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The emerging and promising paradigm of the Internet of Vehicles (IoV) employ vehicle-to-everything communication for facilitating vehicles to not only communicate with one another but also with the supporting roadside infrastructure, vulnerable pedestrians, and the backbone network in a bid to primarily address a number of safety-critical vehicular applications. Nevertheless, owing to the inherent characteristics of IoV networks, in particular, of being (a) highly dynamic in nature and which results in a continual change in the network topology and (b) non-deterministic owing to the intricate nature of its entities and their interrelationships, they are susceptible to a number of malicious attacks. Such kinds of attacks, if and when materialized, jeopardizes the entire IoV network, thereby putting human lives at risk. Whilst the cryptographic-based mechanisms are capable of mitigating the external attacks, the internal attacks are extremely hard to tackle. Trust, therefore, is an indispensable tool since it facilitates in the timely identification and eradication of malicious entities responsible for launching internal attacks in an IoV network. To date, there is no dataset pertinent to trust management in the context of IoV networks and the same has proven to be a bottleneck for conducting an in-depth research in this domain. The manuscript-at-hand, accordingly, presents a first of its kind trust-based IoV dataset encompassing 96,707 interactions amongst 79 vehicles at different time instances. The dataset involves nine salient trust parameters, i.e., packet delivery ratio, similarity, external similarity, internal similarity, familiarity, external familiarity, internal familiarity, reward/punishment, and context, which play a considerable role in ascertaining the trust of a vehicle within an IoV network. Dataset:  https://github.com/wangyingxun/IoV. Dataset License: Creative Commons Attribution 4.0 International. [ABSTRACT FROM AUTHOR]

The emerging yet promising paradigm of the Internet of Vehicles (IoV) has recently gained considerable attention from researchers from academia and industry. As an indispensable constituent of the futuristic smart cities, the underlying essence of the IoV is to facilitate vehicles to exchange safety-critical information with the other vehicles in their neighborhood, vulnerable pedestrians, supporting infrastructure, and the backbone network via vehicle-to-everything communication in a bid to enhance the road safety by mitigating the unwarranted road accidents via ensuring safer navigation together with guaranteeing the intelligent traffic flows. This requires that the safety-critical messages exchanged within an IoV network and the vehicles that disseminate the same are highly reliable (i.e., trustworthy); otherwise, the entire IoV network could be jeopardized. A state-of-the-art trust-based mechanism is, therefore, highly imperative for identifying and removing malicious vehicles from an IoV network. Accordingly, in this paper, a machine learning-based trust management mechanism, MESMERIC, has been proposed that takes into account the notions of direct trust (encompassing the trust attributes of interaction success rate, similarity, familiarity, and reward and punishment), indirect trust (involving confidence of a particular trustor on the neighboring nodes of a trustee, and the direct trust between the said neighboring nodes and the trustee), and context (comprising vehicle types and operating scenarios) in order to not only ascertain the trust of vehicles in an IoV network but to segregate the trustworthy vehicles from the untrustworthy ones by means of an optimal decision boundary. A comprehensive evaluation of the envisaged trust management mechanism has been carried out which demonstrates that it outperforms other state-of-the-art trust management mechanisms. [ABSTRACT FROM AUTHOR]

Over the past decade or so, considerable and rapid advancements in the state of the art within the promising paradigms of the Internet of Things (IoT) and Artificial Intelligence (AI) have accelerated the development of conventional Vehicular Ad Hoc Networks (VANETS) into the Internet of Vehicles (IoV), thereby bringing both connected and autonomous driving much closer to realization. IoV is a new concept in the Intelligent Traffic System (ITS) and an extended application of IoV in intelligent transportation. It enhances the existing capabilities of mobile ad hoc networks by integrating them with IoT so as to build an integrated and unified vehicle-to-vehicle network. It is worth mentioning that academic and industrial researchers are paying increasing attention to the concept of trust. Reliable trust models and accurate trust assessments are anticipated to improve the security of the IoV. This paper, therefore, focuses on the existing trustworthiness management models along with their corresponding trust parameters, as well as the corresponding trust evaluation parameters and simulation, which provide the basis for intelligent and efficient model suggestions and optimal parameter integration. In addition, this paper also puts forward some open research directions that need to be seriously solved before trust can play its due role in enhancing IoV network elasticity. [ABSTRACT FROM AUTHOR]

