Self-Adapted Admission Control Model for Parlay on Heterogeneous Network

2012 ◽  
Vol 546-547 ◽  
pp. 1164-1170
Author(s):  
Hao Zhou ◽  
Jun Ping Wang ◽  
Suo Ju He
Keyword(s):  
Admission Control ◽  
Heterogeneous Networks ◽  
Heterogeneous Network ◽  
Telecommunication Network ◽  
Control Model ◽  
Application Development ◽  
Control Module ◽  
Simulation Results

Parlay Gateway has played an important role in application development on heterogeneous networks. For many third part’s applications accessing Telecommunication Network through it, it is likely to become the bottleneck of whole system. In this paper, the author proposed a self-adapted control model which is effective in admission control of Parlay Gateway. This method is made up of five modules, which are admission control module, waiting queue module, token generating module, scheduling module, and the overload detecting module. According to some simulation results, the author found it is useful and easy to be implemented.

Quantifying QoS in Heterogeneous Networks

2017 ◽  
pp. 223-251
Author(s):  
Farnaz Farid ◽  
Seyed Shahrestani ◽  
Chun Ruan
Keyword(s):  
Wireless Networks ◽  
Heterogeneous Networks ◽  
Heterogeneous Network ◽  
The Other ◽  
Simulation Studies ◽  
Network Resources ◽  
Access Technology ◽  
Vast Number ◽  
Simulation Results ◽  
4G Wireless

The heterogeneous-based 4G wireless networks will offer noticeable advantages for both users and network operators. The users will benefit from the vibrant coverage and capacity. A vast number of available resources will allow them to connect seamlessly to the best available access technology. The network operators, on the other hand, will be benefited from the lower cost and the efficient usage of the network resources. However, managing QoS for video or voice applications over these networks is still a challenging task. In this chapter, a generalized metric-based approach is described for QoS quantification in Heterogeneous networks. To investigate the efficiency of the designed approach, a range of simulation studies based on different models of service over the heterogeneous networks are carried out. The simulation results indicate that the proposed approach facilitates better management and monitoring of heterogeneous network configurations and applications utilizing them.

scholarly journals Optimal Decision-Making to Charge Electric Vehicles in Heterogeneous Networks: Stackelberg Game Approach

Energies ◽  
2019 ◽  
Vol 12 (2) ◽  
pp. 325 ◽  
Author(s):  
Shijun Chen ◽  
Huwei Chen ◽  
Shanhe Jiang
Keyword(s):  
Electric Vehicles ◽  
Heterogeneous Networks ◽  
Demand Uncertainty ◽  
Stackelberg Game ◽  
Optimal Solution ◽  
Stackelberg Equilibrium ◽  
Optimal Decision ◽  
Charging Station ◽  
Simulation Results ◽  
Grid Operators

Electric vehicles (EVs) are designed to improve the efficiency of energy and prevent the environment from being polluted, when they are widely and reasonably used in the transport system. However, due to the feature of EV’s batteries, the charging problem plays an important role in the application of EVs. Fortunately, with the help of advanced technologies, charging stations powered by smart grid operators (SGOs) can easily and conveniently solve the problems and supply charging service to EV users. In this paper, we consider that EVs will be charged by charging station operators (CSOs) in heterogeneous networks (Hetnet), through which they can exchange the information with each other. Considering the trading relationship among EV users, CSOs, and SGOs, we design their own utility functions in Hetnet, where the demand uncertainty is taken into account. In order to maximize the profits, we formulate this charging problem as a four-stage Stackelberg game, through which the optimal strategy is studied and analyzed. In the Stackelberg game model, we theoretically prove and discuss the existence and uniqueness of the Stackelberg equilibrium (SE). Using the proposed iterative algorithm, the optimal solution can be obtained in the optimization problem. The performance of the strategy is shown in the simulation results. It is shown that the simulation results confirm the efficiency of the model in Hetnet.

scholarly journals MultiVERSE: a multiplex and multiplex-heterogeneous network embedding approach

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Léo Pio-Lopez ◽  
Alberto Valdeolivas ◽  
Laurent Tichit ◽  
Élisabeth Remy ◽  
Anaïs Baudot
Keyword(s):  
Heterogeneous Networks ◽  
Heterogeneous Network ◽  
Link Prediction ◽  
Network Embedding ◽  
Multiplex Networks ◽  
Multiplex Network ◽  
Gene Associations ◽  
Different Types ◽  
Embedding Methods ◽  
Node Embeddings

