scholarly journals Wi-Fi Assisted Contextual Multi-Armed Bandit for Neighbor Discovery and Selection in Millimeter Wave Device to Device Communications

Sensors ◽  
2021 ◽  
Vol 21 (8) ◽  
pp. 2835
Author(s):  
Sherief Hashima ◽  
Kohei Hatano ◽  
Hany Kasban ◽  
Ehab Mahmoud Mohamed
Keyword(s):  
Contextual Information ◽  
Neighbor Discovery ◽  
Average Throughput ◽  
Energy Aware ◽  
Trade Off ◽  
Fifth Generation ◽  
Sixth Generation ◽  
Device To Device ◽  
Scenarios Simulation ◽  
Upper Confidence Bound

The unique features of millimeter waves (mmWaves) motivate its leveraging to future, beyond-fifth-generation/sixth-generation (B5G/6G)-based device-to-device (D2D) communications. However, the neighborhood discovery and selection (NDS) problem still needs intelligent solutions due to the trade-off of investigating adjacent devices for the optimum device choice against the crucial beamform training (BT) overhead. In this paper, by making use of multiband (μW/mmWave) standard devices, the mmWave NDS problem is addressed using machine-learning-based contextual multi-armed bandit (CMAB) algorithms. This is done by leveraging the context information of Wi-Fi signal characteristics, i.e., received signal strength (RSS), mean, and variance, to further improve the NDS method. In this setup, the transmitting device acts as the player, the arms are the candidate mmWave D2D links between that device and its neighbors, while the reward is the average throughput. We examine the NDS’s primary trade-off and the impacts of the contextual information on the total performance. Furthermore, modified energy-aware linear upper confidence bound (EA-LinUCB) and contextual Thomson sampling (EA-CTS) algorithms are proposed to handle the problem through reflecting the nearby devices’ withstanding battery levels, which simulate real scenarios. Simulation results ensure the superior efficiency of the proposed algorithms over the single band (mmWave) energy-aware noncontextual MAB algorithms (EA-UCB and EA-TS) and traditional schemes regarding energy efficiency and average throughput with a reasonable convergence rate.

scholarly journals Leveraging Machine-Learning for D2D Communications in 5G/Beyond 5G Networks

Electronics ◽  
2021 ◽  
Vol 10 (2) ◽  
pp. 169
Author(s):  
Sherief Hashima ◽  
Basem M. ElHalawany ◽  
Kohei Hatano ◽  
Kaishun Wu ◽  
Ehab Mahmoud Mohamed
Keyword(s):  
Machine Learning ◽  
Network Architecture ◽  
D2d Communication ◽  
Neighbor Discovery ◽  
Research Directions ◽  
Fifth Generation ◽  
Research Activities ◽  
Comprehensive Survey ◽  
Network Overhead

Device-to-device (D2D) communication is a promising paradigm for the fifth generation (5G) and beyond 5G (B5G) networks. Although D2D communication provides several benefits, including limited interference, energy efficiency, reduced delay, and network overhead, it faces a lot of technical challenges such as network architecture, and neighbor discovery, etc. The complexity of configuring D2D links and managing their interference, especially when using millimeter-wave (mmWave), inspire researchers to leverage different machine-learning (ML) techniques to address these problems towards boosting the performance of D2D networks. In this paper, a comprehensive survey about recent research activities on D2D networks will be explored with putting more emphasis on utilizing mmWave and ML methods. After exploring existing D2D research directions accompanied with their existing conventional solutions, we will show how different ML techniques can be applied to enhance the D2D networks performance over using conventional ways. Then, still open research directions in ML applications on D2D networks will be investigated including their essential needs. A case study of applying multi-armed bandit (MAB) as an efficient online ML tool to enhance the performance of neighbor discovery and selection (NDS) in mmWave D2D networks will be presented. This case study will put emphasis on the high potency of using ML solutions over using the conventional non-ML based methods for highly improving the average throughput performance of mmWave NDS.

scholarly journals Formal Verification of Authentication and Service Authorization Protocols in 5G-Enabled Device-to-Device Communications Using ProVerif

Electronics ◽  
2021 ◽  
Vol 10 (13) ◽  
pp. 1608
Author(s):  
Ed Kamya Kiyemba Edris ◽  
Mahdi Aiash ◽  
Jonathan Loo
Keyword(s):  
Service Providers ◽  
Security Analysis ◽  
Mobile Network ◽  
Network Services ◽  
Control Mechanisms ◽  
D2d Communications ◽  
Fifth Generation ◽  
Device To Device ◽  
Pi Calculus ◽  
Authentication And Authorization

