mTOSSIM: A simulator that estimates battery lifetime in wireless sensor networks

Knowledge of the battery lifetime of the wireless sensor network is important for many situations, such as in evaluation of the location of nodes or the estimation of the connectivity, along time, between devices. However, experimental evaluation is a very time-consuming task. It depends on many factors, such as the use of the radio transceiver or the distance between nodes. Simulations reduce considerably this time. They allow the evaluation of the network behavior before its deployment. This article presents a simulation tool which helps developers to obtain information about battery state. This simulator extends the well-known TOSSIM simulator. Therefore it is possible to evaluate TinyOS applications using an accurate model of the battery consumption and its relation to the radio power transmission. Although an specific indoor scenario is used in testing of simulation, the simulator is not limited to this environment. It is possible to work in outdoor scenarios too. Experimental results validate the proposed model.Junta de Andalucía P07-TIC-02476Junta de Andalucía TIC-570

Improving RSSI based distance estimation for wireless sensor networks

In modern everyday life we see gradually increasing number of wireless sensor devices. In some cases it is necessary to know the accurate location of the devices. Most of the usual techniques developed to get this information require a lot of resources (power, bandwidth, computation, extra hardware) which small embedded devices cannot afford. Therefore techniques, using small resources without the need for extra hardware, need to be developed. Wireless sensor networks are often used inside buildings. In such environment satellite positioning is not available. As a consequence, the location computation must be done in network-based manner. In this thesis a received signal strength indicator (RSSI) based distance estimation technique for 802.15.4 network based on CC2431 radio is discussed. In this approach we try to differentiate between good and erroneous measurements by imposing limits based on standard deviation of RSSI and the number of lost packets. These limits are included as a part of the model parameter estimation process. These limits are optimized in order to improve the resulting distance estimates with minimum loss of connectivity information. We experimentally evaluated the merits of the proposed method and found it to be useful under certain circumstances.fi=Opinnäytetyö kokotekstinä PDF-muodossa.|en=Thesis fulltext in PDF format.|sv=Lärdomsprov tillgängligt som fulltext i PDF-format