PRAC: private and rateless adaptive coded computation at the edge

Rawad Bitar; Yuxuan Xing; Yasaman Keshtkarjahromi; Venkat Dasari; Salim El Rouayheb; Hulya Seferoglu

doi:10.1117/12.2519768

10 May 2019 PRAC: private and rateless adaptive coded computation at the edge

Rawad Bitar, Yuxuan Xing, Yasaman Keshtkarjahromi, Venkat Dasari, Salim El Rouayheb, Hulya Seferoglu

Proceedings Volume 11013, Disruptive Technologies in Information Sciences II; 110130T (2019) https://doi.org/10.1117/12.2519768
Event: SPIE Defense + Commercial Sensing, 2019, Baltimore, MD, United States

Abstract

Edge computing is emerging as a new paradigm to allow processing data near the edge of the network, where the data is typically generated and collected. This enables critical computations at the tactical edge in applications such as Internet of Battlefield Things (IoBT), in which an increasing number of devices (sensors, cameras, health monitoring devices, etc.) collect data that needs to be processed through computationally intensive algorithms with stringent reliability, security and latency constraints. Our key tool is the theory of coded computation, which advocates mixing data in computationally intensive tasks by employing erasure codes and offloading these tasks to other devices for computation. Coded computation is recently gaining interest, thanks to its higher reliability, smaller delay, and lower communication costs. In this paper, we develop a private and rateless adaptive coded computation (PRAC) algorithm by taking into account (i) the privacy requirements of IoBT applications and devices, and (ii) the heterogeneous and time-varying resources of edge devices. We show that PRAC outperforms known secure coded computing methods when resources are heterogeneous. We provide theoretical guarantees on the performance of PRAC and its comparison to baselines. Moreover, we confirm our theoretical results through simulations.

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Citation Download Citation

Rawad Bitar, Yuxuan Xing, Yasaman Keshtkarjahromi, Venkat Dasari, Salim El Rouayheb, and Hulya Seferoglu "PRAC: private and rateless adaptive coded computation at the edge", Proc. SPIE 11013, Disruptive Technologies in Information Sciences II, 110130T (10 May 2019); https://doi.org/10.1117/12.2519768

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