Device-to-Device (D2D) communications will be used as an underlay technology in the Fifth Generation mobile network (5G), which will make network services of multiple Service Providers (SP) available anywhere. The end users will be allowed to access and share services using their User Equipments (UEs), and thus they will require seamless and secured connectivity. At the same time, Mobile Network Operators (MNOs) will use the UE to offload traffic and push contents closer to users relying on D2D communications network. This raises security concerns at different levels of the system architecture and highlights the need for robust authentication and authorization mechanisms to provide secure services access and sharing between D2D users. Therefore, this paper proposes a D2D level security solution that comprises two security protocols, namely, the D2D Service security (DDSec) and the D2D Attributes and Capability security (DDACap) protocols, to provide security for access, caching and sharing data in network-assisted and non-network-assisted D2D communications scenarios. The proposed solution applies Identity-based Encryption (IBE), Elliptic Curve Integrated Encryption Scheme (ECIES) and access control mechanisms for authentication and authorization procedures. We formally verified the proposed protocols using ProVerif and applied pi calculus. We also conducted a security analysis of the proposed protocols.

scholarly journals Randomised Gaussian Process Upper Confidence Bound for Bayesian Optimisation

2020 ◽  
Author(s):  
Julian Berk ◽  
Sunil Gupta ◽  
Santu Rana ◽  
Svetha Venkatesh
Keyword(s):  
Gaussian Process ◽  
Real World ◽  
Confidence Bound ◽  
Trade Off ◽  
Upper Confidence Bound ◽  
Exploration Exploitation

In order to improve the performance of Bayesian optimisation, we develop a modified Gaussian process upper confidence bound (GP-UCB) acquisition function. This is done by sampling the exploration-exploitation trade-off parameter from a distribution. We prove that this allows the expected trade-off parameter to be altered to better suit the problem without compromising a bound on the function's Bayesian regret. We also provide results showing that our method achieves better performance than GP-UCB in a range of real-world and synthetic problems.

scholarly journals Self-Adaptation of mHealth Devices: The Case of the Smart Cane Platform

Proceedings ◽  
2019 ◽  
Vol 31 (1) ◽  
pp. 23 ◽  
Author(s):  
Inmaculada Ayala ◽  
Joaquín Ballesteros ◽  
Juan Caro-Romero ◽  
Mercedes Amor ◽  
Lidia Fuentes
Keyword(s):  
Energy Consumption ◽  
Relative Error ◽  
Contextual Information ◽  
Assistive Technologies ◽  
Assistive Devices ◽  
Product Lines ◽  
Trade Off ◽  
Self Adaptation ◽  
Battery Consumption

Nowadays, more than one billion people are in need of one or more assistive technologies, and this number is expected to increase beyond two billion by 2050. The majority of assistive technologies are supported by battery-operated devices like smartphones and wearables. This means that battery weight is an important concern in such assistive devices because it may affect negatively its ergonomics. Saving power in these assistive devices is of utmost importance for its potential twofold benefits: extend the device life and reduce the global warming aggravated by billion of these devices. Dynamic Software Product Lines (DSPLs) are a suitable technology that supports system adaptation, in this case, to reduce energy consumption at runtime, considering contextual information and the current state of the device. However, a reduction in battery consumption could negatively affect other quality of service parameters, like response time. Therefore, it is important to trade-off battery saving and these other concerns. This work illustrates how to approach the self-adaptation of smart assistive devices by means of a DSPL-based strategy that optimizes battery consumption taking into account other QoS parameters at the same time. We illustrate our proposal with a real case study: a Smart Cane that is integrated with a DSPL platform, Tanit. Experimentation shows that it is possible to make a trade-off between different quality concerns (energy consumption and relative error). The results of the experiments allow us to conclude that the Tanit approach elongates battery duration of the Smart Cane in one day (an increase of a 6% with a relative error of 1%), so we improve the user quality of experience and reduce the energy footprint with a reasonable relative error.

Energy Aware Dynamic Mode Decision for Cellular D2D Communications by Using Integrated Multi-Criteria Decision Making Model

2020 ◽  
Vol 11 (3) ◽  
pp. 131-151 ◽  
Author(s):  
Loganathan Jayakumar ◽  
Ankur Dumka ◽  
S. Janakiraman
Keyword(s):  
Decision Making ◽  
Data Transfer ◽  
Selection Process ◽  
Mode Selection ◽  
Selection Problem ◽  
Dynamic Mode ◽  
Communication Link ◽  
Energy Aware ◽  
Coverage Area ◽  
Device To Device

Recent developments in mobile network communication increases the usage of the cellular users and their wideband data transfer. Sometimes, network operators may get overloaded because of voice and data transmission between nodes which are under the same coverage area. Cellular device-to-device communication is one of the emerging technologies to overcome current increasing demands for spectrum in cellular networks. It reduces network traffic at centralized terminal stations by enabling direct communication link between source and destination. Mode selection is one of the steps required to fix defined configuration for transmitting data between the pairs of nodes. In this article, the mode selection problem has been considered as multi-objective decision-making problem and applied classical multi-criteria decision models such as analytic hierarchy process and technique for order preference by similarity to the ideal solution models. From simulated results, combination of these two has been proven as the most promising combination for mode selection problem in cellular device-to-device communications under three different types of data services such as text, audio, and video. A dynamically mode selection process has to be carried out with multiple factors which are affecting the performance of the system using proposed model.

