Intelligent Vehicular networks Research Papers (original) (raw)

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.

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- Distributed Computing, Parallel Computing, Parallel Programming, Energy

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.

Simulation today plays a key role in the study and understanding of extremely complex systems, which range from transportation networks to virus spread, and include large-scale vehicular ad hoc networks (VANETs). Regarding VANET scenarios, until very recently, simulation has represented the only tool with which it was possible to estimate and compare the performances of different communication protocols. In fact, it was not possible to thoroughly test on the road any VANET-based multi-hop communication system, as no highly dense vehicular testbed exists to this date. This situation has recently changed, with the introduction of a new COGNITIVE approach to VANET systems research, where it has been shown that it is possible to perform realistic experiments using only a few real vehicular resources (i.e., only a few vehicles that are equipped with wireless communication interfaces). Now, the scope of this paper is to show that it is possible to move further ahead along this recently drawn path, utilizing the features provided by cognitive network technologies. In particular, we will show that cognitive interfaces can play a role as an additional tunable dimension to be used within an experimental platform where highly dense vehicular testbeds can be structured, even in the presence of a few real vehicular resources. The advantage is twofold: (a) they can be used to test new strategies for dealing with the scarcity of spectrum in a very dynamic environment as the vehicular one is, and, (b) they can be used to test the performances of VANET protocols as a function of different frequencies and interface switching delays. As an example of how this can be done, we will provide preliminary results from a set of experiments that have been performed with a highway accident warning system and with a cognitive network based on the Microsoft Software Radio (SORA) technology.

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
- by Dr Samya Bhattacharya and +2
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- Intelligent Vehicular networks, Teletraffics & Queueing Theory, Energy Efficient Networks

Although the number of accidents that occur on roads is slowly decreasing in time, as both cars and streets become progressively safer, the Statistics of Road Traffic Accidents study from the United Nations reveals that during the last decade every year an average of 150,000 people have lost their lives and 5.5 million have suffered injuries on the roads of western countries. Among the many proposals that have been made, during the years, to combat such phenomenon, an important place is taken by highway accident warning technologies. Such type of system can play an important role, especially in those cities, like Los Angeles, Seoul and Shanghai, specifically designed for cars, more than for human beings. In fact, when an accident occurs on a highway of a city like Los Angeles, it is vital to warn as rapidly as possible all the approaching vehicles, in order to give them the time to stop before crashing on any unexpected obstacle. Recently, an inter-vehicular accident warning system has been devised, theoretically proven to be optimal in terms of bandwidth usage and covered distance. In this paper, we present preliminary results that assess the feasibility of such system. The presented results and measurements were taken from real experiments, performed on Los Angeles freeways and roads in August 2011. To the best of our knowledge, these are the first real experiments of such magnitude performed in a live setting with an inter-vehicular accident warning system.

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%.

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.

One of the important issues in the routing protocol design in Wireless Sensor Networks (WSNs) is minimizing energy consumption and maximizing network lift time. Nowadays networks and information systems are one of the main parts of modern life that without them, people cannot live. On the hand, the impairment of these networks leads to great and incalculable costs. In this paper, a new method based on clustering has presented that problem of energy consumption is solved. The proposed algorithm is that energy-based clustering can create clusters of the same energy level and distribute energy efficiency across the WNS nodes. This proposed clustering protocol classify network nodes based on energy and neighbourhood criteria and attempts to better balance energy in clusters and ultimately increase network lifetime and maintain network coverage. Results are shown that the proposed algorithm is on average 40% better than LEACH algorithm and 14% better than IBLEACH algorithm.