{"title":"Feed4Cloud: Towards trustworthy QoE-aware cloud service monitoring using blockchain","authors":"Ioanna Angeliki Kapetanidou , Christos-Alexandros Sarros , Giannis Ledakis , Vassilis Tsaoussidis","doi":"10.1016/j.future.2024.107532","DOIUrl":null,"url":null,"abstract":"<div><div>The recent prevalence of microservice-based applications that leverage the capabilities offered by cloud and edge computing, has given rise to highly complex services which create new challenges for efficient monitoring and orchestration. In today’s cloud environments, service monitoring is typically premised on technical Quality of Service (QoS) performance metrics, rather than on Quality of Experience (QoE) as perceived by users. In this paper, we posit that user feedback should also play a significant role in cloud service monitoring. However, we explicitly set a prerequisite: the trustworthiness of user feedback should not be considered guaranteed. Therefore, we have developed Feed4Cloud, the first system to complement QoS monitoring with exclusively trustworthy user feedback for QoE-aware cloud service management. The novelty of our solution lies in two key aspects: First, the establishment of an intermediate verification layer that validates user feedback before it is injected into the orchestration engine. The second key aspect is the use of Blockchain in this layer, as a means to record user feedback in a decentralized and secure way, aiming to achieve non-repudiation and ensure its integrity. In this paper, we present the architectural details of the Feed4Cloud prototype, while placing a particular focus on aspects regarding trustworthy evaluation of service performance. Furthermore, we provide evaluation results that validate the effectiveness of the introduced verification layer and demonstrate that QoE-based service evaluation can consistently be conducted in a trustworthy manner across a wide range of system conditions and user behaviors.</div></div>","PeriodicalId":55132,"journal":{"name":"Future Generation Computer Systems-The International Journal of Escience","volume":null,"pages":null},"PeriodicalIF":6.2000,"publicationDate":"2024-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Future Generation Computer Systems-The International Journal of Escience","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0167739X24004965","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, THEORY & METHODS","Score":null,"Total":0}
引用次数: 0
Abstract
The recent prevalence of microservice-based applications that leverage the capabilities offered by cloud and edge computing, has given rise to highly complex services which create new challenges for efficient monitoring and orchestration. In today’s cloud environments, service monitoring is typically premised on technical Quality of Service (QoS) performance metrics, rather than on Quality of Experience (QoE) as perceived by users. In this paper, we posit that user feedback should also play a significant role in cloud service monitoring. However, we explicitly set a prerequisite: the trustworthiness of user feedback should not be considered guaranteed. Therefore, we have developed Feed4Cloud, the first system to complement QoS monitoring with exclusively trustworthy user feedback for QoE-aware cloud service management. The novelty of our solution lies in two key aspects: First, the establishment of an intermediate verification layer that validates user feedback before it is injected into the orchestration engine. The second key aspect is the use of Blockchain in this layer, as a means to record user feedback in a decentralized and secure way, aiming to achieve non-repudiation and ensure its integrity. In this paper, we present the architectural details of the Feed4Cloud prototype, while placing a particular focus on aspects regarding trustworthy evaluation of service performance. Furthermore, we provide evaluation results that validate the effectiveness of the introduced verification layer and demonstrate that QoE-based service evaluation can consistently be conducted in a trustworthy manner across a wide range of system conditions and user behaviors.
期刊介绍:
Computing infrastructures and systems are constantly evolving, resulting in increasingly complex and collaborative scientific applications. To cope with these advancements, there is a growing need for collaborative tools that can effectively map, control, and execute these applications.
Furthermore, with the explosion of Big Data, there is a requirement for innovative methods and infrastructures to collect, analyze, and derive meaningful insights from the vast amount of data generated. This necessitates the integration of computational and storage capabilities, databases, sensors, and human collaboration.
Future Generation Computer Systems aims to pioneer advancements in distributed systems, collaborative environments, high-performance computing, and Big Data analytics. It strives to stay at the forefront of developments in grids, clouds, and the Internet of Things (IoT) to effectively address the challenges posed by these wide-area, fully distributed sensing and computing systems.