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.File | Dimensione | Formato | |
---|---|---|---|
mottola07enabling.pdf
accesso aperto
Dimensione
773.6 kB
Formato
Adobe PDF
|
773.6 kB | Adobe PDF | Visualizza/Apri |
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.