Bitrate Adaptation of Scalable Bitstreams in a UMTS Environment

2011 ◽  
pp. 147-169
Author(s):  
Nicolas Tizon ◽  
Béatrice Pesquet-Popescu
Keyword(s):  
Network Architecture ◽  
Network Environment ◽  
Channel State ◽  
Input Parameters

In this chapter, we propose a complete streaming framework for a wireless, in particular a 3G/UMTS, network environment. We describe choices one can make in terms of network architecture and then focus on the input parameters used to evaluate network conditions and to perform the adaptation. A particular attention is dedicated to the protocol information one can exploit in order to infer the channel state. In addition, each implementation choice is a compromise between the industrial feasibility and the adaptation efficiency.

scholarly journals MMNET: A Multi-Modal Network Architecture for Underwater Networking

Electronics ◽  
2020 ◽  
Vol 9 (12) ◽  
pp. 2186
Author(s):  
Jun Liu ◽  
Jun Wang ◽  
Shanshan Song ◽  
Junhong Cui ◽  
Xiaoyu Wang ◽  
...  
Keyword(s):  
Heterogeneous Networks ◽  
Network Architecture ◽  
Network Services ◽  
Personalized Recommendation ◽  
Network Resources ◽  
Channel State ◽  
Network Support ◽  
Network Applications ◽  
The Face ◽  
Application Requirements

At present, the key to underwater sensor network (UWSN) research is to provide personalized network support for many underwater applications. In order to achieve this goal, people need a general UWSN. Most of the current UWSN architecture is based on the traditional network, which are limited to a single hardware platform and software platform. Facing the current numerous underwater applications and heterogeneous networks, the UWSN is unable to provide personalized network services according to different application requirements. In this paper, we propose a heterogeneous network framework called MMNET (multimodal network) based on the idea of multimodality, aiming to achieve the compatibility of heterogeneous networks and the scalability of the new architecture. In addition, in the face of the complexity of heterogeneous networks and the personalized needs of network applications, the resource allocation is expressed as a personalized recommendation problem. The distributed personalized recommendation algorithm is used to configure personalized network resources for applications. Each node only needs to solve its own problems, instead of exchanging channel state information by using a distributed algorithm, so the computational complexity can be greatly reduced and signaling is overhead. Finally, we give a special example to prove that our network framework provides a good application.

scholarly journals An Efficient Void Aware Framework for Enabling Internet of Underwater Things

2021 ◽  
Vol 9 (11) ◽  
pp. 1219
Author(s):  
Ahmad M. Khasawneh ◽  
Maryam Altalhi ◽  
Arvind Kumar ◽  
Geetika Aggarwal ◽  
Omprakash Kaiwartya ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Network Architecture ◽  
Information Dissemination ◽  
Pollution Monitoring ◽  
Delivery Ratio ◽  
Network Environment ◽  
Science And Engineering ◽  
Comparative Performance ◽  
Assisted Navigation ◽  
Significant Research

The Internet of Underwater Things (IoUT) is an emerging area in marine science and engineering. It has witnessed significant research and development attention from both academia and industries due to its growing underwater use cases in oceanographic data collection, pollution monitoring, seismic monitoring, tactical surveillance, and assisted navigation for waterway transport. Information dissemination in the underwater network environment is very critical considering network dynamism, unattainable nodes, and limited resources of the tiny IoUT devices. Existing techniques are majorly based on location-centric beacon messages, which results in higher energy consumption, and wastage of computing resources in tiny IoUT devices. Towards this end, this paper presents an efficient void aware (EVA) framework for information dissemination in IoUT environment. Network architecture is modeled considering potential void region identification in the underwater network environment. An efficient void aware (EVA) information dissemination framework is proposed focusing on detecting void network region, and intelligent void aware data forwarding. The comparative performance evaluation attests to the benefits of the proposed framework in terms of energy consumption, network lifetime, packet delivery ratio, and end-to-end delay for information dissemination in IoUT.

scholarly journals A policy conflict detection mechanism for multi-controller software-defined networks

2019 ◽  
Vol 15 (5) ◽  
pp. 155014771984471 ◽  
Author(s):  
You Lu ◽  
Qiming Fu ◽  
Xuefeng Xi ◽  
Zhenping Chen ◽  
Encen Zou ◽  
...  
Keyword(s):  
Network Architecture ◽  
Detection Algorithm ◽  
Conflict Detection ◽  
Detection Methods ◽  
Software Defined Network ◽  
Software Defined Networks ◽  
Network Environment ◽  
Detection Mechanism ◽  
Policy Conflict ◽  
Detection Model

