Papers
Topics
Authors
Recent
Gemini 2.5 Flash
Gemini 2.5 Flash
175 tokens/sec
GPT-4o
7 tokens/sec
Gemini 2.5 Pro Pro
42 tokens/sec
o3 Pro
4 tokens/sec
GPT-4.1 Pro
38 tokens/sec
DeepSeek R1 via Azure Pro
28 tokens/sec
2000 character limit reached

Controlling Congestion via In-Network Content Adaptation (2208.09613v1)

Published 20 Aug 2022 in cs.NI

Abstract: Realizing that it is inherently difficult to precisely match the sending rates at the endhost with the available capacity on dynamic cellular links, we build a system, Octopus, that sends real-time data streams over cellular networks using an imprecise controller (that errs on the side of over-estimating network capacity), and then drops appropriate packets in the cellular network buffers to match the actual capacity. We design parameterized primitives for implementing the packet dropping logic, that the applications at the endhost can configure differently to express different content adaptation policies. Octopus transport encodes the app-specified parameters in packet header fields, which the routers parse to execute the desired dropping behavior. Our evaluation shows how real-time applications involving standard and volumetric videos can be designed to exploit Octopus, and achieve 1.5-50 times better performance than state-of-the-art schemes.

Citations (1)

Summary

We haven't generated a summary for this paper yet.