126 research outputs found
Towards a Holistic Cloud System with End-to-End Performance Guarantees
Computing technologies are undergoing a relentless evolution from both the hardware and software sides, incorporating new mechanisms for low-latency networking, virtualization, operating systems, hardware acceleration, smart services orchestration, serverless computing, hybrid private-public Cloud solutions and others. Therefore, Cloud infrastructures are becoming increasingly attractive for deploying a wider and wider range of applications, including those with more and more stringent timing constraints, like the emerging use case of deploying time-critical applications. However, despite the availability of a number of public Cloud offerings, and of products (or open-source suites) for deploying in-house private Cloud infrastructures, still there are no solutions readily available for managing time-critical software components with predictable end-to-end timing requirements in the range of hundreds or even tens of milliseconds. The goal of this discussion is to present the multi-domain challenges associated with orchestrating a holistic Cloud system with endto- end guarantees, which is the subject of my current PhD investigations
ΠΠΈΠΊΡΠΎΡΠ΅ΡΠ²ΠΈΡΠ½Π°Ρ Π°ΡΡ ΠΈΡΠ΅ΠΊΡΡΡΠ° Π²ΠΈΡΡΡΠ°Π»ΡΠ½ΡΡ ΡΡΠ΅Π½Π°ΠΆΠ΅ΡΠ½ΡΡ ΠΊΠΎΠΌΠΏΠ»Π΅ΠΊΡΠΎΠ²
The task of automating and reducing the complexity of the process of developing virtual training complexes is considered. The analysis of the subject area showed the need to move from a monolithic to a service-oriented version of the architecture. It is found that the use of a monolithic architecture in the implementation of virtual training complexes limits the possibility of modernizing the system, increases its software complexity, and makes it difficult to implement an interface for managing and monitoring the training process. The general concept of the microservice architecture of virtual training