Mobile Ad hoc NETworks (MANETs) are networks in which the participating nodes can move freely without having to worry about maintaining a direct connection to any particular fixed access point. In a MANET, nodes collaborate with each other to form the network and as long as a node is in contact with any other member of the network, it—at least in theory—is part of the network and can communicate with all other nodes. An important function of network management is to observe current network conditions: at the node level, this may mean keeping track of arriving and departing traffic load; at the network level, the system must monitor active routes and changes in network topology. In this research, we present the design and implementation of a distributed network monitoring system for MANETs. Our system is completely distributed, generates no additional traffic on the network and produces a dynamic picture of the network level and node level information on a graphical user interface. In our proposed scheme, multiple monitoring nodes collaborate to achieve a reasonably accurate snapshot of the network conditions. These monitoring nodes passively sniff network traffics and gather information from the network to construct partial network views. They then transmit their findings to a management unit where these local views are put together to produce a comprehensive picture of the network. The communication between all management nodes (a monitoring unit and a management node) takes place in an out-of-band communication link. Therefore, our monitoring solution does not depend on the MANET to perform, hence is robust to network partitioning, link breaks, node's death and node misbehavior in the monitored MANET. Our solution provides a snapshot of the network topology that includes information about node-level behavior ratings and traffic activity. The information provided by our monitoring system can be used for network management as well as for security assessment, including anomaly detection. Information regarding individual nodes' behavior can be used for detecting selfishness in the network. Also, an approximation of arriving and departing traffic levels at each node is important in the context of quality of service, load balancing and congestion control. Furthermore, the network topology picture can provide valuable information to network management in detecting preferred routes, discovering network partitioning and in fault detection. We developed a proof-of-concept implementation of our system, which works with the Optimized Link State Routing (OLSR) protocol. Through experimental studies with up to 10-node MANETs, we were able to determine the feasibility and workability of our system. The scheme proved to be robust with respect to mobility, rapid changes in the network topology and node connectivity. Throughout our experiments we observed that our system replicated changes in the network on the GUI with less than two seconds delay. Also, when deployed in a high-traffic environment, with multiple TCP and UDP flows throughout the network, the system was able to report traffic load on each node accurately and consistently. On average, CPU consumption on monitoring nodes was about 3.5% and the GUI never took up more than 4% of the processing power (general-purpose laptop computers were used throughout the experiments). Also, the overall storage capacity needed for archiving the information files was estimated as 1 Mbytes for monitoring a 10-node MANETs for 30 minutes. Unobtrusive and distributed nature of our proposed approach helps the system to adapt to the constantly changing nature of MANETs and be able to provide valuable network management, security assessment and traffic analysis services, while requiring only modest processing and storage resources. The system is capable of quickly responding to changes in the network and is non-intrusive, generating no additional traffic on the MANET it monitors. / Master of Science

This is the final revision of my M.Sc. Thesis. / Runtime Verification is a technique to extract information from a running system in order to detect executions violating a given correctness specification. In this thesis, we study distributed synchronous/asynchronous runtime verification of systems. In our setting, there is a set of distributed monitors that have only partial views of a large system and are subject to failures. In this context, it is unavoidable that monitors may have different views of the underlying system, and therefore may have different valuations of the correctness property. In this thesis, we propose an automata-based synchronous monitoring algorithm that copes with f crash failures in a distrbuted setting. The algorithm solves the synchronous monitoring problem in f + 1 rounds of communication, and significantly reduces the message size overhead. We also propose an algorithm for distributed crash-resilient asynchronous monitoring that consistently monitors the system under inspection without any communication between monitors. Each local monitor emits a verdict set solely based on its own partial observation, and the intersection of the verdict sets will be the same as the verdict computed by a centralized monitor that has full view of the system. / Thesis / Master of Science (MSc)

Over the last decade, the number, size and complexity of large-scale networked systems has been growing fast, and this trend is expected to accelerate. The best known example of a large-scale networked system is probably the Internet, while large datacenters for cloud services are the most recent ones. In such environments, a key challenge is to develop scalable and adaptive technologies for management functions. This thesis addresses the challenge by engineering several protocols  for distributed monitoring and resource management that are suitable for large-scale networked systems. First, we present G-GAP, a gossip-based protocol we developed for continuous monitoring of aggregates that are computed from device variables. We prove the robustness of this protocol to node failures and validate, through simulations, that its estimation accuracy does not change with increasing size of the monitored system under certain conditions. Second, we present TCA-GAP, a tree-based protocol, and TG-GAP, a gossip-based protocol for the purpose of monitoring threshold crossings of aggregates. For both protocols, we prove correctness properties and show, again through simulations, that both protocols are efficient, by showing that their overhead is at least two orders of magnitude smaller than that of a na\"ive approach, for cases where the monitored aggregate is sufficiently far from the threshold. Third, we present a gossip-based protocol for resource management in cloud environments. The protocol allocates CPU and memory resources to sites that are hosted by the cloud. We prove that the resource allocation computed by the protocol converges exponentially fast to an optimal allocation, for cases where sufficient memory is available. Through simulations, we show that the quality of the resource allocation approaches that of an ideal system when the total memory demand decreases significantly below the memory capacity of the entire system. In addition, we validate that the quality of the allocation does not change with increasing the number of hosted sites and machines, for the case where both metrics are scaled proportionally. Finally, we compare two approaches (tree-based and gossip-based) to engineering protocols for distributed management, for the case of real-time monitoring. Results of our simulation studies indicate that, regardless of the system size and failure rates in the monitored system, gossip protocols incur a significantly larger overhead than tree-based protocols for achieving the same monitoring quality (e.g., estimation accuracy or detection delay). / QC 20101124

