P-PBFT: An improved blockchain algorithm to support large-scale pharmaceutical traceability

With the continuous development of connected and automated vehicles (CAVs) and Internet of Vehicle (IoV) technologies, various application scenarios have put forward higher requirements for vehicular communications. On the one hand, applications related to vehicle driving safety require lower latency and higher throughput. On the other hand, users who use cellular vehicle-to-everything (C-V2X) to transfer data will have to face high communication fees due to the increasing amount of data. Therefore, from the perspective of balancing quality of service (QoS) and user communication costs, this paper integrates dedicated short-range communication (DSRC) and C-V2X, two vehicular communication technologies with their own advantages, into a framework called cluster-based traffic differentiated hybrid routing (CTDHR), to provide services for in-vehicle communication. A vehicle clustering method based on hierarchical clustering is proposed to solve problems (e.g., the communication linking being difficult to maintain and the frequent cell handover due to high-speed movement of vehicles). The CTDHR framework is modeled on the resulting clusters and an objective equation was established. Finally, since the obtained objective equation is a nonlinear integer programming problem, we propose a heuristic algorithm to solve this optimization problem. In the simulation experiments, CTDHR shows better communication performance than the existing DSRC and C-V2X hybrid models. The experimental results show that CTDHR can reduce the communication costs of users while satisfying QoS.

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Design and Optimization of Cluster-Based DSRC and C-V2X Hybrid Routing

A Comprehensive Review on Blockchains for Internet of Vehicles: Challenges and Directions

/pdf/a-comprehensive-review-on-blockchains-for-internet-of-21gu144b.pdf

A comprehensive review on blockchains for Internet of Vehicles: Challenges and directions

The concept of the metaverse has gained increasing attention in recent years, and the development of various new technologies, including digital twin technology, has made it possible to see the metaverse coming to pass. Many academics have begun to investigate various problems after realizing the importance of digital twin technology in building the metaverse. However, when utilizing digital twin technology to construct a metaverse, there remains limited research on how to allocate multibase station resources. This research translates a multibase station wireless resource allocation problem into an integer linear programming constraint model when virtual service providers construct a metaverse. In addition, the optimal VCG reverse auction (OPT-VCGRA) mechanism is designed to maximize social welfare and solve the problem of IoT devices competing for base station wireless resources. Specifically, the problem of the optimal allocation of wireless channel resources and payment rule based on the Vickrey–Clarke–Groves mechanism is solved to achieve optimal allocation and calculation of payment prices. Since the optimal allocation problem is NP-hard, this paper also designs a metaverse digital twin resource allocation and pricing (MDTRAP) mechanism based on monotonic allocation and key value theory. The mechanism sends the resource allocation results of multiple base stations to IoT devices and calculates the price payment when building a metaverse in the real world. This paper shows that both auction mechanisms have incentive compatibility and individual rationality properties. Through experiments, this paper compares the two mechanisms in terms of social welfare, the number of winners, and the overall payment. The MDTRAP mechanism performs similarly to the OPT-VCGRA mechanism in terms of social welfare, the number of winners, and channel utilization but is far superior to the OPT-VCGRA mechanism in terms of execution time and total payment. The trustful experiment also verified the truthfulness of the MDTRAP mechanism. The experimental results show that the MDTRAP mechanism can be used to solve the resource allocation problem of multiple base stations to IoT devices when building a metaverse in the real world and can effectively maximize social welfare.

/pdf/a-truthful-mechanism-for-multibase-station-resource-2i3i65ks.pdf

A Truthful Mechanism for Multibase Station Resource Allocation in Metaverse Digital Twin Framework

Truthful auction mechanisms for resource allocation in the Internet of Vehicles with public blockchain networks

In spatial data mining, co-location pattern mining is intended to discover the sets of spatial features whose instances occur frequently in nearby geographic areas. Co-location pattern mining is an important task in spatial data mining and has been applied in many applications. Although many spatial co-location pattern mining methods applied to point objects have been proposed, few mining approaches are designed for extended spatial objects in practical scenes. Unlike existing works, we develop OESCPM (Online Extended Spatial Co-location Pattern Mining System) to mine co-location patterns over extended objects. OESCPM decomposes extended instances into cells and counts the number of cells belonging to different features. With simple interaction on OESCPM, users can view co-location patterns over interested extended spatial datasets online. 

Wenlu Lou

Papers

Truthful auction mechanisms for resource allocation in the Internet of Vehicles with public blockchain networks

OESCPM: An Online Extended Spatial Co-location Pattern Mining System