An efficient cloud–assisted best–parking algorithm for BikeNet. (20th August 2014) - Chang, Hong–Yi; Huang, Shih–Chang; Lin, Yuan–Wei
Numerous countries have implemented public bike policies. Users can rent a bike in one place, and return it at a different location. However, users that change to another type of transport may spend considerable time searching for a parking space for the bike. This study proposes an efficient best–parking (BP) algorithm for bike networks. This mechanism efficiently offers bike users route with parking spaces nearby destination. This study also presents a parallel BP algorithm based on the MapReduce model to accelerate the computation of the ideal route for parking. Simulation results show that the performance of the proposed algorithm is ~70% better than that of the aggregating data dissemination (ADD) algorithm and 91% better than that of the parking space discovery (PSD) algorithm. The proposed BP algorithm collects parking–space information only as needed. Therefore, the BP communication overhead is considerably lower than that of ADD or PSD algorithms.