Dynamic Patterns for Cloud Application Life-Cycle Management

Cloud applications are by nature dynamic and must react to variations in use, and evolve to adopt new Cloud services, and exploit new capabilities offered by Edge and Fog devices, or within data centers offering Graphics Processing Units (GPUs) or dedicated processors for Artificial Intelligence (AI). Our proposal is to alleviate this complexity by using patterns at all stages of the Cloud application life-cycle: deployment, automatic service discovery, monitoring, and adaptive application evolution. The main idea of this paper is that it is possible to reduce the complexity of composing, deploying, and evolving Cross-Cloud applications using dynamic patterns.

[1]  Ramtin Jabbari,et al.  What is DevOps?: A Systematic Mapping Study on Definitions and Practices , 2016, XP Workshops.

[2]  Hui Song,et al.  CloudMF: Model-Driven Management of Multi-Cloud Applications , 2018, ACM Trans. Internet Techn..

[3]  Gordon S. Blair,et al.  Models@ run.time , 2009, Computer.

[4]  Yu Deng,et al.  Introducing Semantics to Cloud Services Catalogs , 2011, 2011 IEEE International Conference on Services Computing.

[5]  Geir Horn,et al.  MELODIC: Utility Based Cross Cloud Deployment Optimisation , 2018, 2018 32nd International Conference on Advanced Information Networking and Applications Workshops (WAINA).

[6]  Jeffrey O. Kephart,et al.  The Vision of Autonomic Computing , 2003, Computer.

[7]  Yoji Yamato Optimum Application Deployment Technology for Heterogeneous IaaS Cloud , 2017, J. Inf. Process..

[8]  Frank Eliassen,et al.  A development framework and methodology for self-adapting applications in ubiquitous computing environments , 2012, J. Syst. Softw..

[9]  Frank Eliassen,et al.  A comprehensive solution for application-level adaptation , 2009 .

[10]  Manuel Wimmer,et al.  The Evolution of CloudML and its Applications , 2015, CloudMDE@MoDELS.

[11]  Giuseppina Cretella,et al.  Semantic Representation of Cloud Patterns and Services with Automated Reasoning to Support Cloud Application Portability , 2017, IEEE Transactions on Cloud Computing.

[12]  Kent Beck Kent Beck's Guide to Better Smalltalk: CONSTRUCTING ABSTRACTIONS FOR OBJECT-ORIENTED APPLICATIONS , 1997 .

[13]  Jurica Ševa,et al.  Cloud Computing Ontologies: A Systematic Review , 2012 .

[14]  Uwe Zdun,et al.  Architectural Patterns Revisited - A Pattern Language , 2005, EuroPLoP.

[15]  Jens Dietrich,et al.  A formal description of design patterns using OWL , 2005, 2005 Australian Software Engineering Conference.

[16]  Javier Del Ser,et al.  A heuristic approach to the multicriteria design of IaaS cloud infrastructures for Big Data applications , 2018, Expert Syst. J. Knowl. Eng..

[17]  Giuseppina Cretella,et al.  Cloud Portability and Interoperability: Issues and Current Trends , 2015 .

[18]  Leszek A. Maciaszek,et al.  Confluent Factors, Complexity and Resultant Architectures in Modern Software Engineering - A Case of Service Cloud Applications , 2015, BMSD 2015.

[19]  Claus Pahl,et al.  Architectural Patterns for Microservices: A Systematic Mapping Study , 2018, CLOSER.

[20]  Geir Horn,et al.  Cost Benefits of Multi-cloud Deployment of Dynamic Computational Intelligence Applications , 2019, AINA Workshops.

[21]  Flora Amato,et al.  Pattern-based orchestration and automatic verification of composite cloud services , 2016, Comput. Electr. Eng..

[22]  Youki Kadobayashi,et al.  Ontological approach toward cybersecurity in cloud computing , 2010, SIN.

[23]  Kalyanmoy Deb,et al.  A fast and elitist multiobjective genetic algorithm: NSGA-II , 2002, IEEE Trans. Evol. Comput..

[24]  Flora Amato,et al.  Exploiting Cloud and Workflow Patterns for the Analysis of Composite Cloud Services , 2017, Future Gener. Comput. Syst..

[25]  Ralph Johnson,et al.  design patterns elements of reusable object oriented software , 2019 .

[26]  Dmitry Namiot,et al.  On micro-services architecture , 2014 .