Distributed or Centralized Traffic Advisory Systems-The Application's Take

Vehicular networks often consist of computational devices that collect data representing the external environment (e.g., road traffic volume, terrain conditions, and vehicle tracking). The data collected is prone to errors for two reasons: first, the processing algorithms in devices often have only limited capabilities that result in a fuzzy and imprecise representation of the external datum; second, some of the devices may be maliciously faulty mis-reporting the external datum. In such a setting, replicating the devices and voting on the environment data collected by them enhances the trust-worthiness of data reported to the application. The paper describes a cooperation mechanism that embodies two complementary functions: replication of devices and voting among devices. Device-level cooperation is realized using a tree-structured overlay set up over a vehicular network, in which the root node is attached to a data dissemination station and the leaf nodes are attached to the data collection devices in different geographic regions. Voting among the data collected is carried out at the leaf nodes whereupon a sanitized data propagates up the tree towards the root. An intermediate node may also carry out aggregation functions on the data arriving from its downstream tree segments and then forward the aggregated data upstream. The paper describes the voting-based data collection and dissemination as a middleware service.

Vehicular Ad Hoc Networks (VANETs) have emerged as an exciting research and application area. The envisioned applications, as well as some inherent VANET characteristics such as highly dynamic topology, frequently disconnected network, and different and dynamic network density, make data dissemination a challenging task in these networks. Several approaches for data dissemination in VANETs have been recently proposed in the literature. However, more work needs to be done since most of the proposed solutions do not effectively address some or all of the main challenges in these scenarios such as the broadcast storm, network partition and temporal network fragmentation. In this paper, we provide a comprehensive and critical review of proposed techniques for data dissemination in VANETs and identify the main challenges in this area. For this, we first define suitable criteria to classify and organize some of the existing solutions. Next we identify and discuss some open issues and conclude with possible future research directions.

Vehicular ad-hoc networks (VANETs) aim to increase the safety of passengers by making information available beyond the driver’s knowledge. The challenging properties of VANETs such as their dynamic behavior and intermittently connected feature need to be considered when designing a reliable communication protocol in a VANET. In this study, we propose an epidemic and density adaptive protocol for data dissemination in vehicular networks, namely EpiDOL, which utilizes the opposite lane capacity with novel probability functions. We evaluate the performance in terms of end-to-end delay, throughput, overhead and usage ratio of the opposite lane under different vehicular traffic densities via realistic simulations based on SUMO traces in ns-3 simulator. We found out that EpiDOL achieves more than 90% throughput in low densities, and without any additional load to the network 75% throughput in high densities. In terms of throughput EpiDOL outperforms the Edge-Aware and DV-CAST protocols 10% and 40% respectively.

Utility maximization data scheduling in drone-assisted vehicular networks

Among the challenges posed by the problem of data dissemination in wireless sensor networks one that has recently received considerable attention concerns the minimization of the node energy consumption for increasing the overall network lifetime. The sensor devices are battery powered thus energy is the most precious resource of a wireless sensor network since periodically replacing the battery of the nodes in large scale deployments is infeasible. Disseminate the collected data peer to peer to a static control point consumes significant amounts of energy especially for the sensor nodes around to the static sink. In this paper, we present new sink mobility-based data dissemination protocol to minimize energy consumption. We define new sink mobility scheme in which sensor sink periodically moves towards any destination based on the data dissemination frequency calculated during the last period. The simulation result shows that the proposal protocol permits to reduce the energy consumption and prolong the network life.Keywordswireless sensor networksdata disseminationenergy efficiencymobile sink

Reinforcement learning based on routing with infrastructure nodes for data dissemination in vehicular networks (RRIN)

The prosperity of advanced applications in vehicular networks leads to frequent data requests of vehicles, necessitating an increased emphasis on data dissemination capabilities. Multicast transmission, enabling the simultaneous delivery of data to multiple receivers, stands out as a spectrally efficient approach for data dissemination. However, existing approaches in multicast transmission strategy for vehicular networks largely ignore the interference that can arise between multicast links, which results in a degradation of system performance. In this paper, we investigate the issue of joint multicast transmission and bandwidth allocation strategy for enhancing data dissemination in vehicular networks and formulate a problem to maximize the number of packets effectively transmitted by optimizing multicast link establishment, transmitted packets and bandwidth allocation. Because of the coupling of variables in the formulated problem, we decompose the problem into two subproblems and propose the conflict graph based multicast transmission strategy and the graph coloring algorithm based bandwidth allocation strategy for each subproblem. Then, an iterative algorithm is designed for joint optimization. Extensive simulations demonstrate the advantages of proposed strategy.

