The following paper by WiMNet Ph.D. students Varun Gupta and Craig Gutterman, Research Scientist Dr. Yigal Bejerano, Prof. Gil Zussman, and collaborators from Nokia Bell Labs and Verizon was selected as a Runner-up for the Best Paper Award in IEEE INFOCOM’17.
Y. Bejerano, C. Raman, C.-N. Yu, V. Gupta, C. Gutterman, T. Young, H. Infante, Y. Abdelmalek, and G. Zussman, “DyMo: Dynamic Monitoring of large scale LTE-multicast systems,” in Proc. IEEE INFOCOM’17, May 2017. [presentation]
This year IEEE INFOCOM received 1395 submissions and the acceptance ratio was 20.9%.
The paper is motivated by the need to address the growing demand for video delivery over cellular networks in crowded venues (e.g., sport arenas). As envisioned in the AMuSe project, wireless multicast can provide an efficient and cost effective way to deliver content. However, the existing LTE evolved Multimedia Broadcast/Multicast Services (eMBMS) standard lacks efficient mechanisms to monitor the network performance in real time. As a result, the deployment of eMBMS is challenging and impractical. Therefore, cellular operators currently rely on time consuming radio surveys and under-utilize the eMBMS capacity.
The paper proposes the Dynamic Monitoring (DyMo) system for low-overhead feedback collection from thousands of receivers to effectively monitor large eMBMS deployments. DyMo leverages wireless broadcasting capabilities to send group instructions to receivers. These instructions indicate the reporting rates as a function of the observed Quality of Service (QoS). This simple feedback mechanism collects very limited QoS reports and allows for network optimization, thereby ensuring high QoS to the receivers.
The paper evaluates the performance of DyMo using both analysis and extensive simulations. It is shown that DyMo infers the optimal eMBMS settings with extremely low overhead, while meeting strict QoS requirements under different receiver mobility patterns and presence of network component failures. For instance, DyMo can detect the eMBMS Signal-to-Noise Ratio (SNR) experienced by the 0.1% percentile of the receivers with Root Mean Square Error (RMSE) of 0.05% with only 5 to 10 reports per second regardless of the number of receivers.