Temporal Mining for Distributed Systems

Many systems and applications are continuously producing events. These events are used to record the status of the system and trace the behaviors of the systems. By examining these events, system administrators can check the potential problems of these systems. If the temporal dynamics of the systems are further investigated, the underlying patterns can be discovered. The uncovered knowledge can be leveraged to predict the future system behaviors or to mitigate the potential risks of the systems. Moreover, the system administrators can utilize the temporal patterns to set up event management rules to make the system more intelligent. With the popularity of data mining techniques in recent years, these events grad- ually become more and more useful. Despite the recent advances of the data mining techniques, the application to system event mining is still in a rudimentary stage. Most of works are still focusing on episodes mining or frequent pattern discovering. These methods are unable to provide a brief yet comprehensible summary to reveal the valuable information from the high level perspective. Moreover, these methods provide little actionable knowledge to help the system administrators to better man- age the systems. To better make use of the recorded events, more practical techniques are required. From the perspective of data mining, three correlated directions are considered to be helpful for system management: (1) Provide concise yet comprehensive summaries about the running status of the systems; (2) Make the systems more intelligence and autonomous; (3) Effectively detect the abnormal behaviors of the systems. Due to the richness of the event logs, all these directions can be solved in the data-driven manner. And in this way, the robustness of the systems can be enhanced and the goal of autonomous management can be approached. This dissertation mainly focuses on the foregoing directions that leverage tem- poral mining techniques to facilitate system management. More specifically, three concrete topics will be discussed, including event, resource demand prediction, and streaming anomaly detection. Besides the theoretic contributions, the experimental evaluation will also be presented to demonstrate the effectiveness and efficacy of the corresponding solutions.

Formal modeling and analysis techniques for high level Petri nets

Petri Nets are a formal, graphical and executable modeling technique for the specification and analysis of concurrent and distributed systems and have been widely applied in computer science and many other engineering disciplines. Low level Petri nets are simple and useful for modeling control flows but not powerful enough to define data and system functionality. High level Petri nets (HLPNs) have been developed to support data and functionality definitions, such as using complex structured data as tokens and algebraic expressions as transition formulas. Compared to low level Petri nets, HLPNs result in compact system models that are easier to be understood. Therefore, HLPNs are more useful in modeling complex systems. ^ There are two issues in using HLPNs—modeling and analysis. Modeling concerns the abstracting and representing the systems under consideration using HLPNs, and analysis deals with effective ways study the behaviors and properties of the resulting HLPN models. In this dissertation, several modeling and analysis techniques for HLPNs are studied, which are integrated into a framework that is supported by a tool. ^ For modeling, this framework integrates two formal languages: a type of HLPNs called Predicate Transition Net (PrT Net) is used to model a system's behavior and a first-order linear time temporal logic (FOLTL) to specify the system's properties. The main contribution of this dissertation with regard to modeling is to develop a software tool to support the formal modeling capabilities in this framework. ^ For analysis, this framework combines three complementary techniques, simulation, explicit state model checking and bounded model checking (BMC). Simulation is a straightforward and speedy method, but only covers some execution paths in a HLPN model. Explicit state model checking covers all the execution paths but suffers from the state explosion problem. BMC is a tradeoff as it provides a certain level of coverage while more efficient than explicit state model checking. The main contribution of this dissertation with regard to analysis is adapting BMC to analyze HLPN models and integrating the three complementary analysis techniques in a software tool to support the formal analysis capabilities in this framework. ^ The SAMTools developed for this framework in this dissertation integrates three tools: PIPE+ for HLPNs behavioral modeling and simulation, SAMAT for hierarchical structural modeling and property specification, and PIPE+Verifier for behavioral verification.^

