GINGER: a minimizing-effects reprogramming paradigm for distributed sensor networks

Reprogramming the applicative behaviour of distributed sensor networks is becoming a more and more important ability in real-working monitoring applications to include new functionalities or modify the existing ones. Several approaches for reprogramming have been presented in the literature suggesting efficient reprogramming mechanisms. The aim of this paper is to address a problem that received less attention in the scientific community: minimizing the reprogramming effects on the applications running at the networks nodes. This issue is of paramount importance in complex distributed monitoring systems, where the network's behaviour is characterized by several (possibly concurrent) applications running at nodes. This paper suggests a novel reprogramming paradigm, called GINGER, designed to minimize the reprogramming effects on the nodes of distributed sensor networks. Critical aspects, advantages and open points are deeply described and critically commented.