Geo-Linda: a Geometry Aware Distributed Tuple Space

Pauty, Julien; Couderc, Paul; Banâtre, Michel; Berbers, Yolande

doi:10.1109/aina.2007.74

Cited by 10 publications

(12 citation statements)

References 21 publications

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“…The application example shown in Section 4.2 is also related to Geo-Linda [24], another example of spatial coordination approach combining the tuple manipulation of LINDA with the geometric addressing concepts of SPREAD [13]. In Geo-Linda, tuples are read and published over an assortment of geometric primitives, such as boxes, spheres, cylinders, and cones, all defined relative to a device.…”

Section: Related Workmentioning

confidence: 99%

“…Such spatial coordination models have been developed in a number of previous papers [29,17,18,24]. These span multiple application contexts, such as pervasive computing, where mobility, large system scale, and/or situatedness invite the coordination space to be interpreted as a distributed substrate for spatial data structures.…”

Section: Introductionmentioning

confidence: 99%

“…Iterative spreading can then lead to the stabilisation of given tuple structures, which find applications such as retrieval of items of interest in mobile environments, as in the TOTA middleware [17] or the pervasive ecosystems model [30]. These prior models, however, tend to be either ad hoc (e.g., [24]) or tightly tied to a particular metaphor (e.g., [29]). …”

Section: Introductionmentioning

confidence: 99%

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Linda in Space-Time: An Adaptive Coordination Model for Mobile Ad-Hoc Environments

Viroli

Pianini

Beal

2012

Lecture Notes in Computer Science

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Abstract. We present a vision of distributed system coordination as a set of activities affecting the space-time fabric of interaction events. In the tuple space setting that we consider, coordination amounts to control of the spatial and temporal configuration of tuples spread across the network, which in turn drives the behaviour of situated agents. We therefore draw on prior work in spatial computing and distributed systems coordination, to define a new coordination language that adds to the basic Linda primitives a small set of space-time constructs for linking coordination processes with their environment. We show how this framework supports the global-level emergence of adaptive coordination policies, applying it to two example cases: crowd steering in a pervasive computing scenario and a gradient-based implementation of Linda primitives for mobile ad-hoc networks.

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Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Linda in Space-Time: An Adaptive Coordination Model for Mobile Ad-Hoc Environments

Viroli

Pianini

Beal

2012

Lecture Notes in Computer Science

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“…GeoLinda [19] augments federated tuple spaces with a geometrical read operation read(s,p). Every tuple has an associated shape and the rd operation only matches those tuples whose shape intersects the addressing shape s. GeoLinda has been designed to overcome the shortcomings of federated tuple spaces for a small subset of potential context information, namely the physical location of devices.…”

Section: Related Workmentioning

confidence: 99%

Programming mobile context-aware applications with TOTAM

Boix¹,

Scholliers²,

Meuter³

et al. 2014

Journal of Systems and Software

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In tuple space approaches to context-aware mobile systems, the notion of context is defined by the presence or absence of certain tuples in the tuple space. Existing approaches define such presence either by collocation of devices holding the tuples or by replication of tuples across all devices. We show that both approaches can lead to an erroneous perception of context. Collocation ties the perception of context to network connectivity which does not always yield the expected result. Tuple replication can cause that a certain context is perceived even if the device has left the context a long time ago. We propose a tuple space approach in which tuples themselves carry a predicate that determines whether they are in the right context or not. We present a practical API for our approach and show its use by means of the implementation of various mobile applications. Benchmarks show that our approach can lead to a significant increase in performance compared to other approaches.

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“…GeoLinda [14] augments federated tuple spaces with a geometrical read operation read(s,p). Every tuple has an associated shape and the rd operation only matches those tuples whose shape intersects the addressing shape s. GeoLinda has been designed to overcome the shortcomings of federated tuple spaces for a small subset of potential context information, namely the physical location of devices.…”

Section: Related Workmentioning

confidence: 99%

Context-Aware Tuples for the Ambient

Scholliers

Boix

Meuter

et al. 2010

On the Move to Meaningful Internet Systems, OTM 2010

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Abstract. In tuple space approaches to context-aware mobile systems, the notion of context is defined by the presence or absence of certain tuples in the tuple space. Existing approaches define such presence either by collocation of devices holding the tuples or by replication of those tuples across all devices. We show that both approaches can lead to an erroneous perception of context. The former ties the perception of context to network connectivity which does not always yield the expected result. The latter causes context to be perceived even if a device has left that context a long time ago. We propose a tuple space approach in which tuples themselves carry a predicate that determines whether they are in the right context or not. We present a practical API for our approach and show its use by means of the implementation of a mobile game.

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Geo-Linda: a Geometry Aware Distributed Tuple Space

Cited by 10 publications

References 21 publications

Linda in Space-Time: An Adaptive Coordination Model for Mobile Ad-Hoc Environments

Linda in Space-Time: An Adaptive Coordination Model for Mobile Ad-Hoc Environments

Programming mobile context-aware applications with TOTAM

Context-Aware Tuples for the Ambient

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