Hierarchical Control for Self-adaptive IoT Systems A Constraint Programming-Based Adaptation Approach

被引:0
作者
Moghaddam, Mahyar T. [1 ]
Rutten, Eric [2 ]
Giraud, Guillaume [3 ]
机构
[1] Univ Southern Denmark, Odense, Denmark
[2] INRIA Grenoble, Grenoble, France
[3] RTE Paris, Paris, France
来源
PROCEEDINGS OF THE 55TH ANNUAL HAWAII INTERNATIONAL CONFERENCE ON SYSTEM SCIENCES | 2022年
关键词
Software architecture; Self-adaptation; Constraint programming; Performance; Smart grid;
D O I
暂无
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 self-adaptation control of Internet of Things (IoT) systems ought to tackle uncertainties in the dynamic environment (application level), as well as the dynamic computation infrastructure (architecture level). While the control of those two levels is generally separated, they should coordinate to guarantee functionality and quality. This paper proposes a conceptual model for the separation of concerns in controlling the environment and infrastructure events. The approach is applied on a real case: Melle-Longchamp area's smart power transmission network (in France). A hierarchical architecture with a control mechanism formalized with constraint programming (CP) is modeled. The control system assesses the reconfigurations that enhance the quality of service (QoS) while considering the internal and external limitations. The CP considers the desired application level control modes and assesses their feasibility by computing the response time and availability using a Netflow algorithm. The outcomes of this research supported design decisions and provided architectural reconfiguration solutions to the French Power Transmission Company (RTE).
引用
收藏
页码:7627 / 7636
页数:10
相关论文
共 18 条
[1]   Service Placement in Fog Computing Using Constraint Programming [J].
Ait-Salaht, F. ;
Desprez, F. ;
Lebre, A. ;
Prud'homme, C. ;
Abderrahim, M. .
2019 IEEE INTERNATIONAL CONFERENCE ON SERVICES COMPUTING (IEEE SCC 2019), 2019, :19-27
[2]   CoMe4ACloud: An end-to-end framework for autonomic Cloud systems [J].
Al-Shara, Zakarea ;
Alvares, Frederico ;
Bruneliere, Hugo ;
Lejeune, Jonathan ;
Prud'Homme, Charles ;
Ledoux, Thomas .
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE, 2018, 86 :339-354
[3]  
Arbib C., 2019, VIEW OPERATIONS RES, P115, DOI DOI 10.1007/978-3-030-25842-99
[4]  
Parra AA, 2012, CPU-REV INVESTIG EDU, P27
[5]  
Bertoli Marco, 2009, Performance Evaluation Review, V36, P10, DOI 10.1145/1530873.1530877
[6]  
Camara J., 2020, P IEEE ACM 15 INT S
[7]   Optimal Planning for Architecture-Based Self-Adaptation Via Model Checking of Stochastic Games [J].
Camara, Javier ;
Garlan, David ;
Schmerl, Bradley ;
Pandey, Ashutosh .
30TH ANNUAL ACM SYMPOSIUM ON APPLIED COMPUTING, VOLS I AND II, 2015, :428-435
[8]  
Gamez N., 2012, 2 INT WORKSH AD SERV
[9]  
Khazaei H., 2018, P CASCON, P282
[10]  
Litoiu M., 2017, SOFTWARE ENG SELFADA, P9640