Complex Event Processing Techniques Research Articles

A microservice architecture for real-time IoT data processing: A reusable Web of things approach for smart ports

Major advances in telecommunications and the Internet of Things have given rise to numerous smart city scenarios in which smart services are provided. What was once a dream for the future has now become reality. However, the need to provide these smart services quickly, efficiently, in an interoperable manner and in real time is a cutting-edge technological challenge. Although some software architectures offer solutions in this area, these are often limited in terms of reusability and maintenance by independent modules —involving the need for system downtime when maintaining or evolving, as well as by a lack of standards in terms of the interoperability of their interface. In this paper, we propose a fully reusable microservice architecture, standardized through the use of the Web of things paradigm, and with high efficiency in real-time data processing, supported by complex event processing techniques. To illustrate the proposal, we present a fully reusable implementation of the microservices necessary for the deployment of the architecture in the field of air quality monitoring and alerting in smart ports. The performance evaluation of this architecture shows excellent results.

Digital Avatars: Promoting Independent Living for Older Adults

Population ageing, together with the desire to maintain an autonomous lifestyle, poses today’s societies with a challenge that technological advances can help considerably to cope with. The widespread use of smartphones and their increasing computing power and storage capacity make them the ideal tool to achieve this goal. In this paper, we present Digital Avatars, a software framework adapted to the needs of older adults who wish to preserve their lifestyle, but who require assistance through technology. Building on previous work on the People as a Service model, Digital Avatars takes advantage of a smartphone’s capabilities and services to collect information about the people who own them. To do this, it applies Complex Event Processing techniques extended with uncertainty to infer the habits, preferences, and needs of the device owner to build with them an enhanced virtual profile of the user. These virtual profiles are the mechanism for monitoring the quality of life of older adults: analyzing their patterns of activity, reminding them of medication schedules, or detecting risky situations that generate alerts to relatives, caregivers, or the community health system.

Advanced Join Patterns for the Actor Model based on CEP Techniques

Context: Actor-based programming languages offer many essential features for developing modern distributed reactive systems. These systems exploit the actor model's isolation property to fulfill their performance and scalability demands. Unfortunately, the reliance of the model on isolation as its most fundamental property requires programmers to express complex interaction patterns between their actors to be expressed manually in terms of complex combinations of messages sent between the isolated actors. Inquiry: In the last three decades, several language design proposals have been introduced to reduce the complexity that emerges from describing said interaction and coordination of actors. We argue that none of these proposals is satisfactory in order to express the many complex interaction patterns between actors found in modern reactive distributed systems. Approach: We describe seven smart home automation scenarios (in which an actor represents every smart home appliance) to motivate the support by actor languages for five radically different types of message synchronization patterns, which are lacking in modern distributed actor-based languages. Fortunately, these five types of synchronisation patterns have been studied extensively by the Complex Event Processing (CEP) community. Our paper describes how such CEP patterns are elegantly added to an actor-based programming language. Knowledge: Based on our findings, we propose an extension of the single-message matching paradigm of contemporary actor-based languages in order to support a multiple-message matching way of thinking in the same way as proposed by CEP languages. Our proposal thus enriches the actor-model by ways of declaratively describing complex message combinations to which an actor can respond. Grounding: We base the problem-statement of the paper on an online poll in the home automation community that has motivated the real need for the CEP-based synchronisation operators between actors proposed in the paper. Furthermore, we implemented a DSL -- called Sparrow -- that supports said operators and we argue quantitatively (in terms of LOC and in terms of a reduction of the concerns that have to be handled by programmers) that the DSL outperforms existing approaches. Importance: This work aims to provide a set of synchronization operators that help actor-based languages to handle the complex interaction required by modern reactive distributed systems. To the best of our knowledge, our proposal is the first one to add advanced CEP synchronization operators to the -- relatively simplistic single-message based matching -- mechanisms of most actor-based languages.

EVL: A Typed Higher-order Functional Language for Events

We define EVL, a minimal higher-order functional language for dealing with generic events. The notion of generic event extends the well-known notion of event traditionally used in a variety of areas, such as database management, concurrency, reactive systems and cybersecurity. Generic events were introduced in the context of a metamodel to deal with obligations in access control systems. Event specifications are represented as records and we use polymorphic record types to type events in our language. We show how the higher-order capabilities of EVL can be used in the context of Complex Event Processing (CEP), to define higher-order parameterised functions that deal with the usual CEP techniques.

Real-Time Context-Aware Microservice Architecture for Predictive Analytics and Smart Decision-Making

The impressive evolution of the Internet of Things and the great amount of data flowing through the systems provide us with an inspiring scenario for Big Data analytics and advantageous real-time context-aware predictions and smart decision-making. However, this requires a scalable system for constant streaming processing, also provided with the ability of decision-making and action taking based on the performed predictions. This paper aims at proposing a scalable architecture to provide real-time context-aware actions based on predictive streaming processing of data as an evolution of a previously provided event-driven service-oriented architecture which already permitted the context-aware detection and notification of relevant data. For this purpose, we have defined and implemented a microservice-based architecture which provides real-time context-aware actions based on predictive streaming processing of data. As a result, our architecture has been enhanced twofold: on the one hand, the architecture has been supplied with reliable predictions through the use of predictive analytics and complex event processing techniques, which permit the notification of relevant context-aware information ahead of time. On the other, it has been refactored towards a microservice architecture pattern, highly improving its maintenance and evolution. The architecture performance has been evaluated with an air quality case study.

