2020 IEEE International Conference on Cloud Engineering (IC2E)最新文献

WLEC: A Not So Cold Architecture to Mitigate Cold Start Problem in Serverless Computing WLEC:一种缓解无服务器计算冷启动问题的非冷架构

2020 IEEE International Conference on Cloud Engineering (IC2E) Pub Date : 2020-04-01 DOI: 10.1109/IC2E48712.2020.00022

Khondokar Solaiman, Muhammad Abdullah Adnan

引用次数: 19

Energy-Aware Resource Management in Vehicular Edge Computing Systems 车辆边缘计算系统中的能源感知资源管理

2020 IEEE International Conference on Cloud Engineering (IC2E) Pub Date : 2020-04-01 DOI: 10.1109/IC2E48712.2020.00012

Tayebeh Bahreini, Marco Brocanelli, Daniel Grosu

{"title":"Energy-Aware Resource Management in Vehicular Edge Computing Systems","authors":"Tayebeh Bahreini, Marco Brocanelli, Daniel Grosu","doi":"10.1109/IC2E48712.2020.00012","DOIUrl":"https://doi.org/10.1109/IC2E48712.2020.00012","url":null,"abstract":"The low-latency requirements of connected electric vehicles and their increasing computing needs have led to the necessity to move computational nodes from the cloud data centers to edge nodes such as road-side units (RSU). However, offloading the workload of all the vehicles to RSUs may not scale well to an increasing number of vehicles and workloads. To solve this problem, computing nodes can be installed directly on the smart vehicles, so that each vehicle can execute the heavy workload locally, thus forming a vehicular edge computing system. On the other hand, these computational nodes may drain a considerable amount of energy in electric vehicles. It is therefore important to manage the resources of connected electric vehicles to minimize their energy consumption.In this paper, we propose an algorithm that manages the computing nodes of connected electric vehicles for minimized energy consumption. The algorithm achieves energy savings for connected electric vehicles by exploiting the discrete settings of computational power for various performance levels. We evaluate the proposed algorithm and show that it considerably reduces the vehicles’ computational energy consumption compared to state-of-the-art baselines. Specifically, our algorithm achieves 15-85% energy savings compared to a baseline that executes workload locally and an average of 51% energy savings compared to a baseline that offloads vehicles’ workloads only to RSUs.","PeriodicalId":173494,"journal":{"name":"2020 IEEE International Conference on Cloud Engineering (IC2E)","volume":"290 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114441254","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

Decentralized Runtime Monitoring Approach Relying on the Ethereum Blockchain Infrastructure 基于以太坊区块链基础设施的去中心化运行时监控方法

2020 IEEE International Conference on Cloud Engineering (IC2E) Pub Date : 2020-04-01 DOI: 10.1109/IC2E48712.2020.00021

Ahmed Taha, A. Zakaria, Dong Seong Kim, N. Suri

{"title":"Decentralized Runtime Monitoring Approach Relying on the Ethereum Blockchain Infrastructure","authors":"Ahmed Taha, A. Zakaria, Dong Seong Kim, N. Suri","doi":"10.1109/IC2E48712.2020.00021","DOIUrl":"https://doi.org/10.1109/IC2E48712.2020.00021","url":null,"abstract":"Cloud computing offers a model where resources (storage, applications, etc.) are abstracted and provided “as-aservice” in a remotely accessible manner. Although there are numerous claimed benefits of the Cloud to ensure confidentiality, integrity, and availability of the stored data, the number of security breaches is still on the rise. The lack of security assurance and transparency prevented customers/enterprises from trusting the Cloud Service Providers (CSPs). Unless the customer’s security requirements are identified and documented by the CSPs, customers can not be assured that the CSPs will satisfy their requirements. Furthermore, the customer’s compensation upon a violation is a manual time intensive process.In this paper we address the aforementioned challenges by proposing a decentralized customer-based monitoring approach running over Ethereum blockchain. The proposed approach allows the customer(s) to validate the compliance of CSP(s) to the contracted services in the Service Level Agreements (SLAs) and “autonomsly” compensate customers in case of security breaches. At the same time, the proposed approach prevents customers from misreporting for financial gain. The approach builds upon the Ethereum blockchain infrastructure in order to securely store monitoring logs and incorporate SLAs as smart contracts. The compliance validation framework is implemented and its functionality is evaluated on Amazon EC2 and Ethereum Blockchain.","PeriodicalId":173494,"journal":{"name":"2020 IEEE International Conference on Cloud Engineering (IC2E)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129143689","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

Smart Food Scanner System Based on Mobile Edge Computing 基于移动边缘计算的智能食品扫描系统

2020 IEEE International Conference on Cloud Engineering (IC2E) Pub Date : 2020-04-01 DOI: 10.1109/IC2E48712.2020.00009

B. Javadi, Q. Trieu, K. Matawie, R. Calheiros

引用次数: 3

IC2E 2020 Committees IC2E 2020委员会

2020 IEEE International Conference on Cloud Engineering (IC2E) Pub Date : 2020-04-01 DOI: 10.1109/ic2e48712.2020.00006

引用次数: 0

uPredict: A User-Level Profiler-Based Predictive Framework in Multi-Tenant Clouds uPredict:多租户云中基于用户级分析器的预测框架

