Sensor web systems, cyber-physical systems, and the so-called Internet of Things are concepts that share a set of common characteristics. The nature of such systems is highly dynamic and very heterogeneous and issues such as interoperability, energy consumption, or resource management must be properly managed to ensure the operation of the applications within the required quality of service level. In this context, base technologies such as component based software engineering or Service Oriented Architecture can play a central role. Model driven development and middleware technologies also aid in the design, development, and operation of such systems. This paper presents a middleware solution that provides runtime support for the complete lifecycle management of a system consisting of several concurrent applications running over a set of distributed infrastructure nodes. The middleware builds up on top of a general purpose component model and is driven by a quality of service aware self-configuration algorithm that provides stateful reconfiguration capabilities in face of both internal (application triggered) and external (application unaware) reconfiguration events. The platform has been deployed over an automated warehouse supervision system that serves as a case study.
In developed countries, public health systems are under pressure due to the increasing percentage of population over 65. In this context, homecare based on ambient intelligence technology seems to be a suitable solution to allow elderly people to continue to enjoy the comforts of home and help optimize medical resources. Thus, current technological developments make it possible to build complex homecare applications that demand, among others, flexibility mechanisms for being able to evolve as context does (adaptability), as well as avoiding service disruptions in the case of node failure (availability). The solution proposed in this paper copes with these flexibility requirements through the whole life-cycle of the target applications: from design phase to runtime. The proposed domain modeling approach allows medical staff to design customized applications, taking into account the adaptability needs. It also guides software developers during system implementation. The application execution is managed by a multi-agent based middleware, making it possible to meet adaptation requirements, assuring at the same time the availability of the system even for stateful applications.
Sensory environments for healthcare are commonplace nowadays. A patient monitoring system in such an environment deals with sensor data capture, transmission and processing in order to provide on-the-spot support for monitoring the vulnerable and critical patients. A fault in such a system can be hazardous on the health of the patient. Therefore, such a system must be dependable and ensure reliability, fault-tolerance, safety and other critical aspects, in order to deploy it in real scenario. Also, the management of the infrastructure resources must be efficient and the eventual system reconfiguration must be reliably performed. This paper encounters some of these issues and proposes a component platform with specific support for several QoS aspects, namely fault tolerance, safe inter-component communication and resource management. The platform adopts the Service Component Architecture (SCA) model and defines a Data Distribution Service (DDS) binding, which provides the fault tolerance and the required safety-ensuring techniques and measures, as defined in the IEC Multimed Tools Appl
Current automation systems demand flexibility enough to meet the challenging requirements of applications in terms of complexity, extensibility or dynamism. From a global perspective the whole automation system must meet quality of service (QoS) requirements which can be, for instance, energy efficiency, load balance or full availability. This paper presents a reconfiguration-based architecture triggered by a higher level supervision that makes use of a component based middleware. The first step of the supervisory architecture is presented aiming at achieving the availability of the control system even in presence of control equipment failures.
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