Datacenter at the airport: Reasoning About Time-Dependent Parking Lot Occupancy
Sprache des Titels:
Quite recently, Olariu and his co-workers proposed to call a Vehicular Cloud a dynamic group of autonomous vehicles whose excess computing, sensing, communication and storage resources can be coordinated and dynamically allocated to authorized users. What distinguishes vehicular clouds from conventional clouds is the dynamically-changing amount of available resources that, in some cases, may fluctuate rather abruptly. In this work, we take the first step towards making a non-trivial form of vehicular clouds reality. Specifically, we envision a vehicular cloud involving cars in the long-term parking lot of a typical international airport. In order to be able to schedule resources and to assign computational tasks to the various cars in the vehicular cloud, a fundamental prerequisite is to have an accurate picture of the number of vehicles that are expected to be present in the parking lot as a function of time. What makes the problem difficult is the time-varying nature of the arrival and departure rates. In this paper we concern ourselves with predicting the parking occupancy given time-varying arrival and departure rates. In this context, our main contribution is to provide closed forms for the probability distribution of the parking lot occupancy as a function of time, for the expected number of cars in the parking lot and its variance, and for the limiting behavior of these parameters as time increases. In addition to our analytical results, we have obtained a series of empirical results, obtained by extensive simulation, that confirm the accuracy of our analytical predictions.
Sprache der Kurzfassung:
IEEE Transactions on Parallel and Distributed Systems
IEEE Computer Society Digital Library, IEEE Computer Society