Enhanced ethernet congestion management scheme for multicast traffic

Abstract

International audienceThe Quantized Congestion Notification (QCN) is a Layer 2 congestion control scheme for Carrier Ethernet data center networks. The QCN has been standardized as an IEEE 802.1Qau Ethernet Congestion Notification standard. This paper report a results of a QCN study with multicast traffic and proposes an enhancement to the QCN. In fact, in order to be able to scale up, the feedback implosion problem has to be solved. Therefore, we resorted to the representative technique, which uses a selected congestion point (i.e., the overloaded queue in a switch), to provide timely and accurate feedback on behalf of the congested switches in the path of multicast traffic. This paper evaluates the rate variation, the feedback overhead, the loss rate, the stability, the fairness, and the scalability performance of the standard QCN with multicast traffic and the enhanced QCN for multicast traffic. This paper also compares their performance criteria. The evaluation results show that the enhanced proposition of the QCN for multicast traffic gives better results than the standard QCN with multicast traffic. Indeed, the feedback implosion problem is settled by decreasing remarkably the feedback rate

Big data‐driven machine learning‐enabled traffic flow prediction

“…1 The purpose of traffic flow prediction is to provide accurate traffic flow information. Traffic flow prediction has received the attention of the traffic management department and the urban area planning department, with the development of information technology.…”

“…Traffic flow prediction has received the attention of the traffic management department and the urban area planning department, with the development of information technology. 1 The purpose of traffic flow prediction is to provide accurate traffic flow information. However, as the road traffic networks expand and the urban layouts are optimized, traffic flow prediction is affected by many complex systems, many of which are artificially uncontrollable.…”

“…Traffic flow prediction is an important component of intelligent transportation systems (ITSs), and it is also of practical significance for traffic regulation and route navigation. Traffic flow prediction has received the attention of the traffic management department and the urban area planning department, with the development of information technology . The purpose of traffic flow prediction is to provide accurate traffic flow information.…”