AbstractNetwork embedding approaches are gaining momentum to analyse a large variety of networks. Indeed, these approaches have demonstrated their effectiveness in tasks such as community detection, node classification, and link prediction. However, very few network embedding methods have been specifically designed to handle multiplex networks, i.e. networks composed of different layers sharing the same set of nodes but having different types of edges. Moreover, to our knowledge, existing approaches cannot embed multiple nodes from multiplex-heterogeneous networks, i.e. networks composed of several multiplex networks containing both different types of nodes and edges. In this study, we propose MultiVERSE, an extension of the VERSE framework using Random Walks with Restart on Multiplex (RWR-M) and Multiplex-Heterogeneous (RWR-MH) networks. MultiVERSE is a fast and scalable method to learn node embeddings from multiplex and multiplex-heterogeneous networks. We evaluate MultiVERSE on several biological and social networks and demonstrate its performance. MultiVERSE indeed outperforms most of the other methods in the tasks of link prediction and network reconstruction for multiplex network embedding, and is also efficient in link prediction for multiplex-heterogeneous network embedding. Finally, we apply MultiVERSE to study rare disease-gene associations using link prediction and clustering. MultiVERSE is freely available on github at https://github.com/Lpiol/MultiVERSE.

Road Feel Design for Vehicle Steer-by-Wire System Based on Joystick

2013 ◽  
Vol 336-338 ◽  
pp. 734-737
Author(s):  
Hong Yu Zheng ◽  
Ya Ning Han ◽  
Chang Fu Zong
Keyword(s):  
Computer Simulation ◽  
Control Strategy ◽  
Vehicle Speed ◽  
Control Module ◽  
Matlab Simulink ◽  
The Road ◽  
Steering Feel ◽  
Steer By Wire ◽  
Simulation Results ◽  
Wire System

In order to solve the problem of road feel feedback of vehicle steer-by-wire (SBW) system based on joystick, a road feel control strategy was established to analyze the road feel theory of traditional steer system, which included return, assist and damp control module. By verifying the computer simulation results with the control strategy from software of CarSim and Matlab/Simulink, it shows that the proposed strategy can effective get road feel in different vehicle speed conditions and could improve the vehicle maneuverability to achieve desired steering feel by different drivers.

scholarly journals The Reversing Paging Process of Callee in Heterogeneous Networks

2011 ◽  
Vol 1 ◽  
pp. 3-8
Author(s):  
Cong Zhao ◽  
Wei Guo
Keyword(s):  
Heterogeneous Networks ◽  
Mobility Management ◽  
Heterogeneous Network ◽  
Vertical Handoff ◽  
The Past ◽  
The Future ◽  
Wireless Signal ◽  
Set Up

To achieve the goal that anybody could communicate with anyone at anytime in anyplace and in anyway, many technologies, such as GSM、CDMA、WCDMA、CDMA2000、TD-SCDMA、802.11a/b/g and so on, come true in the past years. And now, many B3G or 4G technologies are being studied. It is well-known that the future network would be heterogeneous networks. It is studied in this paper the mobility management of wireless heterogeneous network and a reversing paging process of callee is proposed which integrates paging and handoff. In the process when the caller pages the callee choosing its best suited network on one end, the callee chooses its own best network to begin a reversing paging process to set up the communication. The simulation tells that the proposed process has better performances in the call delay, the call succeeding rate and the wireless signal cost than that of the existing process in which it sets up the call first and then does vertical handoff independently.

Prospects of Open Source Software for Maximizing the User Expectations in Heterogeneous Network

2021 ◽  
pp. 257-271
Author(s):  
Pushpa Singh ◽  
Rajeev Agrawal
Keyword(s):  
Machine Learning ◽  
Open Source ◽  
Real Time ◽  
Open Source Software ◽  
Heterogeneous Networks ◽  
Heterogeneous Network ◽  
Research Work ◽  
Software Tool ◽  
Knn Classifier ◽  
User Expectations

This article focuses on the prospects of open source software and tools for maximizing the user expectations in heterogeneous networks. The open source software Python is used as a software tool in this research work for implementing machine learning technique for the categorization of the types of user in a heterogeneous network (HN). The KNN classifier available in Python defines the type of user category in real time to predict the available users in a particular category for maximizing profit for a business organization.

scholarly journals Research on Optimized Control Model of Freeway Based on Dynamic Traffic Demand Estimation

2014 ◽  
Vol 6 ◽  
pp. 797293 ◽  
Author(s):  
Zhu Jiang ◽  
Shubin Li
Keyword(s):  
Optimal Control ◽  
Real Time ◽  
Demand Estimation ◽  
Control Model ◽  
Control Module ◽  
Traffic Demand ◽  
The Real ◽  
Traffic Conditions ◽  
Real Time Traffic ◽  
Global Optimal

According to the estimation information of dynamic traffic demands, a novel optimal control model of freeway was established on the basis of the hierarchical concept. There are four control modules in this model. The OD prediction module predicts the total traffic demands in a long time and determines the upper bound of the future queuing length in advance; the global optimal control module predicts the future traffic state and establishes the coordination constraints for each ramp in the network; the traffic demand estimation module estimates the real-time traffic conditions for each ramp; the local adaptive control module regulates ramp metering rate according to the estimated information of the real-time traffic conditions and the results optimized by the global optimal control module. The simulation results show that this control system is of a good dynamic performance. It coordinates the benefits of various ramps and optimizes the overall performance of the freeway network.

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