Proceedings of the 12th IEEE/ACM International Conference on Utility and Cloud Computing最新文献

The Overhead of Confidentiality and Client-side Encryption in Cloud Storage Systems 云存储系统中机密性和客户端加密的开销

Proceedings of the 12th IEEE/ACM International Conference on Utility and Cloud Computing Pub Date : 2019-12-02 DOI: 10.1145/3344341.3368808

Eric Henziger, Niklas Carlsson

引用次数: 2

Edge Affinity-based Management of Applications in Fog Computing Environments 雾计算环境下基于边缘亲和力的应用管理

Proceedings of the 12th IEEE/ACM International Conference on Utility and Cloud Computing Pub Date : 2019-12-02 DOI: 10.1145/3344341.3368795

Md. Redowan Mahmud, K. Ramamohanarao, R. Buyya

{"title":"Edge Affinity-based Management of Applications in Fog Computing Environments","authors":"Md. Redowan Mahmud, K. Ramamohanarao, R. Buyya","doi":"10.1145/3344341.3368795","DOIUrl":"https://doi.org/10.1145/3344341.3368795","url":null,"abstract":"Fog computing overcomes the limitations of executing Internet of Things (IoT) applications in remote Cloud datacentres by extending the computation facilities closer to data sources. Since most of the Fog nodes are resource constrained, accommodation of every IoT application within Fog environments is very challenging. Hence, we need to efficiently identify which set of applications should be deployed in Fog. It becomes even more complicated when the application characteristics in terms of urgency, size and flow of inputs are considered simultaneously. The necessity of time-optimized execution further intensifies the application management problem. In this work, we propose a policy for Fog environments that distributes application management tasks across the gateway and the infrastructure level. It classifies and places applications according to their Edge affinity. Edge affinity of an application denotes the relative intensity of different attributes coherent with its characteristics such as user-defined deadline, amount of data per input and sensing frequency of IoT devices, which are required to be addressed within Fog environments to meet its Quality of Service (QoS). The proposed policy also minimizes the service delivery time of applications in Fog infrastructure. Its performance is compared with existing application management policies in both iFogSim-simulated and FogBus-based real environments. The experiment results show that our policy outperforms others in combined QoS enhancement, network relaxation and resource utilization.","PeriodicalId":261870,"journal":{"name":"Proceedings of the 12th IEEE/ACM International Conference on Utility and Cloud Computing","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114992575","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: 28

FogDocker: Start Container Now, Fetch Image Later FogDocker:现在启动容器，稍后获取映像

Proceedings of the 12th IEEE/ACM International Conference on Utility and Cloud Computing Pub Date : 2019-12-02 DOI: 10.1145/3344341.3368811

L. Civolani, G. Pierre, P. Bellavista

引用次数: 14

Container-based Sandboxes for Malware Analysis: A Compromise Worth Considering 基于容器的恶意软件分析沙箱:一个值得考虑的折衷方案

Proceedings of the 12th IEEE/ACM International Conference on Utility and Cloud Computing Pub Date : 2019-12-02 DOI: 10.1145/3344341.3368810

A. Khalimov, Sofiane Benahmed, Rasheed Hussain, S. Kazmi, A. Oracevic, Fatima Hussain, Farhan Ahmad, Kerrache Chaker Abdelaziz

{"title":"Container-based Sandboxes for Malware Analysis: A Compromise Worth Considering","authors":"A. Khalimov, Sofiane Benahmed, Rasheed Hussain, S. Kazmi, A. Oracevic, Fatima Hussain, Farhan Ahmad, Kerrache Chaker Abdelaziz","doi":"10.1145/3344341.3368810","DOIUrl":"https://doi.org/10.1145/3344341.3368810","url":null,"abstract":"Malware analysis relies on monitoring the behavior of a suspected application within a confined, controlled and secure environment. These environments are commonly referred to as \"Sandboxes'' and are often virtualized replicas of a regular system. Hypervisor-based sandboxes were among the most commonly used techniques for malware analysis during the last decade; however, these sandboxes do not often provide the required stealth and transparency to deceive the malware in believing that it is being run in a target machine. This is due to the difference between virtualized systems and bare metal ones; differences which are exploited by the malware as detection artifacts. In this paper, we address the aforementioned problem by exploring the use of container-based environments as an alternative to hypervisor-based sandboxes for malware analysis. More precisely, we explore different ways to monitor containerized applications and make these containers act and look as close to real systems as possible. Our experimental results revealed that Docker containers are a promising option for a sandbox. However, this option comes at the cost of new detection artifacts which make containers subject to fingerprinting through different sources that malware can easily find. We explore these sources and try to address them by various means including system-call introspection. Finally, based on our discoveries, we introduce a container detection tool that will give the research community an opportunity to investigate malware analysis through containers in more details.","PeriodicalId":261870,"journal":{"name":"Proceedings of the 12th IEEE/ACM International Conference on Utility and Cloud Computing","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125680434","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

