Composition of Nondeterministic and Stochastic Services for LTLf Task Specifications

In this paper, we study the composition of services so as to obtain runs satisfying a task specification in Linear Temporal Logic on finite traces (LTLf). We study the problem in the case services are nondeterministic and the LTLf specification can be exactly met, and in the case services are stochastic, where we are interested in maximizing the probability of satisfaction of the LTLf specification and, simultaneously, minimizing the utilization cost of the services. To do so, we combine techniques from LTLf synthesis, service composition \`a la Roman Model, reactive synthesis, and bi-objective lexicographic optimization on MDPs. This framework has several interesting applications, including Smart Manufacturing and Digital Twins.Comment: 23 pages, 1 figur

Uma abordagem baseada em planejamento não-determinístico e SAT para a composição resiliente e automática de web services

Dissertação (mestrado) - Universidade Federal de Santa Catarina, Centro Tecnológico, Programa de Pós-Graduação em Ciência da Computação, Florianópolis, 2016.Web services têm sido cada vez mais adotados por organizações na implantação de processos de negócio e integração de sistemas heterogêneos.Todavia, os Web services estão vulneráveis a uma série de problemas de execução (serviços indisponíveis, resultados insatisfatórios,descumprimento de parâmetros de qualidade, violações de SLA,falhas de comunicação, dentre outros) que podem fazer com que os seus comportamentos sejam diferentes do esperado, impedindo-os de cumprirem com sucesso as tarefas para as quais foram designados. Neste sentido, é importante levar em consideração que o comportamento dos Web services é intrinsecamente não-determinístico, muitas vezes inesperado e inadequado. Vários trabalhos têm sido propostos para se obter, de modo eficiente, composições de Web services. Entretanto,com algumas exceções, a maioria ignora os problemas de execução que podem ocorrer em tempo de execução e afetar as composições. Neste contexto, este trabalho apresenta uma abordagem para a obtenção decomposições resilientes de Web services, isto é, composições capazes de contornar problemas de execução para satisfazer os objetivos do usuário.A abordagem proposta combina planejamento não-determinístico e SAT (satisfazibilidade booleana) para se obter k planos alternativos(composições alternativas de Web services) que solucionam uma dada requisição, onde um plano é visto como uma sequência de ações, e as ações correspondem a invocações de operações de Web services. Os planos obtidos são fundidos em uma estratégia de contingência na forma de uma árvore de decisão binária (composição de Web services resiliente resultante). A estratégia de contingência permite a motores de execução de processos acompanhar o progresso da execução da composição e lidar com problemas que ocorrem em ambientes dinâmicos e não-determinísticos mediante a rápida seleção, com custo mínimo, de uma composição alternativa e compatível com aquela que falhou. Resultados de experimentos com a abordagem proposta mostraram que é possível obter estratégias de contingências em tempos relativamente baixos e com uma quantidade grande e satisfatória de planos. Em torno de um minuto foi possível construir árvores binárias com uma média de 6723 planos, e em torno de cinco minutos árvores binárias foram construídas com uma média de 15148 planos.Abstract : Web services have been increasingly adopted by organizations to implement their business processes and to integrate heterogeneous systems. However, Web services are vulnerable to a wide number of execution problems (e.g., unavailable services, unappropriated results, noncompliance of quality parameters, service level agreement violations, communication failures, among others) which can make them behave differently from the expected and prevent them to comply with their tasks successfully. In this regard, it is important to take into account that the behavior of Web services is intrinsically nondeterministic, often unexpected and inappropriate. Several works have been proposed to efficiently obtain Web service compositions. However, with few exceptions, most of them disregard contingencies which may happen at runtime and affect the compositions. In this context, this paper presents an approach for obtaining resilient compositions of Web services, i.e, compositions that are able to circumvent problems which may occur in the execution environments in order to meet the user goals. This approach combines nondeterministic planning and SAT (boolean satisfiability) to obtain k plans (alternative compositions of Web services) that address a given user request, where a plan is a sequence of actions, and an action corresponds to an invocation of aWeb services operation. The obtained plans are merged into a contingency strategy in the form of a binary decision tree (i.e., the resulting resilient composition of Web services). The contingency strategy enables process execution engines to keep track of the composition execution progress and deal with problems which happen in dynamic and nondeterministic environments by quickly selecting, with minimum cost, a suitable alternative composition to continue the execution towards the satisfaction of the user s goals. Experimental results using this approach have showed that it is possible to obtain contingency strategies in relatively low times and with a large and satisfactory amount of plans. In about one minute it was possible to build binary trees with an average of 6723 plans, and in about five minutes binary trees were built with an average of 15148 plans

