The IEEE 802.15.4 standard is an interesting technology for use in Wireless Body Sensor Networks (WBSN), where entire networks of sensors are carried by humans. In many environments the sensor nodes experience external interference for example, when the WBSN is operated in the 2.4 GHz ISM band and the human moves in a densely populated city, it will likely experience WiFi interference, with a quickly changing ``interference landscape''. In this thesis we propose Adaptive Resource Allocation schemes, to be carried out by the WBSN, which provided noticeable performance gains in such environments. We investigate a range of adaptation schemes and assess their performance both through simulations and experimentally.

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Body sensor networking is a rapidly growing technology. Today wearable sensors are used to measure and monitor e.g. pulse, temperature, skin conductance, heart activity, and movement (through GPS or inertial measurement units). Mobile phones can act as coordinating nodes in wireless personal area networks used in home automation, healthcare, sport and wellness e.g. to measure pulse and distance. Integration of data from multiple sources sensors (data fusion) means that data from each sensor node needs to be associated with data from other sensor nodes sampled at approximately the same time. Accurate methods for time synchronization are therefore a necessary prerequisite for reliable data fusion. This thesis studies time synchronization problems in Bluetooth piconets between multiple wireless sensor nodes connected to a mobile phone that acts as coordinating node. Three different algorithms to enable correct data fusion have been developed, implemented and evaluated. The first is a single clock solution that synchronizes multiple wireless sensor nodes based solely on the mobile phone’s clock. The other two algorithms synchronize the clocks in sensor nodes to the clock in the coordinating node. / <p>QC 20130605</p>