Revisiting Actor Programming in C++

The actor model of computation has gained significant popularity over the last decade. Its high level of abstraction makes it appealing for concurrent applications in parallel and distributed systems. However, designing a real-world actor framework that subsumes full scalability, strong reliability, and high resource efficiency requires many conceptual and algorithmic additives to the original model. In this paper, we report on designing and building CAF, the "C++ Actor Framework". CAF targets at providing a concurrent and distributed native environment for scaling up to very large, high-performance applications, and equally well down to small constrained systems. We present the key specifications and design concepts---in particular a message-transparent architecture, type-safe message interfaces, and pattern matching facilities---that make native actors a viable approach for many robust, elastic, and highly distributed developments. We demonstrate the feasibility of CAF in three scenarios: first for elastic, upscaling environments, second for including heterogeneous hardware like GPGPUs, and third for distributed runtime systems. Extensive performance evaluations indicate ideal runtime behaviour for up to 64 cores at very low memory footprint, or in the presence of GPUs. In these tests, CAF continuously outperforms the competing actor environments Erlang, Charm++, SalsaLite, Scala, ActorFoundry, and even the OpenMPI.Comment: 33 page

Forum Session at the First International Conference on Service Oriented Computing (ICSOC03)

The First International Conference on Service Oriented Computing (ICSOC) was held in Trento, December 15-18, 2003. The focus of the conference ---Service Oriented Computing (SOC)--- is the new emerging paradigm for distributed computing and e-business processing that has evolved from object-oriented and component computing to enable building agile networks of collaborating business applications distributed within and across organizational boundaries. Of the 181 papers submitted to the ICSOC conference, 10 were selected for the forum session which took place on December the 16th, 2003. The papers were chosen based on their technical quality, originality, relevance to SOC and for their nature of being best suited for a poster presentation or a demonstration. This technical report contains the 10 papers presented during the forum session at the ICSOC conference. In particular, the last two papers in the report ere submitted as industrial papers

RTZen: Highly Predictable, Real-Time Java Middleware for Distributed and Embedded Systems

Distributed real-time and embedded (DRE) applications possess stringent quality of service (QoS) requirements, such as predictability, latency, and throughput constraints. Real-Time CORBA, an open middleware standard, allows DRE applications to allocate, schedule, and control resources to ensure predictable end-to-end QoS. The Real-Time Specification for Java (RTSJ) has been developed to provide extensions to Java so that it can be used for real-time systems, in order to bring Java's advantages, such as portability and ease of use, to real-time applications.In this paper, we describe RTZen, an implementation of a Real-Time CORBA Object Request Broker (ORB), designed to comply with the restrictions imposed by RTSJ. RTZen is designed to eliminate the unpredictability caused by garbage collection and improper support for thread scheduling through the use of appropriate data structures, threading models, and memory scopes. RTZen's architecture is also designed to hide the complexities of RTSJ related to distributed programming from the application developer. Empirical results show that RTZen is highly predictable and has acceptable performance. RTZen therefore demonstrates that Real-Time CORBA middleware implemented in real-time Java can meet stringent QoS requirements of DRE applications, while supporting safer, easier, cheaper, and faster development in real-time Java

Analysis of current middleware used in peer-to-peer and grid implementations for enhancement by catallactic mechanisms

This deliverable describes the work done in task 3.1, Middleware analysis: Analysis of current middleware used in peer-to-peer and grid implementations for enhancement by catallactic mechanisms from work package 3, Middleware Implementation. The document is divided in four parts: The introduction with application scenarios and middleware requirements, Catnets middleware architecture, evaluation of existing middleware toolkits, and conclusions. -- Die Arbeit definiert Anforderungen an Grid und Peer-to-Peer Middleware Architekturen und analysiert diese auf ihre Eignung für die prototypische Umsetzung der Katallaxie. Eine Middleware-Architektur für die Umsetzung der Katallaxie in Application Layer Netzwerken wird vorgestellt.Grid Computing

Towards Middleware for Fault-tolerance in Distributed Real-time and Embedded Systems

Abstract. Distributed real-time and embedded (DRE) systems often require support for multiple simultaneous quality of service (QoS) properties, such as real-timeliness and fault tolerance, that operate within resource constrained environments. These resource constraints motivate the need for a lightweight middleware infrastructure, while the need for simultaneous QoS properties require the middleware to provide fault tolerance capabilities that respect time-critical needs of DRE systems. Conventional middleware solutions, such as Fault-tolerant CORBA (FT-CORBA) and Continuous Availability API for J2EE, have limited utility for DRE systems because they are heavyweight (e.g., the complexity of their feature-rich fault tolerance capabilities consumes excessive runtime resources), yet incomplete (e.g., they lack mechanisms that enable fault tolerance while maintaining real-time predictability). This paper provides three contributions to the development and standardization of lightweight real-time and fault-tolerant middleware for DRE systems. First, we discuss the challenges in realizing real-time faulttolerant solutions for DRE systems using contemporary middleware. Second, we describe recent progress towards standardizing a CORBA lightweight fault-tolerance specification for DRE systems. Third, we present the architecture of FLARe, which is a prototype based on the OMG real-time fault-tolerant CORBA middleware standardization efforts that is lightweight (e.g., leverages only those server-and client-side mechanisms required for real-time systems) and predictable (e.g., provides fault-tolerant mechanisms that respect time-critical performance needs of DRE systems)

Techniques and Patterns for Safe and Efficient Real-Time Middleware

Over 90 percent of all microprocessors are now used for real-time and embedded applications. The behavior of these applications is often constrained by the physical world. It is therefore important to devise higher-level languages and middleware that meet conventional functional requirements, as well as dependably and productively enforce real-time constraints. Real-Time Java is emerging as a safe, real-time environment. In this thesis we use it as our experimentation platform; however, our findings are easily adapted to other similar platforms. This thesis provides the following contributions to the study of safe and efficient real-time middleware. First, it identifies potential bottlenecks and problem with respect to guaranteeing real-time performance in middleware. Second, it presents a series of techniques and patterns that allow the design and implementation of safe, predictable, and highly efficient real-time middleware. Third, it provides a set of architectural and design patterns that application developers can use when designing real-time systems. Finally, it provides a methodology for evaluating the merits and benefits of real-time middleware. Empirical results are presented using that methodology for the techniques presented in this thesis. The methodology helps compare the performance and predictability of general, real-time middleware platforms

Real-Time Air quality index application for the City of Cape Town: An event-Driven system with Kafka, CQRS and Clojure

The World Health Organization estimates around 3.7 million premature deaths world-wide were due to ambient air pollution in 2012, 88% of which occurred in low to middle income countries such as South Africa. This project focuses on the development of an event-driven real-time air quality index application for the City of Cape Town. Event streams are being more commonly adopted in data centric applications that aim to produce trend analyses and prediction models. Event-driven systems store immutable raw event data, providing both a history of what has happened in the database, and the current state, thereby assisting with debugging and providing audit trail support. In addition to increasing public accessibility to the city's air quality information, the application has been designed for scalability, extensibility and data analysis through the incorporation of the Command Query Responsibility Segregation, Event Sourcing and Model-View-Controller architectural patterns. The design of the application itself serves as a basic reusable template for any new applications that may require the scalability, extensibility and is inherently data-centric nature as is found in this implementation. By taking advantage of the city's existing air quality monitoring sensor network, the real-time application has the capability to highlight problematic areas within the City of Cape Town with regard to high pollution levels, create greater public awareness, and lays the foundation for the future development of predictive air quality models and pollution forecasts

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