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Nirmal Weerasinghe

dblp:37/2280 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2007
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Human-computer interaction and ubiquitous computing · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer networks
1 paper
Internet of things and sensor networks · 100%
Human-computer interaction and pervasive computing
1 paper
Ubiquitous computing and smart environments · 100%
Computer architecture, parallel and distributed computing, and storage systems
1 paper
Embedded and real-time systems · 100%

Topics — the 3 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Internet of things and sensor networks
networked embedded systems
0.112007
The RUNES Middleware for Networked Embedded Systems and its Application in a Disaster Management Scenario · PerCom 2007
Internet of things and sensor networks
wireless sensor and actuator networks
0.012007
The RUNES Middleware for Networked Embedded Systems and its Application in a Disaster Management Scenario · PerCom 2007
Embedded and real-time systems
networked embedded systems
0.012007
The RUNES Middleware for Networked Embedded Systems and its Application in a Disaster Management Scenario · PerCom 2007

Methods — techniques the papers use, named apart from their topics

runtime reconfiguration · 0.2component-based programming model · 0.2
YearPublicationVenuePosition
2007 The RUNES Middleware for Networked Embedded Systems and its Application in a Disaster Management Scenario
abstract
Due to the inherent nature of their heterogeneity, resource scarcity and dynamism, the provision of middleware for future networked embedded environments is a challenging task. In this paper we present a middleware approach that addresses these key challenges; we also discuss its application in a realistic networked embedded environment. Our application scenario involves fire management in a road tunnel that is instrumented with networked sensor and actuator devices. These devices are able to reconfigure their behaviour and their information dissemination strategies as they become damaged under emergency conditions, and firefighters are able to coordinate their operations and manage sensors and actuators through dynamic reprogramming. Our supporting middleware is based on a two-level architecture: the foundation is a language-independent, component-based programming model that is sufficiently minimal to run on any of the devices typically found in networked embedded environments. Above this is a layer of software components that offer the necessary middleware functionality. Rather than providing a monolithic middleware 'layer', we separate orthogonal areas of middleware functionality into self-contained components that can be selectively and individually deployed according to current resource constraints and application needs. Crucially, the set of such components can be updated at runtime to provide the basis of a highly dynamic and reconfigurable system
Paolo Costa, Geoff Coulson, Richard Gold, Manish Lad, Cecilia Mascolo, Luca Mottola, Gian Pietro Picco, Thirunavukkarasu Sivaharan, Nirmal Weerasinghe, Stefanos Zachariadis
PerCom9