State-of-the-art on evolution and reactivity

This report starts by, in Chapter 1, outlining aspects of querying and updating resources on the Web and on the Semantic Web, including the development of query and update languages to be carried out within the Rewerse project. From this outline, it becomes clear that several existing research areas and topics are of interest for this work in Rewerse. In the remainder of this report we further present state of the art surveys in a selection of such areas and topics. More precisely: in Chapter 2 we give an overview of logics for reasoning about state change and updates; Chapter 3 is devoted to briefly describing existing update languages for the Web, and also for updating logic programs; in Chapter 4 event-condition-action rules, both in the context of active database systems and in the context of semistructured data, are surveyed; in Chapter 5 we give an overview of some relevant rule-based agents frameworks

State-of-the-art on evolution and reactivity

This report starts by, in Chapter 1, outlining aspects of querying and updating resources on the Web and on the Semantic Web, including the development of query and update languages to be carried out within the Rewerse project. From this outline, it becomes clear that several existing research areas and topics are of interest for this work in Rewerse. In the remainder of this report we further present state of the art surveys in a selection of such areas and topics. More precisely: in Chapter 2 we give an overview of logics for reasoning about state change and updates; Chapter 3 is devoted to briefly describing existing update languages for the Web, and also for updating logic programs; in Chapter 4 event-condition-action rules, both in the context of active database systems and in the context of semistructured data, are surveyed; in Chapter 5 we give an overview of some relevant rule-based agents frameworks

Using active database for management of requirements change

Software system development projects experience numerous changes during their life cycle. These changes are inevitable and driven by several factors including changes to a system\u27s environment and changes of customers\u27 needs. Requirements change has been reported as the major contributing factor for poor quality or even failures of software projects. This indicates that management of requirements change still remains a challenging problem in software development. A critical part of the requirements change management process is impact analysis. To carry out impact assessment, traceability information is needed. Over two decades, requirements traceability has been an important research topic in software research, but the actual practice of maintaining traceability information is not always entirely successful. In this thesis, a new traceability technique was presented for mapping dynamic behaviors of requirements into Active Databases. The technique keeps requirements and their related artifacts synchronized with respect to their states. It automatically maintains traceability links between requirements and related artifacts when a requirement is changed. This approach can not only efficiently handle basic and necessary traceability functions, but also centralize reactive behavior by using Active Database to ensure no one bypass traceability policies.Dept. of Computer Science. Paper copy at Leddy Library: Theses & Major Papers - Basement, West Bldg. / Call Number: Thesis2005 .G42. Source: Masters Abstracts International, Volume: 44-03, page: 1401. Thesis (M.Sc.)--University of Windsor (Canada), 2005

Coordination of ECA Rules by Verification and Control

International audienceEvent-Condition-Action (ECA) rules are a widely used language for the high level specification of controllers in adaptive systems, such as Cyber-Physical Systems and smart environments, where devices equipped with sensors and actuators are controlled according to a set of rules. The evaluation and execution of every ECA rule is considered to be independent from the others, but interactions of rule actions can cause the system behaviors to be unpredictable or unsafe. Typical problems are in redundancy of rules, inconsistencies, circularity, or application-dependent safety issues. Hence, there is a need for coordination of ECA rule-based systems in order to ensure safety objectives. We propose a tool-supported method for verifying and controlling the correct interactions of rules, relying on formal models related to reactive systems, and Discrete Controller Synthesis (DCS) to generate correct rule controllers

Towards Large-Scale, Heterogeneous Anomaly Detection Systems in Industrial Networks: A Survey of Current Trends

Industrial Networks (INs) are widespread environments where heterogeneous devices collaborate to control and monitor physical processes. Some of the controlled processes belong to Critical Infrastructures (CIs), and, as such, IN protection is an active research field. Among different types of security solutions, IN Anomaly Detection Systems (ADSs) have received wide attention from the scientific community.While INs have grown in size and in complexity, requiring the development of novel, Big Data solutions for data processing, IN ADSs have not evolved at the same pace. In parallel, the development of BigData frameworks such asHadoop or Spark has led the way for applying Big Data Analytics to the field of cyber-security,mainly focusing on the Information Technology (IT) domain. However, due to the particularities of INs, it is not feasible to directly apply IT security mechanisms in INs, as IN ADSs face unique characteristics. In this work we introduce three main contributions. First, we survey the area of Big Data ADSs that could be applicable to INs and compare the surveyed works. Second, we develop a novel taxonomy to classify existing INbased ADSs. And, finally, we present a discussion of open problems in the field of Big Data ADSs for INs that can lead to further development

A Survey on Transactional Stream Processing

Transactional stream processing (TSP) strives to create a cohesive model that merges the advantages of both transactional and stream-oriented guarantees. Over the past decade, numerous endeavors have contributed to the evolution of TSP solutions, uncovering similarities and distinctions among them. Despite these advances, a universally accepted standard approach for integrating transactional functionality with stream processing remains to be established. Existing TSP solutions predominantly concentrate on specific application characteristics and involve complex design trade-offs. This survey intends to introduce TSP and present our perspective on its future progression. Our primary goals are twofold: to provide insights into the diverse TSP requirements and methodologies, and to inspire the design and development of groundbreaking TSP systems

A Method to Reduce the Cost of Resilience Benchmarking of SelfAdaptive Systems

Ensuring the resilience of self-adaptive systems used in critical infrastructure systems is a concern as their failure has severe societal and financial consequences. The current trends in the growth of the scale and complexity of society\u27s workload demands and the systems built to cope with these demands increases the anxiety surrounding service disruptions. Self-adaptive mechanisms instill dynamic behavior to systems in an effort to improve their resilience to runtime changes that would otherwise result in service disruption or failure, such as faults, errors, and attacks. Thus, the evaluation of a self-adaptive system\u27s resilience is critical to ensure expected operational qualities and elicit trust in their services. However, resilience benchmarking is often overlooked or avoided due to the high cost associated with evaluating the runtime behavior of large and complex self-adaptive systems against an almost infinite number of possible runtime changes. Researchers have focused on techniques to reduce the overall costs of benchmarking while ensuring the comprehensiveness of the evaluation as testing costs have been found to account for 50 to 80% of total system costs. These test suite minimization techniques include the removal of irrelevant, redundant, and repetitive test cases to ensure that only relevant tests that adequately elicit the expected system responses are enumerated. However, these approaches require an exhaustive test suite be defined first and then the irrelevant tests are filtered out, potentially negating any cost savings. This dissertation provides a new approach of defining a resilience changeload for self-adaptive systems by incorporating goal-oriented requirements engineering techniques to extract system information and guide the identification of relevant runtime changes. The approach constructs a goal refinement graph consisting of the system\u27s refined goals, runtime actions, self-adaptive agents, and underlying runtime assumptions that is used to identify obstructing conditions to runtime goal attainment. Graph theory is then used to gauge the impact of obstacles on runtime goal attainment and those that exceed the relevance requirement are included in the resilience changeload for enumeration. The use of system knowledge to guide the changeload definition process increased the relevance of the resilience changeload while minimizing the test suite, resulting in a reduction of overall benchmarking costs. Analysis of case study results confirmed that the new approach was more cost effective on the same subject system over previous work. The new approach was shown to reduce the overall costs by 79.65%, increase the relevance of the defined test suite, reduce the amount of wasted effort, and provide a greater return on investment over previous work by a factor of two

Automated information distribution in low bandwidth environments

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Civil and Environmental Engineering, 1999.Includes bibliographical references (leaves 62-64).by Rabih M. Zbib.S.M