scholarly journals Software-Defined Congestion Control Algorithm for IP Networks

2017 ◽  
Vol 2017 ◽  
pp. 1-8 ◽  
Author(s):  
Yao Hu ◽  
Ting Peng ◽  
Lianming Zhang
Keyword(s):  
Congestion Control ◽  
Transmission Control Protocol ◽  
Rapid Evolution ◽  
Centralized Control ◽  
Network Congestion ◽  
Ip Network ◽  
Key Factor ◽  
Flow Information ◽  
Underlying Network ◽  
The Difference

The rapid evolution of computer networks, increase in the number of Internet users, and popularity of multimedia applications have exacerbated the congestion control problem. Congestion control is a key factor in ensuring network stability and robustness. When the underlying network and flow information are unknown, the transmission control protocol (TCP) must increase or reduce the size of the congestion window to adjust to the changes of traffic in the Internet Protocol (IP) network. However, it is possible that a software-defined approach can relieve the network congestion problem more efficiently. This approach has the characteristic of centralized control and can obtain a global topology for unified network management. In this paper, we propose a software-defined congestion control (SDCC) algorithm for an IP network. We consider the difference between TCP and the user datagram protocol (UDP) and propose a new method to judge node congestion. We initially apply the congestion control mechanism in the congested nodes and then optimize the link utilization to control network congestion.

scholarly journals D-OLIA: A Hybrid MPTCP Congestion Control Algorithm with Network Delay Estimation

Sensors ◽  
2021 ◽  
Vol 21 (17) ◽  
pp. 5764 ◽  
Author(s):  
Tabassum Lubna ◽  
Imtiaz Mahmud ◽  
Geon-Hwan Kim ◽  
You-Ze Cho
Keyword(s):  
Congestion Control ◽  
Transmission Control Protocol ◽  
Network Capacity ◽  
Delay Condition ◽  
Network Delay ◽  
Trip Time ◽  
Congestion Control Algorithm ◽  
Underlying Network ◽  
Improved Performance ◽  
Single Path

With the recent evolution of mobile technology, modern devices equipped with multiple communication interfaces have become popular. The multipath transmission control protocol (MPTCP) has evolved to facilitate multiple communication interfaces through a single TCP connection for faster Internet access. MPTCP congestion control algorithms (MPTCP-CCAs) control data flow by fulfilling three design goals, i.e., ensuring improvement over single-path flows, ensuring fairness, and balancing congestion. Current MPTCP-CCAs cannot fulfill these design goals. For example, the opportunistic-linked increase algorithm (OLIA), a well-known MPTCP-CCA in load balancing, often results in low throughput because it cannot properly utilize the underlying network. In addition, the current Internet has a rapidly changing characteristic due to a large amount of short-lived traffic, making it difficult for MPTCP-CCAs to cope. An awareness of prevailing network delay conditions might help MPTCP-CCAs to utilize the network capacity fully. Therefore, we propose dynamic OLIA (D-OLIA), a hybrid MPTCP-CCA that enhances the performance of OLIA by integrating an awareness of the current network delay condition for deciding the congestion window (CWND) decrease factor. We estimate the current network delay condition, i.e., less-congested or congested, by observing the changes in the round-trip-time (RTT). Based on the estimated network delay condition, we decide the CWND decrease factor in real-time for reducing the CWND during packet loss events. We implemented D-OLIA in the Linux kernel and experimented using the Mininet emulator. The emulation results demonstrate that D-OLIA successfully estimates current network delay conditions and results in approximately a 20% increased throughput compared to the original OLIA. Compared to certain MPTCP-CCAs, it also yields a highly improved performance in terms of throughput, RTT, packet retransmissions, and fairness among the MPTCP sub-flows.

scholarly journals A Comprehensive Overview of TCP Congestion Control in 5G Networks: Research Challenges and Future Perspectives

Sensors ◽  
2021 ◽  
Vol 21 (13) ◽  
pp. 4510
Author(s):  
Josip Lorincz ◽  
Zvonimir Klarin ◽  
Julije Ožegović
Keyword(s):  
Congestion Control ◽  
Transmission Control Protocol ◽  
Mobile Network ◽  
Future Research ◽  
Core Network ◽  
5G Networks ◽  
Comprehensive Overview ◽  
Survey Paper ◽  
High Penetration ◽  
Reliable Communications

