An efficient resource allocation to improve QoS of 5G slicing networks using general processor sharing‐based scheduling algorithm

Fifth generation (5G) slicing is an emerging technology for software‐defined networking/network function virtualization–enabled mobile networks. Improving the utilization and throughput to meet the quality of service (QoS) requirements of 5G slicing is very important for the operators of mobile networks. With growing data traffic from different applications of numerous smart mobile devices having several QoS requirements, we expect networks to face problems of congestion and overload that prevent the effective functioning of a radio access network (RAN). This paper proposes a more effective packet‐based scheduling scheme for data traffic by 5G slicing with two operation modes for improving the resource utilization of 5G cloud RAN and providing an efficient isolation of the 5G slices. These two operation modes are referred to as static sharing resource (SSR) scheme and dynamic sharing resources (DSR) scheme. The SSR scheme is a modified version of an existing method. The goal of this approach is to reallocate the shared available resources of 5G network fairly and maximize the utilization of bandwidth while protecting a 5G slice from overwhelming other 5G slices. Throughput and delays of the system model are also discussed to show its performance limits. On the basis of the simulation outcomes, we observed that the proposed DSR scheme outperforms the SSR scheme in terms of provided delay and throughput. In addition, the token bucket parameters together with the assigned capacity weight for each slice can be selected and configured based on the required QoS. Finally, a good estimate for the maximum delay bounds of the slices is provided by the derived theoretical delay bound.     

A comprehensive and systematic review of the network virtualization techniques in the IoT

Internet of Things (IoT) as one of the last technology in the network domain is an environment of associated physical objects that are reachable through the Internet. Virtualization as the primary technology of IoT has a significant role in its popularization. The visualization strategies have a great impact on the IoT, but, as far as we know, there is not a comprehensive and systematic study in this field. Also, there is no systematic and complete way to discuss and analyze the related strategies. Henceforth, a systematic survey of virtualization techniques is presented in this paper. Different parameters based on the examination of the prevailing methods are considered in three main categorizations. Furthermore, the benefits and weaknesses connected with selected techniques have been discussed, and the significant issues of these techniques are addressed to improve the more efficient virtualization technique for the future.     

Satellite-sensed tropospheric NO2 patterns and anomalies over Indus,Ganges, Brahmaputra,and Meghna river basins

This study presents trends, seasonality, hot spots, and anomalies of tropospheric NO₂ pollution over four basins of Indus, Ganges, Brahmaputra, and Meghna rivers in South Asia using observations from Ozone Monitoring Instrument (OMI) on-board Aura satellite during 2004–2015. For the first time this area, a highly populated and industrialized region with significant emissions of air pollutants, has been discussed collectively. OMI data reveal significantly elevated NO₂ column over the region averaged at (1.9 ± 0.1) × 10¹⁵ molecules cm^–2 (average ± standard deviation of observations) with an increase of 21.12% (slope (0.036 ± 0.004) × 10¹⁵ molecules cm^–2, y-intercept (1.705 ± 0.024) × 10¹⁵ molecules cm^–2, R² = 0.92) during the study period. According to MACCity anthropogenic emissions inventory transportation, energy, residential, and industrial sectors are the major contributors of high NO_x emissions. NO₂ pollution hot spots are identified and their tendencies have been discussed. The hot spots of megacities Lahore (Pakistan) and Dhaka (Bangladesh) are found to be strengthening and expanding over the time. Eastern Ganges Basin shows the highest NO₂ concentration at (2.63 ± 0.22) × 10¹⁵ molecules cm^–2 and growth rate of 3.22% per year mainly linked to power generation, fossil fuel extraction, mining activities, and biomass burning. NO₂ over Indus–Ganges–Brahmaputra–Meghna Basin exhibits seasonal maximum in winter and minimum in monsoon. The highest seasonality is found over Meghna Basin due to large variations in meteorological conditions and large-scale crop-residue burning. Some anomalies in NO₂ levels have been detected linked to intense crop-residue burning events. During these anomalies, exceptionally high levels of daily NO₂ reaching up to 76.23 × 10¹⁵ molecules cm^–2 have been observed over some places in Indus and Meghna Basins.     

