In-network compute extensions for rate-adaptive content delivery in mobile networks

Conference Paper

Traffic from mobile wireless networks has been growing at a fast pace in recent years and is expected to surpass wired traffic very soon. Service providers face significant challenges at such scales including providing seamless mobility, efficient data delivery, security, and provisioning capacity at the wireless edge. In the Mobility First project, we have been exploring clean slate enhancements to the network protocols that can inherently provide support for at-scale mobility and trustworthiness in the Internet. An extensible data plane using pluggable compute-layer services is a key component of this architecture. We believe these extensions can be used to implement in-network services to enhance mobile end-user experience by either off-loading work and/or traffic from mobile devices, or by enabling en-route service-adaptation through context-awareness (e.g., Knowing contemporary access bandwidth). In this work we present details of the architectural support for in-network services within Mobility First, and propose protocol and service-API extensions to flexibly address these pluggable services from end-points. As a demonstrative example, we implement an in network service that does rate adaptation when delivering video streams to mobile devices that experience variable connection quality. We present details of our deployment and evaluation of the non-IP protocols along with compute-layer extensions on the GENI test bed, where we used a set of programmable nodes across 7 distributed sites to configure a Mobility First network with hosts, routers, and in-network compute services.

Full Text

Duke Authors

Cited Authors

  • Bronzino, F; Han, C; Chen, Y; Nagaraja, K; Yang, X; Seskar, I; Raychaudhuri, D

Published Date

  • December 9, 2014

Published In

Start / End Page

  • 511 - 517

International Standard Serial Number (ISSN)

  • 1092-1648

International Standard Book Number 13 (ISBN-13)

  • 9781479962044

Digital Object Identifier (DOI)

  • 10.1109/ICNP.2014.81

Citation Source

  • Scopus