User-centric resource management for embedded multi-core processors

Elham Shamsa; Anil Kanduri; Nima Taherinejad; Alma Probstl; Samarjit Chakraborty; Amir M. Rahmani; Pasi Liljeberg

doi:10.1109/VLSID49098.2020.00025

User-centric resource management for embedded multi-core processors

Elham Shamsa, Anil Kanduri, Nima Taherinejad, Alma Probstl, Samarjit Chakraborty, Amir M. Rahmani, Pasi Liljeberg

Chair of Real-Time Computer Systems

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

7 Scopus citations

Abstract

Modern battery powered Embedded Systems (ES) must provide a high performance with minimal energy consumption to enhance the user experience. However, these two are often conflicting objectives. In current ES resource management techniques, user behavior and preferences are only indirectly or not at all considered. In this paper, we present a novel user- and battery-aware resource management framework for multi-processor architectures that considers these conflicting requirements and dynamic unknown workloads at run-time to maximize user satisfaction. Proposed technique learns user's habits to dynamically adjust the resource management schemes based on the data it collects regarding user's plug-in behavior, battery charge status, and workloads variability at run-time. This information is used to improve the balance between performance and energy consumption, and thus optimize the Quality of Experience (QoE). Our evaluation results show that our framework enhances the user experience by 22% in comparison with the existing state-of-the-art.

Original language	English
Title of host publication	Proceedings - 33rd International Conference on VLSI Design, VLSID 2020 - Held concurrently with 19th International Conference on Embedded Systems
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	43-48
Number of pages	6
ISBN (Electronic)	9781728157016
DOIs	https://doi.org/10.1109/VLSID49098.2020.00025
State	Published - Jan 2020
Event	33rd International Conference on VLSI Design, VLSID 2020 - Bengaluru, India Duration: 4 Jan 2020 → 8 Jan 2020

Publication series

Name	Proceedings - 33rd International Conference on VLSI Design, VLSID 2020 - Held concurrently with 19th International Conference on Embedded Systems

Conference

Conference	33rd International Conference on VLSI Design, VLSID 2020
Country/Territory	India
City	Bengaluru
Period	4/01/20 → 8/01/20

Keywords

Battery-awareness
Energy Consumption
Heterogeneous
Multi-processor
Performance
Personalization
Quality of Experience
Resource Management
User-awareness

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1109/VLSID49098.2020.00025

Cite this

Shamsa, E., Kanduri, A., Taherinejad, N., Probstl, A., Chakraborty, S., Rahmani, A. M., & Liljeberg, P. (2020). User-centric resource management for embedded multi-core processors. In Proceedings - 33rd International Conference on VLSI Design, VLSID 2020 - Held concurrently with 19th International Conference on Embedded Systems (pp. 43-48). Article 9105643 (Proceedings - 33rd International Conference on VLSI Design, VLSID 2020 - Held concurrently with 19th International Conference on Embedded Systems). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/VLSID49098.2020.00025

Shamsa, Elham ; Kanduri, Anil ; Taherinejad, Nima et al. / User-centric resource management for embedded multi-core processors. Proceedings - 33rd International Conference on VLSI Design, VLSID 2020 - Held concurrently with 19th International Conference on Embedded Systems. Institute of Electrical and Electronics Engineers Inc., 2020. pp. 43-48 (Proceedings - 33rd International Conference on VLSI Design, VLSID 2020 - Held concurrently with 19th International Conference on Embedded Systems).

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title = "User-centric resource management for embedded multi-core processors",

abstract = "Modern battery powered Embedded Systems (ES) must provide a high performance with minimal energy consumption to enhance the user experience. However, these two are often conflicting objectives. In current ES resource management techniques, user behavior and preferences are only indirectly or not at all considered. In this paper, we present a novel user- and battery-aware resource management framework for multi-processor architectures that considers these conflicting requirements and dynamic unknown workloads at run-time to maximize user satisfaction. Proposed technique learns user's habits to dynamically adjust the resource management schemes based on the data it collects regarding user's plug-in behavior, battery charge status, and workloads variability at run-time. This information is used to improve the balance between performance and energy consumption, and thus optimize the Quality of Experience (QoE). Our evaluation results show that our framework enhances the user experience by 22% in comparison with the existing state-of-the-art.",

keywords = "Battery-awareness, Energy Consumption, Heterogeneous, Multi-processor, Performance, Personalization, Quality of Experience, Resource Management, User-awareness",

author = "Elham Shamsa and Anil Kanduri and Nima Taherinejad and Alma Probstl and Samarjit Chakraborty and Rahmani, {Amir M.} and Pasi Liljeberg",

note = "Publisher Copyright: {\textcopyright} 2020 IEEE.; 33rd International Conference on VLSI Design, VLSID 2020 ; Conference date: 04-01-2020 Through 08-01-2020",

year = "2020",

month = jan,

doi = "10.1109/VLSID49098.2020.00025",

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series = "Proceedings - 33rd International Conference on VLSI Design, VLSID 2020 - Held concurrently with 19th International Conference on Embedded Systems",

