QoS-enabled middleware for smart grids

Emerging smart grid systems must be able to react quickly and predictably, adapting their operation to changing energy supply and demand, by controlling energy consuming and energy storage devices. An intrinsic problem with smart grids is that energy produced from in-house renewable sources is affected by fluctuating weather factors. The applications driving smart grids operation must rely on a solid communication network that is secure, highly scalable, and always available. Thus, any communication infrastructure for smart grids should support its potential of producing high quantities of real-time data, with the goal of reacting to state changes by actuating on devices in real-time, while providing Quality of Service (QoS)

Amazon, Google and Microsoft Solutions for IoT: Architectures and a Performance Comparison

Internet of Things (IoT) aims to connect the real world made up of devices, sensors and actuators to the virtual world of Internet in order to interconnect devices with each other generating information from the gathered data. Devices, in general, have limited computational power and limited storage capacity. Cloud Computing (CC) has virtually unlimited capacity in terms of storage and computing power, and is based on sharing resources. Therefore, the integration between IoT and CC seems to be one of the most promising solutions. In fact, many of the biggest companies that offer Cloud Services are focusing on the IoT world to offer services also in this direction to their users. In this paper we compare the three main Cloud Platforms (Amazon Web Services, Google Cloud Platform and Microsoft Azure) regarding to the services made available for the IoT. After describing the typical architecture of an IoT application, we map the Cloud-IoT Platforms services with this architecture analyzing the key points for each platform. At the same time, in order to conduct a comparative analysis of performance, we focus on a service made available by all platforms (MQTT middleware) building the reference scenarios and the metrics to be taken into account. Finally, we provide an overview of platform costs based on different loads. The aim is not to declare a winner, but to provide a useful tool to developers to make an informed choice of a platform depending on the use case

Queueing Network Modeling Patterns for Reliable and Unreliable Publish/Subscribe Protocols

International audienceMobile Internet of Things (IoT) applications are typically deployed on resource-constrained devices with intermittent network connectivity. To support the deployment of such applications, the Publish/Subscribe (pub/sub) interaction paradigm is often employed, as it decouples mobile peers in time and space. Furthermore, pub/sub middleware protocols and APIs consider the Things' hardware limitations and support the development of effective applications by providing Quality of Service (QoS) features. These features aim to enable developers to tune an application by switching different levels of response times and delivery success rates. However, the profusion of pub/sub middleware protocols coupled with intermittent network connectivity result in non-trivial application tuning. In this paper, we model the performance of middleware protocols found in IoT, which are classified within the pub/sub interaction paradigm-both reliable and unreliable underlying network layers are considered. We model reliable and unreliable protocols, by considering QoS semantics for data validity, buffer capacities as well as the intermittent availability of peers. Finally, we perform statistical analysis by varying these QoS semantics, demonstrating their significant effect on the rate of successful interactions. We showcase the application of our analysis in concrete scenarios relating to Traffic Information Management systems, that integrate both reliable and unreliable participants. The consequent PerfMP performance modeling pattern may be tailored for a variety of deployments, in order to control fine-grained QoS policies

FireDeX: a Prioritized IoT Data Exchange Middleware for Emergency Response

International audienceReal-time event detection and targeted decision making for emerging mission-critical applications, e.g. smart fire fighting, requires systems that extract and process relevant data from connected IoT devices in the environment. In this paper, we propose FireDeX, a cross-layer middleware that facilitates timely and effective exchange of data for coordinating emergency response activities. FireDeX adopts a publish-subscribe data exchange paradigm with brokers at the network edge to manage prioritized delivery of mission-critical data from IoT sources to relevant subscribers. It incorporates parameters at the application, network, and middleware layers into a data exchange service that accurately estimates end-to-end performance metrics (e.g. delays, success rates). We design an extensible queueing theoretic model that abstracts these cross-layer interactions as a network of queues, thereby making it amenable for rapid analysis. We propose novel algorithms that utilize results of this analysis to tune data exchange configurations (event priorities and dropping policies) while meeting situational awareness requirements and resource constraints. FireDeX leverages Software-Defined Networking (SDN) methodologies to enforce these configurations in the IoT network infrastructure. We evaluate its performance through simulated experiments in a smart building fire response scenario. Our results demonstrate significant improvement to mission-critical data delivery under a variety of conditions. Our application-aware prioritization algorithm improves the value of exchanged information by 36% when compared with no prioritization; the addition of our network-aware drop rate policies improves this performance by 42% over priorities only and by 94% over no prioritization

