Towards a Distributed Systems Model based on Multi-Agent Systems for Reproducing Self-properties

271-288 p. :ilustraciones, libro electrónicoEn este capítulo, presentamos un modelo preliminar de un sistema distribuido (algunos los algoritmos y principios están modelados) que ha sido inspirado por sistemas multi-agentes. Los agentes pueden comunicarse de manera local y establecer una cooperación.Capítulo 11In this chapter, we introduce a preliminary model of a distributed system (some algorithms and principles are modelled) which has been inspired by multi-agent systems. Agents can communicate in a local fashion and establish a cooperation process in order to compute some desired functions as a traditional distributed system, producing an output that is transparent to an end user. Each agent can sense new information, and acts following certain information in a decentralized way. As a result, the output of the implemented functions achieves the same result as a traditional distributed system by using local behaviours. Finally, we show that it is possible to define crashes in the proposed model in a local, natural and easy way. The purpose of doing this is to use this simulated model to introduce behaviours to agents that allow the system to recover from failures by itself, in turn, achieving self-* properties.ISBN: 978958580477

Survey of Autonomic Computing and Experiments on JMX-based Autonomic Features

Autonomic Computing (AC) aims at solving the problem of managing the rapidly-growing complexity of Information Technology systems, by creating self-managing systems. In this thesis, we have surveyed the progress of the AC field, and studied the requirements, models and architectures of AC. The commonly recognized AC requirements are four properties - self-configuring, self-healing, self-optimizing, and self-protecting. The recommended software architecture is the MAPE-K model containing four modules, namely - monitor, analyze, plan and execute, as well as the knowledge repository. In the modern software marketplace, Java Management Extensions (JMX) has facilitated one function of the AC requirements - monitoring. Using JMX, we implemented a package that attempts to assist programming for AC features including socket management, logging, and recovery of distributed computation. In the experiments, we have not only realized the powerful Java capabilities that are unknown to many educators, we also illustrated the feasibility of learning AC in senior computer science courses

IAS: an IoT Architectural Self-adaptation Framework

International audienceThis paper develops a generic approach to model control loops and their interac- tion within the Internet of Things (IoT) environments. We take advantage of MAPE-K loops to enable architectural self-adaptation. The system’s architectural setting is aligned with the adaptation goals and the components run-time situation and constraints. We introduce an integrated framework for IoT Architectural Self-adaptation (IAS) where functional control elements are in charge of environmental adaptation and autonomic control elements handle the functional system’s architectural adaptation. A Queuing Networks (QN) approach was used for modeling the IAS. The IAS-QN can model control levels and their interaction to perform both architectural and environmental adaptations. The IAS-QN was modeled on a smart grid system for the Melle-Longchamp area (France). Our architectural adaptation approach successfully set the propositions to enhance the performance of the electricity trans- mission system. This industrial use-case is a part of CPS4EU European industrial innovation pro ject

Simulación de comportamientos de sistemas distribuidos para obtener robustez y Auto-recuperación de fallas

219 - 241 p. :ilustraciones, libro electrónicoEste capítulo muestra algunos aspectos fundamentales para definir una simulación de comportamientos de sistemas distribuidos para lograr que un sistema sea robusto y se recupere a sí mismo de fallas. Se determina como tarea de interés la colección y la sincronización de datos en nodos conectados en una red y se mencionan algunos subproblemas de interés relacionados con la definición de las fallas y la obtención de las propiedades de robustez y recuperación de fallas. Se utilizaron sistemas multi-agente para diseñar la simulación porque permiten modelar componentes autónomos mediante el uso de un programa de agente.Capítulo 9ISBN: 978958580477

From Algorithmic Computing to Autonomic Computing

In algorithmic computing, the program follows a predefined set of rules – the algorithm. The analyst/designer of the program analyzes the intended tasks of the program, defines the rules for its expected behaviour and programs the implementation. The creators of algorithmic software must therefore foresee, identify and implement all possible cases for its behaviour in the future application! However, what if the problem is not fully defined? Or the environment is uncertain? What if situations are too complex to be predicted? Or the environment is changing dynamically? In many such cases algorithmic computing fails. In such situations, the software needs an additional degree of freedom: Autonomy! Autonomy allows software to adapt to partially defined problems, to uncertain or dynamically changing environments and to situations that are too complex to be predicted. As more and more applications – such as autonomous cars and planes, adaptive power grid management, survivable networks, and many more – fall into this category, a gradual switch from algorithmic computing to autonomic computing takes place. Autonomic computing has become an important software engineering discipline with a rich literature, an active research community, and a growing number of applications.:Introduction 5 1 A Process Data Based Autonomic Optimization of Energy Efficiency in Manufacturing Processes, Daniel Höschele 9 2 Eine autonome Optimierung der Stabilität von Produktionsprozessen auf Basis von Prozessdaten, Richard Horn 25 3 Assuring Safety in Autonomous Systems, Christian Rose 41 4 MAPE-K in der Praxis - Grundlage für eine mögliche automatische Ressourcenzuweisung, in der Cloud Michael Schneider 5

Self-Adaptation in SDN-based IoT Networks

In the digital age, frightening patterns in digital threats are emerging. It is impossible to ignore threats to IoT networks. Threats can take on any of the typical forms, including Denial-of-Service (DoS), Distributed Denial-of-Service (DDoS), Virus assault, Man-in-the-middle attack (Mitm), Advanced Persistent Threats (APT), Password Assault, and more. It is crucial to eliminate all threats from IoT networks and devices. Reinforcement learning to detect anomalies in an IoT network is seen to be the greatest option for correcting risks in a network, hence fixing the afflicted nodes, according to this thesis, "Self-Adaptation of SDN-based IoT Networks." (Markov) MDP policies and MAPE-K loop properties in Self-aware systems are the bases of the design in this thesis. The network system exhibited self-adaptability features, which makes it self-correcting and self-healing. The objective of this research is to propose a means to secure the devices in an IoT network by protecting them from any form of threats and ensuring that the devices function normally. Even at the advent of abnormal functioning of any node in the network, the system should be able to correct itself. A Software Defined Network (SDN) architecture is proposed for the design in a later section, which explains the kind of SDN that should be in place for the intrusion detection system. Further into the thesis, we dived deep into the general overview of deep reinforcement learning. Then comes the implementation, which talks about the kind of reinforcement learning policy used in the work and how the result was derived. The other section discusses the result and discussion, where the result in this work was compared with the result of the traditional machine learning algorithm

Analysis and Development of Autonomous Systems with the Help of Proactive Computing

The work in this Master Thesis contributes to the field of autonomous systems and is looking to explore the possibility of using proactive engines for building autonomous sys- tems. Many approaches to the topic of autonomous systems exist, the contribution to the existing research is the usage of a proactive engine center piece. The proactive engine developed in Prof. Zampunieris’ research team at the University of Luxembourg is used to monitor and support systems. The proactive behaviour is used to add functionalities and properties to stand-alone systems. The ability of adding properties to existing systems is pursued in this work. It is investigated if the possibility of using the proactive engine as control unit for autonomous systems is given. The goal is to add all properties to a system such that this system can be denoted as autonomous. This means the proactive engine needs to supervise and manage the system in a way that the required interaction with humans can be reduced to a minimum. The proactive engine makes use of sensors to monitor the system and its environment. From the gathered data decisions can be taken and the system uses sensors to adapt to its environment and manage itself. The adapted proactive engine that can serve to add autonomy to existing servers could in the future also serve as control unit for newly designed systems