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Collaborative and adaptive mobile device-resident service architectures.

机译:协作和自适应移动设备驻留服务体系结构。

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摘要

Mobile devices, such as smartphones and personal media players, have recently significantly increased in popularity thanks to the rich set of mobile cloud services that they allow users to access. Networked vehicular computing devices are also expected to be commonplace in the near future, as they will enable a wide range of driver assistance services. The ubiquitous penetration of mobile services, however, has been thwarted by their poor user experience; access to mobile cloud services typically occurs over slow and costly long-range cellular communications.;This thesis focuses on improving the user experience of mobile services by reducing the need for costly long-range cellular communications. To achieve this, the thesis proposes to host more service functionality on mobile devices themselves. In this way, mobile devices are often able to serve requests either locally or by contacting neighbor devices over short-range communications. Two novel mobile service architectures are proposed for the two different types of mobile services: traditional non-geo-locality services and emerging geo-locality services.;A service is termed to have the geo-locality property when its data are both generated (sensed or input) and consumed locally, i.e., within a specific geographic region. In other words, for services that have the geo-locality property, only mobile devices within a specific geographic region R can generate the necessary service data and only devices within the very same region R are interested in consuming it. For non-geo-locality services, the data is generated either by cloud servers or by users regardless of their location. Data generation and/or consumption are also typically a function of the users' personal interests and not of their geographic location.;For traditional non-geo-locality services, this thesis proposes the Pocket Cloudlets architecture. The Pocket Cloudlets architecture is a mobile device-resident caching scheme that serves cloud service requests locally on the device, when possible, significantly reducing the need for slow and costly long-range communications. The Pocket Cloudlets architecture leverages both personal user and collaboratively-generated community access patterns to selectively replicate parts of the cloud service locally on the mobile device. Pocket Cloudlets are also adaptively updated by detecting emerging popular service data items and prefetching them on the mobile device. Our analysis shows that the proposed Pocket Cloudlets architecture can effectively augment several traditional cloud services, like mobile web search. PocketSearch, our prototyped mobile search pocket cloudlet, reduces the average service access time by a factor of 2.7x and the required communication bandwidth by 66%.;For emerging geo-locality services, the thesis presents the Region-Resident Services (RegReS) middleware. RegReS allows a rich set of emerging geo-locality services to be fully supported on confederations of mobile devices. Mobile devices collaborate to provide a geo-locality service within a specified region and over a specified service lifetime by utilizing only short-range ad-hoc communications. In this way, RegReS completely eliminates the need for long-range cellular communications. Although mobile devices are becoming increasingly powerful, their resources are constrained and should be used judiciously. RegReS enables the efficient provision of geo-locality services by allowing services to specify their target service carrier density. Only as many service carriers as specified are subsequently maintained by RegReS. As opposed to previously proposed static schemes, RegReS employs a fully distributed, collaborative and adaptive estimation scheme to track the existing service carrier density and make decisions about the spawning of new carriers, when necessary. Thanks to collaboration and adaptation, RegReS can maintain the desired density with only 16% mean absolute error across a wide range of configurations.;To demonstrate the potential of collaborative mobile device-based computing platforms that are enabled by middleware like RegReS, the thesis presents