Context-aware platforms consist of dynamic algorithms that take the context information into account to adapt the behavior of the applications. The relevant context information is modeled in a context model. Recently, a trend has emerged towards capturing the context in an ontology, which formally models the concepts within a certain domain, their relations and properties. Although much research has been done on the subject, the adoption of context-aware services in healthcare is lagging behind what could be expected. The main complaint made by users is that they had to signicantly alter workow patterns to accommodate the system. When new technology is introduced, the behavior of the users changes to adapt to it. Moreover, small dierences in user requirements often occur between dierent

https://biblio.ugent.be/publication/4191983/file/4191994.pdf

A probabilistic ontology-based platform for self-learning context-aware healthcare applications

Sensors are distributed across the globe leading to an avalanche of data about our environment. It is possible today to utilize networks of sensors to detect and identify a multitude of observations, from simple phenomena to complex events and situations. The lack of integration and communication between these networks, however, often isolates important data streams and intensifies the existing problem of too much data and not enough knowledge. With a view to addressing this problem, the semantic sensor Web (SSW) proposes that sensor data be annotated with semantic metadata that will both increase interoperability and provide contextual information essential for situational knowledge.

Semantic Sensor Web

The patient room of the future would be able to sense the needs and preferences of the patients and nurses and adapt itself accordingly by combining all the heterogeneous data offered by the different technologies. This goal can be achieved by developing a context-aware framework, which exploits and integrates the heterogeneous data by utilizing a continuous care ontology. The existing ontology engineering methodologies are rather extreme in their choices to include domain experts. On the one hand, there are methodologies that only discuss the scope, use and requirements of the ontology with the domain experts. On the other hand, there are approaches in which the ontology is completely constructed by the domain experts by providing them with user-friendly and collaborative tools. In this paper, a participatory ontology engineering methodology is presented that finds a middle ground between these two extremes. The methodology actively involves social scientists, ontology engineers and stakeholders. The stakeholders participate in each step of the ontology life cycle without having to construct the ontology themselves or attribute a large amount of their time. The applicability of the methodology is illustrated by presenting the co-created continuous care ontology.

https://biblio.ugent.be/publication/1965779/file/2952298.pdf

Participatory Design of a Continuous Care Ontology - Towards a User-Driven Ontology Engineering Methodology

The main problem in dealing with energy-harvesting (EH) sensor nodes is represented by the scarcity and non-stationarity of powering, due to the nature of the renewable energy sources. In this work, the authors address the problem of task scheduling in processors located in sensor nodes powered by EH sources. Some interesting solutions have appeared in the literature in the recent past, as the lazy scheduling algorithm (LSA), which represents a performing mix of scheduling effectiveness and ease of implementation. With the aim of achieving a more efficient and conservative management of energy resources, a new improved LSA solution is here proposed. Indeed, the automatic ability of foreseeing at run-time the task energy starving (i.e. the impossibility of finalizing a task due to the lack of power) is integrated within the original LSA approach. Moreover, some modifications have been applied in order to reduce the LSA computational complexity and thus maximizing the amount of energy available for task execution. The resulting technique, namely energy-aware LSA, has then been tested in comparison with the original one, and a relevant performance improvement has been registered both in terms of number of executable tasks and in terms of required computational burden.

Energy-aware lazy scheduling algorithm for energy-harvesting sensor nodes

Ontology engineering methodologies tend to emphasize the role of the knowledge engineer or require a very active role of domain experts. In this paper, a participatory ontology engineering method is described that holds the middle ground between these two 'extremes'. After thorough ethnographic research, an interdisciplinary group of domain experts closely interacted with ontology engineers and social scientists in a series of workshops. Once a preliminary ontology was developed, a dynamic care request system was built using the ontology. Additional workshops were organized involving a broader group of domain experts to ensure the applicability of the ontology across continuous care settings. The proposed method successfully actively engaged domain experts in constructing the ontology, without overburdening them. Its applicability is illustrated by presenting the co-created continuous care ontology. The lessons learned during the design and execution of the approach are also presented.

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An ontology co-design method for the co-creation of a continuous care ontology

As the number of wireless sensor network applications continues to grow, the need for specialized task scheduling mechanisms, aware of the sensor devices' capabilities and real-time resource availability, is becoming more and more apparent. In this paper, we therefore propose a generic model for task scheduling in heterogeneous networks, which we subsequently use to schedule distributed reasoning tasks, originating from a real-world WSN monitoring and management application. By means of simulation, we evaluate several developed scheduling heuristics and compare the results to an optimal solution of the same WSN task scheduling problem, obtained using ILP. Experiments show that our heuristics produce acceptable task schedules while maintaining a low resource footprint.