Formal Modeling and Analysis Techniques for High Level Petri Nets

Petri Nets are a formal, graphical and executable modeling technique for the specification and analysis of concurrent and distributed systems and have been widely applied in computer science and many other engineering disciplines. Low level Petri nets are simple and useful for modeling control flows but not powerful enough to define data and system functionality. High level Petri nets (HLPNs) have been developed to support data and functionality definitions, such as using complex structured data as tokens and algebraic expressions as transition formulas. Compared to low level Petri nets, HLPNs result in compact system models that are easier to be understood. Therefore, HLPNs are more useful in modeling complex systems. There are two issues in using HLPNs - modeling and analysis. Modeling concerns the abstracting and representing the systems under consideration using HLPNs, and analysis deals with effective ways study the behaviors and properties of the resulting HLPN models. In this dissertation, several modeling and analysis techniques for HLPNs are studied, which are integrated into a framework that is supported by a tool. For modeling, this framework integrates two formal languages: a type of HLPNs called Predicate Transition Net (PrT Net) is used to model a system's behavior and a first-order linear time temporal logic (FOLTL) to specify the system's properties. The main contribution of this dissertation with regard to modeling is to develop a software tool to support the formal modeling capabilities in this framework. For analysis, this framework combines three complementary techniques, simulation, explicit state model checking and bounded model checking (BMC). Simulation is a straightforward and speedy method, but only covers some execution paths in a HLPN model. Explicit state model checking covers all the execution paths but suffers from the state explosion problem. BMC is a tradeoff as it provides a certain level of coverage while more efficient than explicit state model checking. The main contribution of this dissertation with regard to analysis is adapting BMC to analyze HLPN models and integrating the three complementary analysis techniques in a software tool to support the formal analysis capabilities in this framework. The SAMTools developed for this framework in this dissertation integrates three tools: PIPE+ for HLPNs behavioral modeling and simulation, SAMAT for hierarchical structural modeling and property specification, and PIPE+Verifier for behavioral verification.

A methodology for formally modeling and analyzing software architecture of mobile agent systems

A methodology for formally modeling and analyzing software architecture of mobile agent systems provides a solid basis to develop high quality mobile agent systems, and the methodology is helpful to study other distributed and concurrent systems as well. However, it is a challenge to provide the methodology because of the agent mobility in mobile agent systems.^ The methodology was defined from two essential parts of software architecture: a formalism to define the architectural models and an analysis method to formally verify system properties. The formalism is two-layer Predicate/Transition (PrT) nets extended with dynamic channels, and the analysis method is a hierarchical approach to verify models on different levels. The two-layer modeling formalism smoothly transforms physical models of mobile agent systems into their architectural models. Dynamic channels facilitate the synchronous communication between nets, and they naturally capture the dynamic architecture configuration and agent mobility of mobile agent systems. Component properties are verified based on transformed individual components, system properties are checked in a simplified system model, and interaction properties are analyzed on models composing from involved nets. Based on the formalism and the analysis method, this researcher formally modeled and analyzed a software architecture of mobile agent systems, and designed an architectural model of a medical information processing system based on mobile agents. The model checking tool SPIN was used to verify system properties such as reachability, concurrency and safety of the medical information processing system. ^ From successful modeling and analyzing the software architecture of mobile agent systems, the conclusion is that PrT nets extended with channels are a powerful tool to model mobile agent systems, and the hierarchical analysis method provides a rigorous foundation for the modeling tool. The hierarchical analysis method not only reduces the complexity of the analysis, but also expands the application scope of model checking techniques. The results of formally modeling and analyzing the software architecture of the medical information processing system show that model checking is an effective and an efficient way to verify software architecture. Moreover, this system shows a high level of flexibility, efficiency and low cost of mobile agent technologies. ^

The effects of carbon dioxide fertilization on the ecology of tropical seagrass communities