Ordering, timeliness and reliability for publish/subscribe systems over WAN

In the last few years, the increasing use of the Internet and geo-political, sociological and financial changes induced by globalization, are paving the way for a connected world where the information is always available at the right place and the right time. As such, applications previously deployed for ``closed'' environmets, are now federating into geographically distributed systems connected through a Wide Area Network (WAN). By this evolution, in the near future no system will be isolated: every system will be composed by interconnected systems, i.e., it will be a System of Systems (SoS). Example of SoS are the Large-scale Complex Critical Infrastructure (LCCIs), such as power grids, transport infrastructures (airports and seaports), financial infrastructures, next generation intelligence platforms, to cite a few. In these systems, multiple sources of information generate a high volume of events that need to be delivered to all intended destinations by respecting several Quality of Service (QoS) constraints imposed by the critical nature of LCCIs. As such, particular attention is devoted to the middleware solution used to disseminate information in the SoS. Due to its inherently scalability provided by space, time and synchronization decoupling properties, the publish/subscribe paradigm is becoming attractive for the implementation of a middleware service for LCCIs. However, scalability is not the only requirement exhibited by SoS. Several services need to control a broader set of QoS requirements, such as timeliness, ordering and reliability. Unfortunately, current middleware solutions do not address QoS constraints required by SoS. Current publish/subscribe middleware solutions for the WAN environment offer only a best effort event dissemination, with no additional control on QoS. Just a few implementations try to address some isolated QoS policy, making them not suitable for a SoS scenario. The contribution of this thesis is to devise a QoS layer that can be posed on top of a generic publish/subscribe middleware that enriches its service by addressing: (i) ordering, (ii) reliability and (iii) timeliness in event dissemination in SoS over WAN. Specifically, we first analyze several real case studies, by highlighting their QoS requirements in terms of ordering, reliability and timeliness, and compare these requirements with both current research prototypes and commercial systems. Then, we fill the gap by proposing novel algorithms to address those requirements. The proposed protocols can also be combined together in order to provide the QoS level required by the particular application. In this way, QoS issues do not need to be addressed at application level, so as to leave applications to implement just their native functionalities

Ordering, timeliness and reliability for publish/subscribe systems over WAN

In the last few years, the increasing use of the Internet and geo-political, sociological and financial changes induced by globalization, are paving the way for a connected world where the information is always available at the right place and the right time. As such, applications previously deployed for ``closed'' environmets, are now federating into geographically distributed systems connected through a Wide Area Network (WAN). By this evolution, in the near future no system will be isolated: every system will be composed by interconnected systems, i.e., it will be a System of Systems (SoS). Example of SoS are the Large-scale Complex Critical Infrastructure (LCCIs), such as power grids, transport infrastructures (airports and seaports), financial infrastructures, next generation intelligence platforms, to cite a few. In these systems, multiple sources of information generate a high volume of events that need to be delivered to all intended destinations by respecting several Quality of Service (QoS) constraints imposed by the critical nature of LCCIs. As such, particular attention is devoted to the middleware solution used to disseminate information in the SoS. Due to its inherently scalability provided by space, time and synchronization decoupling properties, the publish/subscribe paradigm is becoming attractive for the implementation of a middleware service for LCCIs. However, scalability is not the only requirement exhibited by SoS. Several services need to control a broader set of QoS requirements, such as timeliness, ordering and reliability. Unfortunately, current middleware solutions do not address QoS constraints required by SoS. Current publish/subscribe middleware solutions for the WAN environment offer only a best effort event dissemination, with no additional control on QoS. Just a few implementations try to address some isolated QoS policy, making them not suitable for a SoS scenario. The contribution of this thesis is to devise a QoS layer that can be posed on top of a generic publish/subscribe middleware that enriches its service by addressing: (i) ordering, (ii) reliability and (iii) timeliness in event dissemination in SoS over WAN. Specifically, we first analyze several real case studies, by highlighting their QoS requirements in terms of ordering, reliability and timeliness, and compare these requirements with both current research prototypes and commercial systems. Then, we fill the gap by proposing novel algorithms to address those requirements. The proposed protocols can also be combined together in order to provide the QoS level required by the particular application. In this way, QoS issues do not need to be addressed at application level, so as to leave applications to implement just their native functionalities

PrioDeX: a Data Exchange middleware for efficient event prioritization in SDN-based IoT systems

