Intelligent Vehicular networks Research Papers (original) (raw)

Clustering is a technique used in network routing to enhance the performance and conserve the network resources. This paper presents a cluster-based routing protocol for VANET utilizing a new addressing scheme in which each node gets an address according to its mobility pattern. Hamming distance technique is used then to partition the network in an address-centric manner. The simulation results show that this protocol enhances routing reachability, whereas reduces routing end-to-end delay and traffic received comparing with two benchmarks namely AODV and DSDV.

Avanti is an international and multidisciplinary project, were undergraduate students, from different backgrounds, have the challenge to design an intelligent vehicle for the Mexican elderly in 2020. This venture is motivated by the convergence of a set of different initiatives: the creation of a new Technology Park, the desire to create a new technology-based businesses and the to need to attract students, innovators and entrepreneurs to propose new solutions to global needs. In this work we are assisted by a group of experts from different geographical regions (Mexico, Spain, Italy and United Kingdom) who help teams of students address this challenge. This short paper presents our work-in-progress by introducing the concepts, people (some 23 teams of students) and challenges associated with this project.

- by Victor Callaghan and +1
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- Development Economics, Teaching and Learning, Education Innovation and Ventures, Science Education

Many safety and non-safety related applications have been envisioned in VANETs. However, efficient data dissemination considering the mobility of vehicle is must for the success of these applications. Although the Road Side Unit (RSU) is a stationary unit, both RSU and vehicle have
limited transmission range that restricts to shorter connection time. This endures a higher request drop rate specially at the overloaded RSUs. A cooperative load balancing (CLB) among the RSUs to use their residual bandwidth can be an effective solution to reduce the request drop rate.
In this paper, we investigate that considering the remaining delay tolerance of submitted requests and the knowledge of fixed road layout, the performance of the cooperative load balancing system can be further improved significantly. We show that this performance gain comes from serving the requests based on the urgency and the efficient load balancing among the junction-RSUs and edge-RSUs. Based on the observations, we propose an Enhanced CLB (ECLB) approach in this
paper. To demonstrate the efficiency of the ECLB approach a number of well-known scheduling algorithms are integrated and an extensive simulation experiments are conducted in the vehicular communication environment that supports the superiority of ECLB over the existing approaches.

Smart cities are promising solution for providing efficient services to the citizens with the use of Information and Communication Technologies. City automation has become essential concept for improving the quality of the citizens' lives, which gives rise to smart cities. Fog computing for Internet of Things (IoT) is considered recently an essential paradigm in smart city scenarios. In this work, we propose energy efficient Fog Servers (FSs), which delivers the information data to the mobile users (in the vehicle). We introduced the concept of energy efficiency through the judicious distribution of non-renewable or/and renewable energy to the FS, which improves outage (and dropping probability. As a first step, we optimise the locations of the FSs for IoT Information Piece Delivery (IoTPD) in a smart city vehicular environment with dropping less than 5%. Then, we maximised the energy savings by pushing dropping to a certain level (5%). To improve the dropping, the available renewable (wind) grid energy is optimally allocated to each FS. This, in turn, also reduces carbon footprint.

- by Samaneh Igder and +1
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- Intelligent Vehicular networks, Energy efficiency, Fog Computing

Providing real-time cloud services to Vehicular Clients (VCs) must cope with delay and delay-jitter issues. Fog computing is an emerging paradigm that aims at distributing small-size self-powered data centers (e.g., Fog nodes) between remote Clouds and VCs, in order to deliver data-dissemination real-time services to the connected VCs. Motivated by these considerations, in this paper, we propose and test an energy-efficient adaptive resource scheduler for Networked Fog Centers (NetFCs). They operate at the edge of the vehicular network and are connected to the served VCs through Infrastructure-to-Vehicular (I2V) TCP/IP-based single-hop mobile links. The goal is to exploit the locally measured states of the TCP/IP connections, in order to maximize the overall communication-plus-computing energy efficiency, while meeting the application-induced hard QoS requirements on the minimum transmission rates, maximum delays and delay-jitters. The resulting energy-efficient scheduler jointly performs: (i) admission control of the input traffic to be processed by the NetFCs; (ii) minimum-energy dispatching of the admitted traffic; (iii) adaptive reconfiguration and consolidation of the Virtual Machines (VMs) hosted by the NetFCs; and, (iv) adaptive control of the traffic injected into the TCP/IP mobile connections. The salient features of the proposed scheduler are that: (i) it is adaptive and admits distributed and scalable implementation; and, (ii) it is capable to provide hard QoS guarantees, in terms of minimum/maximum instantaneous rates of the traffic delivered to the vehicular clients, instantaneous rate-jitters and total processing delays. Actual performance of the proposed scheduler in the presence of: (i) client mobility; (ii) wireless fading; and, (iii) reconfiguration and consolidation costs of the underlying NetFCs, is numerically tested and compared against the corresponding ones of some state-of-the-art schedulers, under both synthetically generated and measured real-world workload traces.

- by Mohammad Shojafar
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- Distributed Computing, Parallel Computing, Parallel Programming, Energy

- by Victor Zamudio
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- Geriatrics, Development Economics, Teaching and Learning, Science Education

We present a beacon-based clustering algorithm aimed at prolonging the cluster lifetime in VANETs. We use a new aggregate local mobility criterion to decide upon cluster reorganisation. The scheme incorporates a contention method to avoid triggering frequent re-organisations when two clusterheads encounter each other for a short period of time. Simulation results show a significant improvement of cluster lifetime and reduced node state/role changes compared to previous popular clustering algorithms.

