scholarly journals A Survey of the Research on Future Internet and Network Architectures

2013 ◽  
Vol E96.B (6) ◽  
pp. 1385-1401 ◽  
Author(s):  
Toru HASEGAWA
Keyword(s):  
Future Internet ◽  
Network Architectures

scholarly journals A Review of Advanced Algebraic Approaches Enabling Network Tomography for Future Network Infrastructures

2020 ◽  
Vol 12 (2) ◽  
pp. 20 ◽  
Author(s):  
Grigorios Kakkavas ◽  
Despoina Gkatzioura ◽  
Vasileios Karyotis ◽  
Symeon Papavassiliou
Keyword(s):  
Network Coding ◽  
Technology Development ◽  
Network Monitoring ◽  
Future Internet ◽  
Network Architectures ◽  
Network Tomography ◽  
Fundamental Operation ◽  
Qualitative Comparison ◽  
Algebraic Approaches

Network tomography has emerged as one of the lean approaches for efficient network monitoring, especially aiming at addressing the ever-increasing requirements for scaling and efficiency in modern network architectures and infrastructures. In this paper, we explore network coding and compressed sensing as enabling technologies in the context of network tomography. Both approaches capitalize on algebraic tools for achieving accuracy while allowing scaling of operation as the size of the monitored network increases. Initially, a brief overview of the tomographic problems and the related classification of methods is provided to better comprehend the problems encountered and solutions provided to date. Subsequently, we present representative approaches that employ either one of the aforementioned technologies and we comparatively describe their fundamental operation. Eventually, we provide a qualitative comparison of features and approaches that can be used for further research and technology development for network monitoring in future Internet infrastructures.

Standardizing a reference model and autonomic network architectures for the self-managing future internet

IEEE Network ◽  
2011 ◽  
Vol 25 (6) ◽  
pp. 50-56 ◽  
Author(s):  
Michal Wodczak ◽  
Tayeb Ben Meriem ◽  
Benoit Radier ◽  
Ranganai Chaparadza ◽  
Kevin Quinn ◽  
...  
Keyword(s):  
Reference Model ◽  
Future Internet ◽  
The Self ◽  
Network Architectures

Future SDN-Based Network Architectures

2015 ◽  
pp. 364-382
Author(s):  
Evangelos Haleplidis ◽  
Spyros Denazis ◽  
Odysseas Koufopavlou
Keyword(s):  
Software Defined Networking ◽  
Future Internet ◽  
Point Of View ◽  
Network Architectures ◽  
Broad Definition ◽  
Programmable Networks ◽  
Rapid Changes ◽  
The Future ◽  
Future Internet Architectures ◽  
Definition Of

Networking has seen a burst of innovation and rapid changes with the advent of Software Defined Networking (SDN). Many people considered SDN to be something new and innovative, but actually SDN is something that has already been proposed almost a decade ago in the era of active and programmable networks, and developed even before that. Coupled with the fact that SDN is a very dynamic area with everyone trying to brand their architecture, research or product as SDN has defined a vague and broad definition of what SDN. This chapter attempts to put SDN into perspective approaching SDN with a more spherical point of view by providing the necessary background of pre-SDN technologies and how SDN came about. Followed by discussion on what SDN means today, what SDN is comprised of and a vision of how SDN will evolve in the future to provide the programmable networks that researchers and operators have longed for for many years now. This chapter closes with a few applicability use cases of the future SDN and wraps up with how SDN fits in the Future Internet Architectures.

scholarly journals Special Issue “Post-IP Networks: Advances on RINA and other Alternative Network Architectures”

Computers ◽  
2020 ◽  
Vol 9 (4) ◽  
pp. 82
Author(s):  
John Day ◽  
Eduard Grasa ◽  
Peyman Teymoori
Keyword(s):  
Research Funding ◽  
Future Internet ◽  
Ip Networks ◽  
Network Protocol ◽  
Network Architectures ◽  
Next Generation ◽  
Special Issue ◽  
Protocol Architecture

Over the last two decades, research funding bodies have supported “Future Internet”, “New-IP”, and “Next Generation” design initiatives intended to reduce network complexity by redesigning the network protocol architecture, questioning some of its key principles [...]

scholarly journals A collaborative caching strategy in contentcentric networking

2018 ◽  
Vol 189 ◽  
pp. 03018 ◽  
Author(s):  
Qing Hu ◽  
Chengming Li ◽  
Touhidul Hasan ◽  
Chengjun Li ◽  
Qingshan Jiang
Keyword(s):  
Performance Optimization ◽  
Future Internet ◽  
Original Data ◽  
Core Area ◽  
Communication Overhead ◽  
Network Architectures ◽  
Data Redundancy ◽  
Content Centric Networking ◽  
Caching Strategy ◽  
Collaborative Caching