The rise of IoT-based system is making an impact on our daily lives and environment. Fog Computing is a paradigm to utilize IoT data and process them at the first hop of access network instead of distant clouds, and it is going to bring promising applications for us. A mature framework for fog computing still lacks until today. In this study, we propose an approach for monitoring fog nodes in a distributed system using the FogFlow framework. We extend the functionality of FogFlow by adding the monitoring capability of Docker containers using cAdvisor. We use Prometheus for collecting distributed data and aggregate them. The monitoring data of the entire distributed system of fog nodes is accessed via an API from Prometheus. Furthermore, the monitoring data is used to perform the ranking of fog nodes to choose the place to place the serverless functions (Fog Function). The ranking mechanism uses Analytical Hierarchy Processes (AHP) to place the fog function according to resource utilization and saturation of fog nodes’ hardware. Finally, an experiment test-bed is set up with an image-processing application to detect faces. The effect of our ranking approach on the Quality of Service is measured and compared to the current FogFlow.

Distributed computing systems (DCS) host a wide variety of enterprise applications in dynamic and uncertain operating environments. These applications require stringent reliability, availability, and quality of service (QoS) guarantee to maintain their service level agreements (SLAs). Due to the growing size and complexity of DCS, an autonomic performance management system is required to maintain SLAs of these applications. A model-based autonomic performance management structure is developed in this dissertation for applications hosted in DCS. A systematic application performance modeling approach is introduced in this dissertation to define the dependency relationships among the system parameters, which impact the application performance. The developed application performance model is used by a model-based predictive controller for managing multi-dimensional QoS objectives of the application. A distributed control structure is also developed to provide scalability for performance management and to eliminate the requirement of approximate behavior modeling in the hierarchical arrangement of DCS. A distributed monitoring system is also introduced in this dissertation to keep track of computational resources utilization, application performance statistics, and scientific application execution in a DCS, with minimum latency and controllable resource overhead. The developed monitoring system is self-configuring, self-aware, and fault-tolerant. It can also be deployed for monitoring of DCS with heterogeneous computing systems. A configurable autonomic performance management system is developed using modelintegrated computing methodologies, which allow administrators to define the initial settings of the application, QoS objectives, system components’ placement, and interaction among these components in a graphical domain specific modeling environment. This configurable performance management system facilitates reusability of the same components, algorithms, and application performance models in different deployment settings.

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Les travaux proposés dans cette thèse s’intéressent à la commande et la surveillance d’une classe particulière de systèmes de production : les systèmes manufacturiers à contraintes de temps de séjour. Nous supposons dans l'étude que les ressources ont déjà été affectées et que l'ordre des opérations est déjà fixé par le module de planification/ordonnancement. Les hypothèses de fonctionnement répétitif avec et sans postes d'assemblage sont adoptées. De manière assez classique pour ce type de problématique, le formalisme utilisé est celui des Réseaux de Petri P-temporels pour l'étude des instants de débuts et de fins des opérations.Une étude de la robustesse des ateliers manufacturiers à contraintes de temps a été développée. La robustesse est abordée avec et sans modification de la commande relative à la robustesse active et à la robustesse passive respectivement, face aux perturbations temporelles. Un algorithme de calcul d'une borne supérieure de la robustesse passive est présenté. De plus, trois stratégies de commande robuste face aux perturbations temporelles ont été développées.Par ailleurs, l’incertitude dans les systèmes de production manufacturière à été étudié. Notre contribution dans ce cadre porte sur l’intégration des résultats concernant la robustesse dans la génération de symptômes et la classification des comptes rendus associés aux différentes opérations en utilisant la logique floue.Partant d’un système commandé, nous avons présenté en détail une démarche à suivre pour la mise en œuvre d’un modèle de surveillance en se basant sur les chroniques et les arbres de défaillance flous. Cette démarche est appliquée à un atelier de production laitière / The works proposed in this thesis are interested in controlling and monitoring of a particular class of production system : manufacturing job-shops with time constraints. We suppose in the study that the resources are allocated and the operations order is fixed by the module of planning/scheduling. The assumptions of repetitive functioning mode with and without assembling tasks are adopted. For this type of problems, the formalism of P-time Petri nets is used in order to study the operations time constraints.A study of the robustness of the manufacturing workshop to time constraints, has been developed. The robustness is approached with and without control reaction qualified as active robustness and passive robustness respectively, towards time disturbances. A computing algorithm of the upper bound of the passive robustness is presented. In addition, three robust control strategies facing time disturbances were developed.Furthermore, uncertainty in manufacturing systems has been studied. Our contribution in this context is by integration of the analytical knowledge of the robustness in the filtering mechanism of sensors signals that are associated to operations, by using fuzzy logic.Starting from a controlled system, we have presented in detail, a method to be followed for the implementation of a monitoring model based on the chronicles and fuzzy fault tree analysis. This approach is applied to a milk production unit