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检索条件"任意字段=IEEE International Conference on Service-Oriented Computing and Applications"

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Information Recapture Technique for service oriented computing 5

Information Recapture Technique for Service Oriented Computi...

引用

5th ieee international conference on computing, Power, and Communication Technologies, IC2PCT 2024

作者： Singh, Takveer Chitkara University Institute of Engineering and Technology Chitkara University Centre for Interdisciplinary Research in Business and Technology Punjab India

ISBN: (纸本)9798350383522

The cloud computing system, which operates via the Internet, provides large, scalable computer resources to users as a service. This technique has attracted significant attention from the scientific and corporate worlds alike. However, the notion of cloud computing lacks methods for knowledge discovery and information retrieval. Put differently, clouds need intelligence and autonomy. Web services are a crucial component of service oriented computing (SOC) in cloud computing environments. Within a cloud context, a single Web service cannot get specific and tailored information from other Web services. Web services may be successfully composed with the aid of agents. This project's primary objective is to offer a method of information extraction in a cloud environment using web services and the multi-agent system idea. © 2024 ieee.

关键词： Cloud computing information retrieval multi-agent systems web services

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The Impact of Directed Pod Eviction on Kubernetes Resource Utilization 17

The Impact of Directed Pod Eviction on Kubernetes Resource U...

引用

17th ieee international Congress on Intelligent and service-oriented Systems Engineering (CISOSE)

作者： Larsson, Oliver Klein, Cristian Elmroth, Erik Umea Univ Dept Comp Sci SE-90187 Umea Sweden

ISBN: (纸本)9798350322392

One of the promises of container orchestration technologies is that they enable effective utilization of hardware resources and thus reduce infrastructure costs. However, as applications scale up and down over time in a Kubernetes-managed environment, the cluster may enter a state of resource fragmentation. In such a state, the cluster's hardware cannot be used to its full potential because resources become locked by poor Pod to Node mappings. This paper shows that such problems are common as workload requirements approach a cluster's resource capacity. Additionally, we present an experimental analysis of directed Pod eviction as a technique to combat the issue of resource fragmentation. Our findings show that directed Pod eviction can reduce resource fragmentation and allow clusters to run a given workload using 16.7% fewer Nodes than is consistently possible using standard Kubernetes scheduling. These findings are unaffected by applying input shaking to the experimental analysis, strengthening confidence in the generality of these resource utilization improvements.

关键词： Cloud computing Kubernetes scheduling directed Pod eviction resource fragmentation resource utilization experimental evaluation Descheduler for Kubernetes

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Intent-based Management for the Distributed computing Continuum 17

Intent-based Management for the Distributed Computing Contin...

引用

17th ieee international Congress on Intelligent and service-oriented Systems Engineering (CISOSE)

作者： Morichetta, Andrea Spring, Nikolaus Raith, Philipp Dustdar, Schahram TU Wien Distributed Syst Grp Vienna Austria

ISBN: (纸本)9798350322392

Managing digital and connected systems has become increasingly challenging in the past decade due to their scale and complexity. A new perspective is required to manage these systems, considering the infrastructure and components from edge to cloud, i.e., in the distributed computing continuum. Serverless computing offers improved scalability and cost efficiency, but balancing and coordinating serverless systems remain complex. Intent-based systems, popular in networking, can provide a solution by translating stakeholder inputs into actions that meet service Level Objectives (SLOs). Their application in the computing continuum can be highly beneficial, but it has yet to be deeply explored. To bridge this gap, we propose a methodology for deploying an intent-based system for the computing continuum. We implement an architectural framework leveraging the serverless paradigm. Furthermore, we focus on defining and implementing the main components for translating the management requirements into actions executed by serverless functions inspired by a threelayer model. Through a Proof of Concept (PoC) deployed in Amazon's AWS cloud and detailed simulations, we showcase how such an approach can resolve conflicts in a complex system, i.e., balancing efficiency and availability. Our work aims to contribute to effectively managing the computing continuum and highlight the potential of intent-based systems in this domain. The experiments' results show our framework's ability to make appropriate scaling decisions, fulfilling both objectives.

关键词： computing continuum intents PoC serverless SLO

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service Localization and User Satisfaction Enabled Multi-Tier computing IoT System 44

Service Localization and User Satisfaction Enabled Multi-Tie...

