A Novel TCP Congestion Control (TCP-CC) Algorithm for Future Internet Applications and Services

2005 ◽  
pp. 75-85
Author(s):  
Haiguang Wang ◽  
Winston Khoon Guan Seah
Keyword(s):  
Congestion Control ◽  
Future Internet ◽  
Internet Applications ◽  
Tcp Congestion Control

A time-dominated TCP congestion control over heterogeneous networks

2008 ◽  
Vol 21 (12) ◽  
pp. 1325-1345 ◽  
Author(s):  
Jongmin Lee ◽  
Hojung Cha ◽  
Rhan Ha
Keyword(s):  
Congestion Control ◽  
Heterogeneous Networks ◽  
Tcp Congestion Control

scholarly journals DeepFogSim: A Toolbox for Execution and Performance Evaluation of the Inference Phase of Conditional Deep Neural Networks with Early Exits Atop Distributed Fog Platforms

2021 ◽  
Vol 11 (1) ◽  
pp. 377
Author(s):  
Michele Scarpiniti ◽  
Enzo Baccarelli ◽  
Alireza Momenzadeh ◽  
Sima Sarv Ahrabi
Keyword(s):  
Neural Networks ◽  
Real Time ◽  
Future Internet ◽  
Operating Conditions ◽  
Graphic User Interface ◽  
Energy Aware ◽  
Internet Applications ◽  
The Real ◽  
Delay Performance ◽  
Hard Constraints

The recent introduction of the so-called Conditional Neural Networks (CDNNs) with multiple early exits, executed atop virtualized multi-tier Fog platforms, makes feasible the real-time and energy-efficient execution of analytics required by future Internet applications. However, until now, toolkits for the evaluation of energy-vs.-delay performance of the inference phase of CDNNs executed on such platforms, have not been available. Motivated by these considerations, in this contribution, we present DeepFogSim. It is a MATLAB-supported software toolbox aiming at testing the performance of virtualized technological platforms for the real-time distributed execution of the inference phase of CDNNs with early exits under IoT realms. The main peculiar features of the proposed DeepFogSim toolbox are that: (i) it allows the joint dynamic energy-aware optimization of the Fog-hosted computing-networking resources under hard constraints on the tolerated inference delays; (ii) it allows the repeatable and customizable simulation of the resulting energy-delay performance of the overall Fog execution platform; (iii) it allows the dynamic tracking of the performed resource allocation under time-varying operating conditions and/or failure events; and (iv) it is equipped with a user-friendly Graphic User Interface (GUI) that supports a number of graphic formats for data rendering. Some numerical results give evidence for about the actual capabilities of the proposed DeepFogSim toolbox.

Design and evaluation of congestion control algorithms in the future Internet

1999 ◽  
Vol 27 (1) ◽  
pp. 212-213 ◽  
Author(s):  
Narayanan Venkitaraman ◽  
Tae-eun Kim ◽  
Kang-Won Lee
Keyword(s):  
Congestion Control ◽  
Future Internet ◽  
Control Algorithms ◽  
The Future
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