Platooning is both a challenging and rewarding application. Challenging since strict timing and reliability requirements are imposed by the distributed control system. Rewarding since considerable fuel reductions are possible. As platooning takes place in a vehicular ad hoc network, the use of IEEE 802.11p is close to mandatory. IEEE 802.11p has problems with its medium access method causing packet collisions and random delays. Therefore, we suggest a token-passing medium access method, where the next token holder is selected based on beacon data age. This has the advantage of allowing beacons to be re-broadcasted in case of extra time in each beacon interval. We show that our token-based method is able to reduce the data age and increase reliability considerably compared to the standard.

Road congestion results in a huge waste of time and productivity for millions of people. A possible way to deal with this problem is to have transportation authorities distribute traffic information to drivers, which, in turn, can decide (or be aided by a navigator) to route around congested areas. Such traffic information can be gathered by relying on static sensors placed at specific road locations (e.g., induction loops and video cameras) or by having single vehicles report their location, speed, and travel time. While the former approach has been widely exploited, the latter has come about only more recently; consequently, its potential is less understood. For this reason, in this paper, we study a realistic test case that allows the evaluation of the effectiveness of such a solution. As part of this process, (a) we designed a system that allows vehicles to crowd-source traffic information in an ad hoc manner, allowing them to dynamically reroute based on individually collected traffic information; (b) we implemented a realistic network-mobility simulator that allowed us to evaluate such a model; and (c) we performed a case study that evaluates whether such a decentralized system can help drivers to minimize trip times, which is the main focus of this paper. This study is based on traffic survey data from Portland, OR, and our results indicate that such navigation systems can indeed greatly improve traffic flow. Finally, to test the feasibility of our approach, we im- plemented our system and ran some real experiments at UCLA’s C-Vet test bed.

- by Victor M Zamudio
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- Geriatrics, Development Economics, Teaching and Learning, Science Education

Recently, long-term, advanced cyber-attacks targeting a specific enterprise or organization have been occurring again. These attacks occur over a long period and bypass detection by security systems unlike the existing attack pattern. For such reason, they create problems such as delayed real-time response and detection after damages have already been incurred. This paper introduces the design of technology that applies real-time network traffic monitoring to detect unknown functional cyber-attack on the network. Specifically, the algorithm was verified and evaluated in terms of performance in an actual commercial environment. Cyber-attack detection performance is expected to be improved by enhancing the algorithm and processing large volumes of traffic.

ABSTRACT In this contribution, we design and test the performance of a distributed and adaptive resource management controller, which allows the optimal exploitation of Cognitive Radio and soft-input/soft-output data fusion in Vehicular Access Networks. The ultimate goal is to allow energy and computing-limited car smartphones to utilize the available Vehicular-to-Infrastructure WiFi connections for performing traffic offloading towards local or remote Clouds by opportunistically acceding to a spectral-limited wireless backbone built up by multiple Roadside Units. For this purpose, we recast the afforded resource management problem into a suitable constrained stochastic Network Utility Maximization problem. Afterwards, we derive the optimal cognitive resource management controller, which dynamically allocates the access time-windows at the serving Roadside Units (i.e., the access points) together with the access rates and traffic flows at the served Vehicular Clients (i.e., the secondary users of the wireless backbone). Interestingly, the developed controller provides hard reliability guarantees to the Cloud Service Provider (i.e., the primary user of the wireless backbone) on a per-slot basis. Furthermore, it is also capable to self-acquire context information about the currently available bandwidth-energy resources, so as to quickly adapt to the mobility-induced abrupt changes of the state of the vehicular network, even in the presence of fadings, imperfect context information and intermittent Vehicular-to-Infrastructure connectivity. Finally, we develop a related access protocol, which supports a fully distributed and scalable implementation of the optimal controller.

- by Mohammad Shojafar and +2
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- Distributed Computing, Computer Engineering, Computer Networks, Energy

This paper deals with a novel approach towards detecting emotions from Malayalam speech. We used Discrete Wavelet Transforms (DWT) for feature extraction and Functional Link Network (FLN) Classifier for recognizing different emotions. From this experiment, the machine can recognize four different emotions such as neutral, happy, sad and anger with an overall recognition accuracy of 63.75%.

Abstract Content-centric networking is a new paradigm conceived for future Internet architectures, where communications are driven by contents instead of host addresses. This paradigm has key potentialities to enable effective and efficient communications in the challenging vehicular environment characterized by short-lived connectivity and highly dynamic network topologies. We design CRoWN, a content-centric framework for vehicular ad-hoc networks, which is implemented on top of the IEEE 802.11 p standard layers and is ...

- by Dr Samya Bhattacharya and +2
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- Intelligent Vehicular networks, Teletraffics & Queueing Theory, Energy Efficient Networks
- by Alessandro Amoroso
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- Computer Science, Mobile Technology, Computer Networks, United Nations
- by Marco Roccetti and +1
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- Wireless Communications, Mobile Technology, Computer Networks, United Nations

Data transport fluctuations affecting vehicular connectivity are inexperienced in fixed access as well as in pedestrian mobility: in this paper we review how solutions known as WAN (wide area network) optimizations can be effective to improve user experience in vehicular clients. We show that the core techniques for enabling WAN optimizations are based on network traffic predictions and can largely benefit from fusion of information available from other vehicular subsystems like GPS navigation.
We argue that a suitable platform for implementing vehicular connectivity consists of commodity LTE (long term evolution) access points docked into properly programmed PLDs (programmable logic devices).