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Deadline Constrained Video Analysis via In-Transit Computational Environments

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journal contribution
posted on 29.07.2020, 11:15 by Ali Reza Zamani, Mengsong Zou, Javier Diaz-Montes, Ioan Petri, Omer Rana, Ashiq Anjum, Manish Parashar
Combining edge processing (at data capture site) with analysis carried out while data is enroute from the capture site to a data center offers a variety of different processing models. Such in-transit nodes include network data centers that have generally been used to support content distribution (providing support for data multicast and caching), but have recently started to offer user-defined programmability, through Software Defined Networks (SDN) capability, e.g., OpenFlow and Network Function Visualization (NFV). We demonstrate how this multi-site computational capability can be aggregated to support video analytics, with Quality of Service and cost constraints (e.g., latency-bound analysis). The use of SDN technology enables separation of the data path from the control path, enabling in-network processing capabilities to be supported as data is migrated across the network. We propose to leverage SDN capability to gain control over the data transport service with the purpose of dynamically establishing data routes such that we can opportunistically exploit the latent computational capabilities located along the network path. Using a number of scenarios, we demonstrate the benefits and limitations of this approach for video analysis, comparing this with the baseline scenario of undertaking all such analysis at a data center located at the core of the infrastructure.

Funding

This work is supported in part by US National Science Foundation via grants numbers ACI 1339036, ACI 1441376. The research at Rutgers was conducted as part of the Rutgers Discovery Informatics Institute (RDI2).

History

Citation

A. R. Zamani et al., "Deadline Constrained Video Analysis via In-Transit Computational Environments," in IEEE Transactions on Services Computing, vol. 13, no. 1, pp. 59-72, 1 Jan.-Feb. 2020, doi: 10.1109/TSC.2017.2653116.

Version

VoR (Version of Record)

Published in

IEEE Transactions on Services Computing

Volume

13

Issue

1

Pagination

59 - 72

Publisher

Institute of Electrical and Electronics Engineers with Computer Society

issn

1939-1374

Acceptance date

11/01/2017

Copyright date

2017

Available date

29/07/2020

Language

en

Publisher version

https://ieeexplore.ieee.org/abstract/document/7817858