Transport Protocol Performance and Impact on QoS while on the Move in Current and Future Low Latency Deployments

Transport protocols and mobile networks have evolved independently leading to a lack of adaptability and quality of service (QoS) degradation while running under the variability circumstances present in cellular access. This chapter evaluates the performance of state-of-the-art transmission control protocol (TCP) implementations in challenging mobility scenarios under 4G latencies and low delays that model the proximity service provisioning of forthcoming 5G networks. The evaluation is focused on selecting the most appropriate TCP flavor for each scenario taking into account two metrics: (1) the goodput-based performance and (2) a balanced performance metric that includes parameters based on goodput, delay and retransmitted packets. The results show that mobility scenarios under 4G latencies require more aggressive TCP solutions in order to overcome the high variability in comparison with low latency conditions. Bottleneck Bandwidth and Round-Trip Time-RTT (BBR) provides better scalability than others and Illinois is more capable of sustaining the goodput with big variability between consecutive samples. Besides, CUBIC performs better in lower available capacity scenarios and regarding the balanced metric. In reduced end-to-end latencies, the most suitable congestion control algorithms (CCAs) to maximize the goodput are NewReno (low available capacity) and CUBIC (high available capacity) when moving with continuous capacity increases. Additionally, BBR shows a balanced and controlled behavior in most of the scenarios

Impacts of Channel Variability on Link-Level Throughput in Wireless Networks

We study analytically and experimentally the throughput of the packetized time-varying discrete erasure channel with feedback, which closely captures the behavior of many practical physical layers. We observe that the channel variability at different time scales affects the link-level throughput positively or negatively depending on its time scale. We show that the increased variability in the channel at a time scale smaller than a single packet increases the link-level throughput, whereas the variability at a time scale longer than a single packet reduces it. We express the throughput as a function of the number of transmissions per packet and evaluate it as in terms of the cumulants of the samples of the stochastic processes, which model the channel. We also illustrate our results experimentally using mote radios