A Proactive, Cost-aware, Optimized Data Replication Strategy in Geo-distributed Cloud Datastores 地理分布式云数据存储中的前瞻性、成本意识、优化的数据复制策略

Proceedings of the 12th IEEE/ACM International Conference on Utility and Cloud Computing Pub Date : 2019-12-02 DOI: 10.1145/3344341.3368799

T. Hsu, A. Kshemkalyani

{"title":"A Proactive, Cost-aware, Optimized Data Replication Strategy in Geo-distributed Cloud Datastores","authors":"T. Hsu, A. Kshemkalyani","doi":"10.1145/3344341.3368799","DOIUrl":"https://doi.org/10.1145/3344341.3368799","url":null,"abstract":"Geo-replicated cloud datastores adopt the replication methodology by placing multiple data replicas at suitable storage zones. This can provide reliable services to customers with high availability, low access latency, low system cost, and decreased bandwidth consumption. However, this has the potential to increase the whole system overheads of maintaining more resource replicas, and to also degrade the system utilization due to unnecessary storage space cost. Thus, it is important to determine the suitable replication zones on-the-fly to increase the availability of data resources and maximize the system utilization. Specifically, it is essential to determine the appropriate number of replicas for different data resources at each zone in a particular time interval. We propose Cost Optimization Replica Placement (CORP) algorithms to enable state-of-art proactive provisioning replication of data resources based on an one-step look-ahead workload behavior pattern forecast over the distributed data storage infrastructure using statistical techniques. The experimental results show the cost effectiveness of the proposed replication strategies.","PeriodicalId":261870,"journal":{"name":"Proceedings of the 12th IEEE/ACM International Conference on Utility and Cloud Computing","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131086510","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: 6

A Systematic Mapping Study on Engineering Function-as-a-Service Platforms and Tools 工程功能即服务平台与工具的系统映射研究

Proceedings of the 12th IEEE/ACM International Conference on Utility and Cloud Computing Pub Date : 2019-12-02 DOI: 10.1145/3344341.3368803

Vladimir Yussupov, Uwe Breitenbücher, F. Leymann, Michael Wurster

引用次数: 28

LESS 少

Proceedings of the 12th IEEE/ACM International Conference on Utility and Cloud Computing Pub Date : 2019-12-02 DOI: 10.1145/3344341.3368807

L. Liu, Jun Xu, Mohit Singh

{"title":"LESS","authors":"L. Liu, Jun Xu, Mohit Singh","doi":"10.1145/3344341.3368807","DOIUrl":"https://doi.org/10.1145/3344341.3368807","url":null,"abstract":"Since about 1950 the inflow of the San Joaquin River to the Delta has been, and still is being greatly reduced. There are long periods when there is no net outflow from the river to the Central -Delta (WRINT-SDWA 19). This causes stagnant water reaches with loss of salinity control and inadequate dissolved oxygen for fish. Upstream appropriative rights granted by the State Board often exceed the total yield of the river system, and direct diversion rights are based on diversion amounts rather than on consumptive use. Appropriators, therefore, are able to keep increasing their consumptive use of the water they divert with a consequent reduction in return flows. Exports from the Tuolumne River to the Bay Area bypass the stream system and have increased about five fold over the last forty years. SDWA 121 shows the effects of some of these diversions on the Delta in a dry year such as 1977. Appropriators on the tributaries with junior water rights have not been required to bypass sufficient unimpaired flows to protect senior water rights and natural channel depletions in the San Joaquin River and southern Delta. The net effect of CVP operations alone is to reduce river flow upstream of Vernalis by about 130,000 acre feet in dry years and 560,000 acre feet in below normal years. This is discussed in the June 1980 joint report by USBR and SDWA on \"The Effects of the CVP Upon The Southern Delta Water Supply\". That report was submitted in Phase I of the Delta Hearings as SDWA 4 and a graph depicting those effects is at SDWA 26.","PeriodicalId":261870,"journal":{"name":"Proceedings of the 12th IEEE/ACM International Conference on Utility and Cloud Computing","volume":"269 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122756753","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: 4

