IDADET: Iterative Double-Sided Auction-Based Data-Energy Transaction Ecosystem in Internet of Vehicles

Abstract

In the era of big data, the unprecedented growth of data has been regarded as an important asset and the commercial application of data acquisition markets has emerged accordingly. With the advancement of vehicle manufacturing and sensor technologies, a large amount of data can be collected and stored in electric vehicles (EV), making the data acquisition scenario gradually extend to the Internet of Vehicles (IoV), and thus the corresponding operational rules and economic feasibility need to be fully investigated there. In this paper, we focus on a general IoV-oriented data acquisition market that consists of a data center, multiple EVs, multiple roadside units (RSUs), and a market operator (broker), with the objective of social welfare maximization (SWM) by identifying the optimal data task allocation. However, due to the inherent information asymmetry and fragmentation in such a market, it is not feasible to solve the SWM problem directly. To this end, we propose an iterative double-sided auction (IDA) mechanism, which leverages the selfinterested feature of RSUs and EVs to decompose the SWM problem, enabling every participant to make decisions in a distributed manner under the broker's coordination. A complete set of operational rules covering the data task allocation, bidding, payment, and reimbursement are elaborately designed to achieve SWM, and energy is adopted as the pricing "currency", such that an IDA-based Data-Energy Transaction (IDADET) ecosystem is established in IoV. We verify the economic feasibility of the proposed IDADET ecosystem by showing its convergence and desirable properties of individual rationality, budget balance, incentive compatibility, and economic efficiency. In addition, considering the psychological effects of practical market participants, we make amendments to the operational rules of the IDADET ecosystem from the behavioral economics perspective, aiming to ensure its long-term well-functioning. Extensive numerical

Big data challenges and opportunities in Internet of Vehicles: a systematic review

“…The proposals cover a spectrum of innovative approaches, ranging from computation offloading (Xu et al , 2019) and energy exchange (Xu et al , 2023) to safety communication mechanisms (Wu et al , 2019) and resource management systems (Lu et al , 2021). Notable strengths include privacy preservation (Xu et al , 2019), efficient data and energy exchange (Xu et al , 2023), safety improvement (Wu et al , 2019), tailored resource allocation (Lu et al , 2021), enhanced connectivity (Liu et al , 2022) and accurate traffic predictions (Guo et al , 2023; Rani and Sharma, 2023). However, common challenges emerge, encompassing issues such as overhead (Xu et al , 2019), network connectivity (Xu et al , 2019), complex auction mechanisms (Xu et al , 2023), computational complexity and data-related complexities (Liu et al , 2022).…”

“…They proposed novel methods to leverage connected vehicles in collecting waste-related data and optimizing waste collection routes, contributing to improved waste management practices in smart cities. Xu et al (2023) focused on exploring the operational dynamics and economic feasibility of an IoV-oriented data acquisition market within the context of the era of big data. They proposed an iterative double-sided auction (IDA) mechanism named IDA-based data-energy transaction (IDADET).…”

“…The proposed method integrates EC capabilities to enable computation offloading from vehicles to edge servers. Xu et al (2023) proposed an IDA-based data-energy transaction ecosystem (IDADET) for the IoV. IDADET facilitates efficient data and energy transactions between connected vehicles and other entities in the IoV ecosystem.…”

“…Xu et al (2023) focused on exploring the operational dynamics and economic feasibility of an IoV-oriented data acquisition market within the context of the era of big data. They proposed an iterative double-sided auction (IDA) mechanism named IDA-based data-energy transaction (IDADET).…”

“…Also, it outlines each proposal’s primary aim and methodology, with the assessment environment section detailing contextual information. The collaborative data gathering proposal introduces a scheme for efficient data gathering (Das and Dash, 2023), energy preservation (Das and Dash, 2023), real-time monitoring (Sahraoui et al , 2022) and fast convergence (Xu et al , 2023) through simulation. However, challenges include coordination complexity and real-world deployment (Das and Dash, 2023), data privacy and integration (Sahraoui et al , 2022; Ijemaru et al , 2023).…”