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44th ieee international conference on Distributed computing Systems (ICDCS)

作者： Gong, Chenyu Ma, Mulei Zeng, Liekang Yang, Yang Wu, Liantao Liu, Zening HKUST Guangzhou IoT Thrust & Res Ctr Digital World Intelligent Th Guangzhou Peoples R China Peng Cheng Lab Shenzhen Peoples R China Terminus Grp Beijing Peoples R China East China Normal Univ Software Engn Inst Shanghai Peoples R China Purple Mt Labs Nanjing Peoples R China

ISBN: (纸本)9798350354720;9798350354713

The rapid expansion of the Internet of Things (IoT) poses challenges to certain applications, such as Digital Twin (DT). While data from user devices can be filtered by human intelligence, this is not feasible for IoT devices. Owing to the voluminous data generated by IoT devices that require transmission and computing, traditional cloud computing architectures may no longer guarantee the Quality of Experience (QoE), even causing network congestion. To address this issue, we propose a novel Cloud-Network-Edge-Terminal (CNET) model, which includes an intelligent edge layer for filtering IoT data. The computing paradigm shift indicates that the network will provide services at the edge rather than in the cloud, which is so-called service localization. To demonstrate the benefits of service localization, we use integrated user requirement descriptions to measure QoE, specifically the concepts of service Requirement Zone (SRZ) and User Satisfaction Ratio (USR). Additionally, we conduct extensive numerical simulations to evaluate the model's performance under varying Degrees of Localization (DoL). Our results show that service localization can significantly improve USR even in changing network conditions.

关键词： service Localization Multi-Tier computing IoT System QoE service Requirement Zone User Satisfaction Ratio Digital Twin

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Learning-based DApp Task Scheduling for Elastic Hybrid computing in Edge Web 3.0 59

Learning-based DApp Task Scheduling for Elastic Hybrid Compu...

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59th Annual ieee international conference on Communications (ieee ICC)

作者： Cai, Xichun Chen, Lixing Bai, Yang Lin, Xi Li, Gaolei Li, Jianhua Shanghai Jiao Tong Univ Sch Elect Informat & Elect Engn Shanghai Peoples R China

ISBN: (纸本)9781728190549

Web 3.0 and Edge computing are inherently compatible, making them an ideal combination for building a secure and efficient distributed service platform to support decentralized applications (DApps). This paper investigates an elastic hybrid computing architecture in Edge Web 3.0, allowing DApp tasks to be executed in a hybrid manner by integrating on-chain and off-chain execution. The principle is to transfer a portion of DApp to an off-chain execution environment, along with an appropriate result verification process, to enhance computing efficiency and reduce blockchain overhead. We formulate a DApp task scheduling problem that jointly optimizes the execution pattern and offloading decision of user tasks. A learning-based DApp task scheduling scheme is designed based on Proximal Policy Optimization (PPO) to minimize the gas cost and service delay of DApps. Particularly, we tailor PPO to handle the hard constraints of service delay, gas consumption, and computing capacity in Edge Web 3.0 by adding regularization terms in the learning objective function. We establish an Edge Web 3.0 testbed based on Goerli, ZkSync, and Ethereum to evaluate the proposed method. The experimental results show that our method outperforms state-of-the-art benchmarks.

关键词： Edge computing Web3.0 hybrid computing

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Proceedings - 17th ieee international conference on service-oriented System Engineering, SOSE 2023

Proceedings - 17th IEEE International Conference on Service-...

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17th ieee international conference on service-oriented System Engineering, SOSE 2023

ISBN: (纸本)9798350322392

The proceedings contain 32 papers. The topics discussed include: improving Medicare fraud detection through big data size reduction techniques;intelligent sampling: a novel approach to optimize workload scheduling in large-scale heterogeneous computing continuum;analyzing organizational structure of microservice projects based on contributor collaboration;cloud-native architectural characteristics and their impacts on software quality: a validation survey;a model-based approach to automotive feature development for updates and upgrades;formal models for the energy-aware cloud-edge computing continuum: analysis and challenges;benchmarks for end-to-end microservices testing;comparison of integration coverage criteria for serverless applications;Kubernetes-enabled detection and resolution of architectural smells for microservices;and a comparison of distributed tracing tools in serverless applications.

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A Game Theoretic Approach for Modeling Composite Network-Cloud service 3

A Game Theoretic Approach for Modeling Composite Network-Clo...

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3rd international conference on Sentiment Analysis and Deep Learning, ICSADL 2024

作者： Shiny, J John Velammal College of Engineering and Technology Department of Information Technology Madurai India

ISBN: (纸本)9798350396157

Traditional way of computing required only stand-alone systems and applications. As time passed on, the amount of computing raised such that form the distributed platform for system and applications. That paved the way for distributed computing. Nowadays we talk about grid and cloud. Cloud computing is a model of computing in which the IT resources required by the end users are provided without any disruption and they are contented. The benefit of using cloud computing is to offer requested services of customer without any delay or interruption. This could be achieved by having good network services. The network which forms the backbone of the connectivity can be virtualized so that it leads to a novel epoch of integrating cloud computing and networking resources using service oriented Architecture paradigm. This article describes about a review of different systems that support network virtualization. This study lists out the challenges that are faced while converging cloud and network services. This study also proposes a theoretical model which involves game theory, that helps in realizing this convergence thus laying a foundation for upcoming generation internet. The game theory involves Nash Equilibrium in finding the best Infrastructure provider and Network service Provider. Also, the best strategy among them is found for the user. Network calculus is extended to involve cloud service along with network services that helps in evaluating the composite service's performance. © 2024 ieee.

