Quality-of-context driven autonomicity

Optimisation in wireless sensor networks is necessary due to the resource constraints of individual devices, bandwidth limits of the communication channel, relatively high probably of sensor failure, and the requirement constraints of the deployed applications in potently highly volatile environments. This paper presents BioANS, a protocol designed to optimise a wireless sensor network for resource efficiency as well as to meet a requirement common to a whole class of WSN applications - namely that the sensor nodes are dynamically selected on some qualitative basis, for example the quality by which they can provide the required context information. The design of BioANS has been inspired by the communication mechanisms that have evolved in natural systems. The protocol tolerates randomness in its environment, including random message loss, and incorporates a non-deterministic ’delayed-bids’ mechanism. A simulation model is used to explore the protocol’s performance in a wide range of WSN configurations. Characteristics evaluated include tolerance to sensor node density and message loss, communication efficiency, and negotiation latency .

Communication system model for information rate evaluation of differential detection over time-varying channels

A communication system model for mutual information performance analysis of multiple-symbol differential M-phase shift keying over time-correlated, time-varying flat-fading communication channels is developed. This model is a finite-state Markov (FSM) equivalent channel representing the cascade of the differential encoder, FSM channel model and differential decoder. A state-space approach is used to model channel phase time correlations. The equivalent model falls in a class that facilitates the use of the forward backward algorithm, enabling the important information theoretic results to be evaluated. Using such a model, one is able to calculate mutual information for differential detection over time-varying fading channels with an essentially finite time set of correlations, including the Clarke fading channel. Using the equivalent channel, it is proved and corroborated by simulations that multiple-symbol differential detection preserves the channel information capacity when the observation interval approaches infinity.