2018 IEEE/ACM Symposium on Edge Computing (SEC)最新文献_第4页

In-Situ Resource Provisioning with Adaptive Scale-out for Regional IoT Services 基于自适应横向扩展的区域物联网服务原位资源配置

2018 IEEE/ACM Symposium on Edge Computing (SEC) Pub Date : 2018-10-01 DOI: 10.1109/SEC.2018.00022

Yugo Nakamura, Teruhiro Mizumoto, H. Suwa, Yutaka Arakawa, H. Yamaguchi, K. Yasumoto

{"title":"In-Situ Resource Provisioning with Adaptive Scale-out for Regional IoT Services","authors":"Yugo Nakamura, Teruhiro Mizumoto, H. Suwa, Yutaka Arakawa, H. Yamaguchi, K. Yasumoto","doi":"10.1109/SEC.2018.00022","DOIUrl":"https://doi.org/10.1109/SEC.2018.00022","url":null,"abstract":"In an era where billions of IoT devices have been deployed, edge/fog computing paradigms are attracting attention for their ability to reduce processing delays and communication overhead. In order to improve Quality of Experience (QoE) of regional IoT services that create timely geo-spatial information in response to users' queries, it is important to efficiently allocate sufficient resources based on the computational demand of each service. However since edge/fog devices are assumed to be heterogeneous (in terms of their computational power, network performance to other devices, deployment density, etc.), provisioning computational resources according to computational demand becomes a challenging constrained optimization problem. In this paper, we formulate a delay constrained regional IoT service provisioning (dcRISP) problem. dcRISP assigns computational resources of devices based on the demand of the regional IoT services in order to maximize users' QoE. We also present dcRISP+, an extension of dcRISP, that enables resource selection to extend beyond the initial area in order to satisfy increasing computational demands. We propose a provisioning algorithm, in-situ resource area selection with adaptive scale out and in-situ task scheduling based on a tabu search, to solve the dcRISP+ problem. We conducted a simulation study of a tourist area in Kyoto where 4,000 IoT devices and 3 types of IoT services were deployed. Results show that our proposed algorithms can obtain higher user QoE compared to conventional resource provisioning algorithms.","PeriodicalId":376439,"journal":{"name":"2018 IEEE/ACM Symposium on Edge Computing (SEC)","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128489819","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: 10

Secure Edge Computing in IoT Systems: Review and Case Studies 物联网系统中的安全边缘计算:回顾和案例研究

2018 IEEE/ACM Symposium on Edge Computing (SEC) Pub Date : 2018-10-01 DOI: 10.1109/SEC.2018.00060

Mohammed Alrowaily, Zhuo Lu

引用次数: 63

An Envy-Free Auction Mechanism for Resource Allocation in Edge Computing Systems 边缘计算系统中资源分配的无嫉妒竞价机制

2018 IEEE/ACM Symposium on Edge Computing (SEC) Pub Date : 2018-10-01 DOI: 10.1109/SEC.2018.00030

Tayebeh Bahreini, H. Badri, Daniel Grosu

{"title":"An Envy-Free Auction Mechanism for Resource Allocation in Edge Computing Systems","authors":"Tayebeh Bahreini, H. Badri, Daniel Grosu","doi":"10.1109/SEC.2018.00030","DOIUrl":"https://doi.org/10.1109/SEC.2018.00030","url":null,"abstract":"One of the major challenges in Mobile Edge Computing~(MEC) systems is to decide how to allocate and price edge/cloud resources so that a given system's objective, such as revenue or social welfare, is optimized. One promising approach is to allocate these resources based on auction models, in which users place bids for using a certain amount of resources. In this paper, we address the problem of resource allocation and pricing in a two-level edge computing system. We consider a system in which servers with different capacities are located in the cloud or at the edge of the network. Mobile users compete for these resources and have heterogeneous demands. We design an auction-based mechanism that allocates and prices edge/cloud resources. The proposed mechanism is novel in the sense that it handles the allocation of resources available at the two-levels of the system by combining features from both position and combinatorial auctions. We show that the proposed mechanism is individually-rational and produces envy-free allocations. The first property guarantees that users are willing to participate in the mechanism, while the second guarantees that when the auction is finished, no user would be happier with the outcome of another user. We evaluate the performance of the proposed mechanism by performing extensive experiments. The experimental results show that the proposed mechanism is scalable and obtains efficient solutions.","PeriodicalId":376439,"journal":{"name":"2018 IEEE/ACM Symposium on Edge Computing (SEC)","volume":"2013 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121685377","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: 31

Demo: Scaling on the Edge – A Benchmarking Suite for Human-in-the-Loop Applicationss 演示:在边缘上扩展-一个用于人在循环应用程序的基准测试套件

2018 IEEE/ACM Symposium on Edge Computing (SEC) Pub Date : 2018-10-01 DOI: 10.1109/SEC.2018.00031

Manuel Osvaldo Jesus Olguin Muñoz, Junjue Wang, M. Satyanarayanan, J. Gross

引用次数: 4

Amino - A Distributed Runtime for Applications Running Dynamically Across Device, Edge and Cloud 氨基-一个分布式运行时的应用程序动态运行跨设备，边缘和云

