College of Sciences


Computer Science

Graduate Level


Graduate Program/Concentration

Computer Science

Publication Date





Researchers have shown that most vehicles spend the majority of their time parked in parking garages, lots, or driveways. During this time, their computing resources are unused and untapped. This has led to substantial interest in Vehicular Cloud, an area of research in which each vehicle acts as a computation node. The main difference between traditional cloud computing and vehicular cloud computing is the availability of nodes. In traditional clouds, nodes are available 24/7, while in vehicular clouds, nodes (vehicles) are only available while parked in parking lots. This creates a dynamic environment as vehicles enter and exit parking garages at random. In this paper, we present a novel framework called ADAM (Auction-based Datacenter Management) for Vehicular Cloud. It uses auction and market design approaches and makes the following contributions: (1) integration of software agents that can search, bid, price, and allocate jobs on behalf of stakeholders, (2) formulation of a truthful auction-based job management system that unifies job allocation, scheduling, and pricing strategies, and (3) simulation studies demonstrating substantial performance benefits. The results of our simulations show that the proposed interactive agents enable efficient processing of large amounts of data, leading to cost savings for stakeholders, reducing the load on conventional clouds, and improving the utility of parked vehicles and parking facilities.


Vehicular networks, Datacenters, Double auction, Smart parking


Macroeconomics | OS and Networks | Other Computer Sciences



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A Novel Parking Management in Smart City Vehicular Datacenters



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