WS-Pro: a Petri net based performance-driven service composition framework

As an emerging area gaining prevalence in the industry, Web Services was established to satisfy the needs for better flexibility and higher reliability in web applications. However, due to the lack of reliable frameworks and difficulties in constructing versatile service composition platform, web developers encountered major obstacles in large-scale deployment of web services. Meanwhile, performance has been one of the major concerns and a largely unexplored area in Web Services research. There is high demand for researchers to conceive and develop feasible solutions to design, monitor, and deploy web service systems that can adapt to failures, especially performance failures. Though many techniques have been proposed to solve this problem, none of them offers a comprehensive solution to overcome the difficulties that challenge practitioners. Central to the performance-engineering studies, performance analysis and performance adaptation are of paramount importance to the success of a software project. The industry learned through many hard lessons the significance of well-founded and well-executed performance engineering plans. An important fact is that it is too expensive to tackle performance evaluation, mostly through performance testing, after the software is developed. This is especially true in recent decades when software complexity has risen sharply. After the system is deployed, performance adaptation is essential to maintaining and improving software system reliability. Performance adaptation provides techniques to mitigate the consequence of performance failures and therefore is an important research issue. Performance adaptation is particularly meaningful for mission-critical software systems and software systems with inevitable frequent performance failures, such as Web Services. This dissertation focuses on Web Services framework and proposes a performance-driven service composition scheme, called WS-Pro, to support both performance analysis and performance adaptation. A formalism of transformation from WS-BPEL to Petri net is first defined to enable the analysis of system properties and facilitate quality prediction. A state-transition based proof is presented to show that the transformed Petri net model correctly simulates the behavior of the WS-BPEL process. The generated Petri net model was augmented using performance data supplied by both historical data and runtime data. Results of executing the Petri nets suggest that optimal composition plans can be achieved based on the proposed method. The performance of service composition procedure is an important research issue which has not been sufficiently treated by researchers. However, such an issue is critical for dynamic service composition, where re-planning must be done in a timely manner. In order to improve the performance of service composition procedure and enhance performance adaptation, this dissertation presents an algorithm to remove loops in the reachability graphs so that a large portion of the computation time of service composition can be moved to a pre-processing unit; hence the response time is shortened during runtime. We also extended the WS-Pro to the ubiquitous computing area to improve fault-tolerance

Combining design and performance in a data visualization management system

Interactive data visualizations have emerged as a prominent way to bring data exploration and analysis capabilities to both technical and non-technical users. Despite their ubiquity and importance across applications, multiple design- and performance-related challenges lurk beneath the visualization creation process. To meet these challenges, application designers either use visualization systems (e.g., Endeca, Tableau, and Splunk) that are tailored to domain-specific analyses, or manually design, implement, and optimize their own solutions. Unfortunately, both approaches typically slow down the creation process. In this paper, we describe the status of our progress towards an end-to-end relational approach in our data visualization management system (DVMS). We introduce DeVIL, a SQL-like language to express static as well as interactive visualizations as database views that combine user inpu

Extension of the behavior composition framework in presence of failures using recovery techniques and AKKA