In today’s data networks, the main protocol used to ensure reliable communications is the transmission control protocol (TCP). The TCP performance is largely determined by the used congestion control (CC) algorithm. TCP CC algorithms have evolved over the past three decades and a large number of CC algorithm variations have been developed to accommodate various network environments. The fifth-generation (5G) mobile network presents a new challenge for the implementation of the TCP CC mechanism, since networks will operate in environments with huge user device density and vast traffic flows. In contrast to the pre-5G networks that operate in the sub-6 GHz bands, the implementation of TCP CC algorithms in 5G mmWave communications will be further compromised with high variations in channel quality and susceptibility to blockages due to high penetration losses and atmospheric absorptions. These challenges will be particularly present in environments such as sensor networks and Internet of Things (IoT) applications. To alleviate these challenges, this paper provides an overview of the most popular single-flow and multy-flow TCP CC algorithms used in pre-5G networks. The related work on the previous examinations of TCP CC algorithm performance in 5G networks is further presented. A possible implementation of TCP CC algorithms is thoroughly analysed with respect to the specificities of 5G networks, such as the usage of high frequencies in the mmWave spectrum, the frequent horizontal and vertical handovers, the implementation of the 5G core network, the usage of beamforming and data buffering, the exploitation of edge computing, and the constantly transmitted always-on signals. Moreover, the capabilities of machine learning technique implementations for the improvement of TCPs CC performance have been presented last, with a discussion on future research opportunities that can contribute to the improvement of TCP CC implementation in 5G networks. This survey paper can serve as the basis for the development of novel solutions that will ensure the reliable implementation of TCP CC in different usage scenarios of 5G networks.

Selective Transport of Water-Soluble Proteins from Aqueous to Ionic Liquid Phase via a Temperature-Sensitive Phase Change of These Mixtures

2012 ◽  
Vol 65 (11) ◽  
pp. 1548 ◽  
Author(s):  
Yuki Kohno ◽  
Nobuhumi Nakamura ◽  
Hiroyuki Ohno
Keyword(s):  
Phase Change ◽  
Aqueous Phase ◽  
Selective Dissolution ◽  
Selective Extraction ◽  
Soluble Proteins ◽  
Water Soluble ◽  
Temperature Sensitive ◽  
Salting Out ◽  
Key Factor ◽  
The Difference

Mixtures of some ionic liquids (ILs) and water show reversible phase change between a homogeneous mixture and phase-separated state by a small change in temperature. Some water-soluble proteins have been migrated from the aqueous to the IL phase. When tetrabutylphosphonium 2,4,6-trimethylbenzenesulfonate was used as an IL, cytochrome c (Cyt.c) was found to be extracted from the water phase to the IL phase. Conversely, both horseradish peroxidase (HRP) and azurin remained in the aqueous phase. This selective extraction was comprehended to be due to the difference in solubility of these proteins in both phases. The separated aqueous phase contained a small amount of IL, which induced the salting-out of Cyt.c. On the other hand, condensed IL phase promoted the salting-in of Cyt.c. As a result, Cyt.c was preferably dissolved in the hydrated IL phase rather than aqueous phase. In the case of HRP, there was only a salting-out profile upon increasing the concentration of IL, which induced selective dissolution of HRP in the aqueous phase. These results clearly suggest that the profile of salting-out and salting-in for proteins is the key factor to facilitate the selective extraction of proteins from aqueous to the IL phase.

scholarly journals A Model-based Scalable Reliable Multicast Transport Protocol for Satellite Networks

2017 ◽  
Vol 1 (1) ◽  
pp. 24
Author(s):  
Prawit Chumchu ◽  
Roksana Boreli ◽  
Aruna Seneviratne
Keyword(s):  
Congestion Control ◽  
Error Control ◽  
Forward Error Correction ◽  
Transmission Control Protocol ◽  
Window Size ◽  
Satellite Networks ◽  
Transport Protocol ◽  
Reliable Multicast ◽  
Auto Repeat Request ◽  
Control Part

In this paper, we design a new scalable reliable multicast transport protocol for satellite networks (RMT). This paper is the extensions of paper in [18]. The proposed protocoldoes not require inspection and/or interception of packets at intermediate nodes. The protocol would not require anymodification of satellites, which could be bent-pipe satellites or onboard processing satellites. The proposed protocol is divided in 2 parts: error control part and congestion control part. In error control part, we intend to solve feedback implosion and improve scalability by using a new hybrid of ARQ (Auto Repeat Request) and adaptive forward error correction (AFEC). The AFEC algorithm adapts proactive redundancy levels following the number of receivers and average packet loss rate. This leads to a number of transmissions and the number of feedback signals are virtually independent of the number of receivers. Therefore, wireless link utilization used by the proposed protocol is virtually independent of the number of multicast receivers. In congestion control part, the proposed protocol employs a new window-based congestion control scheme, which is optimized for satellite networks. To be fair to the other traffics, the congestion control mimics congestion control in the wellknown Transmission Control Protocol (TCP) which relies on “packet conservation” principle. To reduce feedback implosion, only a few receivers, ACKers, are selected to report the receiving status. In addition, in order to avoid “drop-to-zero” problem, we use a new simple wireless loss filter algorithm. This loss filter algorithm significantly reduces the probability of the congestion window size to be unnecessarily reduced because of common wireless losses. Furthermore, to improve achievable throughput, we employ slow start threshold adaptation based on estimated bandwidth. The congestion control also deals with variations in network conditions by dynamically electing ACKers.

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