The proceedings contain 80 papers. The topics discussed include: randomized protocols for resilient peer-to-peer networks;evaluating the performance of 5G NR in indoor environments: an experimental study;an approach t...
The proceedings contain 80 papers. The topics discussed include: randomized protocols for resilient peer-to-peer networks;evaluating the performance of 5G NR in indoor environments: an experimental study;an approach towards reducing training time of the input doubling method via clustering for middle-sized data analysis;analysis of legislative framework governing biometric data;designing a testbed for privacy-preserving voice-based social networks;classical machine learning and large models for text-based emotion recognition;one hop routing optimization approach using machine learning;toward an enhanced stock market forecasting with machine learning and deep learning models;smart agriculture system based on IoT reference architecture and service choreography;and privacy-preserving crime reporting and rewarding in the presence of active insider and outsider adversaries.
The proceedings contain 10 papers. The special focus in this conference is on Distributed Applications and Interoperable systems. The topics include: Simulation of Large Scale Computational Ecosystems with Alchemist: ...
ISBN:
(纸本)9783030781972
The proceedings contain 10 papers. The special focus in this conference is on Distributed Applications and Interoperable systems. The topics include: Simulation of Large Scale Computational Ecosystems with Alchemist: A Tutorial;network Federation for Inter-cloud Operations;specK: Composition of stream Processing Applications over Fog Environments;ASPAS: As Secure as Possible Available systems;portable Intermediate Representation for Efficient Big Data Analytics;shared-Dining: Broadcasting Secret Shares Using Dining-Cryptographers Groups;UCBFed: Using Reinforcement Learning Method to Tackle the Federated Optimization Problem;keVlar-Tz: A Secure Cache for Arm TrustZone: (Practical Experience Report);analysis and Improvement of Heterogeneous Hardware Support in Docker Images.
The proceedings contain 95 papers. The topics discussed include: high-degree noise addition method for the k-degree anonymization algorithm;an algorithm for the automatic precisiation of the meaning of adjectives;stoc...
ISBN:
(纸本)9781728197326
The proceedings contain 95 papers. The topics discussed include: high-degree noise addition method for the k-degree anonymization algorithm;an algorithm for the automatic precisiation of the meaning of adjectives;stochastic unit commitment problem in electricity market;a 3D-CNN classifier for gender discrimination from diffusion tensor imaging of human brain;salient feature extraction in Japanese metaphor generation;acceptability of a decision maker to handle multi-objective optimization on design space;effect of humanoid robot’s reaction on human touch to robot;parametric genetic programming;simultaneous visualization of documents, words and topics by tensor self-organizing map and non-negative matrix factorization;a verification of visualization ability of onomatopoeia thesaurus map for sound-symbolism on Japanese vowels;column-based decoder of internal prediction representation in cortical learning algorithms;and model construction based on variable selection of indicators and alternative data in market forecasting.
The proceedings contain 156 papers. The topics discussed include: integrating machine learning and social sensing in smart city digital twin for citizen feedback;a novel fuzzy identity-based encryption with wireless P...
ISBN:
(纸本)9798350330014
The proceedings contain 156 papers. The topics discussed include: integrating machine learning and social sensing in smart city digital twin for citizen feedback;a novel fuzzy identity-based encryption with wireless PUF for IoT device authentication;RDA-Unet: a retrieval model for radar composite reflectivity factor from Himawari-8 observations;DHIFS: a dynamic and hybrid index method with low memory overhead and efficient file access;multi-agent reinforcement learning for smart city automated traffic light control;st-ConvLSGRU: a radar echo extrapolation method based on LstM and GRU;intelligent maintenance system for wind turbine based on deep belief federated learning;BioNet+: a comprehensive interaction model of finding therapeutics for diseases with graph deep learning;and PBE-Plan: periodic backdoor erasing plan for trustworthy federated learning.
The proceedings contain 386 papers. The topics discussed include: joint distortion estimation and layer selection of unequal error protection for SVC video transmission over FSO networks;research of distributed comput...
ISBN:
(纸本)9781728120584
The proceedings contain 386 papers. The topics discussed include: joint distortion estimation and layer selection of unequal error protection for SVC video transmission over FSO networks;research of distributed computing framework for foreign exchange market monitoring;fusing syntax and word embedding knowledge for measuring semantic similarity;performance modeling and optimization of controller cluster deployments in software-defined WAN;a spam review detection method by verifying consistency among multiple review sites;real-time depth estimation with an optimized encoder-decoder architecture on embedded devices;energy distribution in EV energy network under energy shortage;SLAs-aware online task scheduling based on deep reinforcement learning method in cloud environment;and maximizing revenue with adaptive modulation and multiple FEC in flexible optical networks.
