Related papers: Blockchain-Driven Federation for Distributed Edge …
As an important technology to ensure data security, consistency, traceability, etc., blockchain has been increasingly used in Internet of Things (IoT) applications. The integration of blockchain and edge computing can further improve the…
Mobile Edge Computing (MEC), which incorporates the Cloud, edge nodes and end devices, has shown great potential in bringing data processing closer to the data sources. Meanwhile, Federated learning (FL) has emerged as a promising…
Blockchain has been promoted as a remedy for coordination in fragmented, multi-stakeholder ecosystems, yet many projects stall at pilot stage. Using a design-science approach, we develop the Hybrid Cooperative (HC), a digitally native…
With the rapid growth of Internet of Things (IoT) applications, there's a big demand for more processing power and resources in devices. Mobile Edge Computing (MEC) looks promising for enhancing performance and reducing costs by offloading…
While centralized servers pose a risk of being a single point of failure, decentralized approaches like blockchain offer a compelling solution by implementing a consensus mechanism among multiple entities. Merging distributed computing with…
Federated learning is a new approach to distributed machine learning that offers potential advantages such as reducing communication requirements and distributing the costs of training algorithms. Therefore, it could hold great promise in…
The recurrent neural network has been greatly developed for effectively solving time-varying problems corresponding to complex environments. However, limited by the way of centralized processing, the model performance is greatly affected by…
The number of internet-connected devices has been exponentially growing with the massive volume of heterogeneous data generated from various devices, resulting in a highly intertwined cyber-physical system. Currently, the Edge Intelligence…
Many studies have been done to improve the performance of centrally controlled business processes and enhance the integration between different parties of these collaborations. However, the most serious issues of collaborative business…
Efficient Vehicle-to-Everything enabling cooperation and enhanced decision-making for autonomous vehicles is essential for optimized and safe traffic. Real-time decision-making based on vehicle sensor data, other traffic data, and…
With the advent of blockchain technology, some management tasks of IoT networks can be moved from central systems to distributed validation authorities. Cloud-centric blockchain implementations for IoT have shown satisfactory performance.…
Many researchers have proposed replacing the aggregation server in federated learning with a blockchain system to improve privacy, robustness, and scalability. In this approach, clients would upload their updated models to the blockchain…
The state-of-the-art mobile edge applications are generating intense traffic and posing rigorous latency requirements to service providers. While resource sharing across multiple service providers can be a way to maximize the utilization of…
Mobile edge computing (MEC) is a promising technology that enhances the efficiency of mobile blockchain networks, by enabling miners, often acted by mobile users (MUs) with limited computing resources, to offload resource-intensive mining…
Decentralized Ledger Technology, popularized by the Bitcoin network, aims to keep track of a ledger of valid transactions between agents of a virtual economy without a central institution for coordination. In order to keep track of a…
The needs of emerging applications, such as augmented and virtual reality, federated machine learning, and autonomous driving, have motivated edge computing--the push of computation capabilities to the edge. Various edge computing…
Owing to the large volume of sensed data from the enormous number of IoT devices in operation today, centralized machine learning algorithms operating on such data incur an unbearable training time, and thus cannot satisfy the requirements…
Federated Identity Management has proven its worth by offering economic benefits and convenience to Service Providers and users alike. In such federations, the Identity Provider (IdP) is the solitary entity responsible for managing user…
Edge computing has emerged as a distributed computing paradigm to overcome practical scalability limits of cloud computing. The main principle of edge computing is to leverage on computational resources outside of the cloud for performing…
Federated Learning (FL) is a privacy-preserving distributed machine learning scheme, where each participant data remains on the participating devices and only the local model generated utilizing the local computational power is transmitted…