| Wireless Sensor Networks (WSNs) are an emerging technology, recently finding extensive application in scientific and military surveillance. Sensor networks operate under severe energy constraints and are largely characterized by short-range multi-hop radio communications, which drives the need for energy-adaptive routing schemes in such networks. Fuzzy Diffusion, an energy optimization on the general diffusion schemes for sensor networks, has been shown to offer significant improvements in WSN lifetime and connectivity. The proposed scheme employed fuzzy-logic based resource-aware routing decisions to reduce the amount of network transmissions, thereby conserving energy.
The initial quantification of fuzzy diffusion performance depicted the advantages of extreme conservative routing in dense WSNs. However, an in-depth investigation of the impact of fuzzy decisions on the protocol performance is needed to substantiate the use of fuzzy logic as compared to simpler, straightforward crisp decision-making strategies. Crisp decisions naturally involve less processing, but trade-off accuracy and smooth decision transitions when compared to fuzzy decisions. For short range WSNs, local data processing is much cheaper than radio communications, and so if the fuzzy decisions prove to be significantly efficient in making reliable network estimates, then the amount additional processing incurred might be justified.
Hence the purpose of this research is to analyze the importance of fuzzy logic in computing efficient forwarding decisions, and to quantify the amount of performance loss (if at all) when using crisp decisions. Further, this paper aims at quantifying the network and traffic scenarios under which fuzzy diffusion scheme would be efficient, through a series of simulation experiments.
Note: This abstract will undergo no or little changes after FORM B has been provided. |