Resource Management and Budget Models

In Quality and Resource Management problems tradeoffs are explored between the resources allocated to an application and the quality provided by that application to a user. Such trade-offs are typically multi-objective and allow for different, Pareto optimal solutions. Models for QRM are often combined with a modular virtualization approach. Physical resources are shared between multiple application. A virtual platform is created by allocating resource budgets from each of the needed resources. Applications are then mapping onto such virtual platforms. Both platforms and applications are often defined in a modular way.

QRML is a model and a language that supports automation of online or offline quality and resource management. QRML is agnostic of the specifics or resources or applications. To effectively use it to optimize and configure virtual platforms, budget abstractions need to be defined that act as an interface between the promised resource availability of the resource and the requirement of the application.

For example, a processing budget could be abstractly modeled by a minimum number of cycles \(C\) in any real-time interval \(I\) of a given length. An application may be able to determine what throughput it can deliver based on that budget, for example using timed dataflow modelling and analysis methods, A TDMA based arbiter may be able to determine how many and which of its slots to allocate to the resource budget.

We have developed a prototype run-time resource management infrastructure based on these ideas and the the corresponding budget models, for the CompSOC platform [1][2].

References

  1. Shayan Tabatabaei Nikkhah and Marc Geilen and Dip Goswami and Martijn Koedam and Andrew Nelson and Kees Goossens (2021): A Deployment Framework for Quality-Sensitive Applications in Resource-Constrained Dynamic Environments. In: 2021 24th Euromicro Conference on Digital System Design (DSD), pp. 212-220, 2021.
  2. Shayan Tabatabaei Nikkhah and Marc Geilen and Dip Goswami and Kees Goossens (2020): A Performance Analysis Framework for Real-Time Systems Sharing Multiple Resources. In: 2020 Design, Automation & Test in Europe Conference & Exhibition (DATE), pp. 326-329, 2020.

Selected Related Publications

2021

Nikkhah, Shayan Tabatabaei; Geilen, Marc; Goswami, Dip; Koedam, Martijn; Nelson, Andrew; Goossens, Kees

A Deployment Framework for Quality-Sensitive Applications in Resource-Constrained Dynamic Environments Proceedings Article

In: 2021 24th Euromicro Conference on Digital System Design (DSD), pp. 212-220, 2021.

Links | BibTeX

2020

Nikkhah, Shayan Tabatabaei; Geilen, Marc; Goswami, Dip; Goossens, Kees

A Performance Analysis Framework for Real-Time Systems Sharing Multiple Resources Proceedings Article

In: 2020 Design, Automation & Test in Europe Conference & Exhibition (DATE), pp. 326-329, 2020.

Links | BibTeX

2013

Goossens, Kees; Azevedo, Arnaldo; Chandrasekar, Karthik; Gomony, Manil Dev; Goossens, Sven; Koedam, Martijn; Li, Yonghui; Mirzoyan, Davit; Molnos, Anca; Nejad, Ashkan Beyranvand; Nelson, Andrew; Sinha, Shubhendu

Virtual Execution Platforms for Mixed-time-criticality Systems: The CompSOC Architecture and Design Flow Journal Article

In: SIGBED Rev., vol. 10, no. 3, pp. 23โ€“34, 2013, ISSN: 1551-3688.

Links | BibTeX

2012

Yang, Yang; Geilen, Marc; Basten, Twan; Stuijk, Sander; Corporaal, Henk

Playing games with scenario- and resource-aware SDF graphs through policy iteration Proceedings Article

In: 2012 Design, Automation & Test in Europe Conference & Exhibition (DATE), pp. 194-199, 2012.

Links | BibTeX