Optimal placement of storage nodes in a wireless sensor network

Networks of sensor nodes are usually employed to monitor large areas, collecting data with regular frequency. This large volume of data has to be stored somewhere for answering to external user queries [3]. There are usually two main ways to store data. Source nodes, which are responsible for collecting data, can either locally store the data or transmit them to the sink, a powerful node connected to the external world. Both solutions present some disadvantages. If data are locally stored, several problems may arise: (i) data cannot be accumulated for long periods because nodes are equipped with only limited memory space; (ii) stored data are lost once the energy of a source node – battery operated – is depleted; and (iii) searching data for serving query demand results in networkwide communications. Alternatively, source nodes can forward the collected data to the sink. However, communicating data from the source nodes up to the sink makes the network congested, especially if data are transmitted raw, that is, uncompressed. Limitations to the number of packets a sensor can transmit to the sink per time unit must be also considered [2]. Recently [9, 10], a hybrid solution has been proposed which makes use of a limited number of “special” sensors, more powerful than standard ones in terms of storage, energy, and computational capabilities. Under this model, source nodes may forward their raw data to such special nodes, referred to as storage nodes. Here, raw data are stored and compressed, i.e., reduced in size, to be transmitted to the sink at the time a query demand from external users is submitted. With this two-tier model, if the number of storage nodes is kept limited, the network becomes less congested at the price of a moderate increase of the sensor cost of the network. Indeed, the integration of storage nodes in the tiered architecture for sensor networks is made possible by the new storage-enriched hardware [6, 11] considered to be very practical [5]. The introduction of the storage nodes helps to alleviate the transmission bandwidth problem by distributing the local data transmission to the storage nodes. This hierarchical structure has been instantiated by the popular stargate device [11] and the memory-enhanced sensor nodes by UC Riverside [6]. Those special powerful nodes take advantage of their high transmission, storage and even computational capabilities to alleviate the bandwidth limitation, and also provide auxiliary support for surrounding vulnerable sensors for data back-up. In [9, 10] the problem of selecting a subset