International audienceReal-time event detection and targeted decision making for emerging mission-critical applications require systems that extract and process relevant data from IoT sources in smart spaces. Oftentimes, this data is heterogeneous in size, relevance, and urgency, which creates a challenge when considering that different groups of stakeholders (e.g., first responders, medical staff, government officials, etc) require such data to be delivered in a reliable and timely manner. Furthermore, in mission-critical settings, networks can become constrained due to lossy channels and failed components, which ultimately add to the complexity of the problem. In this paper, we propose PrioDeX, a cross-layer middleware system that enables timely and reliable delivery of mission-critical data from IoT sources to relevant consumers through the prioritization of messages. It integrates parameters at the application, network, and middleware layers into a data exchange service that accurately estimates end-to-end performance metrics through a queueing analytical model. PrioDeX proposes novel algorithms that utilize the results of this analysis to tune data exchange configurations (event priorities and dropping policies), which is necessary for satisfying situational awareness requirements and resource constraints. PrioDeX leverages Software-Defined Networking (SDN) methodologies to enforce these configurations in the IoT network infrastructure. We evaluate our approach using both simulated and prototype-based experiments in a smart building fire response scenario. Our application-aware prioritization algorithm improves the value of exchanged information by 36% when compared with no prioritization; the addition of our network-aware drop rate policies improves this performance by 42% over priorities only and by 94% over no prioritization

Modelling Event-Based Interactions in Component-Based Architectures for Quantitative System Evaluation

This dissertation thesis presents an approach enabling the modelling and quality-of-service prediction of event-based systems at the architecture-level. Applying a two-step model refinement transformation, the approach integrates platform-specific performance influences of the underlying middleware while enabling the use of different existing analytical and simulation-based prediction techniques

Imaging Sensors and Applications

In past decades, various sensor technologies have been used in all areas of our lives, thus improving our quality of life. In particular, imaging sensors have been widely applied in the development of various imaging approaches such as optical imaging, ultrasound imaging, X-ray imaging, and nuclear imaging, and contributed to achieve high sensitivity, miniaturization, and real-time imaging. These advanced image sensing technologies play an important role not only in the medical field but also in the industrial field. This Special Issue covers broad topics on imaging sensors and applications. The scope range of imaging sensors can be extended to novel imaging sensors and diverse imaging systems, including hardware and software advancements. Additionally, biomedical and nondestructive sensing applications are welcome

Integration of Event Processing with Service-oriented Architectures and Business Processes

Data sources like the Internet of Things or Cyber-physical Systems provide enormous amounts of real-time information in form of streams of events. The use of such event streams enables reactive software components as building blocks in a new generation of systems. Businesses, for example, can benefit from the integration of event streams; new services can be provided to customers, or existing business processes can be improved. The development of reactive systems and the integration with existing application landscapes, however, is challenging. While traditional system components follow a pull-based request/reply interaction style, event-based systems follow a push-based interaction scheme; events arrive continuously and application logic is triggered implicitly. To benefit from push-based and pull-based interactions together, an intuitive software abstraction is necessary to integrate push-based application logic with existing systems. In this work we introduce such an abstraction: we present Event Stream Processing Units (SPUs) - a container model for the encapsulation of event-processing application logic at the technical layer as well as at the business process layer. At the technical layer SPUs provide a service-like abstraction and simplify the development of scalable reactive applications. At the business process layer SPUs make event processing explicitly representable. SPUs have a managed lifecycle and are instantiated implicitly - upon arrival of appropriate events - or explicitly upon request. At the business process layer SPUs encapsulate application logic for event stream processing and enable a seamless transition between process models, executable process representations, and components at the IT layer. Throughout this work, we focus on different aspects of the SPU container model: we first introduce the SPU container model and its execution semantics. Since SPUs rely on a publish/subscribe system for event dissemination, we discuss quality of service requirements in the context of event processing. SPUs rely on input in form of events; in event-based systems, however, event production is logically decoupled, i.e., event producers are not aware of the event consumers. This influences the system development process and requires an appropriate methodology. Fur this purpose we present a requirements engineering approach that takes the specifics of event-based applications into account. The integration of events with business processes leads to new business opportunities. SPUs can encapsulate event processing at the abstraction level of business functions and enable a seamless integration with business processes. For this integration, we introduce extensions to the business process modeling notations BPMN and EPCs to model SPUs. We also present a model-to-execute workflow for SPU-containing process models and implementation with business process modeling software. The SPU container model itself is language-agnostic; thus, we present Eventlets as SPU implementation based on Java Enterprise technology. Eventlets are executed inside a distributed middleware and follow a lifecycle. They reduce the development effort of scalable event processing applications as we show in our evaluation. Since the SPU container model introduces an additional layer of abstraction we analyze the overhead in terms of performance and show that Eventlets can compete with traditional event processing approaches in terms of performance. SPUs can be used to process sensitive data, e.g., in health care environments. Thus, privacy protection is an important requirement for certain use cases and we sketch the application of a privacy-preserving event dissemination scheme to protect event consumers and producers from curious brokers. We also quantify the resulting overhead introduced by a privacy-preserving brokering scheme in an evaluation