关键词： Game theory

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Development and Validation of a Proximity-based Wearable computing Testbed for Community-oriented Wearable Systems

Development and Validation of a Proximity-based Wearable Com...

引用

ieee international conference on Pervasive computing and Communications (PerCom)

作者： Li, Qimeng Mangione, Fabrizio Porreca, Francesco Gravina, Raffaele Fortino, Giancarlo Univ Calabria DIMES Arcavacata Di Rende Italy

ISBN: (纸本)9798350304367;9798350304374

In the rapidly evolving digital technology landscape, community-oriented wearable computing systems are emerging as a key tool for enhancing connectivity and interaction within communal spaces. This paper contributes to this burgeoning field by presenting the development and implementation of a proximity-based wearable computing testbed designed to forge stronger links within communities. The testbed exploits Ultra-Wideband (UWB) position sensors, 9-axis motion sensors, edge nodes, and a centralized server, forming a cohesive network that actively facilitates community interactions and engagements. By employing anchors and targets within the UWB sensors, the system achieves high precision in location and distance measurements, laying the groundwork for various proximity-based applications. Integrating 9-axis motion sensors and advanced edge nodes further underscores the system's versatility and robustness in wearable and edge computing. This paper delves into an in-depth exploration and evaluation of the proposed system's architecture, design, and implementation processes. It provides a comprehensive analysis of experimental results and discusses the system's potential impact on enhancing community networks, along with the future directions this technology could take.

关键词： Wearable computing Proximity-Based Smart Communities Testbed Edge computing

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An Efficient Elastic Scaling, service Deployment, and Task Allocation Algorithm for Mobile Edge computing 20

An Efficient Elastic Scaling, Service Deployment, and Task A...

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20th ieee international Wireless Communications and Mobile computing (ieee IWCMC) - Green and Intelligent Communications

作者： Cai, Wentao Zhang, Baoxian Yan, Yan Li, Cheng Univ Chinese Acad Sci Res Ctr Ubiquitous Sensor Networks Beijing 100049 Peoples R China Simon Fraser Univ Sch Engn Sci Burnaby BC V5A 1S6 Canada Mem Univ Elect & Comp Engn St John NL A1B 3X5 Canada

ISBN: (纸本)9798350361261;9798350361278

Mobile Edge computing (MEC) can provide low-latency and workload-intensive computing services to user equipments. Elastic scaling, service placement, and task scheduling are key techniques affecting the performance of an MEC system. Elastic scaling is to determine the set of active servers and also the amount of computation resources allocated for each service deployed at a server, service deployment is to determine the set of services/applications to be deployed at each server, and task scheduling is to determine how tasks are assigned among different servers. In this paper, study an MEC system where user demands fluctuate spatially and temporally. Our objective is to minimize the total power consumption and task response time. We accordingly formulate the joint optimization of elastic scaling, service placement, and task scheduling in this case as a Mixed-Integer Nonlinear Programming (MINLP). Due to the hardness of the problem, we propose an efficient joint elastic scaling, service placement, and task scheduling algorithm. Simulation results show that our proposed algorithm can effectively reduce the system cost as compared with baseline algorithms.

关键词： Mobile edge computing elastic scaling service placement task scheduling

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Wrapyfi: A PythonWrapper for Integrating Robots, Sensors, and applications across Multiple Middleware 24

Wrapyfi: A PythonWrapper for Integrating Robots, Sensors, an...

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19th Annual ACM/ieee international conference on Human-Robot Interaction (HRI)

作者： Abawi, Fares Allgeuer, Philipp Fu, Di Wermter, Stefan Univ Hamburg Hamburg Germany

ISBN: (数字)9798400703225

ISBN: (纸本)9798400703225

Message oriented and robotics middleware play an important role in facilitating robot control, abstracting complex functionality, and unifying communication patterns between sensors and devices. However, using multiple middleware frameworks presents a challenge in integrating diferent robots within a single system. To address this challenge, we present Wrapyf, a Python wrapper supporting multiple message oriented and robotics middleware, including ZeroMQ, YARP, ROS, and ROS 2. Wrapyf also provides plugins for exchanging deep learning framework data, without additional encoding or preprocessing steps. Using Wrapyf eases the development of scripts that run on multiple machines, thereby enabling cross-platform communication and workload distribution. We fnally present the three communication schemes that form the cornerstone of Wrapyf's communication model, along with examples that demonstrate their applicability.

关键词： Message oriented middleware robotics middleware distributed computing deep learning frameworks human-robot interaction

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