Wireless sensor networks are increasingly employed to develop sophisticated applications where heterogeneous nodes are deployed, and multiple parallel activities must be performed. Therefore, application developers require the ability to partition the system based on the node characteristics, and specify complex interactions among different partitions. Existing programming abstractions for sensor networks tackled this problem by providing a notion of scoping. However, this rarely emerges as a first-class programming construct, hence limiting its applicability. To address this issue, in this paper we present a flexible notion of scoping in the context of a sensor network macroprogramming framework. Our approach enables the specification of complex interactions among system partitions, thus greatly simplifying the development process. Moreover, this is not detri- mental to performance: our approach results reasonably close to an optimal solution computed with global system knowledge, while exhibiting a 70% gain w.r.t. baseline solutions.

Enabling Scope-Based Interactions in Sensor Network Macroprogramming

MOTTOLA, LUCA;PICCO, GIAN PIETRO
2007-01-01

Abstract

Wireless sensor networks are increasingly employed to develop sophisticated applications where heterogeneous nodes are deployed, and multiple parallel activities must be performed. Therefore, application developers require the ability to partition the system based on the node characteristics, and specify complex interactions among different partitions. Existing programming abstractions for sensor networks tackled this problem by providing a notion of scoping. However, this rarely emerges as a first-class programming construct, hence limiting its applicability. To address this issue, in this paper we present a flexible notion of scoping in the context of a sensor network macroprogramming framework. Our approach enables the specification of complex interactions among system partitions, thus greatly simplifying the development process. Moreover, this is not detri- mental to performance: our approach results reasonably close to an optimal solution computed with global system knowledge, while exhibiting a 70% gain w.r.t. baseline solutions.
2007
Proceedings of the 4th IEEE International Conference on Mobile Ad-hoc and Sensor Systems (MASS)
9781424414543
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/662356
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