Cyber Secure Framework for Smart Containers Based on Novel Hybrid DTLS Protocol

The Internet of Things (IoTs) is apace growing, billions of IoT devices are connected to the Internet which communicate and exchange data among each other. Applications of IoT can be found in many fields of engineering and sciences such as healthcare, traffic, agriculture, oil and gas industries, and logistics. In logistics, the products which are to be transported may be sensitive and perishable, and require controlled environment. Most of the commercially available logistic containers are not integrated with IoT devices to provide controlled environment parameters inside the container and to transmit data to a remote server. This necessitates the need for designing and fabricating IoT based smart containers. Due to constrained nature of IoT devices, these are prone to different cyber security attacks such as Denial of Service (DoS), Man in Middle (MITM) and Replay. Therefore, designing efficient cyber security framework are required for smart container. The Datagram Transport Layer Security (DTLS) Protocol has emerged as the de facto standard for securing communication in IoT devices. However, it is unable to minimize cyber security attacks such as Denial of Service and Distributed Denial of Service (DDoS) during the handshake process. The main contribution of this paper is to design a cyber secure framework by implementing novel hybrid DTLS protocol in smart container which can efficiently minimize the effects of cyber attacks during handshake process. The performance of our proposed framework is evaluated in terms of energy efficiency, handshake time, throughput and packet delivery ratio. Moreover, the proposed framework is tested in IoT based smart containers. The proposed framework decreases handshake time more than 9% and saves 11% of energy efficiency for transmission in compare of the standard DTLS, while increases packet delivery ratio and throughput by 83% and 87% respectively.     

An enhanced scheme for mutual authentication for healthcare services

With the advent of state-of-art technologies, the Telecare Medicine Information System (TMIS) now offers fast and convenient healthcare services to patients at their doorsteps. However, this architecture engenders new risks and challenges to patients' and the server's confidentiality, integrity and security. In order to avoid any resource abuse and malicious attack, employing an authentication scheme is widely considered as the most effective approach for the TMIS to verify the legitimacy of patients and the server. Therefore, several authentication protocols have been proposed to this end. Very recently, Chaudhry et al. identified that there are vulnerabilities of impersonation attacks in Islam et al.'s scheme. Therefore, they introduced an improved protocol to mitigate those security flaws. Later, Qiu et al. proved that these schemes are vulnerable to the man-in-the-middle, impersonation and offline password guessing attacks. Thus, they introduced an improved scheme based on the fuzzy verifier techniques, which overcome all the security flaws of Chaudhry et al.'s scheme. However, there are still some security flaws in Qiu et al.'s protocol. In this article, we prove that Qiu et al.'s protocol has an incorrect notion of perfect user anonymity and is vulnerable to user impersonation attacks. Therefore, we introduce an improved protocol for authentication, which reduces all the security flaws of Qiu et al.'s protocol. We also make a comparison of our protocol with related protocols, which shows that our introduced protocol is more secure and efficient than previous protocols.     

LPV Modeling and Tracking Control of Dissimilar Redundant Actuation System for Civil Aircraft

International Journal of Control, Automation and Systems - Dissimilar redundant actuation systems (DRAS) are in practice in advanced aircraft in order to increase reliability and to resolve the...     

Secure biometric template generation for multi-factor authentication

In the light of recent security incidents, leading to compromise of services using single factor authentication mechanisms, industry and academia researchers are actively investigating novel multi-factor authentication schemes. Moreover, exposure of unprotected authentication data is a high risk threat for organizations with online presence. The challenge is how to ensure security of multi-factor authentication data without deteriorating the performance of an identity verification system? To solve this problem, we present a novel framework that applies random projections to biometric data (inherence factor), using secure keys derived from passwords (knowledge factor), to generate inherently secure, efficient and revocable/renewable biometric templates for users? verification. We evaluate the security strength of the framework against possible attacks by adversaries. We also undertake a case study of deploying the proposed framework in a two-factor authentication setup that uses users? passwords and dynamic handwritten signatures. Our system preserves the important biometric information even when the user specific password is compromised – a highly desirable feature but not existent in the state-of-the-art transformation techniques. We have evaluated the performance of the framework on three publicly available signature datasets. The results prove that the proposed framework does not undermine the discriminating features of genuine and forged signatures and the verification performance is comparable to that of the state-of-the-art benchmark results.     

