just building ranges from shoe-box-sized Sensoria WINS NG sensors faster routers, switchers, and browsers. A sensor net- with an SH-4 microprocessor to matchbox-sized work is designed to collect information from a physical Berkeley motes with an 8-bit microcontroller. A few environment. Networking will be intimately coupled samples of sensor hardware are shown in Figure 3.7-2; with the needs of sensing and control, and hence the their corresponding capabilities are summarized and application semantics. To optimize for performance and compared in Table 3.7-1. It is well known that commu- resources such as energy, one has to rethink the existing nicating 1 bit over the wireless medium at short ranges TCP/IP stack and design an appropriate sensor network consumes far more energy than processing that bit. For abstraction to support application development. For the Sensoria sensors and Berkeley motes, the ratio of example, in many applications, it is more appropriate to Sensor net Sensor net Gateway Storage Sensor net Sensor net INTERNET Client browsing Storage Figure 3.7-1 Sensor networks significantly expand the existing Internet into physical spaces. The data processing, storage, transport, querying, as well as the internetworking between the TCP/IP and sensor networks present a number of interesting research challenges that must be addressed from a multidisciplinary, cross-layer perspective. Wireless sensor networks CHAPTER 3.7 Figure 3.7-2 Samples of wireless sensor hardware: (a) Sensoria WINS NG 2.0 sensor node; (b) HP iPAQ with 802.11b and microphone; (c) Berkeley/Crossbow sensor mote, alongside a U.S. penny; (d) An early prototype of Smart Dust MEMS integrated sensor, being de- veloped at UC Berkeley. (Picture courtesy of Kris Pister and Jason Hill). address nodes in a sensor network by physical proper- infrastructure support, the sensors have to rely on dis- ties, such as node locations or proximity, than by IP covery protocols to construct local models about the addresses. How and where data is generated by 