2018 IEEE Symposium on Service-Oriented System Engineering (SOSE)最新文献

IoT Service Based on JointCloud Blockchain: The Case Study of Smart Traveling 基于JointCloud区块链的物联网服务——以智慧出行为例

2018 IEEE Symposium on Service-Oriented System Engineering (SOSE) Pub Date : 2018-03-26 DOI: 10.1109/SOSE.2018.00036

Weili Chen, Mingjie Ma, Yongjian Ye, Zibin Zheng, Yuren Zhou

引用次数: 43

Comparing Container-Based Microservices and Workspace as a Service: Which One to Choose? 比较基于容器的微服务和作为服务的工作空间:选择哪一个?

2018 IEEE Symposium on Service-Oriented System Engineering (SOSE) Pub Date : 2018-03-26 DOI: 10.1109/SOSE.2018.00040

Junming Ma, Bo An, Donggang Cao, Xiangqun Chen

引用次数: 1

Service-Oriented IoT Modeling and Its Deviation from Software Services 面向服务的物联网建模及其对软件服务的偏离

2018 IEEE Symposium on Service-Oriented System Engineering (SOSE) Pub Date : 2018-03-26 DOI: 10.1109/SOSE.2018.00014

I. Yen, F. Bastani, Wei Zhu, Hessam Moeini, San-Yih Hwang, Yuqun Zhang

引用次数: 6

Intelligent Resource Scheduling at Scale: A Machine Learning Perspective 大规模智能资源调度:机器学习视角

2018 IEEE Symposium on Service-Oriented System Engineering (SOSE) Pub Date : 2018-03-26 DOI: 10.1109/SOSE.2018.00025

Renyu Yang, Ouyang Xue, Yaofeng Chen, P. Townend, Jie Xu

{"title":"Intelligent Resource Scheduling at Scale: A Machine Learning Perspective","authors":"Renyu Yang, Ouyang Xue, Yaofeng Chen, P. Townend, Jie Xu","doi":"10.1109/SOSE.2018.00025","DOIUrl":"https://doi.org/10.1109/SOSE.2018.00025","url":null,"abstract":"Resource scheduling in a computing system addresses the problem of packing tasks with multi-dimensional resource requirements and non-functional constraints. The exhibited heterogeneity of workload and server characteristics in Cloud-scale or Internet-scale systems is adding further complexity and new challenges to the problem. Compared with,,,, existing solutions based on ad-hoc heuristics, Machine Learning (ML) has the potential to improve further the efficiency of resource management in large-scale systems. In this paper we,,,, will describe and discuss how ML could be used to understand automatically both workloads and environments, and to help to cope with scheduling-related challenges such as consolidating co-located workloads, handling resource requests, guaranteeing application’s QoSs, and mitigating tailed stragglers. We will introduce a generalized ML-based solution to large-scale resource scheduling and demonstrate its effectiveness through a case study that deals with performance-centric node classification and straggler mitigation. We believe that an MLbased method will help to achieve architectural optimization and efficiency improvement.","PeriodicalId":414464,"journal":{"name":"2018 IEEE Symposium on Service-Oriented System Engineering (SOSE)","volume":"106 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133638362","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 26

Cuckoo Migration: Self Migration on JointCloud Using New Hardware Features 杜鹃迁移:在JointCloud上使用新的硬件特性进行自我迁移

2018 IEEE Symposium on Service-Oriented System Engineering (SOSE) Pub Date : 2018-03-26 DOI: 10.1109/SOSE.2018.00033

Ruifeng Liu, Zeyu Mi

{"title":"Cuckoo Migration: Self Migration on JointCloud Using New Hardware Features","authors":"Ruifeng Liu, Zeyu Mi","doi":"10.1109/SOSE.2018.00033","DOIUrl":"https://doi.org/10.1109/SOSE.2018.00033","url":null,"abstract":"Abstract—With the growing number of cloud providers and the increasing market of cloud computing, it’s more and more necessary to realize the cooperation and aggregation of clouds. JointCloud is a framework aiming at facilitating the consociation of various clouds on the market. And the JointCloud Collaboration Environment (JCCE) is the ideal environment for global cloud providers. To realize the clouds cooperation, migration is one of the most important issues that have to be considered. Live migration has always been one of the major primitive operations of virtualization and has been discussed for long. Traditional works deal the migration mainly by using a host-driven migration method, the majority work of which is dominated by the hypervisor. However, as the age of cloud aggregation comes, traditional methods show their defects. In cloud aggregation environment, cloud providers may refuse to supply the migration service to grasp their customers, or the hypervisors are heterogeneous on the two sides of migration. Those problems raise challenges to traditional host-driven methods. In this paper, we propose Cuckoo Migration, a new self- migration method using Intel new hardware feature. We leverage a special processor function, VMFUNC, to create a two-EPT architecture for the guest VM, so that the guest has a mirror memory space, which can be used as the duplication of memory. This paper mainly introduces how we build a two-EPT architecture for the guest and discusses how we leverage such architecture to do our self-migration.","PeriodicalId":414464,"journal":{"name":"2018 IEEE Symposium on Service-Oriented System Engineering (SOSE)","volume":"73 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116177208","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Comparing Imperative and Declarative Process Models with Flow Dependencies 比较具有流依赖关系的命令式和声明式流程模型

