scholarly journals Two Optimization Algorithms for Name-Resolution Server Placement in Information-Centric Networking

2020 ◽  
Vol 10 (10) ◽  
pp. 3588 ◽  
Author(s):  
Jiaqi Li ◽  
Yiqiang Sheng ◽  
Haojiang Deng
Keyword(s):  
Network Architecture ◽  
Information Transfer ◽  
Overlay Networks ◽  
Efficient Solutions ◽  
Placement Problem ◽  
Information Centric Networking ◽  
Fifth Generation ◽  
Server Placement ◽  
Cost Efficient ◽  
The Internet Of Things

Information-centric networking (ICN) is an emerging network architecture that has the potential to address demands related to transmission latency and reliability in fifth-generation (5G) communication technology and the Internet of Things (IoT). As an essential component of ICN, name resolution provides the capability to translate identifiers into locators. Applications have different demands on name-resolution latency. To meet the demands, deploying name-resolution servers at the edge of the network by dividing it into multilayer overlay networks is effective. Moreover, optimization of the deployment of distributed name-resolution servers in such networks to minimize deployment costs is significant. In this paper, we first study the placement problem of the name-resolution server in ICN. Then, two algorithms called IIT-DOWN and IIT-UP are developed based on the heuristic ideas of inter-layer information transfer (IIT) and server reuse. They transfer server placement information and latency information between adjacent layers from different directions. Finally, experiments are conducted on both simulation networks and a real-world dataset. The experimental results reveal that the proposed algorithms outperform state-of-the-art algorithms such as the latency-aware hierarchical elastic area partitioning (LHP) algorithm in finding more cost-efficient solutions with a shorter execution time.

Enalos Suite of Tools: Enhancing Cheminformatics and Nanoinfor - matics through KNIME

2020 ◽  
Vol 27 (38) ◽  
pp. 6523-6535 ◽  
Author(s):  
Antreas Afantitis ◽  
Andreas Tsoumanis ◽  
Georgia Melagraki
Keyword(s):  
Data Analysis ◽  
Virtual Screening ◽  
In Silico ◽  
Model Development ◽  
In Silico Analysis ◽  
Material Design ◽  
Efficient Solutions ◽  
Biological Data ◽  
Cost Efficient ◽  
Silico Analysis

Drug discovery as well as (nano)material design projects demand the in silico analysis of large datasets of compounds with their corresponding properties/activities, as well as the retrieval and virtual screening of more structures in an effort to identify new potent hits. This is a demanding procedure for which various tools must be combined with different input and output formats. To automate the data analysis required we have developed the necessary tools to facilitate a variety of important tasks to construct workflows that will simplify the handling, processing and modeling of cheminformatics data and will provide time and cost efficient solutions, reproducible and easier to maintain. We therefore develop and present a toolbox of >25 processing modules, Enalos+ nodes, that provide very useful operations within KNIME platform for users interested in the nanoinformatics and cheminformatics analysis of chemical and biological data. With a user-friendly interface, Enalos+ Nodes provide a broad range of important functionalities including data mining and retrieval from large available databases and tools for robust and predictive model development and validation. Enalos+ Nodes are available through KNIME as add-ins and offer valuable tools for extracting useful information and analyzing experimental and virtual screening results in a chem- or nano- informatics framework. On top of that, in an effort to: (i) allow big data analysis through Enalos+ KNIME nodes, (ii) accelerate time demanding computations performed within Enalos+ KNIME nodes and (iii) propose new time and cost efficient nodes integrated within Enalos+ toolbox we have investigated and verified the advantage of GPU calculations within the Enalos+ nodes. Demonstration data sets, tutorial and educational videos allow the user to easily apprehend the functions of the nodes that can be applied for in silico analysis of data.

scholarly journals Application of intelligent orienteering based on Internet of things

2020 ◽  
Vol 2020 (1) ◽  
Author(s):  
Donghui Zhang ◽  
Ruijie Liu
Keyword(s):  
Internet Of Things ◽  
Network Architecture ◽  
Emergency Services ◽  
Simulation Experiment ◽  
Experimental Studies ◽  
Signal Stability ◽  
Anchor Nodes ◽  
Set Up ◽  
The Relationship ◽  
The Internet Of Things