/pdf/resource-aware-scheduling-of-distributed-ontological-4pi4azd09y.pdf

Resource-Aware Scheduling of Distributed Ontological Reasoning Tasks in Wireless Sensor Networks

Testbeds as a means to evaluate protocol and software development are gaining importance, not least because of the oftentimes unpredictable influence of environmental behaviour. IBBT, the Interdisciplinary Institute for Broadband Technology, recognizes the importance of such testbeds and has therefore invested in WiLab.t, a wireless sensor and mesh testbed. It contains over 200 wireless and programmable nodes. The monitoring and management of such a testbed is very important so as to guarantee a proper functioning and stable environment to be used by researchers. This is however not a trivial task, even more so when in the future, the testbed is expanded with new devices and as such becomes a heterogeneous environment. Therefore, we have developed an ontology-based monitoring approach, which allows hiding the heterogeneity from the monitoring application and enables to process the data in a formal manner. Additionally, it allows adaptation according to characteristics of the local deployment, without the need to re-engineer the entire monitoring application every time alterations are made to the testbed.

/pdf/distributed-ontology-based-monitoring-on-the-ibbt-wilab-t-2xwmroqffq.pdf

Distributed Ontology-Based Monitoring on the IBBT WiLab.t Infrastructure

We propose a software platform which pairs context awareness with over-the-top (OTT) service deployment. By augmenting OTT services with local context information, we allow them to react upon various types of changes in the environment in which they are being deployed. This lets service providers offer more personalized and fine-grained applications, while making use of a third-party infrastructure, via the OTT paradigm. Through UML diagrams, we describe the architecture of the proposed service platform. By means of a detailed illustrative scenario, the components involved are further clarified. In addition, in order to prove the feasibility of the architecture, a prototype implementation was developed and deployed on a large wireless sensor network test bed. Using a set of benchmarks, we identified the strengths and weaknesses of both test bed and prototype.

/pdf/on-the-design-of-a-flexible-software-platform-for-in-zefj7xclae.pdf

On the design of a flexible software platform for in-building OTT service provisioning

To cope with the evergrowing number of colocated networks and the density they exhibit, we introduce symbiotic networks-networks that intelligently share resources and autonomously adapt to the dynamicity thereof. By allowing the software services provided in such networks to operate in an equally symbiotic manner, new opportunities for the so-called service compositions arise, which take advantage of the multitude of services and combine them to achieve goals set out by the individual networks. To accommodate services in large-scale symbiotic networks, including wireless sensor networks, we propose a software platform which autonomously constructs and orchestrates such compositions. Furthermore, upon changes in the infrastructure, the platform responds by adapting compositions to reflect the changed context. To enable the interaction between services offered by arbitrary partners, the platform deploys ontologies to achieve a common vocabulary and semantic rules to express the policies imposed by the networks involved. By applying the platform to typical scenarios from the field of sensor-augmented cargo transportation and logistics, we illustrate its applicability and, through performance evaluation, show a significant increase in process efficiency. Additionally, by means of a generic problem generator, we quantify the scalability of our platform and show the importance of an appropriate priority function, one of the core constituents of our service composition approach.

https://journals.sagepub.com/doi/pdf/10.1155/2013/684563

Symbiotic Service Composition in Distributed Sensor Networks

We propose symbiotic networks, a novel approach toward sharing of network resources in order to increase the scalability, dependability and energy efficiency of colocated networks. As symbiotic networks offer large amounts of software services, one challenge is to allow these services to operate “symbiotically” as well. By combining services from different parties, service compositions arise, which allow for a richer set of functionality. Creating such compositions, however, requires intricate knowledge about services and their interoperability. Using a semantic domain and service model, we describe SeCoA, a tunable best-first search algorithm for autonomously constructing symbiotic service compositions. A performance evaluation of SeCoA was conducted, showing that the algorithm offers acceptable performance for moderately sized compositions.

/pdf/secoa-autonomous-semantic-service-composition-algorithm-in-1aobrugigs.pdf

Tim De Pauw

Papers

Resource-Aware Scheduling of Distributed Ontological Reasoning Tasks in Wireless Sensor Networks

Distributed Ontology-Based Monitoring on the IBBT WiLab.t Infrastructure

On the design of a flexible software platform for in-building OTT service provisioning

Symbiotic Service Composition in Distributed Sensor Networks

SeCoA: Autonomous semantic service composition algorithm in symbiotic networks