scholarly journals Internet congestion control: From stochastic to dynamical models

2021 ◽  
pp. 2140009
Author(s):  
José M. Amigó ◽  
Angel Giménez ◽  
Oscar Martínez-Bonastre ◽  
José Valero
Keyword(s):  
Early Detection ◽  
Global Stability ◽  
Nonlinear Models ◽  
The Internet ◽  
Random Early Detection ◽  
Data Traffic ◽  
Data Packets ◽  
Complex Processes ◽  
Management Algorithm ◽  
Stability Robustness

Since its inception, control of data congestion on the Internet has been based on stochastic models. One of the first such models was Random Early Detection. Later, this model was reformulated as a dynamical system, with the average queue sizes at a router’s buffer being the states. Recently, the dynamical model has been generalized to improve global stability. In this paper we review the original stochastic model and both nonlinear models of Random Early Detection with a two-fold objective: (i) illustrate how a random model can be “smoothed out” to a deterministic one through data aggregation and (ii) how this translation can shed light into complex processes such as the Internet data traffic. Furthermore, this paper contains new materials concerning the occurrence of chaos, bifurcation diagrams, Lyapunov exponents and global stability robustness with respect to control parameters. The results reviewed and reported here are expected to help design an active queue management algorithm in real conditions, that is, when system parameters such as the number of users and the round-trip time of the data packets change over time. The topic also illustrates the much-needed synergy of a theoretical approach, practical intuition and numerical simulations in engineering.

scholarly journals Congestion Control in CoAP Observe Group Communication

Sensors ◽  
2019 ◽  
Vol 19 (15) ◽  
pp. 3433 ◽  
Author(s):  
Suwannapong ◽  
Khunboa
Keyword(s):  
Early Detection ◽  
Congestion Control ◽  
Control Mechanism ◽  
Group Communication ◽  
Task Force ◽  
Buffer Overflow ◽  
The Internet ◽  
Random Early Detection ◽  
Lossy Networks ◽  
Congestion Control Mechanism

The Constrained Application Protocol (CoAP) is a simple and lightweight machine-to-machine (M2M) protocol for constrained devices for use in lossy networks which offers a small memory capacity and limited processing. Designed and developed by the Internet Engineering Task Force (IETF), it functions as an application layer protocol and benefits from reliable delivery and simple congestion control. It is implemented for request/response message exchanges over the User Datagram Protocol (UDP) to support the Internet of Things (IoT). CoAP also provides a basic congestion control mechanism. In dealing with its own congestion, it relies on a fixed interval retransmission timeout (RTO) and binary exponential backoff (BEB). However, the default CoAP congestion control is considered to be unable to effectively perform group communication and observe resources, and it cannot handle rapid, frequent requests. This results in buffer overflow and packet loss. To overcome these problems, we proposed a new congestion control mechanism for CoAP Observe Group Communication, namely Congestion Control Random Early Detection (CoCo-RED), consisting of (1) determining and calculating an RTO timer, (2) a Revised Random Early Detection (RevRED) algorithm which has recently been developed and primarily based on the buffer management of TCP congestion control, and (3) a Fibonacci Pre-Increment Backoff (FPB) algorithm which waits for backoff time prior to retransmission. All the aforementioned algorithms were therefore implemented instead of the default CoAP mechanism. In this study, evaluations were carried out regarding the efficiency of the developed CoCo-RED using a Cooja simulator. The congestion control mechanism can quickly handle the changing behaviors of network communication, and thus it prevents the buffer overflow that leads to congestions. The results of our experiments indicate that CoCo-RED can control congestion more effectively than the default CoAP in every condition.

scholarly journals Modeling and Performance Analysis of Dynamic Random Early Detection (DRED) Gateway for Congestion Avoidance

10.28945/2920 ◽  
2005 ◽  
Author(s):  
A. A. Akintola ◽  
G. A. Aderounmu ◽  
L. A. Akanbi ◽  
M. O. Adigun
Keyword(s):  
Performance Analysis ◽  
Early Detection ◽  
Early Response ◽  
Congestion Avoidance ◽  
The Internet ◽  
Random Early Detection ◽  
Queue Size ◽  
Global Synchronization ◽  
Improved Performance ◽  
And Performance

One of the most prominent congestion avoidance schemes in the Internet architecture is the Random Early Detection (RED) algorithm. Several modifications and enhancements have been made to the original RED so as to make it more responsive to congestion avoidance at the gateways. In this paper, we introduced the Dynamic Random Early Detection (DRED) model, which uses a newly introduced parameter i.e. warning line. A robust and efficacious technique to measure the burstiness of incoming traffic has been developed and tested. This involves the estimation of the average queue size, avg, which is dynamically adjusted hence the name of our scheme. The empirical results obtained from the simulations show that our DRED scheme responds early enough to the increased number of packets at the gateway. Also, the maximum drop probability of packets show improved performance over the original RED. It was concluded that our scheme demonstrated superiority by avoiding global synchronization and there is great reduction in the fluctuations of the actual queue size. Also, its early response avoids buffer overflow at the gateways when the queue is near full.