Abstract Orienteering has gradually changed from a professional sport to a civilian sport. Especially in recent years, orienteering has been widely popularized. Many colleges and universities in China have also set up this course. With the improvement of people’s living conditions, orienteering has really become a leisure sport in modern people’s life. The reduced difficulty of sports enables more people to participate, but it also exposes a series of problems. As the existing positioning technology is relatively backward, the progress in personnel tracking, emergency services, and other aspects is slow. To solve these problems, a new intelligent orienteering application system is developed based on the Internet of things. ZigBee network architecture is adopted in the system. ZigBee is the mainstream scheme in the current wireless sensor network technology, which has many advantages such as convenient carrying, low power consumption, and signal stability. Due to the complex communication environment in mobile signal, the collected information is processed by signal amplification and signal anti-interference technology. By adding anti-interference devices, video isolators and other devices, the signal is guaranteed to the maximum extent. In order to verify the actual effect of this system, through a number of experimental studies including the relationship between error and traffic radius and the relationship between coverage and the number of anchor nodes, the data shows that the scheme studied in this paper has a greater improvement in comprehensive performance than the traditional scheme, significantly improving the accuracy and coverage. Especially the coverage is close to 100% in the simulation experiment. This research has achieved good results and can be widely used in orienteering training and competition.

scholarly journals Energy-Constrained Design of Joint NOMA-Diversity Schemes with Imperfect Interference Cancellation

Sensors ◽  
2021 ◽  
Vol 21 (12) ◽  
pp. 4194
Author(s):  
Fulvio Babich ◽  
Giulia Buttazzoni ◽  
Francesca Vatta ◽  
Massimiliano Comisso
Keyword(s):  
Interference Cancellation ◽  
Energy Levels ◽  
Random Access ◽  
Actual Performance ◽  
Available Energy ◽  
Fifth Generation ◽  
Code Modulation ◽  
Energy Constrained ◽  
The Relationship ◽  
The Internet Of Things

This study proposes a set of novel random access protocols combining Packet Repetition (PR) schemes, such as Contention Resolution Diversity Slotted Aloha (CRDSA) and Irregular Repetition SA (IRSA), with Non Orthogonal Multiple Access (NOMA). Differently from previous NOMA/CRDSA and NOMA/IRSA proposals, this work analytically derives the energy levels considering two realistic elements: the residual interference due to imperfect Interference Cancellation (IC), and the presence of requirements on the power spent for the transmission. More precisely, the energy-limited scenario is based on the relationship between the average available energy and the selected code modulation pair, thus being of specific interest for the implementation of the Internet of Things (IoT) technology in forthcoming fifth-generation (5G) systems. Moreover, a theoretical model based on the density evolution method is developed and numerically validated by extensive simulations to evaluate the limiting throughput and to explore the actual performance of different NOMA/PR schemes in energy-constrained scenarios.

Preference-aware Edge Server Placement in the Internet of Things

2021 ◽  
pp. 1-1
Author(s):  
Yuanyi Chen ◽  
Yihao Lin ◽  
Zengwei Zheng ◽  
Peng Yu ◽  
Jiaxing Shen ◽  
...  
Keyword(s):  
Internet Of Things ◽  
The Internet ◽  
Server Placement ◽  
The Internet Of Things

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 Peer-To-Peer Multimedia And Information Sharing In Social Networking Web Sites

2021 ◽  
Author(s):  
Shahin Talaei
Keyword(s):  
Social Networking ◽  
Information Sharing ◽  
Web Sites ◽  
Information Transfer ◽  
Overlay Networks ◽  
Performance Testing ◽  
Peer To Peer ◽  
Network Simulator ◽  
Mesh Topology ◽  
Multimedia Distribution

This thesis examines the performance for multimedia distribution and information sharing of social-networking web sites, with a focus on user networks in Facebook. We used real user network data from Facebook together with a synthetic Facebook network in the performance-testing experiments. We tested performance for multimedia distribution and information sharing using three different types of overlay networks: Facebook; structured peer-to-peer (ring topology); and unstructured peer-to-peer (mesh topology). The experiments used Network Simulator 2 (Ns-2) to simulate the network topologies. The results show that structured Peer-to-Peer has the best performance in terms of information transfer, and Facebook has the best performance in regards to average throughput. This thesis shows the strengths and weaknesses of online social networking while sharing information and multimedia content.

scholarly journals Energy performance of 5G backhaul wireless network utilizing hybrid centric-distributed architecture