scholarly journals Sixth Generation (6G) Wireless Networks: Vision, Research Activities, Challenges and Potential Solutions

Symmetry ◽  
2020 ◽  
Vol 12 (4) ◽  
pp. 676 ◽  
Author(s):  
Mohammed H. Alsharif ◽  
Anabi Hilary Kelechi ◽  
Mahmoud A. Albreem ◽  
Shehzad Ashraf Chaudhry ◽  
M. Sultan Zia ◽  
...  
Keyword(s):  
Wireless Networks ◽  
Communication Systems ◽  
Future Research ◽  
Competitive Edge ◽  
Fifth Generation ◽  
Research Activities ◽  
Sixth Generation ◽  
Critical Issues ◽  
Future Research Directions ◽  
Communication Needs

The standardization activities of the fifth generation communications are clearly over and deployment has commenced globally. To sustain the competitive edge of wireless networks, industrial and academia synergy have begun to conceptualize the next generation of wireless communication systems (namely, sixth generation, (6G)) aimed at laying the foundation for the stratification of the communication needs of the 2030s. In support of this vision, this study highlights the most promising lines of research from the recent literature in common directions for the 6G project. Its core contribution involves exploring the critical issues and key potential features of 6G communications, including: (i) vision and key features; (ii) challenges and potential solutions; and (iii) research activities. These controversial research topics were profoundly examined in relation to the motivation of their various sub-domains to achieve a precise, concrete, and concise conclusion. Thus, this article will contribute significantly to opening new horizons for future research directions.

Seasonal Occurrence of Pieris rapae (L.) (Lepidoptera: Pieridae) in Southwest Virginia

1995 ◽  
Vol 30 (2) ◽  
pp. 262-272 ◽  
Author(s):  
David N. Gaines ◽  
L. T. Kok
Keyword(s):  
Count Data ◽  
First Generation ◽  
Pieris Rapae ◽  
Growth Period ◽  
Control Measures ◽  
Seasonal Occurrence ◽  
Fifth Generation ◽  
Sixth Generation ◽  
Field Plots ◽  
Eggs And Larvae

In Virginia, Pieris rapae (L.) phenology is not well established because earlier studies focused on its occurrence within the growth period of a particular crop. In this study, conducted in 1989 and 1990, we sampled multiple crops in both spring and fall plantings and these data were compared with those from earlier studies to obtain an overall pattern of seasonal occurrence. In 1989, spring crops of broccoli, cabbage, and kale were planted in field plots in Montgomery Co., VA, and sampled weekly for the eggs and larvae of P. rapae. In 1990, both spring and fall crops were planted and sampled. Four P. rapae generations (egg count peaks) were observed in 1989 and 1990, but comparison of data from both years suggested a fifth generation was possible in this region. When these data are compared with egg count data from seven previous years (1981–1988; 1985 not included), evidence indicates a first generation in mid-May, and consistent second and third generations in mid-June and mid-July, respectively. The June and July generations were always well defined by high egg and larva counts per plant. Less predictable are the fourth and fifth generations which may both occur in August or one generation each in August and September. When fourth and fifth generations occur in early and late August, a sixth generation may occur in late September. The regular occurrence and size of the second and third generation can facilitate the planning and implementation of biological or other control measures for P. rapae in this region.

scholarly journals Efficient group-based discovery for wireless sensor networks

2017 ◽  
Vol 13 (7) ◽  
pp. 155014771771905 ◽  
Author(s):  
Pengpeng Chen ◽  
Ying Chen ◽  
Shouwan Gao ◽  
Qiang Niu ◽  
Jun Gu
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
High Mobility ◽  
Wireless Sensor ◽  
Relative Distance ◽  
Neighbor Discovery ◽  
Trade Off ◽  
Low Duty Cycle ◽  
Order Of Magnitude

Due to the combination of constrained power, low duty cycle, and high mobility, neighbor discovery is one of the most challenging problems in wireless sensor networks. Existing discovery designs can be divided into two types: pairwise-based and group-based. The former schemes suffer from high discovery delay, while the latter ones accelerate the discovery process but incur too much energy overhead, far from practical. In this article, we propose a novel efficient group-based discovery method based on relative distance, which makes a delicate trade-off between discovery delay and energy consumption. Instead of directly referring to the wake-up schedules of a whole group of nodes, efficient group-based discovery selectively recommends nodes that are most likely to be neighbors, in which the probability is calculated based on the nodes’ relative distance. Moreover, the sequence of received signal strengths are employed to estimate the relative distance for avoiding the effect of the node distribution. Extensive simulations are conducted to verify the effectiveness of the design. The results indicate that efficient group-based discovery statistically achieves a good trade-off between energy cost and discovery latency. Efficient group-based discovery also shows one order of magnitude reduction in discovery delay with a maximum of 6.5% increase in energy consumption compared with typical discovery methods.

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