Abstract: Fault tolerance is an essential property to be satis ed in the composition of services, but reaching a high level of fault tolerance remains a challenge. In the area of ubiquitous computing, the composition of services is inevitable when a request cannot be carried out by a single service, but by a combination of several services. This thesis studies fault tolerance in the context of a general behavior composition framework. This approach raises, rst, the problem of the synthesis of controllers (or compositions) in order to coordinate a set of available services to achieve a new service, the target service and, second, the exploitation of all compositions to make the new service fault tolerant. Although a solution has been proposed by the authors of the behavior composition framework, it is incomplete and has not been evaluated experimentally or in situ. This thesis brings two contributions to this problem. On one hand, it considers the case in which the service selected by the controller is temporarily or permanently unavailable by exploiting recovery techniques to identify a consistent state of the system from which it may progress using other services or leave it in a coherent state when none of the available services no longer allows progression. On the other hand, it evaluates several recovery solutions, each useful in services malfunction situations, using a case study implemented with the aid of Akka, a tool that facilitates the development of reactive, concurrent and distributed systems.La tolérance aux fautes est une propriété indispensable à satisfaire dans la composition de services, mais atteindre un haut de niveau de tolérance aux fautes représente un défi majeur. Dans l'ère de l'informatique ubiquitaire, la composition de services est inévitable lorsqu'une requête ne peut être réalisée par un seul service, mais par la combinaison de plusieurs services. Ce mémoire étudie la tolérance aux fautes dans le contexte d'un cadre général de composition de comportements (behavior composition framework en anglais). Cette approche soulève, tout d'abord, le problème de la synthèse de contrôleurs (ou compositions) de façon à coordonner un ensemble de services disponibles afin de réaliser un nouveau service, le service cible et, ensuite, celui de l'exploitation de l'ensemble des compositions afin de rendre le nouveau service tolérant aux fautes. Bien qu'une solution ait été proposée par les auteurs de ce cadre de composition, elle est incomplète et elle n'a pas été évaluée expérimentalement ou in situ. Ce mémoire apporte deux contributions à ce problème. D'une part, il considère le cas dans lequel le service visé par le contrôleur est temporairement ou définitivement non disponible en exploitant des techniques de reprise afin d'identifier un état cohérent du système à partir duquel il peut progresser en utilisant d'autres services ou de le laisser dans un état cohérent lorsqu'aucun service, parmi ceux disponibles, ne permet plus de progression. D'autre part, il évalue plusieurs solutions de reprise, chacune utile dans des situations particulières de pannes, à l'aide d'une étude de cas implémentée en Akka, un outil qui permet aisément de mettre en oeuvre des systèmes réactifs, concurrents et répartis

Enabling Resilience in Cyber-Physical-Human Water Infrastructures

Rapid urbanization and growth in urban populations have forced community-scale infrastructures (e.g., water, power and natural gas distribution systems, and transportation networks) to operate at their limits. Aging (and failing) infrastructures around the world are becoming increasingly vulnerable to operational degradation, extreme weather, natural disasters and cyber attacks/failures. These trends have wide-ranging socioeconomic consequences and raise public safety concerns. In this thesis, we introduce the notion of cyber-physical-human infrastructures (CPHIs) - smart community-scale infrastructures that bridge technologies with physical infrastructures and people. CPHIs are highly dynamic stochastic systems characterized by complex physical models that exhibit regionwide variability and uncertainty under disruptions. Failures in these distributed settings tend to be difficult to predict and estimate, and expensive to repair. Real-time fault identification is crucial to ensure continuity of lifeline services to customers at adequate levels of quality. Emerging smart community technologies have the potential to transform our failing infrastructures into robust and resilient future CPHIs.In this thesis, we explore one such CPHI - community water infrastructures. Current urban water infrastructures, that are decades (sometimes over a 100 years) old, encompass diverse geophysical regimes. Water stress concerns include the scarcity of supply and an increase in demand due to urbanization. Deterioration and damage to the infrastructure can disrupt water service; contamination events can result in economic and public health consequences. Unfortunately, little investment has gone into modernizing this key lifeline.To enhance the resilience of water systems, we propose an integrated middleware framework for quick and accurate identification of failures in complex water networks that exhibit uncertain behavior. Our proposed approach integrates IoT-based sensing, domain-specific models and simulations with machine learning methods to identify failures (pipe breaks, contamination events). The composition of techniques results in cost-accuracy-latency tradeoffs in fault identification, inherent in CPHIs due to the constraints imposed by cyber components, physical mechanics and human operators. Three key resilience problems are addressed in this thesis; isolation of multiple faults under a small number of failures, state estimation of the water systems under extreme events such as earthquakes, and contaminant source identification in water networks using human-in-the-loop based sensing. By working with real world water agencies (WSSC, DC and LADWP, LA), we first develop an understanding of operations of water CPHI systems. We design and implement a sensor-simulation-data integration framework AquaSCALE, and apply it to localize multiple concurrent pipe failures. We use a mixture of infrastructure measurements (i.e., historical and live water pressure/flow), environmental data (i.e., weather) and human inputs (i.e., twitter feeds), combined and enhanced with the domain model and supervised learning techniques to locate multiple failures at fine levels of granularity (individual pipeline level) with detection time reduced by orders of magnitude (from hours/days to minutes). We next consider the resilience of water infrastructures under extreme events (i.e., earthquakes) - the challenge here is the lack of apriori knowledge and the increased number and severity of damages to infrastructures. We present a graphical model based approach for efficient online state estimation, where the offline graph factorization partitions a given network into disjoint subgraphs, and the belief propagation based inference is executed on-the-fly in a distributed manner on those subgraphs. Our proposed approach can isolate 80% broken pipes and 99% loss-of-service to end-users during an earthquake.Finally, we address issues of water quality - today this is a human-in-the-loop process where operators need to gather water samples for lab tests. We incorporate the necessary abstractions with event processing methods into a workflow, which iteratively selects and refines the set of potential failure points via human-driven grab sampling. Our approach utilizes Hidden Markov Model based representations for event inference, along with reinforcement learning methods for further refining event locations and reducing the cost of human efforts.The proposed techniques are integrated into a middleware architecture, which enables components to communicate/collaborate with one another. We validate our approaches through a prototype implementation with multiple real-world water networks, supply-demand patterns from water utilities and policies set by the U.S. EPA. While our focus here is on water infrastructures in a community, the developed end-to-end solution is applicable to other infrastructures and community services which operate in disruptive and resource-constrained environments

