Low-Latency and High-Security Internet of Things:
The Internet of Things (IoT) changes our daily lives, offering novel applications in an ecosystem of smart and highly heterogeneous devices. In typical IoT scenarios, such as smart cities, smart factories, smart transportation, smart homes and telemedicine, devices need to be connected via high-speed Internet for efficient and reliable communications and faster response times. In addition, the digital industry changes constantly due to advanced technologies, leading to more cyber threats and attacks. Therefore, we need to provide a low-latency and high-security communications in IoT environment.
This workshop aims to bring together contributions from researchers and practitioners focusing on the aforementioned challenges. We solicit original research work in various areas of importance to IoT. Topics of interest include, but are not limited to, the following:
- Intelligent mobile edge computing
- Block-chain based IoT networks
- Distributed, cognitive machine learning for IoT networks
- Mobile broadband reliable low latency communication (MBRLLC)
- Mobile ultra-broadband communications
- Offloading method design for edge management
- Ultra-reliable low latency communications (URLLC)
- Massive Ultra-reliable low latency communications (MURLLC)
- Network architecture and protocol design for high reliability-latency guarantees
- Network slicing and network function virtualization
- Cloud and network security
- Block-chain based security for IoT
- Big data security in IoT
- Trust models and threat issues in IoT
- Service delivery models in IoT
- Privacy and security in IoT
Compressive Sensing:
Compressed sensing (CS), also known as compressive sampling, has made remarkable advances in many different fields in recent years. As an emerging tool for sparse signal acquisition and reconstruction, CS is capable of recovering sparse signals based on measurement data with much smaller sampling rate than the Shannon/Nyquist sampling by exploiting the sparse features of the signals and the properties of the sensing matrices. Thereby, CS has been widely applied in a variety of areas such as signal processing, wireless communications, image processing, computational biology, and remote sensing. Whilst it is believed that CS will continue to be a useful tool for the ever-growing applications, it is pressing to identify and address various new challenges which are deemed to bring in tremendous opportunities for academic and industrial communities.
The workshop aims to attract researchers from academia and industry to share their recent discovery in CS and beyond, to foster the exchange of new ideas as well as future collaborations. We seek original unpublished works in related areas of CS. Topics of interest include, but are not limited to:
- Efficient Compressive Sensing Recovery Algorithms·
- Compressive Sensing Theories/Applications in Signal Processing
- Compressive Sensing Theories/Applications in Communications
- Compressive Sensing Theories/Applications in Natural Image, Hyper Spectral Image, Radar,MRI, etc.
- Compressive Sensing Theories/Applications in Remote Sensing
- Compressive Sensing Theories/Applications in Natural Language Processing
- Compressive Sensing Theories/Applications in Encryption
- Compressive Sensing Theories/Applications in Multimedia
- Compressed Sensing Matrices Design
- Innovative Deep Learning Architectures with Compressive Sensing
- Hardware Implementations of Compressive Sensing
Submission Guidelines:
Authors are invited to submit original papers of no more than 6 pages (standard IEEE proceedings, two-column, 10 pt font, etc.), including figures, tables, and references, in PDF format. Papers should be submitted through EDAS: https://edas.info/newPaper.php?c=29710&track=112452
Workshop Organizers:
Low-Latency and High-Security Internet of Things:
Prof. Junhui Zhao, East China Jiaotong University, China, jhzhao@ecjtu.edu.cn
Prof. Minghua Xia, Sun Yat-sen University, China, xiamingh@mail.sysu.edu.cn
Asso. Prof. Yansha Deng, King’s College London, UK, yansha.deng@kcl.ac.uk
Compressive Sensing:
Prof. Jinming Wen, Jinan University, jinming.wen@mail.mcgill.ca
Prof. Yi Fang, Guangdong University of Technology, fangyi@gdut.edu.cn
Prof. Zilong Liu, University of Essex, zilong.liu@essex.ac.uk
Prof. Zhengchun Zhou, Southwest Jiaotong University, zczhou@126.com
Important Dates:
Workshop Paper Submission: Jun. 1st, 2022 Jun. 16th, 2022
Workshop Paper Acceptance: Jul. 10th, 2022
Workshop Paper Camera-Ready: Jul. 24th, 2022