A situation-driven framework for dynamic security management

We present a dynamic security management framework where security policies are specified according to situations. Situation-based policies easily express complex dynamic security measures, are closer to business, and simplify the policy life cycle management. Situations are specified using complex event processing techniques. The framework is supported by a modular event–based infrastructure where a dedicated situation manager maintains active situations allowing the command center to take dynamic situation–based authorization and obligation decisions. The whole framework has been implemented and showed good performance by simulation. Finally, we detail two real experiments.

Towards an IoT and Big Data Analytics Platform for the Definition of Diabetes Telecare Services

Diabetes is considered as one of chronic disease that requires patient self-monitoring processes and constant care. Patients need to perform frequently a control of glucose level in the blood in order to prevent hypoglycemia episodes. However, efficient detection of hypoglycemia could be done by checking other vital signs. The gaps in the manual monitoring and heavy control process prevent some patients to daily control and follow the progress of their disease; therefore, several metabolic problems could be noticed and need to be taken seriously into consideration. Therefore, tools for efficient disease control are required to allow self-monitoring of blood glucose and other vitals and measures (e.g., activities, dietary). This will allow filling the gap between patients and carers with the main objective to enhance comfort of patients and reduce the treatment costs. The work presented in this paper aims to develop a platform that combines IoT and complex event processing techniques for hypoglycemia detection. A prototype is introduced together with preliminary results to show its effectiveness for the definition of diabetes telecare services, mainly for hypoglycemia detection.

Provenance aware run‐time verification of things for self‐healing Internet of Things applications

SummaryWe propose a run‐time verification mechanism of things for self‐healing capability in the Internet of Things domain. We discuss the software architecture of the proposed verification mechanism and its prototype implementations. To identify faulty running behavior of things, we utilize a complex event processing technique by applying rule‐based pattern detection on the events generated real time. For events, we use a descriptor metadata of the measurements (such as CPU usage, memory usage, and bandwidth usage) taken from Internet of Things devices. To understand the usability and effectiveness of the proposed mechanism, we developed prototype applications using different event processing platforms. We test the prototype implementations for performance and scalability under increasing message rates. The results are promising because the processing overhead of the proposed verification mechanism is negligible.

Sequence Clustering-based Automated Rule Generation for Adaptive Complex Event Processing

In Complex Event Processing (CEP), complex events are detected according to a set of rules that are defined by domain experts. However, it makes the reliability of the system decreased as dynamic changes occur in the domain environment or domain experts make mistakes. To address such problem, this study proposes a Sequence Clustering-based Automated Rule Generation (SCARG) that can automatically generate rules by mining decision-making history of domain experts based on sequence clustering and probabilistic graphical modeling. Furthermore, based on a two-way learning approach, the proposed method is able to support automated regular or occasional rule updates. It makes self-adaptive CEP system possible by combining the rule generation method and the existing dynamic CEP systems. This technique is verified by establishing an automated stock trading system, and the performance of the system is measured in terms of the rate of return. The study solves the aforementioned problems and shows excellent results with an increase of 19.32% in performance when compared to the existing dynamic CEP technique.

온라인 게임 악용 패턴 모니터링 방법의 성능 분석

CEP(Complex Event Processing)는 대규모 정보시스템에서 발생하는 복잡한 이벤트 패턴을 발견하는 기법이다. 게임 사용자가 게임 서버에 접속하여 게임을 수행하는 과정에서 발생하는 이벤트들을 관찰하면서 규칙에 위배되는 행위를 검출하기 위하여 CEP 기법을 사용하는 방법이 제안된 바 있다. 본 연구는 실제 게임서버 DB를 이용하여 선행 연구를 통해 제안된 모니터링 방법에 적용하여 보았다. 이를 통해 CEP 기반의 온라인서비스 감시가 대규모 사용자들이 이용하는 온라인 게임의 부정한 사용자들을 찾아내고 감시하는 것에 효과적임을 관찰하였다. CEP(Complex Event Processing) is a technique to find complex event pattern in a massive information system. Based on CEP technique, an abuse pattern monitoring method has been developed to provide an real-time detection. In the method, the events occurred by game-play are observed to be against the rules using CEP. User abuse patterns are pre-registered in CEP engine. And CEP engine monitors user abuse after aggregating the game data transferred by game logging server. This article provides the performance analysis results of the abuse pattern monitoring method using real game DB. We results that the method proposed in previous study is effective to monitor abusing users.

CEP 기반 온라인 게임 악용 패턴 모니터링 방법

본 연구에서는 CEP(Complex Event Processing) 기법을 사용하여 온라인 게임에서 사용자 악용을 실시간 감지하기 위한 효율적인 방법을 제시한다. CEP는 대규모 정보시스템에서 발생하는 복잡한 이벤트 패턴을 발견하는 기법이다. 본 연구에서는 게임 사용자가 게임 서버에 접속하여 게임을 수행하는 과정에서 발생하는 이벤트들을 관찰하면서 규칙에 위배되는 행위를 검출하기 위하여 CEP 기법을 사용한다. 사용자들이 자주 악용할 가능성이 있는 이벤트 패턴을 미리 복합 이벤트로 설정하여 CEP 엔진에 등록해 두고, CEP 엔진은 게임 서버에서 발생하는 이벤트를 실시간에 필터링하여 사용자 악용을 감시하는 방법이다. Based on a complex event processing technique, an abuse pattern monitoring method is developed to provide an real-time detection. CEP is a technique to find complex event pattern in a massive information system. In this study, the events occurred by game-play are observed to be against the rules using CEP. User abuse patterns are pre-registered in CEP engine. And CEP engine monitors user abuse after aggregating the game data transferred by game logging server.