Optimizing data center network throughput by solving TCP Incast problem using k‐means algorithm

Abstract

SummaryTCP in casting referred to as one of the complex problems in the data center, which receives a huge amount of traffic volume from n number of senders. There are many methods proposed to solve the TCP Incast problem. In this paper, there are two steps proposed: (i) grouping sender nodes using the k‐means algorithm and (ii) handling incoming packets from the senders after grouping. Grouping senders make it easy to handle the incoming packets effectively as the complexity reduces reasonably. This is achieved through the k‐means algorithm that groups the senders and makes a priority queue for each group. The second step can be achieved through Pro‐Ack (Pro‐Acknowledgement) control in one of the methods for handling a huge volume of data at the receiver side. We demonstrated how the incoming packets can be processed and handled effectively through Pro‐Ack control with the help of the k‐means algorithm. Along with the above concepts, the robust algorithm is proposed to make priority queues. The input throughput also out performs with the existing algorithms.

BL‐Hybrid: A graph‐theoretic approach to improving software‐defined networking‐based data center network performance

“…It is widely used for wide‐scale operations, including the processing of large datasets. Also, DCNs require high‐performance modules to simultaneously handle a wide range of network services, entire communications, and data storage and transport 1‐4 . Therefore, using a software‐defined network (SDN) enhances DCN flexibility by decoupling the control core from forwarding functions.…”

“…Whenever static routing is used in distributing the traffic, the same path is used in each cycle, and this can eventually overload the links and decrease the network performance. Consequently, DCNs tend to cause bottlenecks when storing large numbers of network services, as usage requirements overwhelm the server capacity 2,3,12,13 …”