2018 IEEE/ACM 11th International Conference on Utility and Cloud Computing (UCC)最新文献

{"title":"UCC 2018 Technical Program Committee","authors":"","doi":"10.1109/ucc.2018.00008","DOIUrl":"https://doi.org/10.1109/ucc.2018.00008","url":null,"abstract":"","PeriodicalId":288232,"journal":{"name":"2018 IEEE/ACM 11th International Conference on Utility and Cloud Computing (UCC)","volume":"150 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115191910","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}

{"title":"Combining Heuristics to Optimize and Scale the Placement of IoT Applications in the Fog","authors":"Ye Xia, Xavier Etchevers, Loic Letondeur, A. Lèbre, T. Coupaye, F. Desprez","doi":"10.1109/UCC.2018.00024","DOIUrl":"https://doi.org/10.1109/UCC.2018.00024","url":null,"abstract":"As fog computing brings processing and storage resources to the edge of the network, there is an increasing need of automated placement (i.e., host selection) to deploy distributed applications. Such a placement must conform to applications' resource requirements in a heterogeneous fog infrastructure, and deal with the complexity brought by Internet of Things (IoT) applications tied to sensors and actuators. This paper presents four heuristics to address the problem of placing distributed IoT applications in the fog. By combining proposed heuristics, our approach is able to deal with large scale problems, and to efficiently make placement decisions fitting the objective: minimizing placed applications' average response time. The proposed approach is validated through comparative simulation of different heuristic combinations with varying sizes of infrastructures and applications.","PeriodicalId":288232,"journal":{"name":"2018 IEEE/ACM 11th International Conference on Utility and Cloud Computing (UCC)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127954652","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}

{"title":"Message from the UCC 2018 Program Committee Chairs","authors":"","doi":"10.1109/ucc.2018.00006","DOIUrl":"https://doi.org/10.1109/ucc.2018.00006","url":null,"abstract":"","PeriodicalId":288232,"journal":{"name":"2018 IEEE/ACM 11th International Conference on Utility and Cloud Computing (UCC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132606892","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}

{"title":"UVBond: Strong User Binding to VMs for Secure Remote Management in Semi-Trusted Clouds","authors":"Keisuke Inokuchi, Kenichi Kourai","doi":"10.1109/UCC.2018.00030","DOIUrl":"https://doi.org/10.1109/UCC.2018.00030","url":null,"abstract":"In Infrastructure-as-a-Service (IaaS) clouds, remote users access provided virtual machines (VMs) via the management server. The management server is managed by cloud operators, but not all the cloud operators are trusted in semi-trusted clouds. They can execute arbitrary management commands to users' VMs and redirect users' commands to malicious VMs, which is called the VM redirection attack. The root cause is that the binding of users to VMs is weak. In other words, it is difficult to enforce the execution of only users' management commands to their VMs. In this paper, we propose UVBond for strongly binding users to their VMs to solve this problem. UVBond boots user's VM by decrypting its encrypted disk inside the trusted hypervisor. Then it issues a VM descriptor to securely identify that VM. To bridge the semantic gap between high-level management commands and low-level hypercalls, UVBond uses hypercall automata, which accept the sequences of hypercalls issued by commands. We have implemented UVBond in Xen and confirmed that a VM descriptor and hypercall automata prevented attacks and that the overhead was not large.","PeriodicalId":288232,"journal":{"name":"2018 IEEE/ACM 11th International Conference on Utility and Cloud Computing (UCC)","volume":"3 4","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114049892","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}

