ACM Cloud and Autonomic Computing Conference最新文献_第3页

Self-optimizing autonomic control of geographically distributed collaboration applications 地理分布协作应用程序的自优化自主控制

ACM Cloud and Autonomic Computing Conference Pub Date : 2013-08-09 DOI: 10.1145/2494621.2494650

B. Solomon, D. Ionescu, C. Gadea, S. Veres, Marin Litoiu

{"title":"Self-optimizing autonomic control of geographically distributed collaboration applications","authors":"B. Solomon, D. Ionescu, C. Gadea, S. Veres, Marin Litoiu","doi":"10.1145/2494621.2494650","DOIUrl":"https://doi.org/10.1145/2494621.2494650","url":null,"abstract":"In the past few years, cloud computing has become an integral technology both for the day to day running of corporations, as well as in everyday life as more services are offered which use a backend cloud. At the same time online collaboration tools are becoming more important as both businesses and individuals need to share information and collaborate with other entities. Previous work has presented an architecture for a collaboration online application which allows users in different locations to share videos, images and documents while at the same time video chatting. The application's servers are deployed in a cloud environment which can scale up and down based on demand. Furthermore, the design allows the application to be deployed on multiple clouds which are deployed in different geographic locations. Previous work however did not introduce how the application's up and down scaling is to be achieved. In this paper the autonomic system which manages the self-optimizing function of the cloud is presented. The autonomic system itself is a self-organizing system with a control model based on the leaky-bucket theory often used in network congestion control. A testbed for the collaboration application is used in order to gather performance metrics for the model.","PeriodicalId":190559,"journal":{"name":"ACM Cloud and Autonomic Computing Conference","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134116409","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: 3

Enabling autonomic computing on federated advanced cyberinfrastructures 在联邦高级网络基础设施上实现自主计算

ACM Cloud and Autonomic Computing Conference Pub Date : 2013-08-09 DOI: 10.1145/2494621.2494641

J. Montes, Mengsong Zou, I. Rodero, M. Parashar

引用次数: 8

Autonomic operation of massively multiplayer online games in clouds 云上大型多人在线游戏的自主运行

ACM Cloud and Autonomic Computing Conference Pub Date : 2013-08-09 DOI: 10.1145/2494621.2494629

Vlad Nae, R. Prodan, A. Iosup

{"title":"Autonomic operation of massively multiplayer online games in clouds","authors":"Vlad Nae, R. Prodan, A. Iosup","doi":"10.1145/2494621.2494629","DOIUrl":"https://doi.org/10.1145/2494621.2494629","url":null,"abstract":"To support the variable load of Massively Multiplayer On-line Games (MMOGs) with millions of registered users and thousands of active concurrent players, game operators over-provision a large static infrastructure capable of sustaining the peak load with guaranteed Quality of Service (QoS). This leads to inefficient resource utilisation, high service prices, and limited market participation accessible only to the large companies. To address this problem, we propose a new autonomic ecosystem for hosting and operating MMOGs based on cloud computing principles involving four smaller and better focused business actors whose interaction is regulated through Service Level Agreements (SLAs): resource provider, game operator, game provider, and client. In our model, game providers acquire operation SLAs from game operators to satisfy client requests and manage multiple distributed MMOG sessions. Game operators lease on-demand cloud resources based on the dynamic MMOG load and guarantee the required QoS to all clients. We evaluate through simulations based on real MMOG traces and commercial cloud SLAs different methods of ranking MMOG operation offers. We show that considering compensations for SLA faults in the offer selection can lead to over 11% gains in game providers' income, and that adequate ranking of offers can reduce operational costs by up to 60%.","PeriodicalId":190559,"journal":{"name":"ACM Cloud and Autonomic Computing Conference","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134416128","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: 2

An allocation and provisioning model of science cloud for high throughput computing applications 面向高通量计算应用的科学云分配与供应模型

ACM Cloud and Autonomic Computing Conference Pub Date : 2013-08-09 DOI: 10.1145/2494621.2494649

Seoyoung Kim, Jik-Soo Kim, Soonwook Hwang, Yoonhee Kim

{"title":"An allocation and provisioning model of science cloud for high throughput computing applications","authors":"Seoyoung Kim, Jik-Soo Kim, Soonwook Hwang, Yoonhee Kim","doi":"10.1145/2494621.2494649","DOIUrl":"https://doi.org/10.1145/2494621.2494649","url":null,"abstract":"Recent cloud computing enables numerous scientists to earn advantages by serving on-demand and elastic resources whenever they desire computing resources. This science cloud paradigm has been actively developed and investigated to satisfy requirements of the scientists such as performance, feasibility and so on. However, effective allocation and provisioning virtual machines on clouds are still considered as a challenging issue in scientists using high throughput computing, since it determines whether they can earn benefits from economy of scale in clouds or not. Moreover, allocating the \"right\" provisioned cloud resources on an optimal data center is very important as performance can vary widely depending on where and under what circumstances it actually runs. In these reasons, it is required that an appropriate and suitable model for science cloud to support increasing scientists and computations.\u0000 In this paper, we present an allocation and provisioning model of science cloud, especially for high throughput computing applications. In this model, we utilize job traces where statistical method is applied to pick the most influential features for improving application performance. With the feature, the system determines where VM is deployed (allocation) and which instance type is proper (provisioning). An adaptive evaluation step which is subsequent to the job execution enables our model to adapt to dynamical computing environments. We show performance achievements as comparing the proposed model with other policies through experiments. Finally, we expect that improvement on performance as well as reduction of cost from resource consumption through our model.","PeriodicalId":190559,"journal":{"name":"ACM Cloud and Autonomic Computing Conference","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125414129","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: 8

