A robust molecular unit nanogrid servicing as network nodes via molecular installing technology

2017 ◽  
Vol 1 (3) ◽  
pp. 455-459 ◽  
Author(s):  
Guangwei Zhang ◽  
Ying Wei ◽  
Jishu Wang ◽  
Yuyu Liu ◽  
Linghai Xie ◽  
...  
Keyword(s):  
Network Nodes ◽  
Molecular Unit

A nanogrid that consists of four fluorenes and two carbazoles has been synthesized by molecular installing technology from an L-shaped synthon.

COORDINATED DISTRIBUTED SCHEDULING IN WIRELESS MESH NETWORK

2012 ◽  
Vol 3 (3) ◽  
pp. 368-374
Author(s):  
Usha Kumari ◽  
Udai Shankar
Keyword(s):  
Network Performance ◽  
Mesh Networks ◽  
Mac Protocol ◽  
Scheduling Algorithm ◽  
Ieee 802.16 ◽  
Distributed Scheduling ◽  
Mesh Network ◽  
Fourth Generation ◽  
Network Nodes ◽  
Wireless Mesh

IEEE 802.16 based wireless mesh networks (WMNs) are a promising broadband access solution to support flexibility, cost effectiveness and fast deployment of the fourth generation infrastructure based wireless networks. Reducing the time for channel establishment is critical for low latency/interactive Applications. According to IEEE 802.16 MAC protocol, there are three scheduling algorithms for assigning TDMA slots to each network node: centralized and distributed the distributed is further divided into two operational modes coordinated distributed and uncoordinated distributed. In coordinated distributed scheduling algorithm, network nodes have to transmit scheduling message in order to inform other nodes about their transfer schedule. In this paper a new approach is proposed to improve coordinated distributed scheduling efficiency in IEEE 802.16 mesh mode, with respect to three parameter Throughput, Average end to end delay and Normalized Overhead. For evaluating the proposed networks efficiency, several extensive simulations are performed in various network configurations and the most important system parameters which affect the network performance are analyzed

Distance Distribution between Complex Network Nodes in Hyperbolic Space

2016 ◽  
Vol 25 (3) ◽  
pp. 223-236 ◽  
Author(s):  
Gregorio Alanis-Lobato ◽  
Miguel A. Andrade-Navarro ◽  
Keyword(s):  
Complex Network ◽  
Hyperbolic Space ◽  
Distance Distribution ◽  
Network Nodes

PREDICTING CHARACTERISTICS OF SELF SIMILAR TRAFFIC BY SPLINE-EXTRAPOLATION

2019 ◽  
Author(s):  
Irina Strelkovskay ◽  
Irina Solovskaya ◽  
Anastasija Makoganjuk ◽  
Nikolaj Severin
Keyword(s):  
Quality Characteristics ◽  
Traffic Prediction ◽  
Normative Values ◽  
Spline Functions ◽  
Network Nodes ◽  
Traffic Forecasting ◽  
Network Equipment ◽  
Self Similar ◽  
Accuracy Of Prediction

The problem of forecasting self-similar traffic, which is characterized by a considerable number of ripples and the property of long-term dependence, is considered. It is proposed to use the method of spline extrapolation using linear and cubic splines. The results of self-similar traffic prediction were obtained, which will allow to predict the necessary size of the buffer devices of the network nodes in order to avoid congestion in the network and exceed the normative values ​​of QoS quality characteristics. The solution of the problem of self-similar traffic forecasting obtained with the Simulink software package in Matlab environment is considered. A method of extrapolation based on spline functions is developed. The proposed method has several advantages over the known methods, first of all, it is sufficient ease of implementation, low resource intensity and accuracy of prediction, which can be enhanced by the use of quadratic or cubic interpolation spline functions. Using the method of spline extrapolation, the results of self-similar traffic prediction were obtained, which will allow to predict the required volume of buffer devices, thereby avoiding network congestion and exceeding the normative values ​​of QoS quality characteristics. Given that self-similar traffic is characterized by the presence of "bursts" and a long-term dependence between the moments of receipt of applications in this study, given predetermined data to improve the prediction accuracy, it is possible to use extrapolation based on wavelet functions, the so-called wavelet-extrapolation method. Based on the results of traffic forecasting, taking into account the maximum values ​​of network node traffic, you can give practical guidance on how traffic is redistributed across the network. This will balance the load of network objects and increase the efficiency of network equipment.

States analysis and Agent modeling for wireless sensor network nodes

2011 ◽  
Vol 30 (12) ◽  
pp. 3155-3157
Author(s):  
Zhi CHEN ◽  
Jie SHI ◽  
Ying KONG ◽  
Yun ZHANG
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Wireless Sensor ◽  
Agent Modeling ◽  
Network Nodes

Spatial-temporal data collection process models using mobile sinks

2019 ◽  
Vol 942 (12) ◽  
pp. 22-28
Author(s):  
A.V. Materuhin ◽  
V.V. Shakhov ◽  
O.D. Sokolova
Keyword(s):  
Energy Consumption ◽  
Operation Time ◽  
Point Of View ◽  
Process Models ◽  
Temporal Data ◽  
Network Nodes ◽  
Mobile Sinks ◽  
Autonomous Operation ◽  
Data Collection Process ◽  
Spatio Temporal

Optimization of energy consumption in geosensor networks is a very important factor in ensuring stability, since geosensors used for environmental monitoring have limited possibilities for recharging batteries. The article is a concise presentation of the research results in the area of increasing the energy consumption efficiency for the process of collecting spatio-temporal data with wireless geosensor networks. It is shown that in the currently used configurations of geosensor networks there is a predominant direction of the transmitted traffic, which leads to the fact that through the routing nodes that are close to the sinks, a much more traffic passes than through other network nodes. Thus, an imbalance of energy consumption arises in the network, which leads to a decrease in the autonomous operation time of the entire wireless geosensor networks. It is proposed to use the possible mobility of sinks as an optimization resource. A mathematical model for the analysis of the lifetime of a wireless geosensor network using mobile sinks is proposed. The model is analyzed from the point of view of optimization energy consumption by sensors. The proposed approach allows increasing the lifetime of wireless geosensor networks by optimizing the relocation of mobile sinks.