Extension d'un cadre de composition de comportements en présence de pannes à l'aide de techniques de reprise et de AKKA

Abstract: Fault tolerance is an essential property to be satis ed in the composition of services, but reaching a high level of fault tolerance remains a challenge. In the area of ubiquitous computing, the composition of services is inevitable when a request cannot be carried out by a single service, but by a combination of several services. This thesis studies fault tolerance in the context of a general behavior composition framework. This approach raises, rst, the problem of the synthesis of controllers (or compositions) in order to coordinate a set of available services to achieve a new service, the target service and, second, the exploitation of all compositions to make the new service fault tolerant. Although a solution has been proposed by the authors of the behavior composition framework, it is incomplete and has not been evaluated experimentally or in situ. This thesis brings two contributions to this problem. On one hand, it considers the case in which the service selected by the controller is temporarily or permanently unavailable by exploiting recovery techniques to identify a consistent state of the system from which it may progress using other services or leave it in a coherent state when none of the available services no longer allows progression. On the other hand, it evaluates several recovery solutions, each useful in services malfunction situations, using a case study implemented with the aid of Akka, a tool that facilitates the development of reactive, concurrent and distributed systems.La tolérance aux fautes est une propriété indispensable à satisfaire dans la composition de services, mais atteindre un haut de niveau de tolérance aux fautes représente un défi majeur. Dans l'ère de l'informatique ubiquitaire, la composition de services est inévitable lorsqu'une requête ne peut être réalisée par un seul service, mais par la combinaison de plusieurs services. Ce mémoire étudie la tolérance aux fautes dans le contexte d'un cadre général de composition de comportements (behavior composition framework en anglais). Cette approche soulève, tout d'abord, le problème de la synthèse de contrôleurs (ou compositions) de façon à coordonner un ensemble de services disponibles afin de réaliser un nouveau service, le service cible et, ensuite, celui de l'exploitation de l'ensemble des compositions afin de rendre le nouveau service tolérant aux fautes. Bien qu'une solution ait été proposée par les auteurs de ce cadre de composition, elle est incomplète et elle n'a pas été évaluée expérimentalement ou in situ. Ce mémoire apporte deux contributions à ce problème. D'une part, il considère le cas dans lequel le service visé par le contrôleur est temporairement ou définitivement non disponible en exploitant des techniques de reprise afin d'identifier un état cohérent du système à partir duquel il peut progresser en utilisant d'autres services ou de le laisser dans un état cohérent lorsqu'aucun service, parmi ceux disponibles, ne permet plus de progression. D'autre part, il évalue plusieurs solutions de reprise, chacune utile dans des situations particulières de pannes, à l'aide d'une étude de cas implémentée en Akka, un outil qui permet aisément de mettre en oeuvre des systèmes réactifs, concurrents et répartis

