Multi criteria IoT Resource Discovery: A Comparative Analysis
The growth of real world objects with embedded and globally n etworked sensors allows to consolidate the Internet of Things paradigm and increase the number of ap plic tions in the domains of ubiquitous and context aware computing. The merging between Cloud Comput ing and Internet of Things named Cloud of Things will be the key to handle thousands of sensors and thei r data. One of the main challenges in the Cloud of Things is context aware sensor search and selection. Typ ically, sensors require to be searched using two or more conflicting context properties. Most of the existing work uses some kind of multi criteria decision analysis to perform the sensor search and selection, but doe s not show any concern for the quality of the selection presented by these methods. In this paper, we anal yse the behaviour of the SAW, TOPSIS and VIKOR multi objective decision methods and their quality o f selection comparing them with the Paretooptimality solutions. The gathered results allow to analys e and compare these algorithms regarding their behaviour, the number of optimal solutions and redundancy. Copyright c (c) 2016 John Wiley Sons, Ltd.