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Shamsa, E, Kanduri, A, Taherinejad, N, Probstl, A, Chakraborty, S, Rahmani, AM & Liljeberg, P 2020, User-centric resource management for embedded multi-core processors. in Proceedings - 33rd International Conference on VLSI Design, VLSID 2020 - Held concurrently with 19th International Conference on Embedded Systems., 9105643, Proceedings - 33rd International Conference on VLSI Design, VLSID 2020 - Held concurrently with 19th International Conference on Embedded Systems, Institute of Electrical and Electronics Engineers Inc., pp. 43-48, 33rd International Conference on VLSI Design, VLSID 2020, Bengaluru, India, 4/01/20. https://doi.org/10.1109/VLSID49098.2020.00025

User-centric resource management for embedded multi-core processors. / Shamsa, Elham; Kanduri, Anil; Taherinejad, Nima et al.
Proceedings - 33rd International Conference on VLSI Design, VLSID 2020 - Held concurrently with 19th International Conference on Embedded Systems. Institute of Electrical and Electronics Engineers Inc., 2020. p. 43-48 9105643 (Proceedings - 33rd International Conference on VLSI Design, VLSID 2020 - Held concurrently with 19th International Conference on Embedded Systems).

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

TY - GEN

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AU - Shamsa, Elham

AU - Kanduri, Anil

AU - Taherinejad, Nima

AU - Probstl, Alma

AU - Chakraborty, Samarjit

AU - Rahmani, Amir M.

AU - Liljeberg, Pasi

PY - 2020/1

Y1 - 2020/1

N2 - Modern battery powered Embedded Systems (ES) must provide a high performance with minimal energy consumption to enhance the user experience. However, these two are often conflicting objectives. In current ES resource management techniques, user behavior and preferences are only indirectly or not at all considered. In this paper, we present a novel user- and battery-aware resource management framework for multi-processor architectures that considers these conflicting requirements and dynamic unknown workloads at run-time to maximize user satisfaction. Proposed technique learns user's habits to dynamically adjust the resource management schemes based on the data it collects regarding user's plug-in behavior, battery charge status, and workloads variability at run-time. This information is used to improve the balance between performance and energy consumption, and thus optimize the Quality of Experience (QoE). Our evaluation results show that our framework enhances the user experience by 22% in comparison with the existing state-of-the-art.

AB - Modern battery powered Embedded Systems (ES) must provide a high performance with minimal energy consumption to enhance the user experience. However, these two are often conflicting objectives. In current ES resource management techniques, user behavior and preferences are only indirectly or not at all considered. In this paper, we present a novel user- and battery-aware resource management framework for multi-processor architectures that considers these conflicting requirements and dynamic unknown workloads at run-time to maximize user satisfaction. Proposed technique learns user's habits to dynamically adjust the resource management schemes based on the data it collects regarding user's plug-in behavior, battery charge status, and workloads variability at run-time. This information is used to improve the balance between performance and energy consumption, and thus optimize the Quality of Experience (QoE). Our evaluation results show that our framework enhances the user experience by 22% in comparison with the existing state-of-the-art.

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KW - Energy Consumption

KW - Heterogeneous

KW - Multi-processor

KW - Performance

KW - Personalization

KW - Quality of Experience

KW - Resource Management

KW - User-awareness

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DO - 10.1109/VLSID49098.2020.00025

M3 - Conference contribution

AN - SCOPUS:85089192294

T3 - Proceedings - 33rd International Conference on VLSI Design, VLSID 2020 - Held concurrently with 19th International Conference on Embedded Systems

SP - 43

EP - 48

BT - Proceedings - 33rd International Conference on VLSI Design, VLSID 2020 - Held concurrently with 19th International Conference on Embedded Systems

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 33rd International Conference on VLSI Design, VLSID 2020

Y2 - 4 January 2020 through 8 January 2020

ER -

Shamsa E, Kanduri A, Taherinejad N, Probstl A, Chakraborty S, Rahmani AM et al. User-centric resource management for embedded multi-core processors. In Proceedings - 33rd International Conference on VLSI Design, VLSID 2020 - Held concurrently with 19th International Conference on Embedded Systems. Institute of Electrical and Electronics Engineers Inc. 2020. p. 43-48. 9105643. (Proceedings - 33rd International Conference on VLSI Design, VLSID 2020 - Held concurrently with 19th International Conference on Embedded Systems). doi: 10.1109/VLSID49098.2020.00025

User-centric resource management for embedded multi-core processors

Abstract

Publication series

Conference

Keywords

UN SDGs

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