complexes is presented, and definitions of the main and secondary components are given. The scientific novelty of the research lies in the transition from the classical monolithic architecture in the subject area of the HTC to the microservice architecture; eliminating the shortcomings of this approach by implementing a single protocol for the exchange of information between modules; separation of network interaction procedures into software libraries to unify and improve the reliability of the system. The use of isolated, loosely coupled microservices allows developers to use the best technologies, platforms and frameworks for their implementation; separate the graphical interface of the simulator instructor from the visualization and virtual reality system; provide the ability to flexibly replace the main components (visualization, interface, interaction with virtual reality) without changing the architecture and affecting other modules. The decomposition of the structural model of the microservice architecture is carried out, and the specifics of the functioning of the main components are presented. The implementation of microservices networking libraries and a JSON-based data exchange protocol is considered. The practical significance of the proposed architecture lies in the possibility of parallelization and reducing the complexity of the development and modernization of training complexes. The features of the functioning of the systems implemented in the proposed microservice architecture are analyzed.Π ΠΏΡΠ΅Π΄ΡΡΠ°Π²Π»Π΅Π½Π½ΠΎΠΉ ΡΠ°Π±ΠΎΡΠ΅ ΡΠ°ΡΡΠΌΠ°ΡΡΠΈΠ²Π°Π΅ΡΡΡ Π·Π°Π΄Π°ΡΠ° Π°Π²ΡΠΎΠΌΠ°ΡΠΈΠ·Π°ΡΠΈΠΈ ΠΈ ΡΠ½ΠΈΠΆΠ΅Π½ΠΈΡ ΡΠ»ΠΎΠΆΠ½ΠΎΡΡΠΈ ΠΏΡΠΎΡΠ΅ΡΡΠ° ΡΠ°Π·ΡΠ°Π±ΠΎΡΠΊΠΈ Π²ΠΈΡΡΡΠ°Π»ΡΠ½ΡΡ
ΡΡΠ΅Π½Π°ΠΆΠ΅ΡΠ½ΡΡ
ΠΊΠΎΠΌΠΏΠ»Π΅ΠΊΡΠΎΠ². ΠΡΠΎΠ²Π΅Π΄Π΅Π½Π½ΡΠΉ Π°Π½Π°Π»ΠΈΠ· ΠΏΡΠ΅Π΄ΠΌΠ΅ΡΠ½ΠΎΠΉ ΠΎΠ±Π»Π°ΡΡΠΈ ΠΏΠΎΠΊΠ°Π·Π°Π» Π½Π΅ΠΎΠ±Ρ
ΠΎΠ΄ΠΈΠΌΠΎΡΡΡ ΠΏΠ΅ΡΠ΅Ρ
ΠΎΠ΄Π° ΠΎΡ ΠΌΠΎΠ½ΠΎΠ»ΠΈΡΠ½ΠΎΠ³ΠΎ ΠΏΠΎΠ΄Ρ
ΠΎΠ΄Π° ΠΊ ΡΠ΅ΡΠ²ΠΈΡ-ΠΎΡΠΈΠ΅Π½ΡΠΈΡΠΎΠ²Π°Π½Π½ΠΎΠΌΡ Π²Π°ΡΠΈΠ°Π½ΡΡ Π°ΡΡ
