the proceedings contain 53 papers. the topics discussed include: odd-even hash algorithm: a improvement of cuckoo hash algorithm;a novel container workload prediction method based on automatic classification and atten...
ISBN:
(纸本)9781665407458
the proceedings contain 53 papers. the topics discussed include: odd-even hash algorithm: a improvement of cuckoo hash algorithm;a novel container workload prediction method based on automatic classification and attention-based LSTM;solving virtual network mapping fast by combining neural network and MCTS;efficient mining of regional semantic patterns from semantic trajectories on cloud computing;a distributed and parallel tensor hierarchical tucker decomposition on clouds;flow characteristics estimation based on multilayer virtual active counter sharing in data center network;tailor : datacenter load balancing for accelerating distributed deep learning;DWUPP: dynamic weight update through pipelined parallel for distributed training model;KSTA: a strategy for scheduling data-intensive workflows onto cloud computing resources;and a spatial-temporal information based traffic-flow detection method for video surveillance.
Scalability and management cost in cloud computing are few of the top challenges for the cloud providers and large enterprises. In this paper, we present Arktos, a cloud infrastructure platform for managing large-scal...
详细信息
ISBN:
(纸本)9781665460873
Scalability and management cost in cloud computing are few of the top challenges for the cloud providers and large enterprises. In this paper, we present Arktos, a cloud infrastructure platform for managing large-scale compute clusters and running millions of application instances as containers and/or virtual machines (VM). Arktos is envisioned as a stepping-stone from current "single-region" focused cloud infrastructure towards next generation distributed infrastructure in the public and/or private cloud environments. We present details related to the Arktos system architecture and features, important design decisions, and the results and analysis of the performance benchmark testing. Arktos achieves high scalability by partitioning its architecture into two independent components, the resource partition (RP) and the tenant workload partition (TP), with each component scaling independently. Our performance testing using a benchmark tool demonstrates that Arktos with just two RPs and two TPs system setting can already manage a cluster of 50K compute nodes and is able to run 1.5 million workload containers with 5 times system throughput (QPS)1 compared with an existing container management system. three key characteristics differentiate Arktos from other open source cloud platforms such as OpenStack and Kubernetes. Firstly, Arktos architecture is a truly scalable architecture that supports a very large cluster by scaling to more RPs and TPs in the system, Secondly, it unifies the runtime infrastructure to run and manage both VM and container applications natively, therefore eliminating the cost of managing separate technology stacks for VMs and containers. Lastly, Arktos has a unique "virtual cluster" style multi-tenancy design that provides both strong tenancy isolation, including network isolation and transparent resource view.
Graph neural networks (GNNs) are a powerful tool to predict the categories of IoT nodes for providing diverse high-quality services in the social Internet of things (SIoT). Intuitively, SIoT could be divided into seve...
详细信息
SVM is one of the popular methods to solve One-Class classification problem. However, it is time and space-consuming. this fact makes it hard or even impossible to apply SVM for large training sets. In this paper we p...
详细信息
MQTT (Message Queuing Telemetry Transport) has become the perfect messaging protocol for IoT (Internet of things) systems since it is the lightest protocol designed for low bandwidth, high-latency, unreliable networks...
详细信息
this paper presents a decentralized Deep Reinforcement Learning (DRL)-based dynamic channel bonding (DCB) algorithm (i.e., drlDCB) for Wi-Fi networks. Most existing RL-based channel bonding algorithms either are centr...
详细信息
the continuous demand for higher computational performance and the stagnating developments in the general purpose processor landscape have led to a surge in interest for highly specialized and efficient hardware. Comb...
详细信息
ISBN:
(纸本)9783031488023;9783031488030
the continuous demand for higher computational performance and the stagnating developments in the general purpose processor landscape have led to a surge in interest for highly specialized and efficient hardware. Combined withthe rising popularity of parameterizable hardware, a new opportunity to optimize these architectures for particular workloads arises, largely driven by the RISC-V Instruction Set Architecture (ISA). this work present an application-specific optimization methodology for general purpose processors, enabling the development of architectures which are faster and more efficient for their designated workloads. Driven by the Cache-Aware Roofline Model (CARM) insights, the methodology guides the configuration of the memory and computational subsystems of the processor. We apply this methodology to two applications, demonstrating up to a 2.67x performance increase and a 1.34x improvement to energy efficiency.
the development and usage of drones and LiDARs have become common in forestry, archaeology, surveillance, and intruders in recent years. Even though both domains reached a very mature state, the usage, integration of ...
详细信息
Federated Learning (FL) is vulnerable to backdoor attacks through data poisoning if the data is not scrutinized, as malicious participants can inject backdoor triggers in normal samples, leading to poisoned updates. D...
详细信息
Graphics Processing Units (GPUs) are widely used as powerful hardware accelerators for data-intensive tasks. However, their efficacy can be hindered by constraints in device memory and data transfer speeds via the PCI...
详细信息
暂无评论