ElastMan: elasticity manager for elastic key-value stores in the cloud ElastMan:用于云中的弹性键值存储的弹性管理器

ACM Cloud and Autonomic Computing Conference Pub Date : 2013-08-09 DOI: 10.1145/2494621.2494630

A. Al-Shishtawy, Vladimir Vlassov

{"title":"ElastMan: elasticity manager for elastic key-value stores in the cloud","authors":"A. Al-Shishtawy, Vladimir Vlassov","doi":"10.1145/2494621.2494630","DOIUrl":"https://doi.org/10.1145/2494621.2494630","url":null,"abstract":"The increasing spread of elastic Cloud services, together with the pay-as-you-go pricing model of Cloud computing, has led to the need of an elasticity controller. The controller automatically resizes an elastic service in response to changes in workload, in order to meet Service Level Objectives (SLOs) at a reduced cost. However, variable performance of Cloud Virtual Machines and nonlinearities in Cloud services, such as the diminishing reward of adding a service instance with increasing the scale, complicates the controller design. We present the design and evaluation of ElastMan, an elasticity controller for Cloud-based elastic key-value stores. ElastMan combines feedforward and feedback control. Feedforward control is used to respond to spikes in the workload by quickly resizing the service to meet SLOs at a minimal cost. Feedback control is used to correct modeling errors and to handle diurnal workload. To address nonlinearities, our design of ElastMan leverages the near-linear scalability of elastic Cloud services in order to build a scale-independent model of the service. We have implemented and evaluated ElastMan using the Voldemort key-value store running in an OpenStack Cloud environment. Our evaluation shows the feasibility and effectiveness of our approach to automation of Cloud service elasticity.","PeriodicalId":190559,"journal":{"name":"ACM Cloud and Autonomic Computing Conference","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132744486","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: 47

Self-protecting and self-optimizing database systems: implementation and experimental evaluation 自保护自优化数据库系统:实现与实验评价

ACM Cloud and Autonomic Computing Conference Pub Date : 2013-08-09 DOI: 10.1145/2494621.2494631

Firas B. Alomari, D. Menascé

{"title":"Self-protecting and self-optimizing database systems: implementation and experimental evaluation","authors":"Firas B. Alomari, D. Menascé","doi":"10.1145/2494621.2494631","DOIUrl":"https://doi.org/10.1145/2494621.2494631","url":null,"abstract":"The ubiquity of database systems and the emergence of new and different threats require multiple and overlapping security mechanisms. Providing multiple and diverse database intrusion detection and prevention systems (IDPS) is a critical component of the defense-in-depth strategy for DB information systems. However, providing this level of security can greatly impact a system's QoS requirements. It would then be advantageous to use the combination of IDPSs that best meets the security and QoS concerns of the system stakeholders for each workload intensity level. Due to the dynamic variability of the workload intensity, it is not feasible for human beings to continuously reconfigure the system. We offer an autonomic computing approach for a self-protecting and self-optimizing database system environment that captures dynamic and fine-grained tradeoffs between security and QoS. The approach uses a multi-objective utility function that considers security overhead, perceived risk level, and high level stakeholder objectives. We describe the implementation of an autonomic controller that uses combinatorial search techniques and queuing network models to dynamically search for a near-optimal security configuration. We validate our approach experimentally on a TPC-W e-commerce site and show that our approach balances QoS and security goals.","PeriodicalId":190559,"journal":{"name":"ACM Cloud and Autonomic Computing Conference","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133271041","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: 12

Improving cloud infrastructure utilization through overbooking 通过超额预订提高云基础设施利用率

ACM Cloud and Autonomic Computing Conference Pub Date : 2013-08-09 DOI: 10.1145/2494621.2494627

Luis Tomás, Johan Tordsson

引用次数: 101

Autonomic resource provisioning in cloud systems with availability goals 具有可用性目标的云系统中的自主资源供应

ACM Cloud and Autonomic Computing Conference Pub Date : 2013-08-09 DOI: 10.1145/2494621.2494623

E. Casalicchio, D. Menascé, Arwa Aldhalaan

{"title":"Autonomic resource provisioning in cloud systems with availability goals","authors":"E. Casalicchio, D. Menascé, Arwa Aldhalaan","doi":"10.1145/2494621.2494623","DOIUrl":"https://doi.org/10.1145/2494621.2494623","url":null,"abstract":"The elasticity afforded by cloud computing allows consumers to dynamically request and relinquish computing and storage resources and pay for them on a pay-per-use basis. Cloud computing providers rely on virtualization techniques to manage the dynamic nature of their infrastructure allowing consumers to dynamically allocate and deallocate virtual machines of different capacities. Cloud providers need to optimally decide the best allocation of virtual machines to physical machines as the demand varies dynamically. When making such decisions, cloud providers can migrate VMs already allocated and/or use external cloud providers. This paper considers the problem in which the cloud provider wants to maximize its revenue, subject to capacity, availability SLA, and VM migration constraints. The paper presents a heuristic solution, called Near Optimal (NOPT), to this NP-hard problem and discusses the results of its experimental evaluation in comparison with a best fit (BF) allocation strategy. The results show that NOPT provides a 45% improvement in average revenue when compared with BF for the parameters used in the experiment. Moreover, the NOPT algorithm maintained the availability close to one for all classes of users while BF exhibited a lower availability and even failed to meet the availability SLA at times.","PeriodicalId":190559,"journal":{"name":"ACM Cloud and Autonomic Computing Conference","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116925027","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: 67