As edge computing continues to play a pivotal role in modern computingarchitectures, ensuring robust cybersecurity becomes imperative. This paper introduces our emerging results on a comprehensive approach to bolster...
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ISBN:
(纸本)9798350366266;9798350366259
As edge computing continues to play a pivotal role in modern computingarchitectures, ensuring robust cybersecurity becomes imperative. This paper introduces our emerging results on a comprehensive approach to bolster the cyber-resilience of edge computingsystems by incorporating the MAPE-K (Monitor, Analyze, Plan, Execute, and Knowledge) loop. The proposed methodology involves the application of the MAPE-K loop at different levels of an edge computingarchitecture, aiming to create a holistic defense mechanism against cyber attacks. We present a prototype of our framework and assess its viability and efficacy by leveraging real-world edge devices deployed in an industrial production setting. Initial evidence from our results suggests that this novel approach leads us to reconsider how we construct more resilient edge computingarchitectures.
Increasing rate of progress in hardware and artificial intelligence (AI) solutions is enabling a range of software systems to be deployed closer to their users, increasing application of edge software system paradigms...
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ISBN:
(纸本)9798350366266;9798350366259
Increasing rate of progress in hardware and artificial intelligence (AI) solutions is enabling a range of software systems to be deployed closer to their users, increasing application of edge software system paradigms. Edge systems support scenarios in which computation is placed closer to where data is generated and needed, and provide benefits such as reduced latency, bandwidth optimization, and higher resiliency and availability. Users who operate in highly-uncertain and resource-constrained environments, such as first responders, law enforcement, and soldiers, can greatly benefit from edge systems to support timelier decision making. Unfortunately, understanding how different architecture approaches for edge systems impact priority quality concerns is largely neglected by industry and research, yet crucial for national and local safety, optimal resource utilization, and timely decision making. Much of industry is focused on the hardware and networking aspects of edge systems, with very little attention to the software that enables edge capabilities. This paper presents our work to fill this gap, defining a reference architecture for edge systems in highly-uncertain environments, and showing examples of how it has been implemented in practice.
The paper presents a new idea of software architecture inspired by the processing mechanism of the human brain. stimulated by the working of the human brain, we propose an adaptive neural network software architecture...
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ISBN:
(纸本)9798350366266;9798350366259
The paper presents a new idea of software architecture inspired by the processing mechanism of the human brain. stimulated by the working of the human brain, we propose an adaptive neural network software architecture that integrates the principles of neuroevolution for adjusting activation functions and an adaptive mechanism for selecting varying numbers of hidden layers to dynamically adjust the structure, functions, and parameters of the neural network. Utilizing genetic algorithms like crossover and mutation strengthens the architecture to optimize its components to adapt in situations like varying data distribution and learning objectives. We conducted an initial experiment on two benchmark image datasets (MNIst and CIFAR-10) and compared the performance for classification, clustering, and reinforcement learning tasks. We found that applying the proposed architecture with a neural network produces 51% better results. We also found that the results are comparable and better for clustering and reinforcement tasks on both datasets. The article concludes that the proposed architecture improves the performance of these machine-learning tasks over classical techniques and can offer a framework for developing robust and adaptable neural network systems.
Modern software systems in every application domain are increasingly built as distributed systems. Business applications are structured as cooperating microservices, IoT devices communicate with cloud-based services o...
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ISBN:
(纸本)9798350366266;9798350366259
Modern software systems in every application domain are increasingly built as distributed systems. Business applications are structured as cooperating microservices, IoT devices communicate with cloud-based services over a network, and Web sites store data in globally dispersed data centers to support fast access in to localities in which their users reside. Behind all these systems lurk distributed computing infrastructures that architects and engineers must exploit to satisfy application service level agreements. To be successful, it is essential that architects understand the inherent complexity of distributed systems. In this half day tutorial, I'll guide the attendees through the fundamental characteristics that distributed systems exhibit. Each characteristic will be related to the software architecture quality attributes that they directly impact. The topics covered include communications reliability and latencies, message delivery semantics, state management, idempotence, data safety, consistency, time, distributed consensus, cascading failures and failover and recovery. I'll introduce each concept using an example distributed system and multiple 'props' to illustrate concepts. Once I've explained a concept using the example, I'll move on to show how the concept manifests itself in a software system and its effects on quality attributes requirements and inherent trade-offs. The tutorial will be suitable for graduate students, engineers and architects who have no or minimal exposure to distributed systems concepts. The presentation format will be suitable for a mix of both in person and remote participants. It will combine interactive sessions with short technical explanations and examples to illustrate each distributed systems concept.
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