A Scalable Search Engine for Mass Storage Smart Objects Nicolas Anciaux 1,2 Saliha Lallali 1,2 Iulian Sandu Popa1,2 Philippe Pucheral1,2 1INRIA Rocquencourt 2Université de Versailles Saint-Quentin-en-Yvelines 78153 Le Chesnay Cedex, France 78035 Versailles Cedex, France
[email protected] [email protected] ABSTRACT built by querying these data. So far, all these data end up on This paper presents a new embedded search engine designed for centralized servers where they are analyzed and queried. This smart objects. Such devices are generally equipped with centralized model however has two main drawbacks. First, the extremely low RAM and large Flash storage capacity. To tackle ever increasing amount of data transferred from their source (the these conflicting hardware constraints, conventional search smart objects) to their destination (the servers) has a dramatic engines privilege either insertion or query scalability but cannot negative impact on environmental sustainability (i.e., energy meet both requirements at the same time. Moreover, very few waste) and costs (i.e., data transfer). Hence, significant energy solutions support document deletions and updates in this context. and bandwidth savings can be obtained by storing data locally in In this paper, we introduce three design principles, namely Write- smart objects, especially when dealing with large data and seldom Once Partitioning, Linear Pipelining and Background Linear used records [8, 19]. Second, centralizing data sensed about Merging, and show how they can be combined to produce an individuals introduces an unprecedented threat on data privacy embedded search engine reconciling high insert/delete/update rate (e.g., at 1Hz granularity, an electricity smart meter can reveal the and query scalability.