@inproceedings{8f9b9404a26940febb440c8210d7dd60,
title = "Decision-Driven Execution: A Distributed Resource Management Paradigm for the Age of IoT",
abstract = "This paper introduces a novel paradigm for resource management in distributed systems, called decision-driven execution. The paradigm is appropriate for mission-driven systems, where the goal is to enable faster, leaner, and more effective decision making. All resource consumption, in this paradigm, is tied to the needs of making decisions on alternative courses of action. A point of departure from traditional architectures lies in interfaces that allow applications to specify their underlying decision logic. This specification, in turn, allows the system to reason about most effective means to meet information needs of decisions, resulting in simultaneous optimization of decision accuracy, cost, and speed. The paper discusses the overall vision of decision-driven execution, outlining preliminary work and novel challenges.",
keywords = "Decision-driven Execution, Distributed Computing Paradigms, IoT, Learning, Sensor Networks",
author = "Tarek Abdelzaher and Amin, {Md Tanvir A.} and Amotz Bar-Noy and William Dron and Ramesh Govindan and Reginald Hobbs and Shaohan Hu and Kim, {Jung Eun} and Jongdeog Lee and Kelvin Marcus and Shuochao Yao and Yiran Zhao",
note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 37th IEEE International Conference on Distributed Computing Systems, ICDCS 2017 ; Conference date: 05-06-2017 Through 08-06-2017",
year = "2017",
month = jul,
day = "13",
doi = "10.1109/ICDCS.2017.318",
language = "English (US)",
series = "Proceedings - International Conference on Distributed Computing Systems",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "1825--1835",
editor = "Kisung Lee and Ling Liu",
booktitle = "Proceedings - IEEE 37th International Conference on Distributed Computing Systems, ICDCS 2017",
address = "United States",
}