the proceedings contain 222 papers. the topics discussed include: DRL-deploy: adaptive service function chains deployment with deep reinforcement learning;accuracy vs. efficiency: achieving boththrough hardware-aware...
ISBN:
(纸本)9781665435741
the proceedings contain 222 papers. the topics discussed include: DRL-deploy: adaptive service function chains deployment with deep reinforcement learning;accuracy vs. efficiency: achieving boththrough hardware-aware quantization and reconfigurable architecture with mixed precision;cmss: collaborative modeling of safety and security requirements for network protocols;FGPA: fine-grained pipelined acceleration for depthwise separable CNN in resource constraint scenarios;Dyacon: JointCloud dynamic access control model of data security based on verifiable credentials;understanding the runtime overheads of deep learning inference on edge devices;and alleviating imbalance in synchronous distributed training of deep neural networks.
the proceedings contain 161 papers. the topics discussed include: deep learning for phishing detection;a partition matching method for optimal attack path analysis;an energy and robustness adjustable optimization meth...
ISBN:
(纸本)9781728111414
the proceedings contain 161 papers. the topics discussed include: deep learning for phishing detection;a partition matching method for optimal attack path analysis;an energy and robustness adjustable optimization method of file distribution services;deriving the political affinity of twitter users from their followers;on the usability of big (social) data;re-running large-scale parallel programs using two nodes;predicting hacker adoption on darkweb forums using sequential rule mining;an on-the-fly scheduling strategy for distributed stream processing platform;deadlock-free adaptive routing based on the repetitive turn model for 3D network-on-chip;and radix: enabling high-throughput georeferencing for phenotype monitoring over voluminous observational data.
In recent years, edge computing has emerged as a promising solution in the field of network computing. this architecture ensures the availability of distributedcomputing resources located closer to end-users and IoT ...
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ISBN:
(纸本)9798350377873;9798350377866
In recent years, edge computing has emerged as a promising solution in the field of network computing. this architecture ensures the availability of distributedcomputing resources located closer to end-users and IoT devices. However, resource scheduling remains a significant challenge in edge computing, requiring effective strategies to optimize resource utilization and ensure efficient task allocation. In this paper, we propose two hybrid approaches that combine the NawazEnscore-Ham (NEH) algorithm with local search and Greedy Random Adaptive Search Procedure (GRASP) algorithm with local search for modeling and solving data traffic in distributed edge computing environments (DPSDEC). through extensive evaluations, we consistently observe that the NEH algorithm outperforms GRASP, delivering minimized makespan and generating efficient schedules. Moreover, the NEH algorithm performs very well in less complex situations and maintains this advantage even in larger and more complex problems.
the proceedings contain 80 papers. the topics discussed include: back-imaging scheme in RF-powered passive camera system;proactive attack detection at the edge through an ensemble deep learning model;a secure federate...
ISBN:
(纸本)9781665466677
the proceedings contain 80 papers. the topics discussed include: back-imaging scheme in RF-powered passive camera system;proactive attack detection at the edge through an ensemble deep learning model;a secure federated learning mechanism for data privacy protection;OFDM signal design based on electrode-based through-the-earth communication;spiking mean field multi-agent reinforcement learning for dynamic resources allocation in D2D networks;joint optimization of latency and reward for offloading dependent tasks in mobile edge computing;energy-efficient power control and resource allocation based on deep reinforcement learning for d2d communications in cellular networks;a fuzzy Bayesian network based on fault tree for vaccine safety risks analysis;a reinforcement learning-based task classification mechanism for privacy-enhanced mobile crowdsensing strategy;a mobile crowd sensing ecosystem based on fog computing infrastructure;preserving privacy for edge weights in communication networks;and design and implementation of anti-wireless electricity rubbing system.
the primary goal of the economic dispatch (ED) is to organize the generation schedule to fulfill system energy demand at the lowest possible operational cost while meeting all other requirements, including system secu...
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Software Defined Systems (SDS) abstract the actual hardware at different layers with software components, layers such as networking, Storage, Security, Servers, Data Centers, Clouds etc. this abstraction facilitates c...
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this paper proposes an elderly fall detection system based on distributed edge computing and machine learning. the system can identify individual fall events from multiple camera sources and trigger real-time alerts, ...
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ISBN:
(纸本)9798350386851;9798350386844
this paper proposes an elderly fall detection system based on distributed edge computing and machine learning. the system can identify individual fall events from multiple camera sources and trigger real-time alerts, achieving 97% accuracy experimentally.
Volunteer computing (VC) is a type of network computing which exploits idle computing resources provided by vast amount of users on the Internet. In our previous work, we have implemented a prototype system of paralle...
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ISBN:
(纸本)9798350386851;9798350386844
Volunteer computing (VC) is a type of network computing which exploits idle computing resources provided by vast amount of users on the Internet. In our previous work, we have implemented a prototype system of parallel VC withthe approach of server assisted communication and demonstrated the feasibility of parallel computing on a VC environment, not distributedcomputing as in the current VC. In this paper, we evaluate the effectiveness of parallel VC. the nature of nodes' volatility and unreliability in VC makes parallel computing not always effective. through the simulations using open trace data of nodes' behavior, we reveal parallelism and redundancy of job execution which minimize execution time while maintaining high degree of reliability.
the techniques of request duplication and request reissue are used to reduce tail latency in distributed systems by sending redundant read requests to multiple replicas. However, these strategies can fail if the dupli...
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the proceedings contain 35 papers. the topics discussed include: explainable deep learning for cyber-attack detection in electric vehicle charging stations;a confidentiality-preserving distributed linear programming m...
ISBN:
(纸本)9798400711589
the proceedings contain 35 papers. the topics discussed include: explainable deep learning for cyber-attack detection in electric vehicle charging stations;a confidentiality-preserving distributed linear programming model for solving large-scale economic dispatch problems;benchmarking fully homomorphic encryption libraries in IoT devices;assessing ChatGPT’s code generation capabilities with short vs long context programming problems;enhancing sleep disorder diagnosis with a machine learning approach using ensemble neural networks: sleep disorder diagnosis with ensemble neural networks;enhancing EmoBot: an in-depth analysis of user expectation and satisfaction in an emotion-aware chatbot;and knowledge distillation and weight pruning for two-step compression of ConvNets in rice leaf disease classification.
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