DRAAS: Dynamically Reconfigurable Architecture for Autonomic Services

Mezghani, Emna; Halima, Riadh Ben; Drira, Khalil

doi:10.1007/978-1-4614-7518-7_19

Cited by 2 publications

(4 citation statements)

References 41 publications

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“…This architecture has been implemented and experimented successfully with different use cases. It covers the whole cycle of autonomic management including monitoring and analysis of QoS parameters, planning and execution [4].…”

Section: Methodsmentioning

confidence: 99%

Autonomic dynamically reconfigurable architectures for future communication systems

Drira

2017

Proceedings of the 9th International Conference on Management of Digital EcoSystems

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Our objectives involve the development of correct by design models and operational solutions to discover, compose and manage, by automated procedures, the properties of adaptability essential for autonomous reconfiguration. These properties are critical for highly dynamic complex systems such as massive data collection, transport and processing systems, and associated IoT applications. This research direction is of interest for many applications that, on the one hand, have strong reconfiguration requirements to manage mobility, ubiquity, adaptation and self-healing, which are essential for autonomy, and that, on the other hand, are subject to non-functional constraints of quality of service, robustness and reliability. We propose, here, to develop multi-level reconfiguration solutions (VM clusters, application containers, message partitions), in order to manage simultaneously and consistently the adaptation in the different architectural levels. This is necessary for service continuity and end-to-end quality we implemented by coordinating the adaptation actions to satisfy the evolving of the context. CCS Concepts •Computer systems organization → n-tier architectures; •Software and its engineering → Software design engineering; •Networks → Cloud computing;

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Section: Methodsmentioning

confidence: 99%

Autonomic dynamically reconfigurable architectures for future communication systems

Drira

2017

Proceedings of the 9th International Conference on Management of Digital EcoSystems

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“…The functional requirements Once the wearable devices are semantically annotated, they will be configured to send asynchronous data to Apache Kafka 4 , which is a scalable and high-throughput distributed publish/subscribe messaging system. We propose to use Apache Storm 5 to consume the data from the Kafka topics based on Kafka-storm connector. Thus, we developed a topology that encodes the data workflow processing using three bolts that normalize the data, store it in distributed cluster to be analyzed, and detect problems at near real-time (instantiation within the Big Data Stream Detection pattern).…”

Section: Use Case: Patient Health Managementmentioning

confidence: 99%

“…The autonomic computing initiative [3] has a strong focus on managing complex systems through automating tasks based on the MAPE-K loop pattern (abbreviation of Monitoring, Analysis, Plan, Execution, and Knowledge). It has been widely used [5][6][7][8] for designing self-managed systems that automatically adapt their structure and behavior based on the context changes. It seems that adopting the autonomic computing for managing IoT-based system complexity is promising [4].…”

Section: Introductionmentioning

confidence: 99%

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A Model-Driven Methodology for the Design of Autonomic and Cognitive IoT-Based Systems: Application to Healthcare

Mezghani

Expósito

Drira

2017

IEEE Trans. Emerg. Top. Comput. Intell.

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Due to its abilities to capture real-time data concerning the physical world, the Internet of Things (IoT) phenomenon is fast gaining momentum in different applicative domains. Its benefits are not limited to connecting things, but lean on how the collected data is transformed into insights and interact with domain experts for better decisions. Nonetheless, a set of challenges including the complexity of IoT-based systems and the management of the ensuing big and heterogeneous data and as well as the system scalability; need to be addressed for the development of flexible smart IoT-based systems that drive the business decision-making. Consequently, inspired from the human nervous system and cognitive abilities, we have proposed a set of autonomic cognitive design patterns that alleviate the design complexity of smart IoT-based systems, while taking into consideration big data and scalability management. The ultimate goal of these patterns is providing generic and reusable solutions for elaborating flexible smart IoTbased systems able to perceive the collected data and provide decisions. These patterns are articulated within a model-driven methodology that we have proposed to incrementally refine the system functional and nonfunctional requirements. Following the proposed methodology, we have combined and instantiated a set of patterns for developing a flexible cognitive monitoring system to manage patients' health based on heterogeneous wearable devices. We have highlighted the gained flexibility and demonstrated the ability of our system to integrate and process heterogeneous 2 large scale data streams. Finally, we have evaluated the system performance in terms of response time and scalability management.

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DRAAS: Dynamically Reconfigurable Architecture for Autonomic Services

Cited by 2 publications

References 41 publications

Autonomic dynamically reconfigurable architectures for future communication systems

Autonomic dynamically reconfigurable architectures for future communication systems

A Model-Driven Methodology for the Design of Autonomic and Cognitive IoT-Based Systems: Application to Healthcare

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