Increasing atmospheric CO2 concentrations associated with climate change will likely influence a wide variety of ecosystems. Terrestrial research has examined the effects of increasing CO2 concentrations on the functionality of plant systems; with studies ranging in scale from the short-term responses of individual leaves, to long-term ecological responses of complete forests. While terrestrial plants have received much attention, studies on the responses of marine plants (seagrasses) to increased CO 2(aq) concentrations remain relatively sparse, with most research limited to small-scale, ex situ experimentation. Furthermore, few studies have attempted to address similarities between terrestrial and seagrass responses to increases in CO2(aq). The goals of this dissertation are to expand the scope of marine climate change research, and examine how the tropical seagrass, Thalassia testudinum responds to increasing CO 2(aq)concentrations over multiple spatial and temporal scales. ^ Manipulative laboratory and field experimentation reveal that, similar to terrestrial plants, seagrasses strongly respond to increases in CO 2(aq) concentrations. Using a novel field technique, in situ field manipulations show that over short time scales, seagrasses respond to elevated CO2(aq) by increasing leaf photosynthetic rates and the production of soluble carbohydrates. Declines in leaf nutrient (nitrogen and phosphorus) content were additionally detected, paralleling responses from terrestrial systems. Over long time scales, seagrasses increase total above- and belowground biomass with elevated CO2(aq), suggesting that, similar to terrestrial research, pervasive increases in atmospheric and oceanic CO2(aq) concentrations stand to influence the productivity and functionality of these systems. Furthermore, field experiments reveal that seagrass epiphytes, which comprise an important component of seagrass ecosystems, additionally respond to increased CO2(aq) with strong declines in calcified taxa and increases in fleshy taxa. ^ Together, this work demonstrates that increasing CO2(aq) concentrations will alter the functionality of seagrass ecosystems by increasing plant productivity and shifting the composition of the epiphyte community. These results have implications for future rates of carbon storage and sediment production within these widely distributed systems.^

A deontic analysis of inter -organizational control requirements

This research focuses on the design and verification of inter-organizational controls. Instead of looking at a documentary procedure, which is the flow of documents and data among the parties, the research examines the underlying deontic purpose of the procedure, the so-called deontic process, and identifies control requirements to secure this purpose. The vision of the research is a formal theory for streamlining bureaucracy in business and government procedures. ^ Underpinning most inter-organizational procedures are deontic relations, which are about rights and obligations of the parties. When all parties trust each other, they are willing to fulfill their obligations and honor the counter parties’ rights; thus controls may not be needed. The challenge is in cases where trust may not be assumed. In these cases, the parties need to rely on explicit controls to reduce their exposure to the risk of opportunism. However, at present there is no analytic approach or technique to determine which controls are needed for a given contracting or governance situation. ^ The research proposes a formal method for deriving inter-organizational control requirements based on static analysis of deontic relations and dynamic analysis of deontic changes. The formal method will take a deontic process model of an inter-organizational transaction and certain domain knowledge as inputs to automatically generate control requirements that a documentary procedure needs to satisfy in order to limit fraud potentials. The deliverables of the research include a formal representation namely Deontic Petri Nets that combine multiple modal logics and Petri nets for modeling deontic processes, a set of control principles that represent an initial formal theory on the relationships between deontic processes and documentary procedures, and a working prototype that uses model checking technique to identify fraud potentials in a deontic process and generate control requirements to limit them. Fourteen scenarios of two well-known international payment procedures—cash in advance and documentary credit—have been used to test the prototype. The results showed that all control requirements stipulated in these procedures could be derived automatically.^