2018 IEEE Symposium on Service-Oriented System Engineering (SOSE) Pub Date : 2018-03-26 DOI: 10.1109/SOSE.2018.00017

M. Baumann

引用次数: 2

VTDL: A Notation for Data Stream Processing Applications 数据流处理应用的符号

2018 IEEE Symposium on Service-Oriented System Engineering (SOSE) Pub Date : 2018-03-26 DOI: 10.1109/SOSE.2018.00019

C. Hochreiner, Matteo Nardelli, Bernhard Knasmüller, Stefan Schulte, S. Dustdar

引用次数: 1

Overcoming Security Challenges in Microservice Architectures 克服微服务架构中的安全挑战

2018 IEEE Symposium on Service-Oriented System Engineering (SOSE) Pub Date : 2018-03-26 DOI: 10.1109/SOSE.2018.00011

T. Yarygina, A. H. Bagge

{"title":"Overcoming Security Challenges in Microservice Architectures","authors":"T. Yarygina, A. H. Bagge","doi":"10.1109/SOSE.2018.00011","DOIUrl":"https://doi.org/10.1109/SOSE.2018.00011","url":null,"abstract":"The microservice architectural style is an emerging trend in software engineering that allows building highly scalable and flexible systems. However, current state of the art provides only limited insight into the particular security concerns of microservice system. With this paper, we seek to unravel some of the mysteries surrounding microservice security by: providing a taxonomy of microservices security; assessing the security implications of the microservice architecture; and surveying related contemporary solutions, among others Docker Swarm and Netflix security decisions. We offer two important insights. On one hand, microservice security is a multi-faceted problem that requires a layered security solution that is not available out of the box at the moment. On the other hand, if these security challenges are solved, microservice architectures can improve security; their inherent properties of loose coupling, isolation, diversity, and fail fast all contribute to the increased robustness of a system. To address the lack of security guidelines this paper describes the design and implementation of a simple security framework for microservices that can be leveraged by practitioners. Proof-of-concept evaluation results show that the performance overhead of the security mechanisms is around 11%.","PeriodicalId":414464,"journal":{"name":"2018 IEEE Symposium on Service-Oriented System Engineering (SOSE)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115320554","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 73

An Ensemble Signature-Based Approach for Performance Diagnosis in Big Data Platform 基于集成签名的大数据平台性能诊断方法

2018 IEEE Symposium on Service-Oriented System Engineering (SOSE) Pub Date : 2018-03-26 DOI: 10.1109/SOSE.2018.00022

H. Kou, Pengfei Chen

{"title":"An Ensemble Signature-Based Approach for Performance Diagnosis in Big Data Platform","authors":"H. Kou, Pengfei Chen","doi":"10.1109/SOSE.2018.00022","DOIUrl":"https://doi.org/10.1109/SOSE.2018.00022","url":null,"abstract":"The big data platform always suffers from performance problems due to internal impairments (e.g. software bugs) and external impairments (e.g. resource hog). And the situation is exacerbated by the properties of velocity, variety and volume (3Vs) of big data. To recovery the system from performance anomaly, the first step is to find the root causes. In this paper, we propose a novel signature-based performance diagnosis approach to rapidly pinpoint the root causes of performance problems in big data platforms. The performance diagnosis is formalized as a pattern recognition problem. We leverage Maximum Information Criterion (MIC) to express the invariant relationships amongst the performance metrics in the normal state. Each performance problem occurred in the big data platform is signified by a unique binary vector named signature, which consists of a set of violations of MIC invariants. The signatures of multiple performance problems form a signature database. If the Key Performance Indicator (KPI) of the big data application exhibits model drift, our approach can identify the real culprits by retrieving the root causes which have similar signatures to the current performance problem. Moreover, considering the diversity of big data applications, we establish an ensemble approach to treat each application separately. The experiment evaluations in a controlled big data platform show that our approach can pinpoint the real culprits of performance problems in an average 84% precision and 87% recall when one fault occurs, which is better than several state-of-the-art approaches.","PeriodicalId":414464,"journal":{"name":"2018 IEEE Symposium on Service-Oriented System Engineering (SOSE)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124371670","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

DwarfGC: A Space-Efficient and Crash-Consistent Garbage Collector in NVM for Cloud Computing DwarfGC:用于云计算的NVM中空间高效且崩溃一致的垃圾收集器

2018 IEEE Symposium on Service-Oriented System Engineering (SOSE) Pub Date : 2018-03-26 DOI: 10.1109/SOSE.2018.00032

Heting Li, Mingyu Wu

引用次数: 1