Cognitive management of procotol composition enhanced Future Internet elements

This paper presents the final architecture for Cognitive Future Internet Element Management and in-network Dynamic Protocol Composition, as well as the results and insights gained by an prototype implementation and experiments performed. The high complexity of today's network infrastructures and the demand for reliable and robust but inexpensive networks stimulated research on evolving networks to become more autonomous and therefore reducing the need for human intervention. The presented approach is based on integrating a Monitoring, Decision-Making, and Execution (MDE) cycle into the situation aware Network Element Cognitive Manager (NECM). Accepting that the end-to-end paradigm does not hold for all mechanisms, we enable the NECM to control in-network functionality. For the prototype the NECM is complemented by the Dynamic Protocol Composition Framework (DPCF) which allows to control and execute arbitrary protocol functionality in intermediate nodes. For the experime nts we considered a wireless mesh backhaul network which is likely to suffer from packet loss depending on external conditions like weather, reflections on moving objects etc. We could show that packet loss or overload have been recognized and appropriate actions have been taken. The analysis of the experiments showed that the different phases of the M-D-E cyle differ in time consumption by several orders of magnitude which requires architectures for cognitive network management to be designed to align the different processes to achieve optimal results

Prévention de la transmission mère-enfant (PTME) du VIH à l’Ouest-Cameroun: l’expérience du Programme “Mingha” (2003-2007)

Comunicazione orale e abstrac

A survey of autonomic networking architectures: Towards a Unified Management Framework

SUMMARY Academic and industrial research initiatives have sought to make fully autonomic networks a reality. Some of these initiatives pursued a holistic approach, while others focused on setting up functionalities for specific networking domains. These efforts did not succeed in being extensively deployed, because the goals of network operators were not satisfactorily met. These goals include unification of management operations, enablement of end-to-end management and enhancement of the overall system performance in a trusted way, while reducing management cost. In this paper, we analyse a set of existing autonomic management architectures and frameworks with respect to a selected set of criteria. We then identify missing parts and challenges and propose a framework to unify the most promising attributes towards a novel approach of realization of autonomic networking management. We call this proposal Unified Management Framework (UMF). Copyright © 2013 John Wiley & Sons, Ltd

A cognitive management framework for empowering the internet of things

This work presents a Cognitive Management framework for empowering the Internet of Things (IoT). This framework has the ability to dynamically adapt its behaviour, through self-management functionality, taking into account information and knowledge (obtained through machine learning) on the situation (e.g., internal status and status of environment), as well as policies (designating objectives, constraints, rules, etc.). Cognitive technologies constitute a unique and efficient approach for addressing the technological heterogeneity of the IoT and obtaining situation awareness, reliability and efficiency. The paper also presents a first indicative implementation of the proposed framework, comprising real sensors and actuators. The preliminary results of this work demonstrate high potential towards self-reconfigurable IoT. © The Author(s)

A Cognitive Management Framework for Empowering the Internet of Things

This work presents a Cognitive Management framework for empowering the Internet of Things (IoT). This framework has the ability to dynamically adapt its behaviour, through self-management functionality, taking into account information and knowledge (obtained through machine learning) on the situation (e.g., internal status and status of environment), as well as policies (designating objectives, constraints, rules, etc.). Cognitive technologies constitute a unique and efficient approach for addressing the technological heterogeneity of the IoT and obtaining situation awareness, reliability and efficiency. The paper also presents a first indicative implementation of the proposed framework, comprising real sensors and actuators. The preliminary results of this work demonstrate high potential towards self-reconfigurable IoT