A new MDA-SOA based framework for intercloud interoperability

Cloud computing has been one of the most important topics in Information Technology which aims to assure scalable and reliable on-demand services over the Internet. The expansion of the application scope of cloud services would require cooperation between clouds from different providers that have heterogeneous functionalities. This collaboration between different cloud vendors can provide better Quality of Services (QoS) at the lower price. However, current cloud systems have been developed without concerns of seamless cloud interconnection, and actually they do not support intercloud interoperability to enable collaboration between cloud service providers. Hence, the PhD work is motivated to address interoperability issue between cloud providers as a challenging research objective. This thesis proposes a new framework which supports inter-cloud interoperability in a heterogeneous computing resource cloud environment with the goal of dispatching the workload to the most effective clouds available at runtime. Analysing different methodologies that have been applied to resolve various problem scenarios related to interoperability lead us to exploit Model Driven Architecture (MDA) and Service Oriented Architecture (SOA) methods as appropriate approaches for our inter-cloud framework. Moreover, since distributing the operations in a cloud-based environment is a nondeterministic polynomial time (NP-complete) problem, a Genetic Algorithm (GA) based job scheduler proposed as a part of interoperability framework, offering workload migration with the best performance at the least cost. A new Agent Based Simulation (ABS) approach is proposed to model the inter-cloud environment with three types of agents: Cloud Subscriber agent, Cloud Provider agent, and Job agent. The ABS model is proposed to evaluate the proposed framework.Fundação para a Ciência e a Tecnologia (FCT) - (Referencia da bolsa: SFRH SFRH / BD / 33965 / 2009) and EC 7th Framework Programme under grant agreement n° FITMAN 604674 (http://www.fitman-fi.eu

Context-driven methodologies for context-aware and adaptive systems

Applications which are both context-aware and adapting, enhance users’ experience by anticipating their need in relation with their environment and adapt their behavior according to environmental changes. Being by definition both context-aware and adaptive these applications suffer both from faults related to their context-awareness and to their adaptive nature plus from a novel variety of faults originated by the combination of the two. This research work analyzes, classifies, detects, and reports faults belonging to this novel class aiming to improve the robustness of these Context-Aware Adaptive Applications (CAAAs). To better understand the peculiar dynamics driving the CAAAs adaptation mechanism a general high-level architectural model has been designed. This architectural model clearly depicts the stream of information coming from sensors and being computed all the way to the adaptation mechanism. The model identifies a stack of common components representing increasing abstractions of the context and their general interconnections. Known faults involving context data can be re-examined according to this architecture and can be classified in terms of the component in which they are happening and in terms of their abstraction from the environment. Resulting from this classification is a CAAA-oriented fault taxonomy. Our architectural model also underlines that there is a common evolutionary path for CAAAs and shows the importance of the adaptation logic. Indeed most of the adaptation failures are caused by invalid interpretations of the context by the adaptation logic. To prevent such faults we defined a model, the Adaptation Finite-State Machine (A-FSM), describing how the application adapts in response to changes in the context. The A-FSM model is a powerful instrument which allows developers to focus in those context-aware and adaptive aspects in which faults reside. In this model we have identified a set of patterns of faults representing the most common faults in this application domain. Such faults are represented as violation of given properties in the A-FSM. We have created four techniques to detect such faults. Our proposed algorithms are based on three different technologies: enumerative, symbolic and goal planning. Such techniques compensate each other. We have evaluated them by comparing them to each other using both crafted models and models extracted from existing commercial and free applications. In the evaluation we observe the validity, the readability of the reported faults, the scalability and their behavior in limited memory environments. We conclude this Thesis by suggesting possible extensions