Extending TOSCA for Edge and Fog Deployment Support

被引:21
|
作者
Tsagkaropoulos, Andreas [1 ]
Verginadis, Yiannis [1 ,2 ]
Compastie, Maxime [3 ]
Apostolou, Dimitris [1 ,4 ]
Mentzas, Gregoris [1 ]
机构
[1] Natl Tech Univ Athens NTUA, Informat Management Unit IMU, Inst Commun & Comp Syst, Athens 15780, Greece
[2] Athens Univ Econ & Business AUEB, Dept Business Adm, Athens 10434, Greece
[3] ActiveEon SAS, F-06560 Sophia Antipolis, France
[4] Univ Piraeus, Dept Informat, Piraeus 18534, Greece
基金
欧盟地平线“2020”;
关键词
TOSCA; function-as-a-service; fog computing; cloud computing; model-driven engineering; cloud applications; CLOUD;
D O I
10.3390/electronics10060737
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 emergence of fog and edge computing has complemented cloud computing in the design of pervasive, computing-intensive applications. The proximity of fog resources to data sources has contributed to minimizing network operating expenditure and has permitted latency-aware processing. Furthermore, novel approaches such as serverless computing change the structure of applications and challenge the monopoly of traditional Virtual Machine (VM)-based applications. However, the efforts directed to the modeling of cloud applications have not yet evolved to exploit these breakthroughs and handle the whole application lifecycle efficiently. In this work, we present a set of Topology and Orchestration Specification for Cloud Applications (TOSCA) extensions to model applications relying on any combination of the aforementioned technologies. Our approach features a design-time "type-level" flavor and a run time "instance-level" flavor. The introduction of semantic enhancements and the use of two TOSCA flavors enables the optimization of a candidate topology before its deployment. The optimization modeling is achieved using a set of constraints, requirements, and criteria independent from the underlying hosting infrastructure (i.e., clouds, multi-clouds, edge devices). Furthermore, we discuss the advantages of such an approach in comparison to other notable cloud application deployment approaches and provide directions for future research.
引用
收藏
页码:1 / 50
页数:48
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