Clouds and “throat hit”: Effects of liquid composition on nicotine emissions and physical characteristics of electronic cigarette aerosols

Electronic cigarettes (ECIGs) heat and vaporize a liquid mixture to produce an inhalable aerosol that can deliver nicotine to the user. The liquid mixture is typically composed of propylene glycol (PG) and vegetable glycerin (VG), in which are dissolved trace quantities of flavorants and, usually, nicotine. Due to their different chemical and thermodynamic properties, the proportions of PG and VG in the liquid solution may affect nicotine delivery and user sensory experience. In social media and popular culture, greater PG fraction is associated with greater “throat-hit,” a sensation that has been attributed in cigarette smokers to increased presence of vapor-phase nicotine. VG, on the other hand, is associated with thicker and larger exhaled “clouds.” In this study, we aim to investigate how PG/VG ratio influences variables that relate to nicotine delivery and plume visibility. Aerosols from varying PG/VG liquids were generated using a digitally controlled vaping instrument and a commercially available ECIG, and analyzed for nicotine content by GC-MS. Particle mass and number distribution were determined using a six-stage cascade impactor and a fast particle spectrometer (TSI EEPS), with tightly controlled dilution and sampling biases. A Mie theory model was used to compute the aerosol scattering coefficients in the visible spectrum. Decreasing the PG/VG ratio resulted in a decrease in total particulate matter (TPM) and nicotine yield (R² > 0.9, p < .0001). Measured particle count median diameter ranged between 44 and 97nm, and was significantly smaller for PG liquids. Although the particle mass concentration was lower, aerosols produced using liquids that contained VG had an order of magnitude greater light scattering coefficients. These findings indicate that PG/VG ratio is a strong determinant of both nicotine delivery and user sensory experience.

Copyright © 2017 American Association for Aerosol Research     

Relating agility and electronic integration: The role of knowledge and process coordination mechanisms

Current competitive environments necessitate that firms pursue electronic integration in parallel to agility. However, most research to date has examined integration and agility relatively independently and has overlooked the relationship between them. Using coordination theory, this paper suggests that integration enables the two capabilities of agility (i.e., sensing and responding). Results from a study of 303 business unit operations of manufacturing organizations show that integration within business units and with outside partners is positively associated with process coupling of the value chain, both internally and externally. Further, both types of integration are positively associated with knowledge flow within and outside the business unit. In turn, both lead to higher capability to sense change in the business environment and respond to it with agility. This research helps us understand the integration-agility relation better by investigating the role of the knowledge and process capabilities.     

Efficient distance-based outlier detection on uncertain datasets of Gaussian distribution

Uncertain data management, querying and mining have become important because the majority of real world data is accompanied with uncertainty these days. Uncertainty in data is often caused by the deficiency in underlying data collecting equipments or sometimes manually introduced to preserve data privacy. This work discusses the problem of distance-based outlier detection on uncertain datasets of Gaussian distribution. The Naive approach of distance-based outlier on uncertain data is usually infeasible due to expensive distance function. Therefore a cell-based approach is proposed in this work to quickly identify the outliers. The infinite nature of Gaussian distribution prevents to devise effective pruning techniques. Therefore an approximate approach using bounded Gaussian distribution is also proposed. Approximating Gaussian distribution by bounded Gaussian distribution enables an approximate but more efficient cell-based outlier detection approach. An extensive empirical study on synthetic and real datasets show that our proposed approaches are effective, efficient and scalable.