Content-centric Networking (CCN) is one of the most promising network architectures for the future Internet. In-network caching is an attractive feature of CCN, however, the existing research does not consider the off-path nodes, or gives a large communication overhead for cooperation, which makes the caching utilization lower, and hard to achieve comprehensive performance optimization. To reduce the data redundancy and improve the caching utilization, we propose a Regional Hashing Collaborative Caching Strategy (RHCCS). According to calculate the importance of nodes in the network topology, we divide the network into the core area and edge area. In core area, we select the relevant nodes for cooperation, store the block in the off-path nodes with the hashing algorithm, and add a new table in original data structures for routing in the collaborative areas. As for edge area, we deploy the on-path reversion scheme. By simulating in ndnSIM and comparing with the basic caching strategy in CCN, experimental results indicate that the RHCCS can effectively reduce data redundancy, routing hops, requesting delay, and significantly increase the hit rate.

Color Space Transformation using Neural Networks

2019 ◽  
Vol 2019 (1) ◽  
pp. 153-158
Author(s):  
Lindsay MacDonald
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Color Space ◽  
Reflectance Spectra ◽  
Network Architectures ◽  
Color Spaces ◽  
Natural Materials ◽  
Space Transformation ◽  
Color Space Transformation

We investigated how well a multilayer neural network could implement the mapping between two trichromatic color spaces, specifically from camera R,G,B to tristimulus X,Y,Z. For training the network, a set of 800,000 synthetic reflectance spectra was generated. For testing the network, a set of 8,714 real reflectance spectra was collated from instrumental measurements on textiles, paints and natural materials. Various network architectures were tested, with both linear and sigmoidal activations. Results show that over 85% of all test samples had color errors of less than 1.0 ΔE2000 units, much more accurate than could be achieved by regression.

Deep Learning Approaches for Whiteboard Image Quality Enhancement

2019 ◽  
Vol 2019 (1) ◽  
pp. 360-368
Author(s):  
Mekides Assefa Abebe ◽  
Jon Yngve Hardeberg
Keyword(s):  
Deep Learning ◽  
Image Quality ◽  
Image Data ◽  
Quality Enhancement ◽  
Network Architectures ◽  
Learning Approaches ◽  
Data Set ◽  
Image Quality Enhancement ◽  
Processing Techniques ◽  
White Balancing

Different whiteboard image degradations highly reduce the legibility of pen-stroke content as well as the overall quality of the images. Consequently, different researchers addressed the problem through different image enhancement techniques. Most of the state-of-the-art approaches applied common image processing techniques such as background foreground segmentation, text extraction, contrast and color enhancements and white balancing. However, such types of conventional enhancement methods are incapable of recovering severely degraded pen-stroke contents and produce artifacts in the presence of complex pen-stroke illustrations. In order to surmount such problems, the authors have proposed a deep learning based solution. They have contributed a new whiteboard image data set and adopted two deep convolutional neural network architectures for whiteboard image quality enhancement applications. Their different evaluations of the trained models demonstrated their superior performances over the conventional methods.

Enabling Things To Talk in Heterogeneous Self-Organizing Networks—An Exhaustive Critique For IOT

GIS Business ◽  
2019 ◽  
Vol 14 (6) ◽  
pp. 728-750
Author(s):  
Naeem Z Azeemi ◽  
Saira Khan ◽  
Sharmini Enoch ◽  
Riktesh Srivastava ◽  
Omar al Basheer ◽  
...  
Keyword(s):  
Mobile Networks ◽  
Adaptive Modulation ◽  
Sustainable Growth ◽  
Adaptive Modulation And Coding ◽  
Network Architectures ◽  
Multiple Antenna ◽  
Multiple Access Schemes ◽  
Natural Outcome ◽  
Air Interfaces ◽  
The Internet Of Things

The superstructure network in the Internet of Things (IoT) is an emerging network targeted to enable an ecosystem of smart applications and services. It connectsphysical resources and peopletogether with software, hence contribute to sustainable growth, provided it combines and guarantees trustand security for people and businesses.  In this work we presented smart city viewpoint opt-in to the Firth Generation (5G) mobile networks. Both a framework and deployment are explored rigorously to assist and predicting robustness of IoT technologies and applications as a natural outcome of the Third Generation Partnership Project (3GPP) in general and LTE in particular. These technologies are compared on the basis of Air Interfaces and their Specifications i.e. Adaptive Modulation and Coding, Multiple Access Schemes and Multiple Antenna Techniques along with the evolution and comparison of the Network Architectures.

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