transport protocol for WMSN is presented. This protocol utilizes JPEG stream semantics to distinguish the importance of different parts within the stream, and schedules the transmission based on the importance of the information. In order to investigate the performance of the proposed protocol, a novel image mosaicking algorithm is used as a sample WMSN application. The experimental results show that the proposed protocol and application can offer snapshots of the interested environment with larger field-of-view (FOV) and with little delay. The quality of the view can be improved gradually with the arrival of the data representing the higher frequency part of the images.

Motivated by the widespread of file and video streaming over peer-to-peer networks, we propose to investigate the design of a peer-to-peer solution for image-based remote walkthrough. Due to the fact that our scheme relies on images to provide the user with interactive virtual environments, even thin mobile devices can benefit from image-based rendering's lower graphics power demand when compared to geometry rendering. The main objective of this paper is to present our remote walk through system and discuss a simple peer-to-peer distribution algorithm. Similar to peer-to-peer networked virtual environment solutions, our approach involves discovering neighboring peers using region of interest, instead of proximity of peer nodes. The main idea is that closer virtual users will have higher probability for sharing images, as they are navigating in the same region. We also discuss our previous buffering and scheduling mechanisms and how they work in a peer-to-peer environment. We also discuss our simulation experiments in order to evaluate the performance of our approach.

Mobile computing devices with communication capabilities such as PDAs and cell phones are very popular and can be used as an ad-hoc network to interconnect users and services. The visualization of 3D scenes has many interesting applications, for instance, virtual guide, virtual mall, gaming, training, and monitoring. In this paper we focus on how to merge these technologies to stream interactive virtual environments to remote thin clients over ad-hoc networks, while minimizing the overhead. Mobile ad hoc networks poses significant challenges to multimedia streaming, mainly due to the mobility induced changes in bandwidth. We propose a protocol for interactive streaming of image-based rendered scenes which, different from the traditional geometry rendering schemes, is based on images to render photo-realistic views, that proved to be very suitable for such mobile devices. We also propose an image-based representation of 3D scenes and its packetization scheme, and a feedback mechanism to adapt the traffic to the frequent changes in bandwidth, and thus improving the performance of our streaming system. Besides presenting our proposed interactive streaming system, we also discuss the results of the simulation experiments.

JPEG 2000 stands out among the image compression standards as its facilities to provide tools for error-resilience and compression efficiency and image quality. However, these tools cannot correct transmission errors, they can only detect the error, conceal it, and resynchronize the decoder. Therefore, they are not efficient in wireless scenarios. Recently, JPEG 2000 has been extended to support efficient transmissions of JPEG 2000 compressed images over an error-prone wireless network. Though, error protection and correction in wireless image transmission is still a key problem for the multimedia community. In this paper, we propose a joint dynamic error detection for JPEG 2000 encoded image transmission in order to obtain more effective wireless throughput of compressed images. We define an extended code structure to perform joint encoding for transmitters and propose a novel joint error dynamic detection scheme for receivers. An extensive set of simulations was carried out in order to evaluate and demonstrate the performance of our solution, with the proposed method applied to practical CDMA communication systems.

In recent years, we have witnessed a growing interest in multimedia streaming applications over wireless networks. However, while a number of wireless multimedia applications have already been proposed, many issues related to bandwidth management of 3D multimedia streaming over wireless networks remains one of the most challenging task one has to deal with. In this paper, we propose an adaptive rate control algorithm that uses an immediate feedback mechanism in order to determine the network status. In our scheme, both packet loss and round-trip time are used as indicators of whether or not a network is congested, so as to differentiate end-to-end traffic congestion from wireless link errors. Furthermore, in order to pre-fetch images to the client, we propose to use a motion prediction technique. We discuss our schemes, describe their implementation, and present an extensive set of simulation experiments in order to evaluate their performance using ns-2 simulator.

Providing mobile devices with virtual environment walkthrough and real-time streaming movie playback capability is expected to have a profound impact to the entertainment-based applications, such as virtual guides, online gaming, and e-learning, just to name a few. However, it is well known that it is extremely difficult to render complex 3D scenes at interactive frame rates on thin mobile devices known for their lack of proper resources needed to process large volume of 3D virtual environment data. In order to provide virtual environment navigation on thin mobile clients, we propose a hybrid technique which combines both remote geometry rendering and streaming of warped images. In our approach, the server renders a partial panoramic view, which is based on the user's viewpoint and last movements. The server then warps the image's coordinates into cylindrical coordinates, and streams the images to the client device, which will progressively build the panoramic representation of the scene. Furthermore, in order to enhance streaming performance and quality of the interaction, we propose to use a rate control mechanism as well as a prediction of the user's movements within the virtual scene. In this paper we discuss our scheme for remote rendering and streaming of progressive panoramas for mobile devices, and present our experimental results we have obtained in order to validate our proposed technique. Our results indicate clearly that the proposed solution is able to achieve stable frame rates and throughput in error-prone wireless channels.

