Temporal Blockchains for Intelligent Transportation Management and Autonomous Vehicle Support in the Internet of Vehicles

Temporal Blockchains for Intelligent Transportation Management and Autonomous Vehicle Support in the Internet of Vehicles

DOI: 10.4018/978-1-6684-3610-3.ch009
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Abstract

In the internet of vehicles (IoV) field, blockchain technology has been proposed for durable and trustworthy bookkeeping of the exchanged data. However, block timestamps assigned by miners are usually delayed with respect to events that generate the stored data, making them unusable for applications dealing with exact timing, like traffic law enforcement and insurance accident investigation. To overcome this shortcoming, the authors propose to add new timestamps to the blockchain, which are assigned by data originators to represent the valid time of data recorded within a transaction. The resulting enhanced blockchain data model, named BiTchain, can be considered from a temporal database perspective as a bitemporal data model. In order to let users and applications enjoy the potential of BiTchain, they also introduce an expressive temporal query language, named BiTEQL, defined as a TSQL2-like temporal extension of the EQL blockchain query language.
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Introduction

Present and future intelligent transportation and autonomous vehicles applications are using Internet of Vehicles (IoV) (Yang et al., 2014), Flying Ad-Hoc Networks (FANETs) (Bekmezci et al., 2013) and Vehicular Ad-Hoc Networks (VANETs) (Zeadally et al., 2012) as communication infrastructures. In this context, the Blockchain technology has been proposed for durable and trustworthy bookkeeping of the exchanged data (Guo et al., 2018; Diallo et al., 2020; Fu et al., 2020; Gupta et al., 2020; Li et al., 2020a; Narbayeva et al., 2020; Rehman et al., 2020; Javaid et al., 2021; Uddin et al., 2021; Chondrogiannis et al., 2022; Six et al., 2022). A blockchain (Nofer et al., 2017; Dinh et al., 2018; Zheng et al., 2018; Li et al., 2020b) is a public distributed ledger that stores committed transactions in an ordered list, or a chain, of blocks. Such a ledger is maintained by multiple distributed nodes (computers), which are linked in a peer-to-peer network (i.e., without a server node that has full control and central authority) and possibly do not trust each other, through a consensus mechanism (i.e., an agreement among these nodes on the truth of data stored in the blockchain) and cryptography (essentially hash algorithms and digital signatures). Notice that the ledger is replicated over all nodes. A transaction is a sequence of operations applied on some state respecting the ACID properties as in classical database systems. It cannot be modified once it is recorded in a block of the blockchain. A block is made up of a block header and a block body: the former contains, among others, the parent block hash that points to the previous block and a timestamp; the latter essentially contains transactions.

From a database point of view, a blockchain (Dinh et al., 2018; Mohan, 2018; Vo et al., 2018; Xu et al., 2019) can be considered as a distributed and replicated temporal database (Grandi, 2015; Jensen & Snodgrass, 2018a) that stores a large list of blocks: each timestamped block is replicated over all nodes of the network. More precisely, since block timestamps cannot be updated and the whole blockchain is an append-only data structure, a blockchain can be viewed as a transaction-time (Jensen & Snodgrass, 2018b) database, that is a database where each version of a time-varying datum (like the salary of an employee or the price of a product) is stamped with the time when such a version has been inserted in the database.

Among the strengths of blockchain, we find immutability, data integrity, transparency, distribution, absence of central/intermediary entity, and provision of trust in trustless environments. These advantages have lead to a wide use of blockchain technology in several fields, like data science (Liu et al., 2020), supply chains (Behnke & Janssen, 2020), business (Frizzo-Barker et al., 2020), economics (Kher et al., 2020), medicine (Zhang & Boulos, 2020), Internet of Things (IoT) (Pavithran et al., 2020), smart contracts (Singh et al., 2020), e-voting (Khan et al., 2020), finance (Chang et al., 2020), reputation systems (Sharples & Domingue, 2016), and security services (Li et al., 2020b), although it was initially developed to manage cryptocurrencies as Bitcoin (Nakamoto, 2008) and its successors.

Key Terms in this Chapter

Internet of Vehicles (IoV): A wireless network of intelligent vehicles that are connected to Internet and that are communicating according to agreed protocols. IoV is a part of Internet of Things (IoT) and evolves from VANET.

Temporal Query Language: A query language that allows manipulation of time-referenced data.

Valid Time: Temporal dimension concerning when some fact is true in the modeled reality.

Intelligent Transportation System: It is the application of sensing, analysis, control, and communications technologies to ground transportation in order to improve safety, mobility and efficiency

Transaction Time: Temporal dimension concerning when some data is current in the database.

Blockchain: A public distributed ledger that stores committed transactions in an ordered list, or a chain, of blocks. Such a ledger is maintained by multiple distributed nodes (computers) which are linked in a peer-to-peer network and possibly do not trust each other, through a consensus mechanism and cryptography. Notice that the ledger is replicated over all nodes.

Block Timestamp: A component of a block, whose value is set by the miner to represent when the block has been validated. It gives to the blockchain the semantics of a transaction-time database.

VANET: A mobile network whose nodes are moving vehicles. In a VANET, intelligent vehicles on the road interact with each other and with roadside base stations.

Bitemporal Blockchain Data Model: A blockchain data model that maintains the history of data along both transaction time (block timestamp, provided by the miner) and valid time (data validity timestamp, supplied by the data originator).

TSQL2: A temporal extension of the SQL standard designed by a committee of temporal database experts chaired by R.T. Snodgrass in 1995.

Autonomous Vehicle: A vehicle that can, without interaction with a human driver, sense its environment and efficiently drive itself along several types of roads having different characteristics and possibly presenting complex and unexpected situations. It is also known as an automated or a self-driving vehicle, or as a driverless, self-driving or robotic car.

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