Dynamic Services for Assisted Living Environments

Software technologies for assisted living systems can be derived from the more mature domain of pervasive computing and the relative emerging ambient intelligence field. We present herein our position about the need for interoperability enablers extending the software service paradigm and for dependability as key elements of assisted living software systems

A study of existing Ontologies in the IoT-domain

Several domains have adopted the increasing use of IoT-based devices to collect sensor data for generating abstractions and perceptions of the real world. This sensor data is multi-modal and heterogeneous in nature. This heterogeneity induces interoperability issues while developing cross-domain applications, thereby restricting the possibility of reusing sensor data to develop new applications. As a solution to this, semantic approaches have been proposed in the literature to tackle problems related to interoperability of sensor data. Several ontologies have been proposed to handle different aspects of IoT-based sensor data collection, ranging from discovering the IoT sensors for data collection to applying reasoning on the collected sensor data for drawing inferences. In this paper, we survey these existing semantic ontologies to provide an overview of the recent developments in this field. We highlight the fundamental ontological concepts (e.g., sensor-capabilities and context-awareness) required for an IoT-based application, and survey the existing ontologies which include these concepts. Based on our study, we also identify the shortcomings of currently available ontologies, which serves as a stepping stone to state the need for a common unified ontology for the IoT domain.Comment: Submitted to Elsevier JWS SI on Web semantics for the Internet/Web of Thing

Supporting Multi-Cloud in Serverless Computing

Serverless computing is a widely adopted cloud execution model composed of Function-as-a-Service (FaaS) and Backend-as-a-Service (BaaS) offerings. The increased level of abstraction makes vendor lock-in inherent to serverless computing, raising more concerns than previous cloud paradigms. Multi-cloud serverless is a promising emerging approach against vendor lock-in, yet multiple challenges must be overcome to tap its potential. First, we need to be aware of both the performance and cost of each FaaS provider. Second, a multi-cloud architecture must be proposed before deploying a multi-cloud workflow. Domain-specific serverless offerings must then be integrated into the multi-cloud architecture to improve performance or save costs. Moreover, dealing with serverless offerings from multiple providers is challenging. Finally, we require workload portability support for serverless multi-cloud. In this paper, we present a multi-cloud library for cross-serverless offerings. We develop the End Analysis System (EAS) to support comparison among public FaaS providers in terms of performance and cost. Moreover, we design proof-of-concept multi-cloud architectures with domain-specific serverless offerings to alleviate problems such as data gravity. Finally, we deploy workloads on these architectures to evaluate several public FaaS offerings.Comment: Accepted for the 15th IEEE/ACM International Conference on Utility and Cloud Computing Companion (UCC'22 Companion

Social Middleware for Civic Engagement

International audienceCivic engagement refers to any collective action towards the identification and solving of public issues. Current civic technologies are traditional Web-or mobile-based platforms that make difficult, or just impossible, the participation of citizens via different communication technologies. Moreover, connected objects sensing physical-world data can nourish participatory processes by providing physical evidence to citizens; however, leveraging these data is not direct and still a time-consuming process for civic technologies developers. This paper introduces the concept of social middleware for civic engagement. Social middleware allows citizens to engage in participatory processes-supported by civic technologies-via their favorite communication tools, and to interact not only with other citizens but also with relevant connected objects and software platforms. The mission of social middleware goes beyond the connection of all these heterogeneous entities. It aims at easing the implementation of distributed applications oriented toward civic engagement by featuring dedicated built-in services

Scheduling of Continuous Operators for IoT edge Analytics with Time Constraints

International audienceData stream processing and analytics (DSPA) engines are used to extract in (near) real-time valuable information from multiple IoT data streams. Deploying DSPA applications at the IoT network edge through Edge/Fog architectures is currently one of the core challenges for reducing both network delays and network bandwidth usage to reach the Cloud. In this paper, we address the problem of scheduling continuous DSPA operators to Fog-Cloud nodes featuring both computational and network resources. We are paying particular attention to the dynamic workload of these nodes due to variability of IoT data stream rates and the sharing of nodes' resources by multiple DSPA applications. In this respect, we propose TSOO, a resource-aware and time-efficient heuristic algorithm that takes into account the limited Fog computational resources, the real-time response constraints of DSPA applications, as well as, congestion and delay issues on Fog-to-Cloud network resources. Via extensive simulation experiments, we show that TSOO approximates an optimal operators' placement with a low execution cost

