A semantic-driven auto-adaptive architecture for collaborative ubiquitous systems

Sancho, Germán; Tazi, Saïd; Villemur, Thierry

doi:10.1145/1456223.1456354

Cited by 9 publications

(9 citation statements)

References 9 publications

(8 reference statements)

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“…However, both are already dated now and no more recent accounts of the work or other publications by Wolfe are available. Sancho et al (2008) describe an architecture (as work in progress) for the development of adaptive collaborative applications in ubiquitous computing environments. The paper proposes an ontology model containing generic collaboration knowledge as well as domain-specific knowledge, in order to enable architecture adaptation and to support spontaneous and implicit sessions inside groups of humans and devices.…”

Section: Architectures and Frameworkmentioning

confidence: 99%

“…For three of these papers, this is due to the early stage of the presented work (using one or several of the mentioned data categories is envisioned for future applications of the described approaches). The remaining ten papers that do not rely on any usage, user or environment data either (i) describe human-driven personalization (see e.g., Fosh et al, 2014or Roberts et al, 2014, (ii) do not yet provide adaptations but plan this for the future (or provide an infrastructure for doing so, without mentioning which kind of data the approach should later rely on) (see e.g., von Zadow et al, 2014 or Rinck and Hinze, 2011), or (iii) describe architectures or implementations of components that might be used in adaptive collaborative systems but have no relations with collecting and processing user, usage or environment data (see e.g., Sancho et al, 2008or Clayphan et al, 2013.…”

Section: Foundations Of Adaptation and Personalizationmentioning

confidence: 99%

“…Previous activity in a web browser and users' current social context in co-located collaboration Sancho et al (2008) N/A Architecture for collaborative ubiquitous systems Li et al (2007) Usage data Interactions with a activity-centric collaboration environment (e.g., recency or frequency of updates to activity) the higher the internal validity of an experiment (giving one the ability "to draw confident conclusions about cause and effects, " see Gomm, 2008), but the less natural people as participants will behave in such situations leading to decreased external validity (meaning to what extent the experiment gives evidence about the "world outside"). Two researchers rated the study designs on a 7-point Likert scale (with 0.5 steps as minimum interval) within the two end-point options controlled (1) and naturalistic (7).…”

Section: Study Typesmentioning

confidence: 99%

See 2 more Smart Citations

A Systematic Review of Personalized Collaborative Systems

Neumayr

Augstein

2020

Front. Comput. Sci.

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Personalization, aiming at supporting users individually, according to their individual needs and prerequisites, has been discussed in a number of domains including learning, search, or information retrieval. In the field of human–computer interaction, personalization also bears high potential as users might exhibit varying and strongly individual preferences and abilities related to interaction. For instance, there is a good amount of work on personalized or adaptive user interfaces (also under the notion of intelligent user interfaces). Personalized human–computer interaction, however, does not only subsume approaches to support the individual user, it also bears high potential if applied to collaborative settings, for example, through supporting the individuals in a group as well as the group itself (considering all of its special dynamics). In collaborative settings (remote or co-located), there generally is a number of additional challenges related to human-to-human collaboration in a group, such as group communication, awareness or territoriality, device or software tool selection, or selection of collaborators. Personalized Collaborative Systems thus attempt to tackle many of these challenges. For instance, there are collaborative systems that recommend tools, content, or team constellations. Such systems have been suggested in different domains and different collaborative settings and contexts. In most cases, these systems explicitly focus on a certain aspect of personalized collaboration support (such as team composition). This article provides a broader, concise overview of existing approaches to Personalized Collaborative Systems based on a systematic literature review considering the ACM Digital Library.

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Section: Architectures and Frameworkmentioning

confidence: 99%

Section: Foundations Of Adaptation and Personalizationmentioning

confidence: 99%

Section: Study Typesmentioning

confidence: 99%

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A Systematic Review of Personalized Collaborative Systems

Neumayr

Augstein

2020

Front. Comput. Sci.

