Software Energy Consumption Estimation at Architecture-level

被引:3
作者
Li, Deguang [1 ]
Guo, Bing [1 ]
Li, Junke [1 ]
Wang, Jihe [1 ]
Huang, Yanhui [1 ]
Li, Qiang [1 ]
Shen, Yan [2 ]
机构
[1] Sichuan Univ, Coll Comp Sci, Chengdu, Sichuan, Peoples R China
[2] Chengdu Univ Informat Technol, Sch Control Engn, Chengdu, Sichuan, Peoples R China
来源
2016 13TH INTERNATIONAL CONFERENCE ON EMBEDDED SOFTWARE AND SYSTEMS (ICESS) - PROCEEDINGS | 2016年
基金
中国国家自然科学基金;
关键词
energy consumption estimation; architecture-level; complex networks; software energy model;
D O I
10.1109/ICESS.2016.35
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The architecture of software systems can be naturally modeled as complex networks, where entities of software are nodes and interactions between entities are edges. These edges represent data-flows, instruction-flows and control-flows of the software, and these flows driving hardware circuit is the internal cause of the energy consumption of the software. In this research, we model software systems as complex networks, assuming that there is a nonlinear function relation between network characteristics of software and its energy consumption. Based on this assumption, we propose a software energy consumption estimation model at architecture-level. First we measure five network characteristics of software, and then use extreme learning machine (ELM) to fit the relation between network characteristics of software and its energy consumption. Finally we evaluate our energy model on Linux platform and the results show that our model can achieve a 7.9% error rate compared to pTop model, which indicates our assumption is reasonable and our software energy model is effective.
引用
收藏
页码:7 / 11
页数:5
相关论文
共 50 条
  • [41] Reliable Energy Consumption Modeling for an Electric Vehicle Fleet
    Roy, Millend
    Nambi, Akshay
    Sobti, Anupam
    Ganu, Tanuja
    Kalyanaraman, Shivkumar
    Akella, Shankar
    Devi, Jaya Subha
    Sundaresan, S. A.
    PROCEEDINGS OF THE 4TH ACM SIGCAS/SIGCHI CONFERENCE ON COMPUTING AND SUSTAINABLE SOCIETIES, COMPASS'22, 2022, : 29 - 44
  • [42] Methods for Quantifying Energy Consumption in TPC-H
    Poess, Meikel
    Ren, Da Qi
    Rabl, Tilmann
    Jacobsen, Hans-Arno
    PROCEEDINGS OF THE 2018 ACM/SPEC INTERNATIONAL CONFERENCE ON PERFORMANCE ENGINEERING (ICPE '18), 2018, : 293 - 304
  • [43] Estimating the energy consumption of model-view-controller applications
    Guaman, Daniel
    Perez, Jennifer
    Valdiviezo-Diaz, Priscila
    JOURNAL OF SUPERCOMPUTING, 2023, 79 (12) : 13766 - 13793
  • [44] Mesoscopic model framework for estimating electric vehicles' energy consumption
    Zhang, Rui
    Yao, Enjian
    SUSTAINABLE CITIES AND SOCIETY, 2019, 47
  • [45] Estimating the energy consumption of model-view-controller applications
    Daniel Guamán
    Jennifer Pérez
    Priscila Valdiviezo-Diaz
    The Journal of Supercomputing, 2023, 79 : 13766 - 13793
  • [46] ESTIMATION OF CONTROL ENERGY AND CONTROL STRATEGIES FOR COMPLEX NETWORKS
    Wang, Dingjie
    Jin, Suoqin
    Wu, Fang-Xiang
    Zou, Xiufen
    ADVANCES IN COMPLEX SYSTEMS, 2015, 18 (7-8):
  • [47] Methodology to estimate building energy consumption using EnergyPlus Benchmark Models
    Fumo, Nelson
    Mago, Pedro
    Luck, Rogelio
    ENERGY AND BUILDINGS, 2010, 42 (12) : 2331 - 2337
  • [48] TOPOLOGY DESIGN TO REDUCE ENERGY CONSUMPTION OF DISTRIBUTED GRAPH FILTERING IN WSN
    Ben Saad, Leila
    Asensio-Marco, Cesar
    Beferull-Lozano, Baltasar
    2017 IEEE GLOBAL CONFERENCE ON SIGNAL AND INFORMATION PROCESSING (GLOBALSIP 2017), 2017, : 608 - 612
  • [49] Optimal Model of Electric Bus Scheduling Based on Energy Consumption and Battery Loss
    Xing, Yan
    Fu, Quanbo
    Li, Yachao
    Chu, Hanshuo
    Niu, Enyi
    SUSTAINABILITY, 2023, 15 (12)
  • [50] Construction waste resource utilization and energy consumption calculation based on Internet of things
    Fuhua Chang
    Dan Wang
    Soft Computing, 2023, 27 : 7567 - 7578