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Scientific ensemble workflows are commonly executed in Infrastructure-as-a-Service clouds for high-performance computing. The dynamic pricing of spot instances offers a cost-effective way for users to rent cloud resources. However, these instances ...

Federated learning, a promising distributed machine learning paradigm, has been used in various Internet of Things (IoT) environments to solve isolated data island issues and protect data privacy. However, since the central server in federated ...

• We are securing federated learning conducted in IOT through reputation and reverse auction mechanisms.
• Address the problem of federated learning in the presence of malicious workers launching attacks.
• Critical analysis of the model ...

Federated learning is a promising approach in the Internet of Things (IoT) that enables collaborative and distributed machine learning among massive IoT devices without sharing private data, thereby constructing smart IoT applications. However, ...

Along with the spurt of blockchain technology, the problem of blockchain’s closedness is getting more attention, leading to cross-chain technology. Cross-chain technology solves the problem that blockchains cannot be interconnected and opens up ...

Blockchain technology is becoming increasingly mature and has a great deal of research in a variety of industries. Because of its characteristics such as unalterable, decentralized and unforgeable, it has become a general trend that blockchain ...

In recent years, with the popularization and widespread use of mobile smart devices, Crowdsensing has gradually become one of the current research hotspots. The incentive mechanism is an important issue in the research of Crowdsensing. The ...

With the proliferation of intelligent services and applications authorized by artificial intelligence, the Internet of Things has penetrated into many aspects of our daily lives, and the medical field is no exception. The medical Internet of Things (MIoT) ...

An important challenge facing cloud computing is how to correctly and effectively handle and serve millions of users’ requests. Efficient task scheduling in cloud computing can intuitively affect the resource configuration and operating cost of the entire ...

A fragile audio watermarking scheme for content authentication was proposed in the paper. First, two proper positive integers are chosen. Then, the audio signal is segmented. Two moving averages are computed according to the chosen integers in ...

Clustering analysis has been widely used in pattern recognition and image processing in recent years, which is an important research field of data mining. Data publishing in social networks is threatened by the leakage of private information ...

This paper proposes a C-RNN forecasting method for Forex time series data based on deep-Recurrent Neural Network (RNN) and deep Convolutional Neural Network (CNN), which can further improve the prediction accuracy of deep learning algorithm for ...

Applying the proliferated location-based services (LBSs) to social networks has spawned mobile social network (MSN) services that allow users to discover potential friends around them. While enjoying the convenience of MSN services, the mobile users ...

We propose a new multipurpose audio watermarking scheme in which two watermarks are used. For intellectual property protection, audio clip is divided into frames and robust watermark is embedded. At the same time, the feature of each frame is extracted, ...

This paper describes a new Multi-Agent architecture and a task allocation protocol proposed inter-agent cooperation in a multi-agent system. The negotiation protocol is Con- tract Net Protocol (CNP). The broadcast of the Task An- nouncement on CNP tends ...