2020 IEEE International Conference on Cloud Engineering (IC2E) Pub Date : 2020-04-01 DOI: 10.1109/IC2E48712.2020.00015

Hamidreza Moradi, Wei Wang, Amanda Fernandez, Dakai Zhu

{"title":"uPredict: A User-Level Profiler-Based Predictive Framework in Multi-Tenant Clouds","authors":"Hamidreza Moradi, Wei Wang, Amanda Fernandez, Dakai Zhu","doi":"10.1109/IC2E48712.2020.00015","DOIUrl":"https://doi.org/10.1109/IC2E48712.2020.00015","url":null,"abstract":"Accurate performance prediction for cloud applications is an essential component to support many cloud resource management and auto-scaling policies. However, most existing studies on performance prediction for cloud applications in multitenant clouds are at the system level and may require access to performance counters in hypervisors. In this work, we propose uPredict, a user-level profiler-based performance predictive framework for single-VM (virtual machine) applications in multitenant clouds. We designed three micro-benchmarks to assess the contention of CPUs, memory and disks in a VM, respectively. Based on the measured performance of an application and micro-benchmarks, the application and VM-specific predictive models are derived by exploiting various regression and neural network based techniques. These models can then be used to predict the application’s performance using the in-situ profiled resource contention with the micro-benchmarks. We evaluated uPredict extensively with representative benchmarks from PARSEC, NAS Parallel Benchmarks and CloudSuite, on a private cloud and two public clouds. The results show that the average prediction errors are between 10.4% to 17% for various predictive models on the private cloud with high resource contention, while the errors are within 4% on public clouds. A smart load-balancing scheme powered by uPredict is presented and can effectively reduce the execution and turnaround times of the considered application by 19% and 10%, respectively.","PeriodicalId":173494,"journal":{"name":"2020 IEEE International Conference on Cloud Engineering (IC2E)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116704089","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

Message from the Program Chair: IC2E 2020 项目主席致辞:IC2E 2020

2020 IEEE International Conference on Cloud Engineering (IC2E) Pub Date : 2020-04-01 DOI: 10.1109/ic2e48712.2020.00005

引用次数: 0

Hedge Your Bets: Optimizing Long-term Cloud Costs by Mixing VM Purchasing Options 对冲您的赌注:通过混合虚拟机购买选项优化长期云成本

2020 IEEE International Conference on Cloud Engineering (IC2E) Pub Date : 2020-04-01 DOI: 10.1109/IC2E48712.2020.00018

Pradeep Ambati, Noman Bashir, D. Irwin, M. Hajiesmaili, P. Shenoy

{"title":"Hedge Your Bets: Optimizing Long-term Cloud Costs by Mixing VM Purchasing Options","authors":"Pradeep Ambati, Noman Bashir, D. Irwin, M. Hajiesmaili, P. Shenoy","doi":"10.1109/IC2E48712.2020.00018","DOIUrl":"https://doi.org/10.1109/IC2E48712.2020.00018","url":null,"abstract":"Cloud platforms offer the same VMs under many purchasing options that specify different costs and time commitments, such as on-demand, reserved, sustained-use, scheduled reserve, transient, and spot block. In general, the stronger the commitment, i.e., longer and less flexible, the lower the price. However, longer and less flexible time commitments can increase cloud costs for users if future workloads cannot utilize the VMs they committed to buying. Large cloud customers often find it challenging to choose the right mix of purchasing options to reduce their long-term costs, while retaining the ability to adjust capacity up and down in response to workload variations.To address the problem, we design policies to optimize long-term cloud costs by selecting a mix of VM purchasing options based on short- and long-term expectations of workload utilization. We consider a batch trace spanning 4 years from a large shared cluster for a major state University system that includes 14k cores and 60 million job submissions, and evaluate how these jobs could be judiciously executed using cloud servers using our approach. Our results show that our policies incur a cost within 41% of an optimistic optimal offline approach, and 50% less than solely using on-demand VMs.","PeriodicalId":173494,"journal":{"name":"2020 IEEE International Conference on Cloud Engineering (IC2E)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115561496","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

The Ifs and Buts of Less is More: A Serverless Computing Reality Check 少即是多:无服务器计算的现实检验

2020 IEEE International Conference on Cloud Engineering (IC2E) Pub Date : 2020-04-01 DOI: 10.1109/IC2E48712.2020.00023

Jörn Kuhlenkamp, Sebastian Werner, S. Tai

{"title":"The Ifs and Buts of Less is More: A Serverless Computing Reality Check","authors":"Jörn Kuhlenkamp, Sebastian Werner, S. Tai","doi":"10.1109/IC2E48712.2020.00023","DOIUrl":"https://doi.org/10.1109/IC2E48712.2020.00023","url":null,"abstract":"Serverless computing defines a pay-as-you-go cloud execution model, where the unit of computation is a function that a cloud provider executes and auto-scales on behalf of a cloud consumer. Serverless suggests not (or less) caring about servers but focusing (more) on business logic expressed in functions. Server’less’ may be ‘more’ when getting developer expectations and platform propositions right and when engineering solutions that take specific behavior and constraints of (current) Function-as-a-Service platforms into account. To this end, in this invited paper, we present a summary of findings and lessons learned from a series of research experiments conducted over the past two years. We argue that careful attention must be placed on the promises associated with the serverless model, provide a reality-check for five common assumptions, and suggest ways to mitigate unwanted effects. Our findings focus on application workload distribution and computational processing complexity, the specific auto-scaling mechanisms in place, the behavior and strategies implemented with operational tasks, the constraints and limitations existing when composing functions, and the costs of executing functions.","PeriodicalId":173494,"journal":{"name":"2020 IEEE International Conference on Cloud Engineering (IC2E)","volume":"78 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114454030","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: 18

Towards Non-Intrusive Software Introspection and Beyond 迈向非侵入式软件自省及超越

2020 IEEE International Conference on Cloud Engineering (IC2E) Pub Date : 2020-04-01 DOI: 10.1109/IC2E48712.2020.00025

Apoorve Mohan, S. Nadgowda, Bhautik Pipaliya, Sona Varma, Sahil Suneja, C. Isci, G. Cooperman, Peter Desnoyers, O. Krieger, Ata Turk

引用次数: 3