{"title":"StreamSight: A Query-Driven Framework for Streaming Analytics in Edge Computing","authors":"Z. Georgiou, Moysis Symeonides, Demetris Trihinas, G. Pallis, M. Dikaiakos","doi":"10.1109/UCC.2018.00023","DOIUrl":"https://doi.org/10.1109/UCC.2018.00023","url":null,"abstract":"Edge computing is the emerging architectural paradigm extending cloud technologies to the logical extremes of the network for on-demand and delay-sensitive services. However, once service placement on edge-enabling resources has been dealt with, a new challenge arises: how to process enormous volumes of streaming data to provide query-driven analytics while still satisfying the delay-critical servicing requirements. To overcome this challenge we introduce StreamSight, a framework for edge-enabled IoT services which provides a rich and declarative query model abstraction for expressing complex analytics on monitoring data streams and then dynamically compiling these queries into stream processing jobs for continuous execution on distributed processing engines. To overcome the resource restrictive barriers in edge computing deployments, StreamSight outputs the query execution plan so that intermediate results are reused and not continuously recomputed. In turn, StreamSight enables users to express various optimization strategies (e.g., approximate answers, query prioritization) and constraints (e.g., sample size, error-bounds) so that delay-sensitive requirements relevant to their deployment are not violated. We evaluate our framework on Apache Spark with real-world workloads and show that leveraging StreamSight can significantly increase performance by 4x while still satisfying all accuracy guarantees.","PeriodicalId":288232,"journal":{"name":"2018 IEEE/ACM 11th International Conference on Utility and Cloud Computing (UCC)","volume":"650 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116420042","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}

{"title":"A Predictive Anti-Correlated Virtual Machine Placement Algorithm for Green Cloud Computing","authors":"Rachael Shaw, E. Howley, E. Barrett","doi":"10.1109/UCC.2018.00035","DOIUrl":"https://doi.org/10.1109/UCC.2018.00035","url":null,"abstract":"Energy related costs and environmental sustainability present a significant challenge for cloud computing practitioners and the development of next generation data centers. In efficient resource management is one of the greatest causes of high energy consumption in the operation of data centers today. Virtual Machine (VM) placement is a promising technique to save energy and improve resource management. A key challenge for VM placement algorithms is the ability to accurately forecast future resource demands due to the dynamic nature of cloud applications. Furthermore, the literature rarely considers placement strategies based on co-located resource consumption which has the potential to improve allocation decisions. Using real workload traces this work presents a comparative study of the most widely used prediction models and introduces a novel predictive anti-correlated VM placement approach. Our empirical results demonstrate how the proposed approach reduces energy by 18% while also reducing service violations by over 47% compared to some of the most commonly used placement policies.","PeriodicalId":288232,"journal":{"name":"2018 IEEE/ACM 11th International Conference on Utility and Cloud Computing (UCC)","volume":"81 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128567094","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}

{"title":"Joint Load-Balancing and Energy-Aware Virtual Machine Placement for Network-on-Chip Systems","authors":"Xuanzhang Liu, Lena Mashayekhy","doi":"10.1109/UCC.2018.00021","DOIUrl":"https://doi.org/10.1109/UCC.2018.00021","url":null,"abstract":"Virtualization is one of the key enabler technologies of cloud computing in providing on-demand sharing of computing resources. Virtualization requires mechanisms and algorithms for virtual resource allocation, virtual machine deployment, migration, and servers consolidation. Most of the existing studies have only focused on how to solve the problem of virtual resource allocation among servers. However, as cloud servers with multi-core architectures become popular, the virtual machine resource allocation in a single server becomes a critical challenge. In this paper, we propose a multi-objective virtual machine placement algorithm by jointly considering energy efficiency and load balancing criteria in a multi-core server with the Network-on-Chip architecture. Our proposed algorithm is based on Markov approximation optimization theory. We perform extensive experiments to evaluate our proposed algorithm. The results show that our proposed algorithm achieves higher energy efficiency, load balancing, and calculation speed compared with the state-of-the-art algorithms.","PeriodicalId":288232,"journal":{"name":"2018 IEEE/ACM 11th International Conference on Utility and Cloud Computing (UCC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130190419","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}

