Aggregate computing is a macro-level approach for programming collective intelligence and self-organisation in distributedsystems. In this paradigm, system behaviour unfolds as a combination of a system-wide program,...
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ISBN:
(数字)9781665471374
ISBN:
(纸本)9781665471374
Aggregate computing is a macro-level approach for programming collective intelligence and self-organisation in distributedsystems. In this paradigm, system behaviour unfolds as a combination of a system-wide program, functionally manipulating distributed data structures called computational fields, and a distributed protocol where devices work at asynchronous rounds comprising sense-compute-interact steps. Interestingly, there exists a large amount of flexibility in how aggregate systems.could actually execute while preserving the desired functionality. The ideal place for making choices about execution is the aggregate computing platform (or middleware), which can be engineered with the goal of promoting efficiency and other non-functional goals. In this work, we explore the possibility of applying Reinforcement Learning at the platform level in order to optimise aspects of a collective computation while achieving coherent functional goals. This idea is substantiated through synthetic experiments of data propagation and collection, where we show how Q-Learning could reduce the power consumption of aggregate computations.
This study proposes an optimal scheduling model for distributed generation (DG) within smart microgrids, incorporating various distributed energy resources (DERs) such as photovoltaic panels, wind turbines, biomass ge...
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The proceedings contain 23 papers. The topics discussed include: location privacy protection method on mobile social mode;jointly events extraction for database alarm based on dynamic matching strategy and GCN;distrib...
ISBN:
(纸本)9798350343755
The proceedings contain 23 papers. The topics discussed include: location privacy protection method on mobile social mode;jointly events extraction for database alarm based on dynamic matching strategy and GCN;distributed PV sharing service mechanism for park based on the concept of sharing economy;distributed energy sharing service mechanism for prosumers in the IoT-enable integrated energy park;research on big data intelligent analysis method and key technologies for the management of main equipment in power grid transmission and transformation based on digital twin technology;study on the medium fusion data storage technology for high performance airborne sensors;and lightweight design with variable density honeycomb structures for mission-critical embedded devices.
Using massive multi-input multi-output (massive MIMO) techniques in the modern wireless transmission links offers highest performance and best spectral efficiency among all the recent techniques. On the other hand, on...
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We introduce TNIC, a trusted NIC architecture for building trustworthy distributedsystems.deployed in heterogeneous, untrusted (Byzantine) cloud environments. TNIC builds a minimal, formally verified, silicon root-of...
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ISBN:
(纸本)9798400710797
We introduce TNIC, a trusted NIC architecture for building trustworthy distributedsystems.deployed in heterogeneous, untrusted (Byzantine) cloud environments. TNIC builds a minimal, formally verified, silicon root-of-trust at the network interface level. We strive for three primary design goals: (1) a host CPU-agnostic unified security architecture by providing trustworthy network-level isolation;(2) a minimalistic and verifiable TCB based on a silicon root-of-trust by providing two core properties of transferable authentication and non-equivocation;and (3) a hardware-accelerated trustworthy network stack leveraging SmartNICs. Based on the TNIC architecture and associated network stack, we present a generic set of programming APIs and a recipe for building high-performance, trustworthy, distributedsystems.for Byzantine settings. We formally verify the safety and security properties of our TNIC while demonstrating its use by building four trustworthy distributedsystems. Our evaluation of TNIC shows up to 6x performance improvement compared to CPU-centric TEE systems.
This study developed and implemented a machine learning-driven HR system designed to enhance recruitment outcomes, particularly in online interviews. Challenges such as candidate impersonation, interview question memo...
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Multi-Robot Multi-Target Tracking (MR-MTT) addresses the problem that a swarm of mobile robots actively detect and move to maintain surveillance of a team of dynamic targets, which is a fundamental problem in the mode...
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The proceedings contain 34 papers. The topics discussed include: fake and untrue news dataset (FUND): an expanded dataset for fake news classification;blind remote sensing images quality estimation and denoising;desig...
ISBN:
(纸本)9798350313666
The proceedings contain 34 papers. The topics discussed include: fake and untrue news dataset (FUND): an expanded dataset for fake news classification;blind remote sensing images quality estimation and denoising;design of a small Beidou rdSS shaped circular polarization dual frequency transceiver antenna;big data analytics for literary translation: a case study on female images in 'Moment in Peking';improving YOLOv5n for lightweight ship target detection;DPS-CR: a task scheduling algorithm based on computation reuse in vehicular edge computing;a model parameter update strategy for enhanced asynchronous federated learning algorithm;research on error handling techniques for speech interaction;an anonymous user discovery algorithm based on the naive bayes algorithm;user frustration: shaping the experience of automotive and computing;and GoatWatch: towards the development of a goat GrowthTracking – Internet of Things technology in an e-commerce platform.
Blockchain technology's decentralized and immutable data storage has changed a number of sectors. But typical blockchain networks scalability issues prevent them from being widely used for large-scale applications...
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The proceedings contain 114 papers. The topics discussed include: multi-attribute featured layout generation for graphic design using capsule networks;combining CNNs and Bi-LSTMs for enhanced network intrusion detecti...
ISBN:
(纸本)9798350321487
The proceedings contain 114 papers. The topics discussed include: multi-attribute featured layout generation for graphic design using capsule networks;combining CNNs and Bi-LSTMs for enhanced network intrusion detection: a deep learning approach;IoT-based monitoring of refrigerated vaccine storage: a literature review and a proposed solution;review the recent IoT systems.for healthcare applications;combining data mining with rigorous whole-genome phylogenetics enables detailed comparative genomics from over 2.3 million genomes across Coronaviridae;fake news detection using cellular automata based deep learning;a new approach to sentiment analysis on twitter data with LSTM;action localization and recognition through unsupervised I3D and TSN;and improving prospective healthcare outcomes by leveraging open data and explainable AI.
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