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“…This solution proposes a multilayer modeling of system architectures in order to manage collaborative activities carried out by groups of user in complex scenarios. This framework proposes a generic collaboration ontology and aims to deploy and configure collaborative session for users using event‐based communication modules. It is implemented using ontology and graph models and rule‐oriented techniques.…”

Section: State Of the Artmentioning

confidence: 99%

FRAMESELF: an ontology‐based framework for the self‐management of machine‐to‐machine systems

Alaya

Monteil

2013

Concurrency and Computation

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Machine-to-machine (M2M) systems need to connect thousands of heterogeneous machines that are widely distributed and frequently evolve according to their environment changes. Keeping such systems alive is costly in terms of time and money. The increasing complexity of M2M communications places M2M development and research under strain. Autonomic computing paradigm is widely believed to be a promising solution to self-manage this complexity. This paper proposes FRAMESELF, an ontology-based framework designed for the self-configuration of M2M communications. A variety of communication modules based on service-oriented and event-driven communication patterns is dynamically selected and configured in deployment plans. A generic and extensible control loop components diagram detailing the monitoring, analyzing, planning, and executing processes are provided. Ontology models describing the M2M architecture and M2M communication patterns are proposed. A smart metering use case is experimented to validate the proposed approach and to calculate the overload generated by FRAMESELF facing scalability. Copyright at building computing systems capable of managing themselves with minimum human intervention. Autonomic computing encompasses four self-management capabilities including self-configuring, self-healing, self-optimizing, and self-protecting. Up until the present time, available autonomic systems are restricted to specific problems and are not widely applied in M2M because of the vertical fragmentation of M2M application domains and lack of standardization. Although the European Telecommunication Standards Institute (ETSI) has recently specified a horizontal service platform for M2M services interoperability, no effective self-management capability was intergraded in the ETSI approach.With the advent of technology, the possibility has arisen to integrate the autonomic computing paradigm into a horizontal M2M service platform. Such platform should be able to automatically manage communication between interacting machines by taking actions based on what happening in the environment. Administrators interact with the system only to monitor business processes or to alter the objectives. M2M systems need semantic representations and reasoning capabilities to overcome their increasing complexly. An autonomic M2M system must be able to provide semantic descriptions of interacting machines with respect to both their context characteristics and their behaviors or situations. From a concrete point of view, interacting entities need to be made semantically and automatically interoperable. Any management system will be, then, capable to dynamically detect these entities and capture their contexts in order to identify what are the changes that are happening in the environment, infer the current situation, and react accordingly.In the present effort, FRAMESELF [1], an ontology-based framework, was designed and implemented for the self-management of M2M communications according to machines profiles and applications roles. On the one ha...

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“…Gryphon [14] aims to solve the major problems in message brokering. It uses features of distributed publish/subscribe communications technology which seems an important step to boost monitoring performance.…”

Section: Related Workmentioning

confidence: 99%

Autonomic computing system for self-management of machine-to-machine networks

Alaya

Matoussi

Monteil

et al. 2012

Proceedings of the 2012 International Workshop on Self-Aware Internet of Things

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The internet of things consists of a high amount of heterogeneous objects that are widely distributed and evolve frequently according to their context changes. Management of such a complex environment is costly in terms of time and money. Machine to Machine (M2M) networks will soon become virtually impossible to administer. Designing context aware autonomic system for M2M networks with capability of self-management is a challenge. This paper proposes an autonomic computing system based on standardized M2M architecture and composed of generic and extensible autonomic managers. Autonomic managers communicate with each other to enable self-management of application, service and communication layers based on knowledge models and reasoning rules. A smart metering use case is experimented to illustrate the proposed solution.

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A semantic-driven auto-adaptive architecture for collaborative ubiquitous systems

Cited by 9 publications

References 9 publications

A Systematic Review of Personalized Collaborative Systems

A Systematic Review of Personalized Collaborative Systems

FRAMESELF: an ontology‐based framework for the self‐management of machine‐to‐machine systems

Autonomic computing system for self-management of machine-to-machine networks

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