ΠΈΡΠ΅ΠΊΡΡΡΡ. ΠΡΡΠ²Π»Π΅Π½ΠΎ, ΡΡΠΎ ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π½ΠΈΠ΅ ΠΌΠΎΠ½ΠΎΠ»ΠΈΡΠ½ΠΎΠΉ Π°ΡΡ
ΠΈΡΠ΅ΠΊΡΡΡΡ ΠΏΡΠΈ ΡΠ΅Π°Π»ΠΈΠ·Π°ΡΠΈΠΈ Π²ΠΈΡΡΡΠ°Π»ΡΠ½ΡΡ
ΡΡΠ΅Π½Π°ΠΆΠ΅ΡΠ½ΡΡ
ΠΊΠΎΠΌΠΏΠ»Π΅ΠΊΡΠΎΠ² ΠΎΠ³ΡΠ°Π½ΠΈΡΠΈΠ²Π°Π΅Ρ Π²ΠΎΠ·ΠΌΠΎΠΆΠ½ΠΎΡΡΡ ΠΌΠΎΠ΄Π΅ΡΠ½ΠΈΠ·Π°ΡΠΈΠΈ ΡΠΈΡΡΠ΅ΠΌΡ, ΡΠ²Π΅Π»ΠΈΡΠΈΠ²Π°Π΅Ρ Π΅Π΅ ΠΏΡΠΎΠ³ΡΠ°ΠΌΠΌΠ½ΡΡ ΡΠ»ΠΎΠΆΠ½ΠΎΡΡΡ, Π·Π°ΡΡΡΠ΄Π½ΡΠ΅Ρ ΡΠ΅Π°Π»ΠΈΠ·Π°ΡΠΈΡ ΠΈΠ½ΡΠ΅ΡΡΠ΅ΠΉΡΠ° Π΄Π»Ρ ΡΠΏΡΠ°Π²Π»Π΅Π½ΠΈΡ ΠΈ ΠΌΠΎΠ½ΠΈΡΠΎΡΠΈΠ½Π³Π° ΠΏΡΠΎΡΠ΅ΡΡΠ° ΠΏΠΎΠ΄Π³ΠΎΡΠΎΠ²ΠΊΠΈ. ΠΡΠ΅Π΄ΡΡΠ°Π²Π»Π΅Π½Π° ΠΎΠ±ΡΠ°Ρ ΠΊΠΎΠ½ΡΠ΅ΠΏΡΠΈΡ ΠΌΠΈΠΊΡΠΎΡΠ΅ΡΠ²ΠΈΡΠ½ΠΎΠΉ Π°ΡΡ
ΠΈΡΠ΅ΠΊΡΡΡΡ Π²ΠΈΡΡΡΠ°Π»ΡΠ½ΡΡ
ΡΡΠ΅Π½Π°ΠΆΠ΅ΡΠ½ΡΡ
ΠΊΠΎΠΌΠΏΠ»Π΅ΠΊΡΠΎΠ², Π΄Π°Π½Ρ ΠΎΠΏΡΠ΅Π΄Π΅Π»Π΅Π½ΠΈΡ ΠΎΡΠ½ΠΎΠ²Π½ΡΡ
ΠΈ Π²ΡΠΎΡΠΎΡΡΠ΅ΠΏΠ΅Π½Π½ΡΡ
ΠΊΠΎΠΌΠΏΠΎΠ½Π΅Π½ΡΠΎΠ². ΠΠ°ΡΡΠ½Π°Ρ Π½ΠΎΠ²ΠΈΠ·Π½Π° ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΡ Π·Π°ΠΊΠ»ΡΡΠ°Π΅ΡΡΡ Π² ΠΏΠ΅ΡΠ΅Ρ
ΠΎΠ΄Π΅ ΠΎΡ ΠΊΠ»Π°ΡΡΠΈΡΠ΅ΡΠΊΠΎΠΉ ΠΌΠΎΠ½ΠΎΠ»ΠΈΡΠ½ΠΎΠΉ Π°ΡΡ
ΠΈΡΠ΅ΠΊΡΡΡΡ Π² ΠΏΡΠ΅Π΄ΠΌΠ΅ΡΠ½ΠΎΠΉ ΠΎΠ±Π»Π°ΡΡΠΈ ΠΠ’Π ΠΊ ΠΌΠΈΠΊΡΠΎΡΠ΅ΡΠ²ΠΈΡΠ½ΠΎΠΉ Π°ΡΡ
ΠΈΡΠ΅ΠΊΡΡΡΠ΅ ΠΈ ΡΡΡΡΠ°Π½Π΅Π½ΠΈΠΈ Π½Π΅Π΄ΠΎΡΡΠ°ΡΠΊΠΎΠ² Π΄Π°Π½Π½ΠΎΠ³ΠΎ ΠΏΠΎΠ΄Ρ
ΠΎΠ΄Π° Π·Π° ΡΡΠ΅Ρ ΡΠ΅Π°Π»ΠΈΠ·Π°ΡΠΈΠΈ Π΅Π΄ΠΈΠ½ΠΎΠ³ΠΎ ΠΏΡΠΎΡΠΎΠΊΠΎΠ»Π° ΠΎΠ±ΠΌΠ΅Π½Π° ΠΈΠ½ΡΠΎΡΠΌΠ°ΡΠΈΠ΅ΠΉ ΠΌΠ΅ΠΆΠ΄Ρ ΠΌΠΎΠ΄ΡΠ»ΡΠΌΠΈ ΠΈ ΠΎΡΠ΄Π΅Π»Π΅Π½ΠΈΡ ΠΏΡΠΎΡΠ΅Π΄ΡΡ ΡΠ΅ΡΠ΅Π²ΠΎΠ³ΠΎ Π²Π·Π°ΠΈΠΌΠΎΠ΄Π΅ΠΉΡΡΠ²ΠΈΡ Π² ΠΏΡΠΎΠ³ΡΠ°ΠΌΠΌΠ½ΡΠ΅ Π±ΠΈΠ±Π»ΠΈΠΎΡΠ΅ΠΊΠΈ Π² ΠΊΠ°ΠΆΠ΄ΠΎΠΌ ΠΌΠΈΠΊΡΠΎΡΠ΅ΡΠ²ΠΈΡΠ΅ Π΄Π»Ρ ΡΠ½ΠΈΡΠΈΠΊΠ°ΡΠΈΠΈ ΠΈ ΠΏΠΎΠ²ΡΡΠ΅Π½ΠΈΡ Π½Π°Π΄Π΅ΠΆΠ½ΠΎΡΡΠΈ ΡΠ°Π±ΠΎΡΡ ΡΠΈΡΡΠ΅ΠΌΡ. ΠΡΠΈΠΌΠ΅Π½Π΅Π½ΠΈΠ΅ ΠΈΠ·ΠΎΠ»ΠΈΡΠΎΠ²Π°Π½Π½ΡΡ
, ΡΠ»Π°Π±ΠΎ ΡΠ²ΡΠ·Π°Π½Π½ΡΡ
ΠΌΠΈΠΊΡΠΎΡΠ΅ΡΠ²ΠΈΡΠΎΠ² ΠΏΠΎΠ·Π²ΠΎΠ»ΡΠ΅Ρ ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°ΡΡ ΠΎΠΏΡΠΈΠΌΠ°Π»ΡΠ½ΡΠ΅ ΡΠ΅Ρ
Π½ΠΎΠ»ΠΎΠ³ΠΈΠΈ, ΠΏΠ»Π°ΡΡΠΎΡΠΌΡ ΠΈ ΡΡΠ΅ΠΉΠΌΠ²ΠΎΡΠΊΠΈ Π΄Π»Ρ ΠΈΡ
ΡΠ΅Π°Π»ΠΈΠ·Π°ΡΠΈΠΈ, ΠΎΡΠ΄Π΅Π»ΠΈΡΡ Π³ΡΠ°ΡΠΈΡΠ΅ΡΠΊΠΈΠΉ ΠΈΠ½ΡΠ΅ΡΡΠ΅ΠΉΡ ΠΈΠ½ΡΡΡΡΠΊΡΠΎΡΠ° ΡΡΠ΅Π½Π°ΠΆΠ΅ΡΠ° ΠΎΡ ΡΠΈΡΡΠ΅ΠΌΡ Π²ΠΈΠ·ΡΠ°Π»ΠΈΠ·Π°ΡΠΈΠΈ ΠΈ Π²ΠΈΡΡΡΠ°Π»ΡΠ½ΠΎΠΉ ΡΠ΅Π°Π»ΡΠ½ΠΎΡΡΠΈ, ΠΎΠ±Π΅ΡΠΏΠ΅ΡΠΈΡΡ Π²ΠΎΠ·ΠΌΠΎΠΆΠ½ΠΎΡΡΡ Π³ΠΈΠ±ΠΊΠΎΠΉ Π·Π°ΠΌΠ΅Π½Ρ ΠΎΡΠ½ΠΎΠ²Π½ΡΡ
