The feasibility of supporting large-scale live streaming applications with dynamic application end-points

TLDR

Application end‑point architectures have proven viable for distributed computing and file sharing, but their feasibility for bandwidth‑intensive live streaming—especially at large scale where heterogeneous bandwidth and dynamic group membership complicate overlay construction—is largely unknown. This study investigates whether application end‑point architectures can feasibly support large‑scale live‑streaming groups. The authors assess feasibility by examining three requirements—resource sufficiency, overlay stability amid group dynamics, and efficient overlay construction—using real‑world CDN traces of live audio and video viewers and evaluating several design alternatives. The results show that in many real‑world scenarios all three requirements are met, and simple algorithms can satisfy them, confirming the feasibility of large‑scale live streaming with application end‑point architectures.

Abstract

While application end-point architectures have proven to be viable solutions for large-scale distributed applications such as distributed computing and file-sharing, there is little known about its feasibility for more bandwidth-demanding applications such as live streaming. Heterogeneity in bandwidth resources and dynamic group membership, inherent properties of application end-points, may adversely affect the construction of a usable and efficient overlay. At large scales, the problems become even more challenging. In this paper, we study one of the most prominent architectural issues in overlay multicast: the feasibility of supporting large-scale groups using an application end-point architecture. We look at three key requirements for feasibility: (i) are there enough resources to construct an overlay, (ii) can a stable and connected overlay be maintained in the presence of group dynamics, and (iii) can an efficient overlay be constructed? Using traces from a large content delivery network, we characterize the behavior of users watching live audio and video streams. We show that in many common real-world scenarios, all three requirements are satisfied. In addition, we evaluate the performance of several design alternatives and show that simple algorithms have the potential to meet these requirements in practice. Overall, our results argue for the feasibility of supporting large-scale live streaming using an application end-point architecture.