Investigation of Fault Detection Methods in Wireless Sensor Networks | Charalampos Orfanidis
| | Abstract | Wireless sensor networks (WSNs) consist of distributed embedded wireless devices that are used to monitor environmental conditions such as temperature, pressure, sound, etc. Some common characteristics of WSNs are their constrained resources and the fact that they are often deployed in harsh and hostile environments. The sensor nodes of the network can suffer from several faults which could be cause by the environment or from a node malfunction. One consequence of a fault may be the degradation of the communication between the nodes which may affect the whole network topology. For this reason, fault detection is significant for the proper function of a WSN. However, the classical fault detection mechanisms used in regular computer networks cannot be used by WSNs due to constrained resources and extended communication cost, making fault detection a more complex procedure. The resource constrained nature of a WSN calls for an energy-efficient protocol which will achieve the required performance level of the sensor, consuming the least possible amount of energy. A protocol like this can offer extended lifetime to the network and satisfying performance. The faults which may appear are numerous and there are several ways to classify them. There are many scientific articles focusing on fault detection in WSNs, but they do not include the energy-efficiency factor. The intention of this project is to make an analysis of fault detection methods according to their energy-efficiency and overall performance. This analysis is based on existing scientific literature about fault detection techniques on WSNs. | | Type | Master's thesis [Academic thesis] | | Year | 2015 | | Publisher | Technical University of Denmark, Department of Applied Mathematics and Computer Science | | Address | Richard Petersens Plads, Building 324, DK-2800 Kgs. Lyngby, Denmark, compute@compute.dtu.dk | | Series | DTU Compute M.Sc.-2014 | | Note | DTU supervisor: Nicola Dragoni, ndra@dtu.dk, DTU Compute | | Electronic version(s) | [pdf] | | Publication link | http://www.compute.dtu.dk/English.aspx | | BibTeX data | [bibtex] | | IMM Group(s) | Computer Science & Engineering |
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