The Block Propagation in Blockchain-Based Vehicular Networks

Zhang, Xuefei; Xia, Wenbo; Wang, Xiaochen; Liu, Junjie; Cui, Qimei; Tao, Xiaofeng; Liu, Ren Ping

doi:10.1109/jiot.2021.3074924

Cited by 17 publications

(3 citation statements)

References 35 publications

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“…The vehicles were configured to move on Manhattan roads following a random waypoint mobility model. A random waypoint mobility model is used to simulate the vehicle's mobility as described in [41], [42], [43]. This mobility model presents one of the most dynamic and complex environments, as it contains a wide range of moving patterns along the path.…”

Section: Simulation Scenarios and Resultsmentioning

confidence: 99%

Toward Network Slicing Enabled Edge Computing: A Cloud-Native Approach for Slice Mobility

Shah¹,

Gregory²,

Li³

2023

Preprint

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<p>Network slicing is a key enabler for 5G and beyond networks that permits operators to provide scalable, flexible, and dedicated networks over a common physical infrastructure. To cope with the rising demand for Ultra-Reliable and Low-Latency Communication (URLLC) in beyond 5G networks, the provision of dedicated secure networks closer to the users is essential. Multi-access Edge Computing (MEC) is a promising technology that provides data and computational resources closer to mobile users. However, MEC servers are resource-constrained, and offering dedicated service-specific network slices at the edge in a highly dynamic and mobile environment is challenging. Network slicing and MEC are being evolved by two different standardization bodies that limit their integration and raise mobility challenges that deserve more attention. We propose a cloud-native microservices architecture for network slice mobility management in MEC that permits each MEC slice to be distributed as stateless and independently deployable microservices. The proposal separates the MEC slice operational data and the user context, as each network function in an MEC slice stores the context in a separate shared database. The proposed architecture leverages new SDN extended federation modules in compliance with the ETSI requirements for inter-MEC system coordination. The federation modules support a more flexible and scalable creation of network slices at MEC servers, efficient resource utilization, and mobility of network slices across MEC servers. The simulation results show that our proposed architecture outperforms the existing SDN-based approaches for network slicing in MEC by achieving high slice acceptance rates and reduced slice migration delay.</p>

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Section: Simulation Scenarios and Resultsmentioning

confidence: 99%

Toward Network Slicing Enabled Edge Computing: A Cloud-Native Approach for Slice Mobility

Shah¹,

Gregory²,

Li³

2023

Preprint

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“…Long et al [15] optimized the block propagation in wireless blockchain networks by the partial engagement of nodes and optimal transmission routing based on a distributed Steiner tree. However, since the delay of transaction collection and block propagation is relatively high in MANETs [35], the geographical location of the miner and its connectivity in the network largely affect the blockchain performance.…”

Section: Manet-based Blockchainmentioning

confidence: 99%

A Robust Sharding-Enabled Blockchain with Efficient Hashgraph Mechanism for MANETs

Lai

Zhao

et al. 2023

Applied Sciences

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Blockchain establishes security and trust in mobile ad hoc networks (MANETs). Due to the decentralized and opportunistic communication characteristics of MANETs, hashgraph consensus is more applicable to the MANET-based blockchain. Sharding scales the consensus further through disjoint nodes in multiple shards simultaneously updating ledgers. However, the dynamic addition and deletion of nodes in a shard pose challenges regarding robustness and efficiency. Particularly, the shard is vulnerable to Sybil attacks and targeted attacks, and dishonest gossip reduces the efficiency of hashgraph consensus. Therefore, we proposed a behavior-based sharding hashgraph scheme. First, dishonest behaviors of nodes are recorded in a decentralized blacklist. Gossip information is sent to a reliable neighbor, and gossip information from another reliable neighbor is received. Second, a tree-assisted inter-sharding consensus is proposed to prevent Sybil attacks. The combination of shard recovery and reconfiguration based on node state is devised to prevent targeted attacks. Finally, we conducted the performance evaluation including security analysis and experimental evaluation to reveal the security and efficiency of the proposed scheme.

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“…Dynamic spectrum sharing is studied in [15], where reinforcement learning is utilized to analyze the resourcesharing structure and spectrum-sharing process in a blockchain system combined with 6G hybrid cloud. Authors in [16] study the dynamics of block propagation and provide a closedform expression for block propagation time, in blockchainbased vehicular ad-hoc networks. The work [17] minimizes the latency in storing data by intelligent transaction migration policy by exploiting the Markov process and deep deterministic policy gradient.…”

Section: Introductionmentioning

confidence: 99%

Countering Active Attacks on RAFT-Based IoT Blockchain Networks

et al. 2023

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This paper considers an Internet of Things (IoT) blockchain wireless network consisting of a leader node and various follower nodes which together implement the RAFT consensus protocol to verify a blockchain transaction, as requested by a blockchain client. Further, two kinds of active attacks, i.e., jamming and impersonation, are considered on the IoT blockchain network due to the presence of multiple active malicious nodes in the close vicinity. When the IoT network is under a jamming attack, we utilize the stochastic geometry tool to derive the closed-form expressions for the coverage probabilities for both uplink and downlink IoT transmissions (which eventually translate to blockchain transaction success rate). On the other hand, when the IoT network is under an impersonation attack, we propose a novel method that enables a receive IoT node to exploit the pathloss of a transmit IoT node as its fingerprint to implement a binary hypothesis test for transmit node identification. To this end, we also provide the closed-form expressions for the probabilities of false alarm, missed detection, and miss-classification. Finally, we present detailed simulation results that indicate the following: i) the coverage probability (and hence blockchain transaction success rate) improves as the jammers' locations move away from the IoT network, ii) the three error probabilities decrease (i.e., chances of corruption of the blockchain ledger data due to false data injection by malicious node decrease) as a function of the quality of the link between the transmit and receive IoT node.

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The Block Propagation in Blockchain-Based Vehicular Networks

Cited by 17 publications

References 35 publications

Toward Network Slicing Enabled Edge Computing: A Cloud-Native Approach for Slice Mobility

Toward Network Slicing Enabled Edge Computing: A Cloud-Native Approach for Slice Mobility

A Robust Sharding-Enabled Blockchain with Efficient Hashgraph Mechanism for MANETs

Countering Active Attacks on RAFT-Based IoT Blockchain Networks

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