Decision-Driven Execution: A Distributed Resource Management Paradigm for the Age of IoT

Abdelzaher, Tarek; Amin, Tanvir Al; Bar-Noy, Amotz; Dron, William; Govindan, Ramesh; Hobbs, Reginald L.; Hu, Shaohan; Kim, Jung-Eun; Lee, Jongdeog; Marcus, Kelvin; Yao, Shuochao; Zhao, Yiran

doi:10.1109/icdcs.2017.318

Cited by 12 publications

(18 citation statements)

References 9 publications

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“…Recent work has made initial progress at solving the above cyber-physical network resource management problem [5,[23][24][25]. The work bears resemblance to prior database research that considered explicit data access transactions and required a degree of data freshness [26][27][28][29].…”

Section: Related Workmentioning

confidence: 89%

“…An abbreviated version of this work was presented at ICDCS 2017 [5]. This paper reviews the earlier work, places the effort in the broader category of decision-driven resource management frameworks, offers additional detail on the algorithms and implementation and significantly expands the evaluation results.…”

Section: Introductionmentioning

confidence: 99%

“…The system can then collect such information ahead of time and update it as the situation changes. In recent work, this information delivery paradigm was called decision-driven execution [5]. It re-thinks scheduling and communication to consider application models that are more pertinent to mission-driven quality-of-service-aware cyber-physical systems.…”

Section: Introductionmentioning

confidence: 99%

“…The choice of decision model itself gives rise to interesting research questions that warrant further attention. In the simplest model, decisions are viewed as choices of a course of action among multiple alternatives [5,25]. More on the decision model will be mentioned later in the paper.…”

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confidence: 99%

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Athena: Towards Decision-Centric Anticipatory Sensor Information Delivery

Lee

Marcus

Abdelzaher

et al. 2018

JSAN

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Abstract:The paper introduces a new direction in quality-of-service-aware networked sensing that designs communication protocols and scheduling policies for data delivery that are optimized specifically for decision needs. The work complements present decision monitoring and support tools and falls in the larger framework of decision-driven resource management. A hallmark of the new protocols is that they are aware of the inference structure used to arrive at decisions (from logical predicates), as well as the data (and data quality) that need to be furnished to successfully evaluate the unknowns on which these decisions are based. Such protocols can therefore anticipate and deliver precisely the right data, at the right level of quality, from the right sources, at the right time, to enable valid and timely decisions at minimum cost to the underlying network. This paper presents the decision model used and the protocol design philosophy, reviews the key recent results and describes a novel system, called Athena, that is the first to embody the aforementioned data delivery paradigm. Evaluation results are presented that compare the performance of decision-centric anticipatory information delivery to several baselines, demonstrating its various advantages in terms of decision timeliness, validity and network resources used. The paper concludes with a discussion of remaining future challenges in this emerging area.

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Section: Related Workmentioning

confidence: 89%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

mentioning

confidence: 99%

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Athena: Towards Decision-Centric Anticipatory Sensor Information Delivery

Lee

Marcus

Abdelzaher

et al. 2018

JSAN

Self Cite

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“…Furthermore, a real-time decision-maker should require IoT devices to provide minimal sensor data necessary for decision-making only to avoid possible network congestion and significant energy consumption in IoT devices for transmitting redundant sensor data wirelessly. Logic predicates, also called Boolean queries, can effectively evaluate alternative courses of action in IoT [8,12,13]. For example, an ambulance may try to find an available route among several alternative routes to a patient where some of them are unavailable due to construction, a social/political event, or disaster.…”

Section: Introductionmentioning

confidence: 99%

A Review of Efficient Real-Time Decision Making in the Internet of Things

Kang

2022

Technologies

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Emerging applications of IoT (the Internet of Things), such as smart transportation, health, and energy, are envisioned to greatly enhance the societal infrastructure and quality of life of individuals. In such innovative IoT applications, cost-efficient real-time decision-making is critical to facilitate, for example, effective transportation management and healthcare. In this paper, we formally define real-time decision tasks in IoT, review cutting-edge approaches that aim to efficiently schedule real-time decision tasks to meet their timing and data freshness constraints, review state-of-the-art approaches for efficient sensor data analytics in IoT, and discuss future research directions.

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A Proactive Decision-Driven Architecture for Information-Aware Internet-of-Things Applications

Darwish

2021

Advances in Intelligent Systems and Computing

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Decision-Driven Execution: A Distributed Resource Management Paradigm for the Age of IoT

Cited by 12 publications

References 9 publications

Athena: Towards Decision-Centric Anticipatory Sensor Information Delivery

Athena: Towards Decision-Centric Anticipatory Sensor Information Delivery

A Review of Efficient Real-Time Decision Making in the Internet of Things

A Proactive Decision-Driven Architecture for Information-Aware Internet-of-Things Applications

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