Due to the diffusion of Internet of Things (IoT), many devices such as water meters, smart dumpsters, and many other objects have the capacity to record data. Gathering these data from the devices is a problem that could be solved in three ways: by building a huge network infrastructure, by using regular workforce or by using opportunistic IoT networks, i.e. by using as mobile hotspots the devices of selected users. The latter is cheaper than the others, requiring only the payment of a reward to the users. In this paper, we introduce a Multi Period Assignment problem, i.e. a problem for planning the operations of Opportunistic IoT networks. The problem minimizes the sum of user rewards, while gathering data from all devices. An effective heuristic method able to deal with realistic-sized instances is presented. The heuristic is able to find, by using a reasonable amount of time, the optimum for 124 out of 128 instances and reach gaps smaller than 0.1% for the remaining 4 instances
Multi Period Assignment Problem for Social Engagement and Opportunistic IoT / Fadda, Edoardo; Mana, Dario; Perboli, Guido; Tadei, Roberto. - ELETTRONICO. - 2:(2017), pp. 760-765. (Intervento presentato al convegno 41st IEEE Annual Computer Software and Applications Conference Workshops, COMPSAC 2017 tenutosi a ita nel 2017) [10.1109/COMPSAC.2017.173].
Multi Period Assignment Problem for Social Engagement and Opportunistic IoT
Fadda, Edoardo;Perboli, Guido;Tadei, Roberto
2017
Abstract
Due to the diffusion of Internet of Things (IoT), many devices such as water meters, smart dumpsters, and many other objects have the capacity to record data. Gathering these data from the devices is a problem that could be solved in three ways: by building a huge network infrastructure, by using regular workforce or by using opportunistic IoT networks, i.e. by using as mobile hotspots the devices of selected users. The latter is cheaper than the others, requiring only the payment of a reward to the users. In this paper, we introduce a Multi Period Assignment problem, i.e. a problem for planning the operations of Opportunistic IoT networks. The problem minimizes the sum of user rewards, while gathering data from all devices. An effective heuristic method able to deal with realistic-sized instances is presented. The heuristic is able to find, by using a reasonable amount of time, the optimum for 124 out of 128 instances and reach gaps smaller than 0.1% for the remaining 4 instancesFile | Dimensione | Formato | |
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https://hdl.handle.net/11583/2786362