ΠΊΠΎΠΌΠΏΠΎΠ½Π΅Π½ΡΠΎΠ² (Π²ΠΈΠ·ΡΠ°Π»ΠΈΠ·Π°ΡΠΈΠΈ, ΠΈΠ½ΡΠ΅ΡΡΠ΅ΠΉΡΠ°, Π²Π·Π°ΠΈΠΌΠΎΠ΄Π΅ΠΉΡΡΠ²ΠΈΡ Ρ Π²ΠΈΡΡΡΠ°Π»ΡΠ½ΠΎΠΉ ΡΠ΅Π°Π»ΡΠ½ΠΎΡΡΡΡ) Π±Π΅Π· ΠΈΠ·ΠΌΠ΅Π½Π΅Π½ΠΈΡ Π°ΡΡ
ΠΈΡΠ΅ΠΊΡΡΡΡ ΠΈ Π²Π»ΠΈΡΠ½ΠΈΡ Π½Π° ΠΎΡΡΠ°Π»ΡΠ½ΡΠ΅ ΠΌΠΎΠ΄ΡΠ»ΠΈ. ΠΡΡΡΠ΅ΡΡΠ²Π»Π΅Π½Π° Π΄Π΅ΠΊΠΎΠΌΠΏΠΎΠ·ΠΈΡΠΈΡ ΡΡΡΡΠΊΡΡΡΠ½ΠΎΠΉ ΠΌΠΎΠ΄Π΅Π»ΠΈ ΠΌΠΈΠΊΡΠΎΡΠ΅ΡΠ²ΠΈΡΠ½ΠΎΠΉ Π°ΡΡ
ΠΈΡΠ΅ΠΊΡΡΡΡ, ΠΏΡΠ΅Π΄ΡΡΠ°Π²Π»Π΅Π½Π° ΡΠΏΠ΅ΡΠΈΡΠΈΠΊΠ° ΡΡΠ½ΠΊΡΠΈΠΎΠ½ΠΈΡΠΎΠ²Π°Π½ΠΈΡ ΠΎΡΠ½ΠΎΠ²Π½ΡΡ
ΠΊΠΎΠΌΠΏΠΎΠ½Π΅Π½ΡΠΎΠ². Π Π°ΡΡΠΌΠΎΡΡΠ΅Π½Π° ΡΠ΅Π°Π»ΠΈΠ·Π°ΡΠΈΡ Π±ΠΈΠ±Π»ΠΈΠΎΡΠ΅ΠΊ ΡΠ΅ΡΠ΅Π²ΠΎΠ³ΠΎ Π²Π·Π°ΠΈΠΌΠΎΠ΄Π΅ΠΉΡΡΠ²ΠΈΡ ΠΌΠΈΠΊΡΠΎΡΠ΅ΡΠ²ΠΈΡΠΎΠ² ΠΈ ΠΏΡΠΎΡΠΎΠΊΠΎΠ»Π° ΠΎΠ±ΠΌΠ΅Π½Π° Π΄Π°Π½Π½ΡΡ
Π½Π° ΠΎΡΠ½ΠΎΠ²Π΅ JSON. ΠΡΠ°ΠΊΡΠΈΡΠ΅ΡΠΊΠ°Ρ Π·Π½Π°ΡΠΈΠΌΠΎΡΡΡ ΠΏΡΠ΅Π΄Π»ΠΎΠΆΠ΅Π½Π½ΠΎΠΉ Π°ΡΡ
ΠΈΡΠ΅ΠΊΡΡΡΡ ΡΠΎΡΡΠΎΠΈΡ Π² Π²ΠΎΠ·ΠΌΠΎΠΆΠ½ΠΎΡΡΠΈ ΡΠ°ΡΠΏΠ°ΡΠ°Π»Π»Π΅Π»ΠΈΠ²Π°Π½ΠΈΡ ΠΈ ΡΠ½ΠΈΠΆΠ΅Π½ΠΈΡ ΡΠ»ΠΎΠΆΠ½ΠΎΡΡΠΈ ΠΏΡΠΎΡΠ΅ΡΡΠ° ΡΠ°Π·ΡΠ°Π±ΠΎΡΠΊΠΈ ΠΈ ΠΌΠΎΠ΄Π΅ΡΠ½ΠΈΠ·Π°ΡΠΈΠΈ ΡΡΠ΅Π½Π°ΠΆΠ΅ΡΠ½ΡΡ
ΠΊΠΎΠΌΠΏΠ»Π΅ΠΊΡΠΎΠ². ΠΡΠΎΠ°Π½Π°Π»ΠΈΠ·ΠΈΡΠΎΠ²Π°Π½Ρ ΠΎΡΠΎΠ±Π΅Π½Π½ΠΎΡΡΠΈ ΡΡΠ½ΠΊΡΠΈΠΎΠ½ΠΈΡΠΎΠ²Π°Π½ΠΈΡ ΡΠΈΡΡΠ΅ΠΌ, ΡΠ΅Π°Π»ΠΈΠ·ΠΎΠ²Π°Π½Π½ΡΡ
Π½Π° ΠΏΡΠ΅Π΄Π»ΠΎΠΆΠ΅Π½Π½ΠΎΠΉ ΠΌΠΈΠΊΡΠΎΡΠ΅ΡΠ²ΠΈΡΠ½ΠΎΠΉ Π°ΡΡ
ΠΈΡΠ΅ΠΊΡΡΡΠ΅
ΠΠΈΠΊΡΠΎΡΠ΅ΡΠ²ΠΈΡΠ½Π°Ρ Π°ΡΡ ΠΈΡΠ΅ΠΊΡΡΡΠ° Π²ΠΈΡΡΡΠ°Π»ΡΠ½ΡΡ ΡΡΠ΅Π½Π°ΠΆΠ΅ΡΠ½ΡΡ ΠΊΠΎΠΌΠΏΠ»Π΅ΠΊΡΠΎΠ²
Π ΠΏΡΠ΅Π΄ΡΡΠ°Π²Π»Π΅Π½Π½ΠΎΠΉ ΡΠ°Π±ΠΎΡΠ΅ ΡΠ°ΡΡΠΌΠ°ΡΡΠΈΠ²Π°Π΅ΡΡΡ Π·Π°Π΄Π°ΡΠ° Π°Π²ΡΠΎΠΌΠ°ΡΠΈΠ·Π°ΡΠΈΠΈ ΠΈ ΡΠ½ΠΈΠΆΠ΅Π½ΠΈΡ ΡΠ»ΠΎΠΆΠ½ΠΎΡΡΠΈ ΠΏΡΠΎΡΠ΅ΡΡΠ° ΡΠ°Π·ΡΠ°Π±ΠΎΡΠΊΠΈ Π²ΠΈΡΡΡΠ°Π»ΡΠ½ΡΡ
ΡΡΠ΅Π½Π°ΠΆΠ΅ΡΠ½ΡΡ
ΠΊΠΎΠΌΠΏΠ»Π΅ΠΊΡΠΎΠ². ΠΡΠΎΠ²Π΅Π΄Π΅Π½Π½ΡΠΉ Π°Π½Π°Π»ΠΈΠ· ΠΏΡΠ΅Π΄ΠΌΠ΅ΡΠ½ΠΎΠΉ ΠΎΠ±Π»Π°ΡΡΠΈ ΠΏΠΎΠΊΠ°Π·Π°Π» Π½Π΅ΠΎΠ±Ρ
ΠΎΠ΄ΠΈΠΌΠΎΡΡΡ ΠΏΠ΅ΡΠ΅Ρ
ΠΎΠ΄Π° ΠΎΡ ΠΌΠΎΠ½ΠΎΠ»ΠΈΡΠ½ΠΎΠ³ΠΎ ΠΏΠΎΠ΄Ρ
ΠΎΠ΄Π° ΠΊ ΡΠ΅ΡΠ²ΠΈΡ-ΠΎΡΠΈΠ΅Π½ΡΠΈΡΠΎΠ²Π°Π½Π½ΠΎΠΌΡ Π²Π°ΡΠΈΠ°Π½ΡΡ Π°ΡΡ
ΠΈΡΠ΅ΠΊΡΡΡΡ. ΠΡΡΠ²Π»Π΅Π½ΠΎ, ΡΡΠΎ ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π½ΠΈΠ΅ ΠΌΠΎΠ½ΠΎΠ»ΠΈΡΠ½ΠΎΠΉ Π°ΡΡ
ΠΈΡΠ΅ΠΊΡΡΡΡ ΠΏΡΠΈ ΡΠ΅Π°Π»ΠΈΠ·Π°ΡΠΈΠΈ Π²ΠΈΡΡΡΠ°Π»ΡΠ½ΡΡ
ΡΡΠ΅Π½Π°ΠΆΠ΅ΡΠ½ΡΡ