{"title":"A Framework for Optimization, Service Placement, and Runtime Operation in the Fog","authors":"O. Skarlat, Vasileios Karagiannis, T. Rausch, Kevin Bachmann, Stefan Schulte","doi":"10.1109/UCC.2018.00025","DOIUrl":"https://doi.org/10.1109/UCC.2018.00025","url":null,"abstract":"Fog computing provides a paradigm for executing Internet of Things services. Enabling the coordinated cooperation among computational, storage, and networking resources in the fog can be challenging due to the volatility of resources. For this reason, we design an architecture and implement a representative framework called FogFrame that defines the necessary communication mechanisms for instantiating and maintaining service execution in the fog. To evaluate our approach, we conduct a series of experiments that show how service placement, deployment, and execution is performed by the framework, and how the framework operates at runtime, i.e., adapts to changes in the available resources, balances the workload and recovers from resource failures and overloads.","PeriodicalId":288232,"journal":{"name":"2018 IEEE/ACM 11th International Conference on Utility and Cloud Computing (UCC)","volume":"136 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122781859","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}

{"title":"Combining VM Preemption Schemes to Improve Vertical Memory Elasticity Scheduling in Clouds","authors":"J. Valencia, Cristina Boeres, Vinod E. F. Rebello","doi":"10.1109/UCC.2018.00014","DOIUrl":"https://doi.org/10.1109/UCC.2018.00014","url":null,"abstract":"Server consolidation and resource elasticity are among two of the most important resource management features in cloud and edge computing. One of two forms of elasticity is often adopted. While horizontal elasticity is concerned with the acquisition and release of computational nodes in accordance with demand, vertical elasticity focuses on the distribution of a node's resources among its hosted virtual machines (VMs) or containers, by adjusting the capacity of the resource types allocated to each individual VM in accordance with its respective application's needs. In the case of vertical elasticity, when insufficient resources are available to allocate to a given VM, its application's performance may suffer degradation. For online applications, the only alternative is to live-migrate the VM to another server. On the other hand, when running batch jobs, the resource-constrained VM could also be suspended or saved to disk and revived elsewhere or on the same host, when resources become available. Given that memory availability has a significant influence on performance and system throughput, this paper investigates the viability of integrating VM migration, pausing and suspension schemes as part of a VM scheduling strategy to support the execution of both online and batch applications in a virtualized infrastructure employing memory elasticity. Results show that combining such schemes can provide utilization benefits for cloud service providers when memory is scarce.","PeriodicalId":288232,"journal":{"name":"2018 IEEE/ACM 11th International Conference on Utility and Cloud Computing (UCC)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123992548","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}

{"title":"Reducing Tail Latencies while Improving Resiliency to Timing Errors for Stream Processing Workloads","authors":"Geoffrey Phi C. Tran, J. Walters, S. Crago","doi":"10.1109/UCC.2018.00028","DOIUrl":"https://doi.org/10.1109/UCC.2018.00028","url":null,"abstract":"Stream processing is an increasingly popular model for online data processing that can be partitioned into streams of elements. It is commonly used in real-time data analytics services, such as processing Twitter tweets and Internet of Things (IoT) device feeds. Current stream processing frameworks boast high throughput and low average latency. However, users of these frameworks may desire lower tail latencies and better real-time performance for their applications. In practice, there are a number of errors that can affect the performance of stream processing applications, such as garbage collection and resource contention. For some applications, these errors may cause unacceptable violations of real-time constraints. In this paper we propose applying redundancy in the data processing pipeline to increase the resiliency of stream processing applications to timing errors. This results in better real-time performance and a reduction in tail latency. We present a methodology and apply this redundancy in a framework based on Twitter's Heron. Finally, we evaluate the effectiveness of this technique against a range of injected timing errors using benchmarks from Intel's Storm Benchmark. Our results show that redundant tuple processing can effectively reduce the tail latency, and that the number of missed deadlines can also be reduced by up to 94% in the best case. We also study the potential effects of duplication when applied at different stages in the topology. For the topologies in this paper, we further observe that duplication is most effective when computation is redundant at the first bolt. Finally, we evaluate the additional overhead that duplicating tuples brings to a stream processing topology. Our results also show that computation overhead scales slower than communication, and that the real-time performance is improved in spite of the overheads. Overall we conclude that redundancy through duplicated tuples is indeed a powerful tool for increasing the resiliency to intermittent runtime timing errors.","PeriodicalId":288232,"journal":{"name":"2018 IEEE/ACM 11th International Conference on Utility and Cloud Computing (UCC)","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126078441","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}