Ferries play an important role in data dissemination in delay tolerant networks (DTN). The DTN routing hierarchical topology (DRHT) includes three fundamental concepts: ferries messages, ferries routes and clusters. We use ferries in DRHT to improve network performance. In the DRHT, the intra-cluster routing is managed by the cluster head, while the inter-cluster routing is managed by the ferries messages. In this work, we analyse the behavior of ferries’ problem of data dissemination in the DRHT. More specifically, in order to analyse the inter-cluster communication in the DRHT, we formulate game stochastic which models the behavior of the ferries.

In this work we consider the important problem of energy balanced data dissemination in wireless sensor networks (WSN), where data are generated by the sensors and must be routed toward a unique sink. Sensors route data by either sending the data directly to the sink or in a multi-hop fashion by delivering the data to a neighboring sensor. W e decompose the transmission range of sensors into concentric circular bands rings based on a minimum transmission distance between any pair of sensors. We also propose a data dissemination protocol that exploits the above-mentioned decomposition to meet the specific requirements of a sensing application in terms of trade-off between energy and source-to-sink delay. We prove that the use of sensors nodes, which lie on or closely to the shortest path between a source and a sink, as proxy forwarders in data dissemination from sources to a sink, helps simultaneously balance energy consumption and delay. Furthermore, this protocol is based on stochastic estimation methods and is adaptive to environmental changes

In this paper, we examine the problem of large-volume data dissemination via overlay networks. A natural way to maximize the throughput of an overlay multicast session is to split the traffic and feed them into multiple trees. While in single-tree solutions, bandwidth of leaf nodes may remain largely under-utilized, multi-tree solutions increase the chances for a node to contribute its bandwidth by being a relaying node in at least one of the trees. We study the following problems: (1) What is the maximum capacity multi-tree solutions can exploit from overlay networks? (2) When multiple sessions compete within the same network, what is the relationship of two contradictory goals: achieving fairness and maximizing overall throughput? (3) What is the impact of IP routing in achieving at constraining the optimal performance of overlay multicast.We extend the multicommodity flow model to the case of overlay data dissemination, where each commodity is associated with an overlay session, rather than the traditional source-destination pair. We first prove that the problem is solvable in polynomial time, then propose an e-approximation algorithm, assuming that each commodity can be split in arbitrary ways. The solution to this problem establishes the theoretical upper bound of overall throughput that any multi-tree solution could reach. We then study the same problem with the restriction that each commodity can only be split and fed into a limited number of trees. A randomized rounding algorithm and an online tree-construction algorithm are presented. All these algorithms are evaluated by extensive simulations.

Fog and Mist computing exploits computational resources of IoT devices located at the edge of the network. This new infrastructure brings benefits related to latency and Internet bandwidth utilization when compared with Cloud computing. However, this scenario is quite challenging mainly due to the considerable heterogeneity of the devices and to the dynamicity of the network topology what adds new issues related to security, privacy, data availability, and service availability, among others. Despite the theme of data dissemination and data storage had been relatively explored in fields of Sensor Wireless Network (WSN) and Vehicular Ad Hoc Networks (VANETs), we found few studies in the Fog computing research area. Then, this work focuses on the problem of data availability and dissemination in this environment by proposing a distributed algorithm using ideas from evolutionary computation and epidemic models. Results obtained through simulation suggest that the algorithm presents proper results in maintaining data availability in the Fog and Mist Computing environments, even under severe conditions.

