FSM: FBS Set Management, An energy efficient multi-drone 3D trajectory approach in cellular networks

Nowadays, Unmanned Aerial Vehicles (UAVs) have been significantly improved, and one of their most important applications is to provide temporary coverage for cellular users. Terrestrial Base Station cannot service all users due to disasters or events such as ground BS breakdowns, bad weather conditions, natural disasters, transmission errors, etc. The UAV can be sent to the target location and establishes the necessary communication links without requiring any predetermined infrastructure and covers that area. Finding the optimal location and the appropriate number (DBS) of drone-BS in this area is a challenge. In this paper, the optimal location and optimal number of DBSs are distributed in the current state of the users and the subsequent user states determined by the prediction. Finally, the DBS transition is optimized from the current state to the predicted future locations. The simulation results show that the proposed method can provide acceptable coverage on the network

Comparison and verification of turbulence Reynolds-averaged Navier-Stokes closures to model spatially varied flows

The robustness and accuracy of Reynolds-averaged Navier–Stokes (RANS) models was investigated for complex turbulent flow in an open channel receiving lateral inflow, also known as spatially varied flow with increasing discharge (SVF). The three RANS turbulence models tested include realizable k–ε, shear stress transport k–ω and Reynolds stress model based on their prominence to model jets in crossflows. Results were compared to experimental laser Doppler velocimetry measurements from a previous study. RANS results in the uniform flow region and farther from the jet centreline were more accurate than within the lateral inflow region. On the leeward side of the jet, RANS models failed to capture the downward velocity vectors resulting in major deviations in vertical velocity. Among RANS models minor variations were noted at impingement and near the water surface. Regardless of inadequately predicting complex characteristics of SVF, RANS models matched experimental water surface profiles and proved more superior to the theoretical approach currently used for design purposes

The evolution of Blockchain: a bibliometric study

© 2019 The Authors. Published by IEEE. This is an open access article available under a Creative Commons licence. The published version can be accessed at the following link on the publisher’s website: https://doi.org/10.1109/ACCESS.2019.2895646Blockchain as emerging technology is revolutionizing several industries, and its abundant privileges have opened up a bunch of research directions in various industries; thereby, it has acquired many interests from the research community. The rapid evolution of blockchain research papers in recent years has resulted in a need to conduct research studies that investigate a detailed analysis of the current body of knowledge in this field. To address this need, a few review papers have been published to report the latest accomplishments and challenges of blockchain technology from different perspectives. Nonetheless, there has not been any bibliometric analysis of the state of the art in blockchain where Web of Science (WoS) has been taken into consideration as a literature database. Hence, a thorough analysis of the current body of knowledge in blockchain research through a bibliometric study would be needed. In this paper, we performed a bibliometric analysis of all Blockchain’s conference papers, articles, and review papers that have been indexed byWoS from 2013 to 2018. We have analyzed those collected papers against five research questions. The results revealed some valuable insights, including yearly publications and citations trends, hottest research areas, top-ten influential papers, favorite publication venues, and most supportive funding bodies. The findings of this paper offer several implications that can be used as a guideline by both fresh and experienced researchers to establish a baseline before initiating a blockchain research project in the future.Published versio

Deterrence and prevention-based model to mitigate information security insider threats in organisations

This is an accepted manuscript of an article published by Elsevier in Future Generation Computer Systems, available online: https://doi.org/10.1016/j.future.2019.03.024 The accepted version of the publication may differ from the final published version.Previous studies show that information security breaches and privacy violations are important issues for organisations and people. It is acknowledged that decreasing the risk in this domain requires consideration of the technological aspects of information security alongside human aspects. Employees intentionally or unintentionally account for a significant portion of the threats to information assets in organisations. This research presents a novel conceptual framework to mitigate the risk of insiders using deterrence and prevention approaches. Deterrence factors discourage employees from engaging in information security misbehaviour in organisations, and situational crime prevention factors encourage them to prevent information security misconduct. Our findings show that perceived sanctions certainty and severity significantly influence individuals’ attitudes and deter them from information security misconduct. In addition, the output revealed that increasing the effort, risk and reducing the reward (benefits of crime) influence the employees’ attitudes towards prevent information security misbehaviour. However, removing excuses and reducing provocations do not significantly influence individuals’ attitudes towards prevent information security misconduct. Finally, the output of the data analysis also showed that subjective norms, perceived behavioural control and attitude influence individuals’ intentions, and, ultimately, their behaviour towards avoiding information security misbehaviour.Published versio

Fog vehicular computing: augmentation of fog computing using vehicular cloud computing

© 20XX IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. This is an accepted manuscript of an article published by IEEE in IEEE Vehicular Technology Magazine, available online: http://dx.doi.org/10.1109/MVT.2017.2667499 The accepted version of the publication may differ from the final published version.Fog computing has emerged as a promising solution for accommodating the surge of mobile traffic and reducing latency, both known to be inherent problems of cloud computing. Fog services, including computation, storage, and networking, are hosted in the vicinity of end users (edge of the network), and, as a result, reliable access is provisioned to delay-sensitive mobile applications. However, in some cases, the fog computing capacity is overwhelmed by the growing number of demands from patrons, particularly during peak hours, and this can subsequently result in acute performance degradation. In this article, we address this problem by proposing a new concept called fog vehicular computing (FVC) to augment the computation and storage power of fog computing. We also design a comprehensive architecture for FVC and present a number of salient applications. The result of implementation clearly shows the effectiveness of the proposed architecture. Finally, some open issues and envisioned directions are discussed for future research in the context of FVC.Published versio