2019 ◽  
Vol 16 (3) ◽  
pp. 1343
Author(s):  
Hamza Mohammed Ridha Al-Khafaji ◽  
Hasan Shakir Majdi
Keyword(s):  
Energy Efficiency ◽  
Wireless Network ◽  
Network Architecture ◽  
Energy Performance ◽  
Small Cells ◽  
Network Architectures ◽  
Distributed Architecture ◽  
Wireless Backhaul ◽  
Fifth Generation ◽  
5G Network

<p>This paper scrutinizes the influence of deployment scenarios on the energy performance of fifth-generation (5G) network at various backhaul wireless frequency bands. An innovative network architecture, the hybrid centric-distributed, is employed and its energy efficiency (EE) model is analyzed. The obtained results confirm that the EE of the 5G network increases with an increasing number of small cells and degrades with an increasing frequency of wireless backhaul and radius of small cells regardless of the network architectures. Moreover, the hybrid centric-distributed architecture augments the EE when compared with the distributed architecture.</p>

scholarly journals A Multi-User Schedule Method for Non-Orthogonal Multiple Access in 5G Heterogeneous Network

2019 ◽  
Vol 37 (2) ◽  
pp. 337-343
Author(s):  
Yi Xie
Keyword(s):  
Heterogeneous Network ◽  
Network Architecture ◽  
Multiple Access ◽  
Average Rate ◽  
Small Cells ◽  
Fifth Generation ◽  
Scheduling Method ◽  
New Type ◽  
Multiuser Scheduling ◽  
Better Than

Heterogeneous network is supposed to be the dominant network architecture of the fifth generation (5G) cellular network, which means small cells are overlaid on the macrocell. The beamforming (BF) and cell expansion are two important approaches to serve users in small cells. Furthermore, non-orthogonal multiple access (NOMA) is a new type of multiple access multiplexing which improves system performance without taking up extra spectrum resources. Therefore, it becomes one promising technique in 5G. In this paper, NOMA is applied in a 5G heterogeneous network with biased small cells. The BF strategy and the multiuser scheduling method are proposed. The main user in NOMA is scheduled inside the original coverage of the small cell while the side user is chosen from the biased expansion area. The BF strategy that is executed depends on the channel of main user. The multiuser scheduling method is to maximize the rate performance. The proposed method can provide performance benefits. Simulation results show that the proposed methods can be well applied in heterogeneous networks. The achieved performance gain is approximately twice better than traditional OMA and has 10% improvement to the stochastic schedule method. In addition, the average rate of cell edge users is improved.

scholarly journals A DIAGNOSTIC EXPERT SYSTEM TO OVERCOME CONSTRUCTION PROBLEMS IN RIGID HIGHWAY PAVEMENT

2013 ◽  
Vol 19 (6) ◽  
pp. 846-861 ◽  
Author(s):  
Ahmed Mancy Mosa ◽  
Mohd Raihan Taha ◽  
Amiruddin Ismail ◽  
Riza Atiq O. K. Rahmat
Keyword(s):  
Expert System ◽  
Expert Knowledge ◽  
Computer Software ◽  
Efficient Solutions ◽  
Construction Sites ◽  
Literature Reviews ◽  
System Verification ◽  
Cost Efficient ◽  
Expert Reasoning

Constructing highway pavements faces complex problems, which are affected by multiple factors, where solution is nearly impossible without expert assistance. Diagnosing such construction problems and suggesting most suitable cost efficient solutions requires significant engineering expertise, which might not be available in all construction sites due to inadequate resource and remote locations. Developing an expert system in this domain is a very effective way to help novice engineers to overcome these problems and to learn about them. Moreover, the system can be used as an archive to document engineering knowledge and to share expertise among the experts in this domain. This article describes the development and evaluation stages of such a system, including knowledge acquisition, knowledge representation, system building, and system verification and validation. The initial knowledge is acquired from literature reviews. More expert knowledge is elicited through interviews and questionnaires. This knowledge is documented, analyzed, represented, and converted to computer software using the Visual Basic programming language and the system is called ES-CCPRHP. The system has been verified and validated in three ways: by extensive testing, comparison between system performance and expert reasoning, and case study. It can therefore be employed with confidence by end users.

Sign in / Sign up

Export Citation Format

Share Document