Scheduling Dynamic IoT Task Graphs

Mohammadali Khodabandehlou; Jared Coleman; Bhaskar Krishnamachari

doi:10.1145/3715014.3724039

Scheduling Dynamic IoT Task Graphs

Mohammadali Khodabandehlou
, Jared Coleman
, Bhaskar Krishnamachari

Computer Science

University of Southern California

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

Scheduling a given graph of tasks on a processing network has been a topic of interest and has been extensively studied, including for IoT applications. However, scheduling a series of task graphs that arrive at different time instances is still under-explored. We discuss this problem and introduce two approaches for it: Residual and Cumulative. We demonstrate using two subtle examples that both approaches face performance challenges.

Original language	English
Title of host publication	Proceedings of the 23rd ACM Conference on Embedded Networked Sensor Systems
Place of Publication	New York, NY, USA
Publisher	Association for Computing Machinery
Pages	624-625
Number of pages	2
ISBN (Print)	9798400714795
DOIs	https://doi.org/10.1145/3715014.3724039
State	Published - 2025

Keywords

Department: Computer Science
Email: [email protected]

Access to Document

10.1145/3715014.3724039

Cite this

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title = "Scheduling Dynamic IoT Task Graphs",

abstract = "Scheduling a given graph of tasks on a processing network has been a topic of interest and has been extensively studied, including for IoT applications. However, scheduling a series of task graphs that arrive at different time instances is still under-explored. We discuss this problem and introduce two approaches for it: Residual and Cumulative. We demonstrate using two subtle examples that both approaches face performance challenges.",

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AB - Scheduling a given graph of tasks on a processing network has been a topic of interest and has been extensively studied, including for IoT applications. However, scheduling a series of task graphs that arrive at different time instances is still under-explored. We discuss this problem and introduce two approaches for it: Residual and Cumulative. We demonstrate using two subtle examples that both approaches face performance challenges.

KW - Department: Computer Science

KW - Email: [email protected]

U2 - 10.1145/3715014.3724039

DO - 10.1145/3715014.3724039

M3 - Conference contribution

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BT - Proceedings of the 23rd ACM Conference on Embedded Networked Sensor Systems

PB - Association for Computing Machinery

CY - New York, NY, USA

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