a rich set of novel services that such platforms can enable. More specifically, the thesis focuses on the type of services that are typically most challenging and resource-intensive (e.g., CPU), camera-based services. We introduce five such services and prototype SignalGuru, a camera-based traffic signal schedule advisory service. SignalGuru leverages opportunistic sensing and collaboration across windshield-mounted smartphones and their cameras to provide drivers with information about the schedule of traffic signals ahead. Results from two deployments of SignalGuru, using iPhones in cars in Cambridge (MA, USA) and Singapore, show that traffic signal schedule can be predicted with very good accuracy. On average, SignalGuru comes within 0.66s, for pre-timed traffic signals and within 2.45s, for traffic-adaptive traffic signals. Feeding SignalGuru's predicted traffic schedule to our Green Light Optimal Speed Advisory (GLOSA) application, our vehicle fuel consumption measurements show savings of 20.3%, on average. SignalGuru information can also be fed into several other envisioned applications to further improve fuel efficiency, vehicle flow, travel time and road safety. The example of SignalGuru illustrates that with collaboration and adaptation, mobile device-based computing platforms can support a rich set of challenging services without the help of cloud servers and the associated long-range communications.;Overall, this thesis advocates and demonstrates that, with collaboration and adaptation, mobile devices can effectively support a rich set of services and thus reduce the need for slow and costly long-range cellular communications to cloud servers. Several traditional cloud services that operate on very large amounts of data can be selectively and adaptively hosted on mobile devices. Furthermore, novel mobile services that may seem prohibitively resource-intensive and challenging can be enabled and hosted on confederations of collaborating mobile devices. In this way, the mobile user experience can be greatly improved and a significant amount of the increasingly scarce long-range communication bandwidth can be saved.
机译:由于智能手机和个人媒体播放器等移动设备允许用户访问,因此移动设备(例如智能手机和个人媒体播放器)的普及程度最近显着提高。预计在不久的将来,联网的车辆计算设备将变得司空见惯,因为它们将实现广泛的驾驶员辅助服务。但是,移动服务无处不在的普及已因其糟糕的用户体验而受阻。对移动云服务的访问通常发生在速度较慢且昂贵的远程蜂窝通信上。;本文着重于通过减少对昂贵的远程蜂窝通信的需求来改善移动服务的用户体验。为了实现这一点,本文提出在移动设备本身上托管更多的服务功能。这样,移动设备通常能够在本地或通过短距离通信联系邻居设备来服务请求。针对两种不同类型的移动服务,提出了两种新颖的移动服务体系结构:传统的非地理位置服务和新兴的地理位置服务。;当服务的数据都生成(感知)时,该服务被称为具有地理位置属性或输入)并在本地(即特定地理区域内)消费。换句话说,对于具有地理位置特性的服务,只有特定地理区域R内的移动设备才能生成必要的服务数据,只有非常相同的区域R内的设备才有兴趣使用它。对于非地理区域服务,数据由云服务器或用户生成,无论其位置在哪里。数据的生成和/或使用通常也取决于用户的个人利益,而不是其地理位置。;对于传统的非地理位置服务,本文提出了Pocket Cloudlets体系结构。 Pocket Cloudlets体系结构是一种驻留在设备上的移动设备缓存方案,在可能的情况下,可以在设备上本地服务于云服务请求,从而大大减少了对缓慢而昂贵的远程通信的需求。 Pocket Cloudlets架构利用个人用户和协作生成的社区访问模式来选择性地在移动设备上本地复制部分云服务。通过检测新兴的流行服务数据项并在移动设备上预取它们,还可以自适应地更新Pocket Cloudlets。我们的分析表明,提出的Pocket Cloudlets体系结构可以有效地增强一些传统的云服务,例如移动Web搜索。 PocketSearch是我们的原型移动搜索袖珍Cloudlet的原型,可将平均服务访问时间减少2.7倍,并将所需的通信带宽减少66%。 。 RegReS允许在移动设备联合会上完全支持丰富的新兴地理区域服务集。通过仅利用短距离自组织通信,移动设备协作以在指定区域内并在指定服务寿命内提供地理定位服务。这样,RegReS完全消除了对远程蜂窝通信的需求。尽管移动设备变得越来越强大,但其资源却受到限制,应谨慎使用。 RegReS通过允许服务指定其目标服务运营商密度来实现高效的地理定位服务。 RegReS随后仅维护指定数量的服务运营商。与以前提出的静态方案相反,RegReS采用完全分布式,协作和自适应的估计方案来跟踪现有的服务载波密度,并在必要时做出有关产生新载波的决策。得益于协作和适应,RegReS可以在广泛的配置范围内以16%的平均绝对误差保持所需的密度。为了证明由RegReS等中间件支持的基于协作移动设备的计算平台的潜力,本文提出了此类平台可以启用的一系列丰富的新颖服务。更具体地说,本文着重于通常最具挑战性和资源密集型(例如,CPU),基于照相机的服务的服务类型。我们介绍了五种此类服务,以及基于摄像头的交通信号时间表咨询服务SignalGuru的原型。 SignalGuru利用安装在挡风玻璃上的智能手机及其摄像头的机会感应和协作,为驾驶员提供有关前方交通信号灯时间表的信息。两次部署SignalGuru的结果表明,在剑桥(美国马萨诸塞州)和新加坡的汽车上使用iPhone时,可以非常准确地预测交通信号的时间表。平均而言,SignalGuru在0.66s之内,用于预定时交通信号,在2.45s之内,用于适应交通的交通信号。将SignalGuru的预测交通时间表输入到我们的绿灯最佳速度咨询(GLOSA)应用程序中,我们的车辆油耗测量结果表明平均可节省20.3%。 SignalGuru信息也可以输入到其他一些预想的应用程序中,以进一步提高燃油效率,车辆流量,行驶时间和道路安全。 SignalGuru的示例说明,通过协作和适应,基于移动设备的计算平台无需云服务器和相关的远程通信即可支持一组具有挑战性的服务。总体而言,本文主张并证明,通过通过协作和适应,移动设备可以有效地支持丰富的服务集,从而减少了对云服务器进行缓慢而昂贵的远程蜂窝通信的需求。可以在移动设备上有选择地自适应地托管几种基于大量数据的传统云服务。此外,可以启用看起来似乎过于耗费资源和挑战性的新颖移动服务,并将其托管在协作移动设备联合会上。这样,可以极大地改善移动用户的体验,并且可以节省大量日益稀缺的远程通信带宽。

著录项

  • 作者

    Koukoumidis, Emmanouil.;

  • 作者单位

    Princeton University.;

  • 授予单位 Princeton University.;
  • 学科 Engineering Computer.;Computer Science.
  • 学位 Ph.D.
  • 年度 2012
  • 页码 214 p.
  • 总页数 214
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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