GPS Aided GEO Augmented Navigation Enabled Energy Efficient Routing for Mobile Ad-hoc Wireless Networks

2017 ◽  
Vol 2 (7) ◽  
pp. 5-8
Author(s):  
Neeraj Verma ◽  
Kuber Mohan
Keyword(s):  
Energy Efficient ◽  
Ad Hoc ◽  
Mobile Ad Hoc Network ◽  
Critical Issue ◽  
Ad Hoc Wireless Networks ◽  
Energy Utilization ◽  
Energy Efficient Routing ◽  
Network Nodes ◽  
Mobile Ad Hoc ◽  
Hoc Networks

Energy is a critical issue in Mobile Ad-hoc Network. Nodes in Network are working in presence of limited or less energy due to dynamic nature of nodes or infrastructure less network. MANET has no infrastructure so nodes in MANET work on dynamic routing. In this way, energy proficient routing is required for reducing energy utilization. Energy proficient routing plans can extraordinarily reduce energy utilization and augments the lifetime of the networks. Scalability of Ad Hoc Networks can be enhanced by using land data, for example, in LAR, GPSR etc. They utilize physical area data; regularly from GPS (Global Positioning System).GPS empowers a gadget to decide their position as in longitude, Latitude and Altitude by getting this data from the satellites. There has been significant effort in proposing energy efficient routing protocols with the help of GAGAN (GPS Aided GEO Augmented Navigation) which have accuracy to approx One meter in India or its neighbor countries. GAGAN is a route framework which is helped by both GPS and nearby telemetry information to possibly give quicker and more exact situating and navigational information.

scholarly journals You Only Look Once, But Compute Twice: Service Function Chaining for Low-Latency Object Detection in Softwarized Networks

2021 ◽  
Vol 11 (5) ◽  
pp. 2177
Author(s):  
Zuo Xiang ◽  
Patrick Seeling ◽  
Frank H. P. Fitzek
Keyword(s):  
Machine Learning ◽  
Object Detection ◽  
Low Latency ◽  
Connected Vehicles ◽  
Network Nodes ◽  
Machine Learning Model ◽  
Fold Reduction ◽  
Broad Variety ◽  
Computational Resources ◽  
Service Latency

With increasing numbers of computer vision and object detection application scenarios, those requiring ultra-low service latency times have become increasingly prominent; e.g., those for autonomous and connected vehicles or smart city applications. The incorporation of machine learning through the applications of trained models in these scenarios can pose a computational challenge. The softwarization of networks provides opportunities to incorporate computing into the network, increasing flexibility by distributing workloads through offloading from client and edge nodes over in-network nodes to servers. In this article, we present an example for splitting the inference component of the YOLOv2 trained machine learning model between client, network, and service side processing to reduce the overall service latency. Assuming a client has 20% of the server computational resources, we observe a more than 12-fold reduction of service latency when incorporating our service split compared to on-client processing and and an increase in speed of more than 25% compared to performing everything on the server. Our approach is not only applicable to object detection, but can also be applied in a broad variety of machine learning-based applications and services.

scholarly journals Polaritonic XY-Ising machine

Nanophotonics ◽  
2020 ◽  
Vol 9 (13) ◽  
pp. 4127-4138 ◽  
Author(s):  
Kirill P. Kalinin ◽  
Alberto Amo ◽  
Jacqueline Bloch ◽  
Natalia G. Berloff
Keyword(s):  
Dissipative Systems ◽  
Phase Information ◽  
Physical Origin ◽  
Continuous Spin ◽  
Network Nodes ◽  
Computing Platform ◽  
Ability To Act ◽  
Spin Hamiltonians ◽  
Long Range Interactions ◽  
Accuracy And Stability

AbstractGain-dissipative systems of various physical origin have recently shown the ability to act as analogue minimisers of hard combinatorial optimisation problems. Whether or not these proposals will lead to any advantage in performance over the classical computations depends on the ability to establish controllable couplings for sufficiently dense short- and long-range interactions between the spins. Here, we propose a polaritonic XY-Ising machine based on a network of geometrically isolated polariton condensates capable of minimising discrete and continuous spin Hamiltonians. We elucidate the performance of the proposed computing platform for two types of couplings: relative and absolute. The interactions between the network nodes might be controlled by redirecting the emission between the condensates or by sending the phase information between nodes using resonant excitation. We discuss the conditions under which the proposed machine leads to a pure polariton simulator with pre-programmed couplings or results in a hybrid classical polariton simulator. We argue that the proposed architecture for the remote coupling control offers an improvement over geometrically coupled condensates in both accuracy and stability as well as increases versatility, range, and connectivity of spin Hamiltonians that can be simulated with polariton networks.

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