With the recent advances of mobile computing devices with communication capabilities, virtual environment walkthrough and real-time streaming movie playback for mobile devices has opened a new class of 3D virtual environment exploration based applications such as virtual guides and malls, online gaming, training and monitoring, just to name a few. The challenge lies in how to provide a rich and detailed 3D virtual environment on thin mobile devices that are known for their lack of proper resources to process large scale 3D geometric data. In this paper, we focus on defining a new approach to remote rendering and interactive visualization of 3D virtual environments on thin mobile devices such as PDAs and cell phones. To this end, we propose efficient end-to-end streaming and rate control protocols to support the requirements of bandwidth-demanding multimedia systems. The main purpose of our proposed rate control scheme is to achieve both high end-to-end throughput and low frame rate ºuctuation in order to adapt data traffic to the frequent changes of the bandwidth and error rate, mainly due to the nature of wireless networks. We discuss the design of our proposed streaming and rate control algorithms, and report on the their performance evaluation using an extensive set of simulation experiments.

Applications that require fine-grain monitoring of physical environments subjected to critical conditions, such as fire, leaking of toxic gases and explosions, pose a great challenge to sensor network protocols. These networks have to provide a fast, reliable, fault tolerant and energy aware channel for events diffusion, which meets the requirements of query-based, event-driven and periodic sensor networks application scenarios. These requirements have to be met even in the presence of emergency conditions that can lead to node failures and path disruption to the sink. This paper presents HPEQ (hierarchical periodic, event-driven and query-based), a cluster-based routing protocol that groups sensor nodes to efficiently relay the sensed data to the sink. In HPEQ protocol nodes with more residual energy are selected as aggregator nodes that relay data to the sink by uniformly distributing energy dissipation among the nodes, and reducing latency and network data traffic. HPEQ is based on a previous protocol, PEQ, that meets sensor networks requirements for critical conditions surveillance applications. HPEQ uses the publish/subscribe paradigm to disseminate requests across the network. The algorithm was implemented using NS-2 simulator and compared to PEQ and to the directed diffusion paradigm. Important metrics were evaluated showing that the proposed algorithm can be a potential solution to meet constraints and requirements of events delivery in critical conditions monitoring applications

With the recent development of wireless communications and multimedia systems, 3D image-based scenes with photo-realistic rendered images and rendering performance have recently received a great deal of interests.In this paper, we focus upon 3D scenes streaming over heterogeneous wireless communication networks, and we propose a real-time transport protocol for streaming 3D scenes based rendered by image morphing. Our approach is based upon 2D images (i.e., subfunction of plenoptic function) which are taken as a representation of 3D scenes while the view morphing is used to render new images. Based on these assumptions, we have designed the real-time transport protocol (RTP) payload format and packetization schemes for streaming 3D image-based scenes. Furtheremore, in order to enhance the robutness of our streaming mechanism, a special packetization scheme has been developed and a feedback mechanism is proposed to deal wih the drastic changes of the wireless network bandwidth using a periodic feedback schema within the Real-time Control Protocol (RTCP).We discuss our proposed protocol and present an extensive set of simulation experiments to evaluate the performance of our protocol using a variery of real world senarios.

Wireless Actor and Sensor Networks (WSANs) are increasingly being deployed for fine-grain monitoring of physical environments subjected to critical conditions such as fire, leaking of toxic gases and explosions. A great challenge to these networks is to provide a fast and reliable channel for events diffusion. However, the order in which events are received can interfere directly with the correct interpretation of what is going on in the physical environment being monitored. Therefore, the ordering of events in WSANs can be a major requirement for critical security monitoring applications because by handling event ordering, ambiguities can be dealt with, increasing the accuracy of what is being monitored. This paper presents OBC (Ordering by Confirmation), a novel protocol for event ordering in WSANs. This low latency and energy aware protocol was evaluated against existing solutions, showing that it can save more energy and achieve lower latencies in situations where the network density, event rate and network dimension increase. The main goal of this protocol is to meet the needs of critical conditions monitoring applications, contributing to reduce death risks and patrimony losses.

Sensor networks are increasingly being deployed for fine-grain monitoring of physical environments subjected to critical conditions such as fire, leaking of toxic gases and explosions. A great challenge to these networks is to provide a fast, reliable and fault tolerant channel for events diffusion, which meets the requirements of query-based, event-driven and periodic sensor networks application scenarios, even in the presence of emergency conditions that can lead to node failures and path disruption to the sink that receives those events. This paper presents a fault tolerant and low latency algorithm, which we refer to as PEQ (Periodic, Event-Driven and Query-Based Protocol), that meets sensor networks requirements for critical conditions surveillance applications. The algorithm uses the publish/subscribe paradigm to disseminate requests across the network and an ack-based scheme to provide fault tolerance. The algorithm was implemented using NS-2 simulator and compared to the Directed Diffusion paradigm. Important metrics were evaluated showing that the proposed algorithm can be a proper solution to meet constraints and requirements of events delivery in critical conditions monitoring applications.