ΠΊΠΎΠΌΠΏΠ»Π΅ΠΊΡΠΎΠ² ΠΎΠ³ΡΠ°Π½ΠΈΡΠΈΠ²Π°Π΅Ρ Π²ΠΎΠ·ΠΌΠΎΠΆΠ½ΠΎΡΡΡ ΠΌΠΎΠ΄Π΅ΡΠ½ΠΈΠ·Π°ΡΠΈΠΈ ΡΠΈΡΡΠ΅ΠΌΡ, ΡΠ²Π΅Π»ΠΈΡΠΈΠ²Π°Π΅Ρ Π΅Π΅ ΠΏΡΠΎΠ³ΡΠ°ΠΌΠΌΠ½ΡΡ ΡΠ»ΠΎΠΆΠ½ΠΎΡΡΡ, Π·Π°ΡΡΡΠ΄Π½ΡΠ΅Ρ ΡΠ΅Π°Π»ΠΈΠ·Π°ΡΠΈΡ ΠΈΠ½ΡΠ΅ΡΡΠ΅ΠΉΡΠ° Π΄Π»Ρ ΡΠΏΡΠ°Π²Π»Π΅Π½ΠΈΡ ΠΈ ΠΌΠΎΠ½ΠΈΡΠΎΡΠΈΠ½Π³Π° ΠΏΡΠΎΡΠ΅ΡΡΠ° ΠΏΠΎΠ΄Π³ΠΎΡΠΎΠ²ΠΊΠΈ. ΠΡΠ΅Π΄ΡΡΠ°Π²Π»Π΅Π½Π° ΠΎΠ±ΡΠ°Ρ ΠΊΠΎΠ½ΡΠ΅ΠΏΡΠΈΡ ΠΌΠΈΠΊΡΠΎΡΠ΅ΡΠ²ΠΈΡΠ½ΠΎΠΉ Π°ΡΡ
ΠΈΡΠ΅ΠΊΡΡΡΡ Π²ΠΈΡΡΡΠ°Π»ΡΠ½ΡΡ
ΡΡΠ΅Π½Π°ΠΆΠ΅ΡΠ½ΡΡ
ΠΊΠΎΠΌΠΏΠ»Π΅ΠΊΡΠΎΠ², Π΄Π°Π½Ρ ΠΎΠΏΡΠ΅Π΄Π΅Π»Π΅Π½ΠΈΡ ΠΎΡΠ½ΠΎΠ²Π½ΡΡ
ΠΈ Π²ΡΠΎΡΠΎΡΡΠ΅ΠΏΠ΅Π½Π½ΡΡ
ΠΊΠΎΠΌΠΏΠΎΠ½Π΅Π½ΡΠΎΠ². ΠΠ°ΡΡΠ½Π°Ρ Π½ΠΎΠ²ΠΈΠ·Π½Π° ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΡ Π·Π°ΠΊΠ»ΡΡΠ°Π΅ΡΡΡ Π² ΠΏΠ΅ΡΠ΅Ρ
ΠΎΠ΄Π΅ ΠΎΡ ΠΊΠ»Π°ΡΡΠΈΡΠ΅ΡΠΊΠΎΠΉ ΠΌΠΎΠ½ΠΎΠ»ΠΈΡΠ½ΠΎΠΉ Π°ΡΡ
ΠΈΡΠ΅ΠΊΡΡΡΡ Π² ΠΏΡΠ΅Π΄ΠΌΠ΅ΡΠ½ΠΎΠΉ ΠΎΠ±Π»Π°ΡΡΠΈ ΠΠ’Π ΠΊ ΠΌΠΈΠΊΡΠΎΡΠ΅ΡΠ²ΠΈΡΠ½ΠΎΠΉ Π°ΡΡ
ΠΈΡΠ΅ΠΊΡΡΡΠ΅ ΠΈ ΡΡΡΡΠ°Π½Π΅Π½ΠΈΠΈ Π½Π΅Π΄ΠΎΡΡΠ°ΡΠΊΠΎΠ² Π΄Π°Π½Π½ΠΎΠ³ΠΎ ΠΏΠΎΠ΄Ρ
ΠΎΠ΄Π° Π·Π° ΡΡΠ΅Ρ ΡΠ΅Π°Π»ΠΈΠ·Π°ΡΠΈΠΈ Π΅Π΄ΠΈΠ½ΠΎΠ³ΠΎ ΠΏΡΠΎΡΠΎΠΊΠΎΠ»Π° ΠΎΠ±ΠΌΠ΅Π½Π° ΠΈΠ½ΡΠΎΡΠΌΠ°ΡΠΈΠ΅ΠΉ ΠΌΠ΅ΠΆΠ΄Ρ ΠΌΠΎΠ΄ΡΠ»ΡΠΌΠΈ ΠΈ ΠΎΡΠ΄Π΅Π»Π΅Π½ΠΈΡ ΠΏΡΠΎΡΠ΅Π΄ΡΡ ΡΠ΅ΡΠ΅Π²ΠΎΠ³ΠΎ Π²Π·Π°ΠΈΠΌΠΎΠ΄Π΅ΠΉΡΡΠ²ΠΈΡ Π² ΠΏΡΠΎΠ³ΡΠ°ΠΌΠΌΠ½ΡΠ΅ Π±ΠΈΠ±Π»ΠΈΠΎΡΠ΅ΠΊΠΈ Π² ΠΊΠ°ΠΆΠ΄ΠΎΠΌ ΠΌΠΈΠΊΡΠΎΡΠ΅ΡΠ²ΠΈΡΠ΅ Π΄Π»Ρ ΡΠ½ΠΈΡΠΈΠΊΠ°ΡΠΈΠΈ ΠΈ ΠΏΠΎΠ²ΡΡΠ΅Π½ΠΈΡ Π½Π°Π΄Π΅ΠΆΠ½ΠΎΡΡΠΈ ΡΠ°Π±ΠΎΡΡ ΡΠΈΡΡΠ΅ΠΌΡ. ΠΡΠΈΠΌΠ΅Π½Π΅Π½ΠΈΠ΅ ΠΈΠ·ΠΎΠ»ΠΈΡΠΎΠ²Π°Π½Π½ΡΡ
, ΡΠ»Π°Π±ΠΎ ΡΠ²ΡΠ·Π°Π½Π½ΡΡ
ΠΌΠΈΠΊΡΠΎΡΠ΅ΡΠ²ΠΈΡΠΎΠ² ΠΏΠΎΠ·Π²ΠΎΠ»ΡΠ΅Ρ ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°ΡΡ ΠΎΠΏΡΠΈΠΌΠ°Π»ΡΠ½ΡΠ΅ ΡΠ΅Ρ
Π½ΠΎΠ»ΠΎΠ³ΠΈΠΈ, ΠΏΠ»Π°ΡΡΠΎΡΠΌΡ ΠΈ ΡΡΠ΅ΠΉΠΌΠ²ΠΎΡΠΊΠΈ Π΄Π»Ρ ΠΈΡ
ΡΠ΅Π°Π»ΠΈΠ·Π°ΡΠΈΠΈ, ΠΎΡΠ΄Π΅Π»ΠΈΡΡ Π³ΡΠ°ΡΠΈΡΠ΅ΡΠΊΠΈΠΉ ΠΈΠ½ΡΠ΅ΡΡΠ΅ΠΉΡ ΠΈΠ½ΡΡΡΡΠΊΡΠΎΡΠ° ΡΡΠ΅Π½Π°ΠΆΠ΅ΡΠ° ΠΎΡ ΡΠΈΡΡΠ΅ΠΌΡ Π²ΠΈΠ·ΡΠ°Π»ΠΈΠ·Π°ΡΠΈΠΈ ΠΈ Π²ΠΈΡΡΡΠ°Π»ΡΠ½ΠΎΠΉ ΡΠ΅Π°Π»ΡΠ½ΠΎΡΡΠΈ, ΠΎΠ±Π΅ΡΠΏΠ΅ΡΠΈΡΡ Π²ΠΎΠ·ΠΌΠΎΠΆΠ½ΠΎΡΡΡ Π³ΠΈΠ±ΠΊΠΎΠΉ Π·Π°ΠΌΠ΅Π½Ρ ΠΎΡΠ½ΠΎΠ²Π½ΡΡ
ΠΊΠΎΠΌΠΏΠΎΠ½Π΅Π½ΡΠΎΠ² (Π²ΠΈΠ·ΡΠ°Π»ΠΈΠ·Π°ΡΠΈΠΈ, ΠΈΠ½ΡΠ΅ΡΡΠ΅ΠΉΡΠ°, Π²Π·Π°ΠΈΠΌΠΎΠ΄Π΅ΠΉΡΡΠ²ΠΈΡ Ρ Π²ΠΈΡΡΡΠ°Π»ΡΠ½ΠΎΠΉ ΡΠ΅Π°Π»ΡΠ½ΠΎΡΡΡΡ) Π±Π΅Π· ΠΈΠ·ΠΌΠ΅Π½Π΅Π½ΠΈΡ Π°ΡΡ
ΠΈΡΠ΅ΠΊΡΡΡΡ ΠΈ Π²Π»ΠΈΡΠ½ΠΈΡ Π½Π° ΠΎΡΡΠ°Π»ΡΠ½ΡΠ΅ ΠΌΠΎΠ΄ΡΠ»ΠΈ. ΠΡΡΡΠ΅ΡΡΠ²Π»Π΅Π½Π° Π΄Π΅ΠΊΠΎΠΌΠΏΠΎΠ·ΠΈΡΠΈΡ ΡΡΡΡΠΊΡΡΡΠ½ΠΎΠΉ ΠΌΠΎΠ΄Π΅Π»ΠΈ ΠΌΠΈΠΊΡΠΎΡΠ΅ΡΠ²ΠΈΡΠ½ΠΎΠΉ Π°ΡΡ
ΠΈΡΠ΅ΠΊΡΡΡΡ, ΠΏΡΠ΅Π΄ΡΡΠ°Π²Π»Π΅Π½Π° ΡΠΏΠ΅ΡΠΈΡΠΈΠΊΠ° ΡΡΠ½ΠΊΡΠΈΠΎΠ½ΠΈΡΠΎΠ²Π°Π½ΠΈΡ ΠΎΡΠ½ΠΎΠ²Π½ΡΡ
