A Novel Parking Management in Smart City Vehicular Datacenters

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.https://digitalcommons.odu.edu/gradposters2023_sciences/1019/thumbnail.jp

Unmasking Deception in VANETs: A Decentralized Approach to Verifying Truth in Motion

VANET, which stands for Vehicular Ad Hoc Network, is a wireless network that allows vehicles to communicate with each other and with infrastructure, such as Roadside Units (RSUs), with the aim of enhancing road safety and improving the overall driving experience through real-time exchange of information and data. VANET has various applications, including traffic management, road safety alerts, and navigation. However, the security of VANET can be compromised if a malicious user alters the content of messages transmitted, which can harm both individual vehicles and the overall trust in VANET technology. Ensuring the correctness of messages is crucial for the success of VANET, as fake messages pose a threat to traffic safety, human lives, and the credibility of VANET. This poster presents a novel framework for efficiently identifying vehicles that spread fake messages in VANET. The framework divides messages into two categories, urgent and non-urgent, and handles them using a decentralized priority queue consisting of trusted RSUs. The RSUs register dynamic security keys of the vehicles and broadcast the valid ones in their range for quick message exchange. The simulation results show that the framework is scalable and can efficiently identify vehicles that spread fake messages while providing secure communication and guaranteeing the QoS requirements of safety-related VANET applications.https://digitalcommons.odu.edu/gradposters2023_sciences/1009/thumbnail.jp

Search for dark matter produced in association with bottom or top quarks in √s = 13 TeV pp collisions with the ATLAS detector

A search for weakly interacting massive particle dark matter produced in association with bottom or top quarks is presented. Final states containing third-generation quarks and miss- ing transverse momentum are considered. The analysis uses 36.1 fb−1 of proton–proton collision data recorded by the ATLAS experiment at √s = 13 TeV in 2015 and 2016. No significant excess of events above the estimated backgrounds is observed. The results are in- terpreted in the framework of simplified models of spin-0 dark-matter mediators. For colour- neutral spin-0 mediators produced in association with top quarks and decaying into a pair of dark-matter particles, mediator masses below 50 GeV are excluded assuming a dark-matter candidate mass of 1 GeV and unitary couplings. For scalar and pseudoscalar mediators produced in association with bottom quarks, the search sets limits on the production cross- section of 300 times the predicted rate for mediators with masses between 10 and 50 GeV and assuming a dark-matter mass of 1 GeV and unitary coupling. Constraints on colour- charged scalar simplified models are also presented. Assuming a dark-matter particle mass of 35 GeV, mediator particles with mass below 1.1 TeV are excluded for couplings yielding a dark-matter relic density consistent with measurements