Smart Contracts cannot get external data directly due to the closure and determinacy of blockchain itself, limiting the extensibility of blockchain applications. Oracle is proposed to serve as a data feed to offer aut...
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ISBN:
(纸本)9781665434799
Smart Contracts cannot get external data directly due to the closure and determinacy of blockchain itself, limiting the extensibility of blockchain applications. Oracle is proposed to serve as a data feed to offer authenticated and deterministic external data to smart contracts. However, existing centralized oracles are efficient but vulnerable to targeted attacks and suffering from a single point of failure, while existing decentralized oracles are inefficient. the paper presents a trusted blockchain oracle based on a decentralized Trusted Execution Environment (TEE) network called Tora, which embraces both efficiency and availability. the key of Tora is a hybrid consensus mechanism withthe confidential available group selection based on Proof-of-Availability (PoA). We have implemented a prototype of Tora on Ethereum with Intel Software Guard eXtensions (SGX) and evaluated it with a data-fetch use case on different measurements, including gas costs, off-chain execution time, group selection results and throughput. the results show that Tora provides considerable efficiency and scalability.
Low-latency stream processing applications (SPA) distribute the event streams on parallel instances of the application9;s operators to avoid queuing. Each operator has a set of processing nodes for its *** and fog ...
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ISBN:
(纸本)9781665439022
Low-latency stream processing applications (SPA) distribute the event streams on parallel instances of the application's operators to avoid queuing. Each operator has a set of processing nodes for its *** and fog infrastructures promise, among other things, low communication latency and are thus of interest for low-latency SPAs. Yet, they include heterogeneous, even volatile nodes which makes the parallel processing of SPAs challengingAvailable solutions for parallel SPAs often assume homogeneity and stable ***, we aim to balance the stream processing among heterogeneous, instable infrastructures using a decentralized control mechanism. We propose a decentralized, dynamic, and lightweight approach to re-balance SPA-load according to the nodes current performance, while minimizing latencies. In doing so, we introduce the Coda-EFC framework for window-based stream processing on heterogeneous distributed infrastructures. It dynamically adapts its load balancing to node performance without computing quickly outdated schedules and aims for latency-optimal load balancing. We introduce two adaptive load balancing strategiesone tailored for heterogeneous, dynamic infrastructures, the other an adaptation of a state-of-the art approach.
In order to solve the problem of high memory usage and large GPU computation in the case of a single machine. In this paper, MobileNet and Pytorch deep learning framework and Flink big data computing framework are dee...
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ISBN:
(数字)9798350376548
ISBN:
(纸本)9798350376555
In order to solve the problem of high memory usage and large GPU computation in the case of a single machine. In this paper, MobileNet and Pytorch deep learning framework and Flink big data computing framework are deeply integrated through DepthWise Convolution technology, and a distributed deep learning model is designed and implemented. Firstly, Pytorch is used to quickly build a neural network to save memory, and then MobileNet is used to quickly improve the running speed of the neural network. Finally, Flink is used for parallelcomputing and cluster resource scheduling. the experimental comparison shows that the model not only effectively saves the memory occupation, but also greatly reduces the calculation amount of the convolute-onal layer of the neural network, and can maintain high prediction accuracy.
Fault tolerance of parallel and distributedapplications is one of the concerns that becomes topical for large computer clusters and large distributed systems. For a long time the common solution to this problem was c...
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Agent-based systems are inherently distributed and parallel by a distributed memory model, but agent-based simulation is often characterised by a shared memory model. this paper discusses the challenges of and solutio...
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ISBN:
(纸本)9789897585289
Agent-based systems are inherently distributed and parallel by a distributed memory model, but agent-based simulation is often characterised by a shared memory model. this paper discusses the challenges of and solution for large-scale distributed agent-based simulation using virtual machines. Simulation of large-scale multi-agent systems with more than 10000 agents on a single processor node requires high computational times that can be far beyond the constraints set by the users, e.g., in real-time capable simulations. parallel and distributed simulation involves the transformation of shared to a communication-based distributed memory model that can create a significant communication overhead. In this work, instead distributing an originally monolithic simulator with visualisation, a loosely coupled distributed agent process platform cluster network performing the agent processing for simulation is monitored by a visualisation and simulation control service. A typical use case of traffic simulation in smart city context is used for evaluation the performance of the proposed DSEJAMON architecture.
this study examines the numerous approaches to cybersecurity and cloud computing offered by various authors in the past. Coverage includes cloud computing intrusion detection and prevention systems, cloud forensics an...
this study examines the numerous approaches to cybersecurity and cloud computing offered by various authors in the past. Coverage includes cloud computing intrusion detection and prevention systems, cloud forensics and anti-forensics technologies, strategies for enhancing security and privacy in cloud environments, key management and cryptographic strategies, securing multi-cloud environments, cloud computing confidentiality, and distributed authentication and authorization schemes for big data sharing. these studies provide useful information on the most recent techniques used to safeguard private data, ensure cloud security, and improve cloud services. the study emphasizes the significance of robust security measures, data protection, and efficient administration strategies in a cloud environment that is constantly evolving. this study provides the foundation for future research and advancements on the topic of cloud security by contributing to a greater understanding of the sector's problems and solutions.
this study introduces substantial contributions to the field of Low-Rate Detection of Distribution Denial of Service (DDoS) Attacks, leveraging convolutional neural networks (CNNs) with an attention mechanism and inco...
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the paper describes the experience of building distributed web applications based on the interactive computingtechnologies of the Jupyter project. the new architecture of such applications is proposed, considering th...
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the 6th Workshop for Young Scientists in Computer Science & Software Engineering showcases cutting-edge research from emerging talents. this volume comprises diverse papers illuminating emerging technologies9; ...
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Among the limitations of current quantum machines, the qubits count represents one of the most critical challenges for porting reasonably large computational problems, such as those coming from real-world applications...
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