ΠΊΠΎΠΌΠΏΠΎΠ½Π΅Π½ΡΠΎΠ². Π Π°ΡΡΠΌΠΎΡΡΠ΅Π½Π° ΡΠ΅Π°Π»ΠΈΠ·Π°ΡΠΈΡ Π±ΠΈΠ±Π»ΠΈΠΎΡΠ΅ΠΊ ΡΠ΅ΡΠ΅Π²ΠΎΠ³ΠΎ Π²Π·Π°ΠΈΠΌΠΎΠ΄Π΅ΠΉΡΡΠ²ΠΈΡ ΠΌΠΈΠΊΡΠΎΡΠ΅ΡΠ²ΠΈΡΠΎΠ² ΠΈ ΠΏΡΠΎΡΠΎΠΊΠΎΠ»Π° ΠΎΠ±ΠΌΠ΅Π½Π° Π΄Π°Π½Π½ΡΡ
Π½Π° ΠΎΡΠ½ΠΎΠ²Π΅ JSON. ΠΡΠ°ΠΊΡΠΈΡΠ΅ΡΠΊΠ°Ρ Π·Π½Π°ΡΠΈΠΌΠΎΡΡΡ ΠΏΡΠ΅Π΄Π»ΠΎΠΆΠ΅Π½Π½ΠΎΠΉ Π°ΡΡ
ΠΈΡΠ΅ΠΊΡΡΡΡ ΡΠΎΡΡΠΎΠΈΡ Π² Π²ΠΎΠ·ΠΌΠΎΠΆΠ½ΠΎΡΡΠΈ ΡΠ°ΡΠΏΠ°ΡΠ°Π»Π»Π΅Π»ΠΈΠ²Π°Π½ΠΈΡ ΠΈ ΡΠ½ΠΈΠΆΠ΅Π½ΠΈΡ ΡΠ»ΠΎΠΆΠ½ΠΎΡΡΠΈ ΠΏΡΠΎΡΠ΅ΡΡΠ° ΡΠ°Π·ΡΠ°Π±ΠΎΡΠΊΠΈ ΠΈ ΠΌΠΎΠ΄Π΅ΡΠ½ΠΈΠ·Π°ΡΠΈΠΈ ΡΡΠ΅Π½Π°ΠΆΠ΅ΡΠ½ΡΡ
ΠΊΠΎΠΌΠΏΠ»Π΅ΠΊΡΠΎΠ². ΠΡΠΎΠ°Π½Π°Π»ΠΈΠ·ΠΈΡΠΎΠ²Π°Π½Ρ ΠΎΡΠΎΠ±Π΅Π½Π½ΠΎΡΡΠΈ ΡΡΠ½ΠΊΡΠΈΠΎΠ½ΠΈΡΠΎΠ²Π°Π½ΠΈΡ ΡΠΈΡΡΠ΅ΠΌ, ΡΠ΅Π°Π»ΠΈΠ·ΠΎΠ²Π°Π½Π½ΡΡ
Π½Π° ΠΏΡΠ΅Π΄Π»ΠΎΠΆΠ΅Π½Π½ΠΎΠΉ ΠΌΠΈΠΊΡΠΎΡΠ΅ΡΠ²ΠΈΡΠ½ΠΎΠΉ Π°ΡΡ
ΠΈΡΠ΅ΠΊΡΡΡΠ΅
SynerCreteβ18: interdisciplinary approaches for cement-based materials and structural concrete: synergizing expertise and bridging scales of space and time, vol. 2
info:eu-repo/semantics/publishedVersio
Dynamic digital factories for agile supply chains: An architectural approach
Digital factories comprise a multi-layered integration of various activities along the factories and product lifecycles. A central aspect of a digital factory is that of enabling the product lifecycle stakeholders to collaborate through the use of software solutions. The digital factory thus expands outside the company boundaries and offers the opportunity to collaborate on business processes affecting the whole supply chain. This paper discusses an interoperability architecture for digital factories. To this end, it delves into the issue by analysing the key requirements for enabling a scalable factory architecture characterized by access to services, aggregation of data, and orchestration of production processes. Then, the paper revises the state-of-the-art w.r.t. these requirements and proposes an architectural framework conjugating features of both service-oriented and data-sharing architectures. The framework is exemplified through a case study