QoS Composition and Analysis in Reconfigurable Web Services Choreographies

International audienceQuality of Service (QoS) in orchestrated web services compositions have been well studied with probabilistic and multi-dimensional models. Choreographies that involve message passing among services, on the other hand, require further analysis. In this paper, we begin with the set of QoS domains that may be studied in case of choreographies and the algebraic rules for their composition. As choreographies manage QoS composition in a distributed fashion, techniques to enrich functional specifications with QoS are examined using the model proposed in the CHOReOS project. These are further analyzed with choreographies that may reconfigure due to functional or QoS requirements. Studies on the effects of such reconfiguration on multiple QoS domains can lead to better understanding of optimal runtime configurations along with associated tradeoffs. A goal programming approach is also proposed to choose Pareto optimal solutions with respect to diverse QoS domains

Efficient Scheduling of Streaming Operators for IoT Edge Analytics

International audienceData stream processing and analytics (DSPA) applications are widely used to process the ever increasing amounts of data streams produced by highly geographical distributed data sources such as fixed and mobile IoT devices in order to extract valuable information in a timely manner for real-time actuation. To efficiently handle this ever increasing amount of data streams, the emerging Edge/Fog computing paradigms is used as the middle-tier between the Cloud and the IoT devices to process data streams closer to their sources and to reduce the network resource usage and network delay to reach the Cloud. In this paper, we account for the fact that both network resources and computational resources can be limited and shareable among multiple DSPA applications in the Edge-Fog-Cloud architecture, hence it is necessary to ensure their efficient usage. In this respect, we propose a resource-aware and time-efficient heuristic called SOO that identifies a good DSPA operator placement on the Edge-Fog-Cloud architecture towards optimizing the trade-off between the computational and network resource usage. Via thorough simulation experiments, we show that the solution provided by SOO is very close to the optimal one while the execution time is considerably reduced

Probabilistic Event Dropping for Intermittently Connected Subscribers over Pub/Sub Systems

International audienceInternet of Things (IoT) aim to leverage data from multiple sensors, actuators and devices for improving peoples' daily life and safety. Multiple data sources must be integrated, analyzed from the corresponding application and notify interested stakeholders. To support the data exchange between data sources and stakeholders, the publish/subscribe (pub/sub) middleware is often employed. Pub/sub provides additional mechanisms such as reliable messaging, event dropping, prioritization, etc. The event dropping mechanism is often used to satisfy Quality of Service (QoS) requirements and ensure system stability. To enable event dropping, basic approaches apply finite buffers or data validity periods and more sophisticated ones are information-aware. In this paper, we introduce a pub/sub mechanism for probabilistic event dropping by considering the stakeholders' intermittent connectivity and QoS requirements. We model the pub/sub middleware as a network of queues which includes a novel ON/OFF queueing model that enables the definition of join probabilities. We validate our analytical model via simulation and compare our mechanism with existing ones. Experimental results can be used as insights for developing hybrid dropping mechanisms

Scheduling Continuous Operators for IoT Edge Analytics

International audienceIn this paper we are interested in exploring the Edge-Fog-Cloud architecture as an alternative approach to the Cloud-based IoT data analytics. Given the limitations of Fog in terms of limited computational resources that can also be shared among multiple analytics with continuous operators over data streams, we introduce a holistic cost model that accounts both the network and computational resources available in the Edge-Fog-Cloud architecture. Then, we propose scheduling algorithms RCS and SOO-CPLEX for placing continuous operators for data stream analytics at the network edge. The former dynamically places continuous operators between the Cloud and the Fog according to the evolution of data streams rates and uses as less as possible Fog computational resources to satisfy the constraints regarding the usage of both computational and network resources. The latter statically places continuous operators between the Cloud and the Fog to minimize the overall computational and network resource usage cost. Based on thorough experiments, we evaluate the effectiveness of SOO-CPLEX and RCS using simulation

Interconnecting and Monitoring Heterogeneous Things in IoT Applications

International audienceInternet of Things (IoT) applications incorporate heterogeneous devices that employ different middleware protocols (MQTT, CoAP, WebSocket, etc). In this paper we present an extension of our cross-integration platform which supports the interoperability of IoT devices. In particular, we introduce the VSB Web Console which enables the development and monitoring of applications with heterogeneous IoT devices. We showcase our approach using the Fire Detection scenario