On Execution Platforms for Large-Scale Aggregate Computing

被引:20
|
作者
Viroli, Mirko [1 ]
Casadei, Roberto [1 ]
Pianini, Danilo [1 ]
机构
[1] Univ Bologna, Via Sacchi 3, I-47521 Cesena, Italy
来源
UBICOMP'16 ADJUNCT: PROCEEDINGS OF THE 2016 ACM INTERNATIONAL JOINT CONFERENCE ON PERVASIVE AND UBIQUITOUS COMPUTING | 2016年
关键词
Aggregate computing; Large-scale systems; Internet of Things; Execution platforms; Cloud computing;
D O I
10.1145/2968219.2979129
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
Aggregate computing is proposed as a computational model and associated toolchain to engineer adaptive large-scale situated systems, including IoT and wearable computing systems. Though originated in the context of WSN-like (peer-to-peer and fully distributed) systems, we argue it is a model that can transparently fit a variety of execution platforms (decentralised, server-mediated, cloud/fog-oriented), due to its ability of declaratively designing systems by global-level abstractions: it opens the possibility of intrinsically supporting forms of load balancing, elasticity and toleration of medium- and long-term changes of computational infrastructures. To ground the discussion, we present ongoing work in the context of scafi, a language and platform support for computational fields based on the Scala programming language and Akka actor framework.
引用
收藏
页码:1321 / 1326
页数:6
相关论文
共 50 条
  • [21] Automated Execution of Large-Scale Daylighting and Glare Simulations in a Cloud-Based Parallel Computing Environment
    Labib, Rania
    Baltazar, Juan-Carlos
    PROCEEDINGS OF BUILDING SIMULATION 2019: 16TH CONFERENCE OF IBPSA, 2020, : 1545 - 1551
  • [22] Automated parametric execution and documentation for large-scale simulations
    Kelsey, RL
    Bisset, KR
    Webster, RB
    ENABLING TECHNOLOGY FOR SIMULATION SCIENCE V, 2001, 4367 : 202 - 208
  • [23] A large-scale study on research code quality and execution
    Trisovic, Ana
    Lau, Matthew K.
    Pasquier, Thomas
    Crosas, Merce
    SCIENTIFIC DATA, 2022, 9 (01)
  • [24] A large-scale study on research code quality and execution
    Ana Trisovic
    Matthew K. Lau
    Thomas Pasquier
    Mercè Crosas
    Scientific Data, 9
  • [25] Modeling Application Resilience in Large-scale Parallel Execution
    Wu, Kai
    Dong, Wenqian
    Guan, Qiang
    DeBardeleben, Nathan
    Li, Dong
    PROCEEDINGS OF THE 47TH INTERNATIONAL CONFERENCE ON PARALLEL PROCESSING, 2018,
  • [26] Greening Duplication-Based Dependent-Tasks Scheduling on Heterogeneous Large-Scale Computing Platforms
    Hagras, Tarek
    Atef, Asmaa
    Mahdy, Yousef B.
    JOURNAL OF GRID COMPUTING, 2021, 19 (01)
  • [27] Cryogenic III-V and Nb electronics integrated on silicon for large-scale quantum computing platforms
    Jeong, Jaeyong
    Kim, Seong Kwang
    Suh, Yoon-Je
    Lee, Jisung
    Choi, Joonyoung
    Kim, Joon Pyo
    Kim, Bong Ho
    Park, Juhyuk
    Shim, Joonsup
    Rheem, Nahyun
    Lee, Chan Jik
    Jo, Younjung
    Geum, Dae-Myeong
    Park, Seung-Young
    Kim, Jongmin
    Kim, Sanghyeon
    NATURE COMMUNICATIONS, 2024, 15 (01)
  • [28] Greening Duplication-Based Dependent-Tasks Scheduling on Heterogeneous Large-Scale Computing Platforms
    Tarek Hagras
    Asmaa Atef
    Yousef B. Mahdy
    Journal of Grid Computing, 2021, 19
  • [29] A Data Fusion Framework for Large-Scale Measurement Platforms
    Rattadilok, Prapa
    McCall, John
    Burbridge, Trevor
    Soppera, Andrea
    Eardley, Philip
    PROCEEDINGS 2015 IEEE INTERNATIONAL CONFERENCE ON BIG DATA, 2015, : 2150 - 2158
  • [30] Aggregate Effects of Large-Scale Campaigns on Voter Turnout
    Enos, Ryan D.
    Fowler, Anthony
    POLITICAL SCIENCE RESEARCH AND METHODS, 2018, 6 (04) : 733 - 751