Code verification/validation with respect to experimental data banks

Vehicular Ad-Hoc Networks (VANETs) are a fast growing technology that many governments and automobile manufacturers are investing in to provide not only safer and more secure roads, but also informational and entertainment-based applications for drivers. The applications developed for VANETs can be classified into multiple categories (safety, informational, entertainment). Most VANET applications, regardless of their category, depend on having certain vehicular data (vehicular speed, X position and Y position) available. Although these applications appear to use the same vehicular data, the characteristics of this data (i.e., amount, accuracy, and update rate) will vary based on the application category. For example, safety applications need an accurate version of the vehicular data with high frequency, but over short distances. Informational applications relax the data frequency constraint as they need the vehicular data to be reasonably accurate with less frequency, but over longer distances. If each of these applications shares the vehicular data with only its peers using its own mechanism, this behavior will not only introduce redundant functionalities (sending, receiving, processing, etc.) for handling the same data, but also wastefully consume the bandwidth by broadcasting the same data multiple times. Despite the differences in the data characteristics needed by each application, this data can be still shared. Vehicular networks introduce the potential for many co-existing applications. If we do not address the problem of data redundancy early, it may hinder the deployment and usefulness of many of these applications. Therefore, we developed a framework, cluster-based accurate syntactic compression of aggregated data in VANETs (CASCADE), for efficiently aggregating and disseminating commonly-used vehicular data. CASCADE is architccted as a layer that provides applications with a customized version of the vehicular data, based on parameters that each application registers with CASCADE. Additionally, the framework performs the common data handling functionalities (sending, receiving, aggregating, etc.) needed by the applications. This dissertation makes the following contributions: (1) a lossless data compression technique based on differential coding that is tailored for the characteristics of vehicular data; (2) a syntactic data aggregation mechanism that can represent the vehicular data in a 1.5 km area in one IEEE 802.11 frame; (3) a light-weight position verification technique that quickly detects false data with very low false positives; (4) a probabilistic data dissemination technique that alleviates the spatial broadcast storm problem and effectively uses the bandwidth to disseminate data to distant areas in a short amount of time in addition to having less redundancy and more coverage than other techniques. (5) a mechanism for recovering from the communication discontinuity problem in short time based on the traffic density in the opposite direction; (6) an investigation of the possible data structures for representing the vehicular data in a searchable format; (7) a parametric mechanism for matching the vehicular data and providing a customized version of the data that satisfies certain characteristics based on the parameter value. CASCADE through its four major components, local view, extended view, data security and data dissemination, provides an efficient solution for the problem of scalability for VANET applications.

Vehicular plays an important role in day-to-day world in the field of automobiles. VANETs are the subclass of mobile ad-hoc Networks which have no central infrastructure. Nodes are highly mobile in VANET. VANET is distinguished from MANET by their features, design and applications. A Vehicular Ad-Hoc Network or VANET is a sub form of Mobile Ad-Hoc Network or MANET that provides communication between vehicles and between vehicles and road-side base stations with an aim of providing efficient and safe transportation. A vehicle in VANET is considered to be an intelligent mobile node capable of communicating with its neighbors and other vehicles in the network. VANET introduces more challenges aspects as compare to MANET because of high mobility of nodes and fast topology changes in VANET. In this paper, VANET basics structure, its architecture, challenges, applications are discussed. Data dissemination is a challenging task because by utilizing limited bandwidth, maximum data has to disseminate over the vehicular network. Many researchers have provided several techniques to disseminate data so that the data can be accessed more efficiently. Major stress is given to this topic where data dissemination types and its protocols are compared.

In this paper, we for the first time consider the space-time network coding (STNC) to propose a novel cooperative data dissemination strategy in the time-division multiple access (TDMA) manner for the vehicle network, to overcome the shortcomings of the traditional network coding (NC) techniques with carrier sense multiple access/collision avoidance (CSMA/CA) protocol, i.e, high signal detection complexity and channel collision problem. An optimal relay selection strategy in the procedure of cooperative data dissemination is proposed to maximize the average system capacity for the data dissemination. In a addition, a suboptimal relay selection strategy is put forward to reduce the computation complexity and thus makes the developed data dissemination strategy more practical. Compared with the non-cooperative data dissemination, the proposed cooperative data dissemination via STNC has better performance in terms of the average system capacity, the average user equipment (UE) capacity, and the average data dissemination delay.