Related Experiment Videos
Performance evaluation of TCP congestion control variants across application workloads in cloud based networks
Aravinda Swamy D1, Ananya Hegde1, Anantha Chary C M1
1Department of Information Science and Engineering, B.M.S. College of Engineering, Bengaluru, India.
Abstract:
Choosing the right Transmission Control Protocol (TCP) congestion control algorithm matters more in shared cloud environments than is often appreciated, yet head-to-head comparisons across heterogeneous, concurrently running workloads remain rare in the literature. We evaluated three widely used variants Cubic, Reno, and Bottleneck Bandwidth and Round-trip propagation time (BBR) under four workload types: synthetic throughput testing with iperf3, real-time stream processing using Apache Kafka and Apache Flink, distributed I/O, and compute-intensive sorting via Hadoop TeraSort. All experiments ran inside a dumbbell network topology built on four Amazon Web Services (AWS) m7i-flex.large Elastic Compute Cloud (EC2) instances, with a dedicated forwarding node and static routing forcing every flow through that single contention point. Across every metric we measured throughput, end-to-end latency, retransmission count, and job completion time the three variants behaved quite differently depending on the workload. The results give concrete, workload-specific guidance for operators choosing a congestion control policy in multitenant cloud deployments.
Related Concept Videos
Maximum Power Flow and Line Loadability
Production Efficiency
Quantifying Work
Pipe Flowrate Measurement
The orifice meter is a simple,...
Distributed Loads
For example, consider a bookshelf filled with books stacked vertically adjacent to each other. The weight of the books is evenly distributed over the length of the shelf. As a result, the pressure at different locations on the surface of the...