Cordies:Expressive event correlation in distributed systems

Complex Event Processing (CEP) is the method of choice for the observation of system states and situations by means of events. A number of systems have been introduced that provide CEP in selected environments. Some are restricted to centralised systems, or to systems with synchronous communication, or to a limited space of event relations that are defined in advance. Many modern systems, though, are inherently distributed and asynchronous, and require a more powerful CEP. We present Cordies, a distributed system for the detection of correlated events that is designed for the operation in large-scale, heterogeneous networks and adapts dynamically to changing network conditions. With its expressive language to describe event relations, it is suitable for environments where neither the event space nor the situations of interest are predefined but are constantly adapted. In addition, Cordies supports Quality-of-Service (QoS) for communication in distributed event correlation detection

Identifying the Challenges in Reducing Latency in GSN using Predictors

Simulations based on real-time data continuously gathered from sensor networks all over the world have received growing attention due to the increasing availability of measured data. Furthermore, predictive techniques have been employed in the realm of such networks to reduce communication for energy-efficiency. However, research has focused on the high amounts of data transferred rather than latency requirements posed by the applications. We propose using predictors to supply data with low latency as required for accurate simulations. This paper investigates requirements for a successful combination of these concepts and discusses challenges that arise

A network abstraction for control systems

Networked control systems (NCS), such as the smart power grid, implement feedback control loops by connecting distributed sensors and actuators to a remote controller over a communication network. In order to avoid the costly and time-consuming installation of dedicated networks, NCS can benefit from utilizing readily available IP networks such as the Internet. However, as control systems are typically sensitive to delay and loss, the integration of such systems over best-effort networks becomes a challenge, which we address in this paper with two main contributions. First, we propose an end-to-end transport abstraction for NCS based on a novel probabilistic quality of service specification which (1) is compatible with existing control models and (2) provides the network with application-specific knowledge about the relation between system performance and network-relevant metrics. Second, we realize this abstraction at the network layer with an optimal routing algorithm, which fulfils the required QoS while minimizing the usage of network resources. We show that our approach lends itself to the implementation with state-of-the-art software-defined networking (SDN) technologies, and demonstrate its effectiveness in our evaluation

Comfort-Oriented Metamorphic House (COMETAE)

Publications Internes de l'IRISA ISSN : 2102-6327This proposal aims at challenging the existing design paradigm of residential building architecture with insights from pervasive computing, robotics, human-computer interaction and cognitive ergonomics. ICT and architecture will be holistically integrated in order to realize a radical advancement leading to metamorphic houses. Supported by ICT, domestic environments will self-adapt to the ongoing activities of inhabitants, to increase the comfort of living and optimize the use of space and energy. The same physical space will be transformed for diff erent uses, giving inhabitants the illusion of living in a bigger, more adapted and more comfortable place. The traditional tradeoff between comfort and energy conservation will also be revisited, thanks to an optimal exploitation of natural light, heat and ventilation. The realization of the targeted breakthrough will be achieved through cross-fertilization between involved disciplines and by the support of a panel of final users, architects and building engineers in the design, development and evaluation phases. COMETAE will introduce a novel approach to smart spaces research, where the space is itself an actuator of the system. Indoor environment, space and energy use will be optimized with respect to environmental factors, occupants' activities and life cycle, by orchestrating adaptive robotic building components, while ensuring occupants' safety. New coupling between inhabitants and their environment will be enabled by combining human-computer interaction and space recon guration, considering beauty of interaction and multi-user scenarios. This proposal opens the way towards a radically new use of ICT, needed to address future limitations of space and energy in the domestic environment, imposed by the ongoing and future evolutions of technology, environmental questions and socio-demographic factors

Predictable Low-Latency Event Detection With Parallel Complex Event Processing

The tremendous number of sensors and smart objects being deployed in the Internet of Things (IoT) pose the potential for IT systems to detect and react to live-situations. For using this hidden potential, complex event processing (CEP) systems offer means to efficiently detect event patterns (complex events) in the sensor streams and therefore, help in realizing a "distributed intelligence" in the IoT. With the increasing number of data sources and the increasing volume at which data is produced, parallelization of event detection is crucial to limit the time events need to be buffered before they actually can be processed. In this paper, we propose a pattern-sensitive partitioning model for data streams that is capable of achieving a high degree of parallelism in detecting event patterns, which formerly could only consistently be detected in a sequential manner or at a low parallelization degree. Moreover, we propose methods to dynamically adapt the parallelization degree to limit the buffering imposed on event detection in the presence of dynamic changes to the workload. Extensive evaluations of the system behavior show that the proposed partitioning model allows for a high degree of parallelism and that the proposed adaptation methods are able to meet a buffering limit for event detection under high and dynamic workloads