Microgrid deployments are expanding around the world as the most suitable solution to integrate distributed renewable energy sources to meet the increasing load demands and to power-up the remote areas. The installation of DC microgrid can improve system efficiency and reduces the cost of electrical infrastructure compared to the AC microgrid. However, the main challenge of implementing DC microgrid is the existing structure of the AC distribution system. In addition to the previous researches performed on DC microgrids, this paper proposes a framework to assess the technical and financial benefits of implementing the AC and DC microgrids. The power loss, voltage drop and system efficiency have been investigated for the AC and DC microgrids during the steady-state condition. Furthermore, the dynamic behaviors of AC and DC microgrids have been analyzed when each system subjected to disturbance such as short-circuit fault, aiming to evaluate the system response. In the next stage, techno-economic analysis has been carried out to determine the optimal size of solar PV system connected to each AC or DC microgrid with its energy storage, according to the meteorological and load profile data of the selected remote area in Sarawak (Malaysia). The study presented in this paper justifies that DC microgrid is potentially more beneficial than AC microgrid. However, the stability of the system during fault condition is the main problem in the DC microgrid. Therefore, it can be concluded that the protection and control of DC microgrids should be the key areas of future researches. [ABSTRACT FROM AUTHOR]

The excessive delay due to the complexity of the decoding process at the relay node results in additional delays at the destination which is a significant issue in cooperative communication channels. A low complexity min-sum (MS) based algorithm called the Variable Global Optimization min-sum (VGOMS) algorithm has been developed to minimise the error corrective performance. The proposed VGOMS algorithm apply the optimization scaling factor at the bit node processing of the variable node operation which have significantly less complexity as compared with the check node operation or both variable node and check node operation. In this study, a straightforward Particle Swarm Optimization approach was used to determine the optimal scaling factor to obtain optimized error corrective performance of the algorithm. The proposed system model uses the channel combining large-scale and small-scale effects which used extensively in cooperative communications. The performance of the VGOMS algorithm performance was compared with four existing decoding algorithms (MS, OMS, NMS, SP) and was found better than the original min-sum (MS) in term of bit error rate (BER) performance and the first algorithm reach optimal BER in error floor region from 3 others existing decoding algorithm (MS, OMS, NMS) after Sum-Product (SP) algorithm. The VGOMS algorithm was therefore shown to have a significantly better compromise between the implementation of good error performance and low computational complexity. [ABSTRACT FROM AUTHOR]

Hydrodynamic instabilities play a silent lethal role for the systems involving steam as one of its working fluid. They reduce the fatigue life of the pipes by exerting stresses at their walls. These instabilities created at the interface between steam and water and propagated towards the walls of the confinement. In the current research, three physical characteristics of these hydrodynamic instabilities have been discussed using Computational Fluid Dynamic (CFD) as well as experimental approaches. These characteristics include their spatial prevalence on the length scale, amplitude, and the number of their occurrences. All of these characteristics have been predicted at specific hydrodynamic conditions in terms of temperature fluctuations. It has been observed that these characteristics are exhibited by the hydrodynamic instabilities in a random and non-deterministic manner. © 2016 Curtin University of Technology and John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Purpose -- The paper aims to propose an optimized handover necessity estimation scheme for a mobile terminal (MT) traversing from a third-generation (3G) cellular network into the wireless local area network (WLAN) cell for reducing the number of handover failures and unnecessary handovers. Design/methodology/approach -- The proposed optimized handover necessity estimation scheme comprises of two algorithms -- a "travelling time prediction" reliant on consecutive received signal strength (RSS) measurements and MT's velocity, and a "time threshold estimation" depending on the handover latency, WLAN's cell radius, tolerable handover failure probability and the tolerable unnecessary handover probability. Findings -- Our performance analysis reveals that the suggested mechanism effectively minimizes the number of handover failures and unnecessary handovers by 60 per cent as compared to the already proposed schemes in the literature. Originality/value -- The convergence of Internet and wireless mobile communication accompanied by a massive increase in the number of cellular subscribers has led mobility management to emerge as a significant and challenging domain for wireless mobile communication over the Internet. Mobility management enables serving networks to locate roaming terminals for the call delivery (location management) and ensures a seamless connection as MT enters into the new service area (handover management). In this manuscript, an optimized handover necessity estimation scheme has been envisaged for reducing the probability of handover failures and unnecessary handovers from 3G cellular networks to WLANs to provide optimal network utilization along with an enhanced user satisfaction. Performance analysis reveals that the suggested scheme yields enhanced results as compared to the schemes already proposed in the literature. [ABSTRACT FROM AUTHOR]