Microservices-based IoT Application Placement within Heterogeneous and Resource Constrained Fog Computing Environments 基于微服务的物联网应用在异构和资源约束雾计算环境中的放置

Proceedings of the 12th IEEE/ACM International Conference on Utility and Cloud Computing Pub Date : 2019-12-02 DOI: 10.1145/3344341.3368800

Samodha Pallewatta, V. Kostakos, R. Buyya

{"title":"Microservices-based IoT Application Placement within Heterogeneous and Resource Constrained Fog Computing Environments","authors":"Samodha Pallewatta, V. Kostakos, R. Buyya","doi":"10.1145/3344341.3368800","DOIUrl":"https://doi.org/10.1145/3344341.3368800","url":null,"abstract":"Fog computing paradigm has created innovation opportunities within Internet of Things (IoT) domain by extending cloud services to the edge of the network. Due to the distributed, heterogeneous and resource constrained nature of the Fog computing nodes, Fog applications need to be developed as a collection of interdependent, lightweight modules. Since this concept aligns with the goals of microservices architecture, efficient placement of microservices-based IoT applications within Fog environments has the potential to fully leverage capabilities of Fog devices. In this paper, we propose a decentralized microservices-based IoT application placement policy for heterogeneous and resource constrained Fog environments. The proposed policy utilizes the independently deployable and scalable nature of microservices to place them as close as possible to the data source to minimize latency and network usage. Moreover, it aims to handle service discovery and load balancing related challenges of the microservices architecture. We implement and evaluate our policy using iFogSim simulated Fog environment. Results of the simulations show around 85% improvement in latency and network usage for the proposed microservice placement policy when compared with Cloud-only placement approach and around 40% improvement over an alternative Fog application placement method known as Edge-ward placement policy. Moreover, the decentralized placement approach proposed in this paper demonstrates significant reduction in microservice placement delay over centralized placement.","PeriodicalId":261870,"journal":{"name":"Proceedings of the 12th IEEE/ACM International Conference on Utility and Cloud Computing","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134026547","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: 53

Modelling and Prediction of Resource Utilization of Hadoop Clusters: A Machine Learning Approach Hadoop集群资源利用建模与预测:一种机器学习方法

Proceedings of the 12th IEEE/ACM International Conference on Utility and Cloud Computing Pub Date : 2019-12-02 DOI: 10.1145/3344341.3368821

H. Tariq, Harith Al-Sahaf, I. Welch

{"title":"Modelling and Prediction of Resource Utilization of Hadoop Clusters: A Machine Learning Approach","authors":"H. Tariq, Harith Al-Sahaf, I. Welch","doi":"10.1145/3344341.3368821","DOIUrl":"https://doi.org/10.1145/3344341.3368821","url":null,"abstract":"Hadoop is a distributed computing framework that has a large number of configurable parameters. These parameters have impact on system resources and execution time. Optimizing the performance of a Hadoop cluster by tuning such a large number of parameters is a tedious task. Most current big data modeling approaches does not include complex interaction between configuration parameters and the cluster environment changes such as different datasets or query. This makes it difficult to predict the performance or resource utilization of a cluster when we use real-world datasets because of their size and content. This paper presents the modeling of resource utilization of Hadoop cluster on the basis of Hadoop configuration parameters and dataset structure. Our approach builds a machine learning based-model using Hive-based Hadoop query and then predict the outcome for a particular parameter setting and query type. We used decision trees to build models for each of our performance metric measures. Decision rules were extracted from these tree-based models and evaluated for their ability to generalize to unseen data. Our experiments predicted that the percentage of columns selected, mappers and replica has a statistically significant impact over the utilization of different resources in Hadoop cluster.","PeriodicalId":261870,"journal":{"name":"Proceedings of the 12th IEEE/ACM International Conference on Utility and Cloud Computing","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115367955","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: 6

SLO-ML: A Language for Service Level Objective Modelling in Multi-cloud Applications l - ml:多云应用中服务水平目标建模语言

Proceedings of the 12th IEEE/ACM International Conference on Utility and Cloud Computing Pub Date : 2019-12-02 DOI: 10.1145/3344341.3368805

Abdessalam Elhabbash, Assylbek Jumagaliyev, G. Blair, Yehia El-khatib

引用次数: 2