How to Place Your Apps in the Fog -- State of the Art and Open Challenges
Fog computing aims at extending the Cloud towards the IoT so to achieve
improved QoS and to empower latency-sensitive and bandwidth-hungry
applications. The Fog calls for novel models and algorithms to distribute
multi-service applications in such a way that data processing occurs wherever
it is best-placed, based on both functional and non-functional requirements.
This survey reviews the existing methodologies to solve the application
placement problem in the Fog, while pursuing three main objectives. First, it
offers a comprehensive overview on the currently employed algorithms, on the
availability of open-source prototypes, and on the size of test use cases.
Second, it classifies the literature based on the application and Fog
infrastructure characteristics that are captured by available models, with a
focus on the considered constraints and the optimised metrics. Finally, it
identifies some open challenges in application placement in the Fog
Logic-based Technologies for Intelligent Systems: State of the Art and Perspectives
Together with the disruptive development of modern sub-symbolic approaches to artificial intelligence (AI), symbolic approaches to classical AI are re-gaining momentum, as more and more researchers exploit their potential to make AI more comprehensible, explainable, and therefore trustworthy. Since logic-based approaches lay at the core of symbolic AI, summarizing their state of the art is of paramount importance now more than ever, in order to identify trends, benefits, key features, gaps, and limitations of the techniques proposed so far, as well as to identify promising research perspectives. Along this line, this paper provides an overview of logic-based approaches and technologies by sketching their evolution and pointing out their main application areas. Future perspectives for exploitation of logic-based technologies are discussed as well, in order to identify those research fields that deserve more attention, considering the areas that already exploit logic-based approaches as well as those that are more likely to adopt logic-based approaches in the future
Robust Contract Evolution in a TypeSafe MicroServices Architecture
Microservices architectures allow for short deployment cycles and immediate
effects but offer no safety mechanisms when service contracts need to be
changed. Maintaining the soundness of microservice architectures is an
error-prone task that is only accessible to the most disciplined development
teams. We present a microservice management system that statically verifies
service interfaces and supports the seamless evolution of compatible
interfaces. We define a compatibility relation that captures real evolution
patterns and embodies known good practices on the evolution of interfaces.
Namely, we allow for the addition, removal, and renaming of data fields of a
producer module without breaking or needing to upgrade consumer services. The
evolution of interfaces is supported by runtime generated proxy components that
dynamically adapt data exchanged between services to match with the statically
checked service code.The model was instantiated in a core language whose
semantics is defined by a labeled transition system and a type system that
prevents breaking changes from being deployed. Standard soundness results for
the core language entail the existence of adapters, hence the absence of
adaptation errors and the correctness of the management model. This adaptive
approach allows for gradual deployment of modules, without halting the whole
system and avoiding losing or misinterpreting data exchanged between system
nodes. Experimental data shows that an average of 69% of deployments that would
require adaptation and recompilation are safe under our approach
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