A Deontic Analysis of Inter-Organizational Control Requirements

This research focuses on the design and verification of inter-organizational controls. Instead of looking at a documentary procedure, which is the flow of documents and data among the parties, the research examines the underlying deontic purpose of the procedure, the so-called deontic process, and identifies control requirements to secure this purpose. The vision of the research is a formal theory for streamlining bureaucracy in business and government procedures. Underpinning most inter-organizational procedures are deontic relations, which are about rights and obligations of the parties. When all parties trust each other, they are willing to fulfill their obligations and honor the counter parties’ rights; thus controls may not be needed. The challenge is in cases where trust may not be assumed. In these cases, the parties need to rely on explicit controls to reduce their exposure to the risk of opportunism. However, at present there is no analytic approach or technique to determine which controls are needed for a given contracting or governance situation. The research proposes a formal method for deriving inter-organizational control requirements based on static analysis of deontic relations and dynamic analysis of deontic changes. The formal method will take a deontic process model of an inter-organizational transaction and certain domain knowledge as inputs to automatically generate control requirements that a documentary procedure needs to satisfy in order to limit fraud potentials. The deliverables of the research include a formal representation namely Deontic Petri Nets that combine multiple modal logics and Petri nets for modeling deontic processes, a set of control principles that represent an initial formal theory on the relationships between deontic processes and documentary procedures, and a working prototype that uses model checking technique to identify fraud potentials in a deontic process and generate control requirements to limit them. Fourteen scenarios of two well-known international payment procedures -- cash in advance and documentary credit -- have been used to test the prototype. The results showed that all control requirements stipulated in these procedures could be derived automatically.

GIS-integrated mathematical modeling of social phenomena at macro- and micro- levels—a multivariate geographically-weighted regression model for identifying locations vulnerable to hosting terrorist safe-houses: France as case study

Adaptability and invisibility are hallmarks of modern terrorism, and keeping pace with its dynamic nature presents a serious challenge for societies throughout the world. Innovations in computer science have incorporated applied mathematics to develop a wide array of predictive models to support the variety of approaches to counterterrorism. Predictive models are usually designed to forecast the location of attacks. Although this may protect individual structures or locations, it does not reduce the threat—it merely changes the target. While predictive models dedicated to events or social relationships receive much attention where the mathematical and social science communities intersect, models dedicated to terrorist locations such as safe-houses (rather than their targets or training sites) are rare and possibly nonexistent. At the time of this research, there were no publically available models designed to predict locations where violent extremists are likely to reside. This research uses France as a case study to present a complex systems model that incorporates multiple quantitative, qualitative and geospatial variables that differ in terms of scale, weight, and type. Though many of these variables are recognized by specialists in security studies, there remains controversy with respect to their relative importance, degree of interaction, and interdependence. Additionally, some of the variables proposed in this research are not generally recognized as drivers, yet they warrant examination based on their potential role within a complex system. This research tested multiple regression models and determined that geographically-weighted regression analysis produced the most accurate result to accommodate non-stationary coefficient behavior, demonstrating that geographic variables are critical to understanding and predicting the phenomenon of terrorism. This dissertation presents a flexible prototypical model that can be refined and applied to other regions to inform stakeholders such as policy-makers and law enforcement in their efforts to improve national security and enhance quality-of-life.

A nested Petri net framework for modeling and analyzing multi-agent systems

In the past two decades, multi-agent systems (MAS) have emerged as a new paradigm for conceptualizing large and complex distributed software systems. A multi-agent system view provides a natural abstraction for both the structure and the behavior of modern-day software systems. Although there were many conceptual frameworks for using multi-agent systems, there was no well established and widely accepted method for modeling multi-agent systems. This dissertation research addressed the representation and analysis of multi-agent systems based on model-oriented formal methods. The objective was to provide a systematic approach for studying MAS at an early stage of system development to ensure the quality of design. ^ Given that there was no well-defined formal model directly supporting agent-oriented modeling, this study was centered on three main topics: (1) adapting a well-known formal model, predicate transition nets (PrT nets), to support MAS modeling; (2) formulating a modeling methodology to ease the construction of formal MAS models; and (3) developing a technique to support machine analysis of formal MAS models using model checking technology. PrT nets were extended to include the notions of dynamic structure, agent communication and coordination to support agent-oriented modeling. An aspect-oriented technique was developed to address the modularity of agent models and compositionality of incremental analysis. A set of translation rules were defined to systematically translate formal MAS models to concrete models that can be verified through the model checker SPIN (Simple Promela Interpreter). ^ This dissertation presents the framework developed for modeling and analyzing MAS, including a well-defined process model based on nested PrT nets, and a comprehensive methodology to guide the construction and analysis of formal MAS models.^