scholarly journals A Highly Effective Route for Real-Time Traffic Using an IoT Smart Algorithm for Tele-Surgery Using 5G Networks

2021 ◽  
Vol 10 (2) ◽  
pp. 30
Author(s):  
Radwan S. Abujassar ◽  
Husam Yaseen ◽  
Ahmad Samed Al-Adwan
Keyword(s):  
Live Streaming ◽  
Data Traffic ◽  
Data Packets ◽  
Real Time Traffic ◽  
Medical Quality ◽  
Optimal Smoothing ◽  
Patient Will ◽  
Three Stages ◽  
Exchange Data

Nowadays, networks use many different paths to exchange data. However, our research will construct a reliable path in the networks among a huge number of nodes for use in tele-surgery using medical applications such as healthcare tracking applications, including tele-surgery which lead to optimizing medical quality of service (m-QoS) during the COVID-19 situation. Many people could not travel due to the current issues, for fear of spreading the covid-19 virus. Therefore, our paper will provide a very trusted and reliable method of communication between a doctor and his patient so that the latter can do his operation even from a far distance. The communication between the doctor and his/her patient will be monitored by our proposed algorithm to make sure that the data will be received without delay. We test how we can invest buffer space that can be used efficiently to reduce delays between source and destination, avoiding loss of high-priority data packets. The results are presented in three stages. First, we show how to obtain the greatest possible reduction in rate variability when the surgeon begins an operation using live streaming. Second, the proposed algorithm reduces congestion on the determined path used for the online surgery. Third, we have evaluated the affection of optimal smoothing algorithm on the network parameters such as peak-to-mean ratio and delay to optimize m-QoS. We propose a new Smart-Rout Control algorithm (s-RCA) for creating a virtual smart path between source and destination to transfer the required data traffic between them, considering the number of hops and link delay. This provides a reliable connection that can be used in healthcare surgery to guarantee that all instructions are received without any delay, to be executed instantly. This idea can improve m-QoS in distance surgery, with trusted paths. The new s-RCA can be adapted with an existing routing protocol to track the primary path and monitor emergency packets received in node buffers, for direct forwarding via the demand path, with extended features.

Design and development of an intelligent system based on the Internet of Things for the early detection of forest fires

2022 ◽  
Vol 12 (2) ◽  
pp. 0-0
Keyword(s):  
Neural Network ◽  
Early Detection ◽  
Forest Fires ◽  
Mobile Applications ◽  
Intelligent System ◽  
The Internet ◽  
Scientific Practices ◽  
Depth Analysis ◽  
Neural Network Algorithm ◽  
The Internet Of Things

Automatic environmental monitoring is a field that encompasses several scientific practices for the assessment of risks that may negatively impact a given environment, such as the forest. A forest is a natural environment that hosts various forms of plant and animal life, so preserving the forest is a top priority. To this end, the authors of this paper will focus on the development of an intelligent system for the early detection of forest fires, based on an IoT solution. This latter will thus facilitate the exploitation of the functionalities offered by the Cloud and mobile applications. Detecting and predicting forest fires with accuracy is a difficult task that requires machine learning and an in-depth analysis of environmental conditions. This leads the authors to adopt the forward neural network algorithm by highlighting its contribution through real experiments, performed on the prototype developed in this paper.

scholarly journals Realtime Data Traffic Analyser Locomotive of Big Data Analytics

2020 ◽  
Vol 8 (6) ◽  
pp. 5643-5646
Keyword(s):  
Communication Networks ◽  
Data Storage ◽  
Communication Systems ◽  
Mean Field ◽  
Big Data Analytics ◽  
The Internet ◽  
Data Traffic ◽  
Time Data ◽  
Storage Security ◽  
Internet Users

Since last decade, the exponential growth of the internet users and the size of data over the internet is increasing day by day, which lead to increase the complexity of the systems by implementing policies and security to avoid attacks on systems and networks. It is very important to understand and analyses the real time data traffic of the communication systems. The purpose of this paper to design a customized Java based application which enables analysts to capture the traffic at the bottleneck under the mean field communication environment where a large number of devices are communicating with each other. The sending data for further processing for analysis the trend to overcome vulnerabilities or to manage the effectiveness of the communication systems. The proposed application enables to capture 8 different types of protocol traffic such as HTTP, HTTPS, SMTP, UDP, TCP, ICMP and POP3. The application allows for analysis of the incoming/outgoing traffic in the visual to understand the nature of communication networks which lead to improve the performance of the networks with respect to hardware, software, data storage, security and reliability.

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