Large Language Models such as ChatGPT have risen in prominence recently leading to the need to analyse their strengths and limitations on various tasks. the objective of this work is to evaluate the performance of Lar...
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the proceedings contain 2463 papers. the topics discussed include: DDoS attacks mitigation: a review of ai-based strategies and techniques;multiscale analysis of nonlinear time series using wavelet decomposition;advan...
ISBN:
(纸本)9798350370249
the proceedings contain 2463 papers. the topics discussed include: DDoS attacks mitigation: a review of ai-based strategies and techniques;multiscale analysis of nonlinear time series using wavelet decomposition;advanced low-power SRAM design techniques at 16nm node: combining multi-threshold voltage, MOSFET stacking, and body biasing;forecasting low energy data aggregation utilizing ARIMA models;federated split learning with HyperNetworks for medical image classification;machine vision for measurement accuracy in industrial automation;implementing linear modulation schemes with field programmable analog arrays;real-time attendance system with liveness detection and multi-face recognition using transfer learning;design of novel CPW fed high isolation quad-port MIMO antenna with dual-band resonance;and anomaly detection in video surveillance.
Withthe increasing penetration of renewable sources, distributed Energy Resources (DER) are emerging as a crucial components of modern power systems. In a distribution system integrated withdistributed Generation Sy...
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ISBN:
(纸本)9798350385939;9798350385922
Withthe increasing penetration of renewable sources, distributed Energy Resources (DER) are emerging as a crucial components of modern power systems. In a distribution system integrated withdistributed Generation systems (DG's), efficient power management is crucial to minimize energy losses and maximize effective utilization of electrical energy. the power losses in distribution system have been on higher side due to low X/R ratio and high AT&C losses. this paper presents the minimization of power losses in a radial distribution system integrated with DG's. the load flow analysis is carried out using Forward-Backward Sweep (FBS) method. the optimal power levels of DG's for power loss reduction are obtained by using Particle Swarm Optimization (PSO) algorithm. the proposed method is efficient on a standard IEEE 15 bus radial distribution system.
Cloud and Fog computing are complementary technologies used for complex Internet of things (IoT) based deployment of applications. With an increase in the number of internetconnected devices, the volume of data genera...
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ISBN:
(纸本)9781665477062
Cloud and Fog computing are complementary technologies used for complex Internet of things (IoT) based deployment of applications. With an increase in the number of internetconnected devices, the volume of data generated and processed at higher speeds has increased substantially. Serving a large amount of data and workloads for predictive decisions in real-time using fog computing without Service-Level Objective (SLO) violation is a challenge. Integration of multiple cloud services and platforms with fog computing can resolve this issue by providing additional resources. In this work, we present a general-purpose System for Inference Request Management (SIRM) aimed at automatically generating a suitable execution workflow to execute ML/DL inference requests using fog with Function-as-a-Service (FaaS) and Machine Learning-as-a-service (MLaaS) offered by cloud vendors. Generated workflow minimizes the cost of deployment as well as SLO violations. the use of SIRM results in less than 5% violations when tested using health domain and recommender system based applications.
the proceedings contain 53 papers. the topics discussed include: context-aware root cause localization in distributed traces using social network analysis;enhancing the performance of deep learning model based object ...
ISBN:
(纸本)9798400704451
the proceedings contain 53 papers. the topics discussed include: context-aware root cause localization in distributed traces using social network analysis;enhancing the performance of deep learning model based object detection using parallel processing;fair sharing of data in autotuning research;mastering computer vision inference frameworks;matrix network analyzer: a new decomposition algorithm for phase-type queueing networks;towards efficient diagnosis of performance bottlenecks in microservice-based applications;KubePlaybook: a repository of ansible playbooks for Kubernetes auto-remediation with LLMs;efficient unsupervised latency culprit ranking in distributed traces with GNN and critical path analysis;and network analysis of microservices: a case study on Alibaba production clusters.
the proceedings contain 22 papers. the topics discussed include: sampling in cloud benchmarking: a critical review and methodological guidelines;enhancing machine learning performance in dynamic cloud environments wit...
ISBN:
(纸本)9798331507589
the proceedings contain 22 papers. the topics discussed include: sampling in cloud benchmarking: a critical review and methodological guidelines;enhancing machine learning performance in dynamic cloud environments with auto-adaptive models;optimal distribution of ML models over edge for applications with high input frequency;Ataru: a lightweight VMM+Runtime for low latency serverless functions;blockchain-based framework for stock market operations: IPOs, trading, and dividend distribution;evaluating fine-tuned BERT-based language models for web API recommendation;enhancing security in EV charging systems: a hybrid detection and mitigation approach;and SW forecaster: an intelligent data-driven approach for water usage demand forecasting.
the growing popularity of data-intensive applications in cloud computing necessitates a cost-effective approach to harnessing distributed processing capabilities. However, the wide variety of instance types and config...
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Neural-enhanced video streaming (e.g., super-resolution) is an ongoing revolution which can provide extremely high-quality video streaming services breaking the restriction of bandwidth. However, such enhancements req...
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ISBN:
(纸本)9798400704123
Neural-enhanced video streaming (e.g., super-resolution) is an ongoing revolution which can provide extremely high-quality video streaming services breaking the restriction of bandwidth. However, such enhancements require intense computation power that is not affordable for a single mobile device, which hinders their real-world deployment. To address the limitation, we propose OASIS, the first system that facilitates multiple users in close proximity to execute intense neural-enhanced video streaming in realtime. To this end, OASIS intelligently distributes computation tasks among multiple mobile devices, selects appropriate video bitrates and super-resolution models, and optimizes video chunk delivery. As a result, the expensive neural-enhanced streaming is done through distributed collaboration, achieving optimal quality of experience (QoE). We implement and evaluate OASIS on commodity smartphones from different vendors, under various network and computation conditions. Extensive experiments demonstrate the high efficiency of OASIS: it improves the video streaming QoE by 40%-200% and reduces each participant's energy consumption by 60% when the system scales up from a single device to six devices.
Side computing is a rising technique used for connected networks' allotted and cooperative media algorithms. Part computing refers to processing operations being carried out near the source of the facts, generally...
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this paper examines the ability of advanced safety algorithms to permit at ease mobile computing. Using encryption in the transmission of information and application layer mechanisms are discussed with particular atte...
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