CREAM: Coordination and Reliability Mechanisms for Adaptive Mobile Middleware

CREAM:自适应移动中间件的协调和可靠性机制

基本信息

  • 批准号:
    EP/C544773/2
  • 负责人:
  • 金额:
    --
  • 依托单位:
  • 依托单位国家:
    英国
  • 项目类别:
    Fellowship
  • 财政年份:
    2008
  • 资助国家:
    英国
  • 起止时间:
    2008 至 无数据
  • 项目状态:
    已结题

项目摘要

The number of mobile phones in Europe is higher than the number of personal computers. The number of devices surrounding our daily life, including tiny sensors, is rising exponentially. However, the software and communication mechanisms used to network these devices are still the ones that we have been devised 30 years ago for standard computer systems. Mobile networks are by orders of magnitude more dynamic than traditional systems and have often less resources (energy, memory, bandwidth). This calls for a radical change in the communication mechanisms applied. The proposed work will devise novel mechanisms for the communication among networked mobile devices. These mechanisms will have to combine spatial and temporal concerns in order to be able to cope with the dynamicity and the resource limitations of mobile systems. To understand and reason about these concerns, we will investigate their formal underpinning through appropriate calculi. Reliable communication is usually very expensive in terms of resources but sometimes needed: we will devise new techniques for obtaining different levels of reliability through dynamic prediction of network behaviour. New methods for collecting and sharing data will be designed, including novel adaptive transactions, which adjust to the variability of the network and to the resources available. We will evaluate the appropriateness of these mechanisms in small scale applications and in large scale simulations.
欧洲的移动的电话数量高于个人电脑数量。围绕我们日常生活的设备数量,包括微型传感器,正在呈指数级增长。然而,用于将这些设备联网的软件和通信机制仍然是我们30年前为标准计算机系统设计的那些。移动的网络比传统系统的动态性高出几个数量级,并且通常具有更少的资源(能量、存储器、带宽)。这就要求彻底改变所采用的沟通机制。拟议的工作将设计新的机制,网络移动的设备之间的通信。这些机制必须将联合收割机的空间和时间问题结合起来,以便能够科普移动的系统的动态性和资源限制。为了理解和推理这些问题,我们将通过适当的演算来研究它们的形式基础。可靠的通信通常是非常昂贵的资源,但有时需要:我们将设计新的技术,通过动态预测网络行为获得不同程度的可靠性。将设计收集和共享数据的新方法,包括新的自适应交易,这些交易将根据网络的可变性和可用资源进行调整。我们将评估这些机制在小规模应用和大规模模拟中的适当性。

项目成果

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Cecilia Mascolo其他文献

Stress Inference from Abdominal Sounds using Machine Learning
使用机器学习从腹音进行压力推断
Towards Adversarial Robustness with Early Exit Ensembles
通过早期退出集成实现对抗鲁棒性
Emotion Recognition from Speech Signals by Mel-Spectrogram and a CNN-RNN
通过 Mel 谱图和 CNN-RNN 从语音信号进行情绪识别
  • DOI:
  • 发表时间:
  • 期刊:
  • 影响因子:
    0
  • 作者:
    R. Sharan;Cecilia Mascolo;‡. Bj¨ornW.Schuller
  • 通讯作者:
    ‡. Bj¨ornW.Schuller
Denoising Cough Sound Recordings Using Neural Networks *
使用神经网络对咳嗽录音进行降噪*
Towards Open Respiratory Acoustic Foundation Models: Pretraining and Benchmarking
迈向开放呼吸声学基础模型:预训练和基准测试
  • DOI:
  • 发表时间:
    2024
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Yuwei Zhang;Tong Xia;Jing Han;Y. Wu;Georgios Rizos;Yang Liu;Mohammed Mosuily;Jagmohan Chauhan;Cecilia Mascolo
  • 通讯作者:
    Cecilia Mascolo

Cecilia Mascolo的其他文献

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{{ truncateString('Cecilia Mascolo', 18)}}的其他基金

MicroPhysio: In-Ear Microphone based Physiological Monitoring
MicroPhysio:基于入耳式麦克风的生理监测
  • 批准号:
    EP/Y035925/1
  • 财政年份:
    2024
  • 资助金额:
    --
  • 项目类别:
    Research Grant
GALE: Global Accessibility to Local Experience
GALE:全球可获取本地经验
  • 批准号:
    EP/K019392/1
  • 财政年份:
    2013
  • 资助金额:
    --
  • 项目类别:
    Research Grant
MOLTEN: Mathematics Of Large Technological Evolving Networks
MOLTEN:大型技术演进网络的数学
  • 批准号:
    EP/I017321/1
  • 财政年份:
    2011
  • 资助金额:
    --
  • 项目类别:
    Research Grant
FRESNEL: FedeRatEd Secure sensor NEtwork Laboratory
FRESNEL:FedeRatEd 安全传感器网络实验室
  • 批准号:
    EP/G069557/1
  • 财政年份:
    2010
  • 资助金额:
    --
  • 项目类别:
    Research Grant
WILDSENSING: A Hybrid Framework of Mobile and Sensor Nodes for Wildlife Monitoring
WILDSENSING:用于野生动物监测的移动和传感器节点的混合框架
  • 批准号:
    EP/E012914/2
  • 财政年份:
    2008
  • 资助金额:
    --
  • 项目类别:
    Research Grant
WILDSENSING: A Hybrid Framework of Mobile and Sensor Nodes for Wildlife Monitoring
WILDSENSING:用于野生动物监测的移动和传感器节点的混合框架
  • 批准号:
    EP/E012914/1
  • 财政年份:
    2007
  • 资助金额:
    --
  • 项目类别:
    Research Grant

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