Mashup is an information system development project based on Web services. It can build new business processes by mixing data, resources and APIs from different sites or applications, and meet new user needs. However,...
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Smart contracts play a vital role in blockchain applications, supporting an expanding array of services as the number of blockchains rises. As service requirements become increasingly complex, the need for access and ...
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Mobile Edge computing (MEC) offers computational services near data sources to meet numerous real-time data processing demands of end devices. Scheduling dependent tasks in resource-constrained environments is a key r...
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ISBN:
(数字)9798350368369
ISBN:
(纸本)9798350368376
Mobile Edge computing (MEC) offers computational services near data sources to meet numerous real-time data processing demands of end devices. Scheduling dependent tasks in resource-constrained environments is a key research focus in MEC, aimed at enhancing the completion rates of applications within their deadlines. However, most existing works overlook the resource competition among requests arriving at different times, leading to decreased application completion rates. In this paper, we propose a dependent task online scheduling approach for multiple applications to optimize application completion rates. For multiple applications with deadline constraints, where tasks within each application may have dependencies, we propose a multi-priority task sequencing algorithm to determine the execution order of tasks. To accommodate scenarios where requests arrive at different times, we introduce a priority-based queue to dynamically adjust task execution order based on urgency and resource demands. Finally, by comparing with baseline approaches, experimental results demonstrate that our approach can improve the application completion rate by approximately 41.02%, demonstrating its effectiveness.
Nowadays, the integration of blockchain and MANET improves both MANET security and blockchain scalability. Hashgraph can better support the MANET-based blockchain by its inherent features, i.e., gossip about gossip, B...
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Blockchain is a peer-to-peer network system that stores chains of transaction data. Blockchain is decentralized and immutable. Once data is added to the chain, it cannot be modified or deleted. Smart contracts are int...
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The evaluation of outputs from large language models (LLMs) is an important part of LLMs’ born. A comprehensive evaluation for LLMs requires substantial human and material resources. This work proposes a crowdsourcin...
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Smart contracts play a vital role in blockchain applications, supporting an expanding array of services as the number of blockchains rises. As service requirements become increasingly complex, the need for access and ...
Smart contracts play a vital role in blockchain applications, supporting an expanding array of services as the number of blockchains rises. As service requirements become increasingly complex, the need for access and collaboration among multiple smart contracts becomes more prevalent. However, achieving access between smart contracts on different blockchains presents a significant challenge in the Internet of Blockchain scenario comprising numerous heterogeneous blockchains. In this paper, we first explore the problem of smart contract access in cross-heterogeneous blockchain scenarios. Then, an Oracle gateway-based cross-chain smart contract access architecture and a subscription-based cross-chain smart contract active access mechanism are proposed. Finally, a prototype is implemented to show that our architecture and mechanism can support cross-chain smart contract access for heterogeneous blockchains and reduce the complexity and latency of cross-chain smart contract access.
With the development of deep learning, especially driven by advanced models such as Graph Neural Networks (GNN), smart contract vulnerability detection is gradually moving toward automation and intelligence. Although ...
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ISBN:
(数字)9798331506209
ISBN:
(纸本)9798331506216
With the development of deep learning, especially driven by advanced models such as Graph Neural Networks (GNN), smart contract vulnerability detection is gradually moving toward automation and intelligence. Although existing deep learning detection methods have improved the efficiency of vulnerability detection to some extent, they fail to fully explore and utilize the rich syntactic and semantic information in smart contracts and generally suffer from insufficient feature extraction. In this paper, we propose a new method for smart contract vulnerability detection that combines a Multi-Information Contract Graph (MIG) with a Hierarchical Graph Feature Extraction model (HGFE). MIG integrates key information such as control flow, data flow, and vulnerability feature flow within smart contracts, fully mining and utilizing the rich syntactic and semantic features of smart contracts, providing the model with comprehensive feature representation. HGFE applies a multilayer feature extraction strategy, combining global and local feature extraction, and comprehensively considers multiple dimensions of information within the contract graph, thereby fully extracting the features of the contract graph. The experimental results demonstrate that our method significantly enhances the ability to detect potential vulnerabilities in smart contracts, achieving a maximum accuracy and precision of 97.29% and 97.70%, respectively, outperforming other advanced methods.
Electronic archives are electronic files with very high security requirements. We use block chain technology to implement a distributed PKI system. On this basis, we build an archives system ArchivesChain based on blo...
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In this paper, we present a garbage image classification framework to tackle the waste sorting problem which besets residents around the world every day. The proposed framework consists of two modules, a convolutional...
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