2018 IEEE/ACM Symposium on Edge Computing (SEC) Pub Date : 2018-10-01 DOI: 10.1109/SEC.2018.00046

Ying Xiong, Donghui Zhuo, Sungwook Moon, Michael Xie, Isaac Ackerman, Quinton Hoole

{"title":"Amino - A Distributed Runtime for Applications Running Dynamically Across Device, Edge and Cloud","authors":"Ying Xiong, Donghui Zhuo, Sungwook Moon, Michael Xie, Isaac Ackerman, Quinton Hoole","doi":"10.1109/SEC.2018.00046","DOIUrl":"https://doi.org/10.1109/SEC.2018.00046","url":null,"abstract":"This paper presents a framework and runtime system, Amino, for developing and executing distributed applications in highly dynamic computing environment consisting of cloud resources, edge nodes and/or devices such as phones and smart cameras. This work is based on Sapphire [1] - a general-purpose distributed programming platform. In Sapphire, application objects (called Sapphire Objects) run inside kernel servers (KS), and Kernel server instance runs on every device or cloud node. Between Kernel Server and an application object is a layer called Deployment Manager (DM). Inbound and outbound communications to/from Sapphire objects will be intercepted and processed by deployment manager. Each DM provides one specific distributed system capabilities, e.g. caching, resource leasing, replication, data partitioning etc. Programmers selectively choose DMs to manage Sapphire objects. As part of this work (Amino), we re-implemented and extended Sapphire platform to support the invocation of methods on objects written in multiple languages and to support attaching multiple DMs to a Sapphire object for increased distribution capabilities. Finally, in the work, we introduce a code offloading design for dynamically moving application objects between devices and cloud servers at runtime to optimize a user specified objective, e.g. to reduce latency or to save energy consumption.","PeriodicalId":376439,"journal":{"name":"2018 IEEE/ACM Symposium on Edge Computing (SEC)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128864959","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

DyCREM: Dynamic Credit Risk Management Using Edge-Based Blockchain DyCREM:基于边缘区块链的动态信用风险管理

2018 IEEE/ACM Symposium on Edge Computing (SEC) Pub Date : 2018-10-01 DOI: 10.1109/SEC.2018.00039

Youhuizi Li, Weisong Shi, Mohit Kumar, Jun Chen

引用次数: 5

F-MStorm: Feedback-Based Online Distributed Mobile Stream Processing F-MStorm:基于反馈的在线分布式移动流处理

2018 IEEE/ACM Symposium on Edge Computing (SEC) Pub Date : 2018-10-01 DOI: 10.1109/SEC.2018.00027

M. Chao, ChenKuang Yang, Yukun Zeng, R. Stoleru

{"title":"F-MStorm: Feedback-Based Online Distributed Mobile Stream Processing","authors":"M. Chao, ChenKuang Yang, Yukun Zeng, R. Stoleru","doi":"10.1109/SEC.2018.00027","DOIUrl":"https://doi.org/10.1109/SEC.2018.00027","url":null,"abstract":"A distributed mobile stream processing system allows mobile devices to process stream data that exceeds any single device's computation capability without the help of infrastructure. It is paramount to have such a system in many critical application scenarios, such as military operations and disaster response, yet an efficient online mobile stream processing system is still missing. In this paper, we make the key observation that the unique characteristics of mobile stream processing call for a feedback-based system design, which is in sharp contrast with the static configuration and scheduling of the current mobile stream processing system, \"MStorm\". At first, we demonstrate the inefficiencies of MStorm through several real-world experiments. Then, we propose F-MStorm, a feedback-based online distributed mobile stream processing system, which adopts the feedback-based approach in the configuration, scheduling and execution levels of system design. We implement F-MStorm on Android phones and evaluate its performance through benchmark applications. We show that it achieves up to 3x lower response time, 10% higher throughput and consumes 23% less communication energy than the state-of-the-art systems.","PeriodicalId":376439,"journal":{"name":"2018 IEEE/ACM Symposium on Edge Computing (SEC)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127208546","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

Latency-Oblivious Incentive Service Offloading in Mobile Edge Computing 移动边缘计算中的延迟无关激励服务卸载

2018 IEEE/ACM Symposium on Edge Computing (SEC) Pub Date : 2018-10-01 DOI: 10.1109/SEC.2018.00042

Amit Samanta, Yong Li

引用次数: 13

FECBench: An Extensible Framework for Pinpointing Sources of Performance Interference in the Cloud-Edge Resource Spectrum FECBench:用于在云边缘资源频谱中精确定位性能干扰源的可扩展框架

2018 IEEE/ACM Symposium on Edge Computing (SEC) Pub Date : 2018-10-01 DOI: 10.1109/SEC.2018.00034

Yogesh D. Barve, Shashank Shekhar, A. Chhokra, S. Khare, Anirban Bhattacharjee, A. Gokhale

引用次数: 7

Dependency Mining for Service Resilience at the Edge 边缘服务弹性的依赖挖掘

2018 IEEE/ACM Symposium on Edge Computing (SEC) Pub Date : 2018-10-01 DOI: 10.1109/SEC.2018.00024

Atakan Aral, I. Brandić

引用次数: 33