As the network environment expands and becomes more complex, the deficiencies of decision-making capabilities in the single-controller software-defined network architecture are increasingly exposed. Currently, software-defined networks have gradually adopted a multi-controller-based architecture. However, in this architecture, multiple controllers may cause conflicts in the flow policies, which may cause failures such as security and route conflicts. Most of the existing detection methods are only aimed at specific types of conflicts. Aiming at the above insufficiency, this article proposes a policy conflict detection mechanism for multi-controller software-defined network. First, it quantifies and classifies the software-defined policy conflict itself to provide the basis for detection mechanism; then, it proposes a conflict detection model and its deployment scheme for multi-controller software-defined networks; finally, based on the software-defined flow policy’s structure, a multi-branch tree-based policy conflict detection algorithm is proposed to accurately detect the universal types of conflicts. The experimental results under the campus network environment prove that our method can effectively detect the conflict of flow policies existing in the multi-controller software-defined network and has advantages over the existing methods in the integrity, accuracy, and efficiency of the detection.

scholarly journals Model order reduction based on Runge–Kutta neural networks

2021 ◽  
Vol 2 ◽  
Author(s):  
Qinyu Zhuang ◽  
Juan Manuel Lorenzi ◽  
Hans-Joachim Bungartz ◽  
Dirk Hartmann
Keyword(s):  
Dimension Reduction ◽  
Network Architecture ◽  
Model Order Reduction ◽  
Order Reduction ◽  
System State ◽  
Model Reconstruction ◽  
Constant Input ◽  
Model Order ◽  
Input Parameters ◽  
Runge Kutta

Abstract Model order reduction (MOR) methods enable the generation of real-time-capable digital twins, with the potential to unlock various novel value streams in industry. While traditional projection-based methods are robust and accurate for linear problems, incorporating machine learning to deal with nonlinearity becomes a new choice for reducing complex problems. These kinds of methods are independent to the numerical solver for the full order model and keep the nonintrusiveness of the whole workflow. Such methods usually consist of two steps. The first step is the dimension reduction by a projection-based method, and the second is the model reconstruction by a neural network (NN). In this work, we apply some modifications for both steps respectively and investigate how they are impacted by testing with three different simulation models. In all cases Proper orthogonal decomposition is used for dimension reduction. For this step, the effects of generating the snapshot database with constant input parameters is compared with time-dependent input parameters. For the model reconstruction step, three types of NN architectures are compared: multilayer perceptron (MLP), explicit Euler NN (EENN), and Runge–Kutta NN (RKNN). The MLPs learn the system state directly, whereas EENNs and RKNNs learn the derivative of system state and predict the new state as a numerical integrator. In the tests, RKNNs show their advantage as the network architecture informed by higher-order numerical strategy.

Fuzzy Sets Theory in Comparison with Stochastic Methods to Analyse Nonlinear Behaviour of a Steel Member under Compression

2005 ◽  
Vol 10 (1) ◽  
pp. 65-75 ◽  
Author(s):  
Z. Kala
Keyword(s):  
Fuzzy Sets ◽  
Carrying Capacity ◽  
Stochastic Methods ◽  
Nonlinear Behaviour ◽  
Load Carrying Capacity ◽  
Load Carrying ◽  
Input Parameters ◽  
Stochastic Solution ◽  
Fuzzy Solution ◽  
Sets Theory

The load-carrying capacity of the member with imperfections under axial compression is analysed in the present paper. The study is divided into two parts: (i) in the first one, the input parameters are considered to be random numbers (with distribution of probability functions obtained from experimental results and/or tolerance standard), while (ii) in the other one, the input parameters are considered to be fuzzy numbers (with membership functions). The load-carrying capacity was calculated by geometrical nonlinear solution of a beam by means of the finite element method. In the case (ii), the membership function was determined by applying the fuzzy sets, whereas in the case (i), the distribution probability function of load-carrying capacity was determined. For (i) stochastic solution, the numerical simulation Monte Carlo method was applied, whereas for (ii) fuzzy solution, the method of the so-called α cuts was applied. The design load-carrying capacity was determined according to the EC3 and EN1990 standards. The results of the fuzzy, stochastic and deterministic analyses are compared in the concluding part of the paper.

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