Dynamic remote data auditing for securing big data storage in cloud computing / Mehdi Sookhak

Nowadays, organizations produce a huge amount of sensitive data, such as personal information, financial data, and electronic health records. Consequently, the amount of digital data produced has increased correspondingly and often overwhelmed the data storage capacity of many organizations. The management of such a large amount of data in local storage system is difficult and incurs high expenses because of high-capacity storage systems needed and the expert personnel to manage them. Although the cost of storage hardware has tremendously decreased in recent years, about 75% of the total ownership cost is still assigned tomanage data storage. It is not surprising, therefore, that cloud computing is now embraced as a key technology to provide a convenient, on-demand network access to a shared pool of configurable computing resources, and demands minimum service provider interaction or management effort. Organizations now have an option to outsource their data to cloud storage to decrease the burden on local data storage and also to reduce maintenance cost. Although the cloud offers tangible benefits to data owners, outsourcing data to a remote server and delegating management of data to an untrusted cloud service provider, can lead to loss of physical control over the data. To the clients, the cloud is inherently neither secure nor reliable and this poses new challenges to the confidentiality, integrity, and availability of data in cloud computing. Without a local copy of the data, traditional integrity verification techniques such as hash functions and signatures are inapplicable in the cloud storage. Also, it is impossible to download a large-size file from the cloud storage. The situation is made worse when users access data using their mobile devices. In this context, a more efficient technique is required to remotely verify the integrity of the outsourced data in the cloud. In this research, a new remote data auditing method is proposed for securing data storage in cloud computing based on an algebraic signature. This signature allows the auditor to check data possession in cloud storage, and this incurs fewer computational overheads on the auditor and server in comparison to Homomorphic cryptosystem. Moreover, a new data structure – Divide and Conquer Table (D&CT) – is designed to efficiently update the outsourced data dynamically by performing insert, append, delete, and modify operations by the data owner. Furthermore, the proposed method is implemented in the real environment to prove the security, justify the performance of our method, and compare with the most familiar and the stat-of-the-art data auditing methods on the basis of computation and communication cost. It is found that by employing the proposed RDA method the computational and communication costs of data integrity is reduced. D&CT data structure reduces the computation cost of data update for normal and large-scale files markedly. Hence, the proposed RDA provides an efficient and secure solution for mobile cloud computing

Classification of energy-efficient routing protocols for wireless sensor networks

In recent years, research on Wireless Sensor Networks (WSNs) has become one of the main topics in electronic and computer fields. Since, the WSNs include many low cost and low power sensor nodes and battery replacement in harsh environments is usually impossible, an energy-efficient paradigm for all layers of protocol stack specially routing schemes is necessary to prolong the sensors' lifetime. In this paper, we first specify the sources of energy consumption in a typical sensor node, and then we classify the energy-efficient routings into three main categories such as flat, hierarchical, and geographic mechanisms based on underlying network structure. However, protocols employing simultaneous schemes such as bio-inspired methods, quality of service, multi-path and querybased manners are also discussed. In this taxonomy, special attention has been devoted to the energy-aware QoS-based and bio-inspired routing algorithms which have not yet obtained much consideration in the literature. Moreover, each class covers a variety of the state-of-the-art routing and cross-layer protocols, which motivate potential ideas for future works. Finally, we compare these mechanisms and discuss open research issues

A Framework for Component Selection Considering Dark Sides of Artificial Intelligence: A Case Study on Autonomous Vehicle

Nowadays, intelligent systems play an important role in a wide range of applications, including financial ones, smart cities, healthcare, and transportation. Most of the intelligent systems are composed of prefabricated components. Inappropriate composition of components may lead to unsafe, power-consuming, and vulnerable intelligent systems. Although artificial intelligence-based systems can provide various advantages for humanity, they have several dark sides that can affect our lives. Some terms, such as security, trust, privacy, safety, and fairness, relate to the dark sides of artificial intelligence, which may be inherent to the intelligent systems. Existing solutions either focus on solving a specific problem or consider the some other challenge without addressing the fundamental issues of artificial intelligence. In other words, there is no general framework to conduct a component selection process while considering the dark sides in the literature. Hence, in this paper, we proposed a new framework for the component selection of intelligent systems while considering the dark sides of artificial intelligence. This framework consists of four phases, namely, component analyzing, extracting criteria and weighting, formulating the problem as multiple knapsacks, and finding components. To the best of our knowledge, this is the first component selection framework to deal with the dark sides of artificial intelligence. We also developed a case study for the component selection issue in autonomous vehicles to demonstrate the application of the proposed framework. Six components along with four criteria (i.e., energy consumption, security, privacy, and complexity) were analyzed and weighted by experts via analytic hierarchy process (AHP) method. The results clearly show that the appropriate composition of components was selected through the proposed framework for the desired functions