Sustainable Computing and Communication at the Edge (SONATA)

边缘可持续计算和通信 (SONATA)

• 批准号: EP/W035960/1
• 负责人: Deniz Gunduz
• 金额: $ 25.77万
• 依托单位: Imperial College London
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2022
• 资助国家: 英国
• 起止时间: 2022 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=EP%2FW035960%2F1
• 关键词: Sustainable; Computing; Communication; Edge; SONATA

Modern communication networks are rapidly evolving into sophisticated systems combining communication and computing capabilities. Computation at the network edge is the key to supporting many emerging applications, from extended reality to smart health, smart cities, smart factories and autonomous driving. SONATA is motivated by the fact that the large scale adoption of edge intelligence technology, while benefiting human productivity and efficiency, will result in a surge of data and computation in mobile networks, which, in turn, will exacerbate their already significant energy consumption. SONATA is an interdisciplinary effort to tame this growing energy demand by combining memristive hardware and energy harvesting technologies with novel machine learning algorithms and physical layer communication techniques. In particular, we want to combine the energy efficient in-memory computing and learning potential of memristive devices with an "over-the-air computation (OAC)" approach to edge learning, which turns the air from a purely communication medium to a computation unit. Our project not only aims at reducing the energy requirements of edge learning systems drastically, but also focuses on making them robust against stochastic failures, due to unreliable hardware or energy sources. We will exploit tools from circuit design, coding theory, wireless communications, machine learning and network science to achieve these goals. Results from SONATA will open up new directions for research and development of technologies that will allow mobile systems to offer the much anticipated communication and computing services in a sustainable manner.

现代通信网络正在迅速发展成为结合通信和计算能力的复杂系统。网络边缘的计算是支持许多新兴应用的关键，从延展实境到智能健康、智能城市、智能工厂和自动驾驶。SONATA的动机是，大规模采用边缘智能技术，虽然有利于人类的生产力和效率，但将导致移动的网络中的数据和计算激增，这反过来又会加剧其已经显着的能源消耗。SONATA是一个跨学科的努力，通过将忆阻硬件和能量收集技术与新型机器学习算法和物理层通信技术相结合，来驯服这种不断增长的能源需求。特别是，我们希望将联合收割机的内存计算和忆阻设备的学习潜力与“空中计算（OAC）”方法结合起来进行边缘学习，将空气从纯粹的通信介质转变为计算单元。我们的项目不仅旨在大幅降低边缘学习系统的能源需求，而且还专注于使它们能够抵御由于不可靠的硬件或能源而导致的随机故障。我们将利用电路设计，编码理论，无线通信，机器学习和网络科学的工具来实现这些目标。SONATA的成果将为技术研发开辟新的方向，使移动的系统能够以可持续的方式提供备受期待的通信和计算服务。

项目成果

Bayesian Over-the-Air Computation

• DOI: 10.1109/jsac.2022.3229428
• 发表时间: 2021-09
• 期刊: IEEE Journal on Selected Areas in Communications
• 影响因子: 16.4
• 作者: Yulin Shao;Deniz Gündüz;S. Liew

All You Need Is Feedback: Communication With Block Attention Feedback Codes

• DOI: 10.1109/jsait.2022.3223901
• 发表时间: 2022-06
• 期刊: IEEE Journal on Selected Areas in Information Theory
• 作者: Emre Ozfatura;Yulin Shao;A. Perotti;B. Popović;Deniz Gündüz

Semantic Communications With Discrete-Time Analog Transmission: A PAPR Perspective

离散时间模拟传输的语义通信：PAPR 视角

• DOI: 10.1109/lwc.2022.3232946
• 发表时间: 2023
• 期刊: IEEE Wireless Communications Letters
• 影响因子: 6.3
• 作者: Shao Y

Collaborative Semantic Communication for Edge Inference

• DOI: 10.1109/lwc.2023.3256006
• 发表时间: 2023-01
• 期刊: IEEE Wireless Communications Letters
• 影响因子: 6.3
• 作者: W. F. Lo;N. Mital;Haotian Wu;Deniz Gündüz

Beyond Transmitting Bits: Context, Semantics, and Task-Oriented Communications

• DOI: 10.1109/jsac.2022.3223408
• 发表时间: 2023-01-01
• 期刊: IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS
• 影响因子: 16.4
• 作者: Gunduz, Deniz;Qin, Zhijin;Chae, Chan-Byoung
• 通讯作者: Chae, Chan-Byoung