Tutorial 1: Production scheduling and multi-agent transportation in complex industrial processes

                   -Ziyan Zhao, Assistant Professor, Northeastern University

Tutorial 2: Memetic Computation for Combinatorial Optimization

                 -Yangming Zhou, Associate Professor, Shanghai Jiao Tong University

Prof. Nirwan Ansari

Distinguished Professor of Electrical and Computer Engineering at the New Jersey Institute of Technology (NJIT), USA; IEEE Fellow, NAI Fellow; Editor-in-Chief of IEEE Wireless Communications

Title: On Green Internet of Things

Abstract: Internet of Things (IoT) networks are composed of essential communication infrastructures and edge devices, which enhance our understanding of the world and facilitate the efficient operation of modern life. However, large-scale IoT deployments inevitably result in unprecedented energy consumption, particularly for powering IoT networks. Specifically, communication infrastructures like cellular base stations significantly contribute to increasing global carbon emissions. Additionally, IoT wireless sensors, as edge devices, are projected to become some of the highest energy consumers in the near future. Recognizing the negative impact on the environment and climate change, the reliance on traditional, on-grid brown energy for IoT networks has garnered increasing attention. To meet global carbon peak and neutrality targets and establish an eco-friendly, energy-sustainable society, a transformative solution is the use of green (renewable) energy to power IoT networks. In this keynote, I will discuss several advanced technologies aimed at "greening" both communication infrastructures and edge devices, providing a pathway towards sustainable IoT networks.

Prof. Nei Kato

Full professor and the Dean with Graduate School of Information Sciences, Tohoku University, Japan; Fellow of The Engineering Academy of Japan; IEEE Fellow, IEICE Fellow; Editor-in-Chief of IEEE Internet of Things Journal

Title: Task Scheduling for Multi-Access Edge Computing in IRS-Aided Vehicular Networks

Multi-access Edge Computing (MEC) has played an important role in realizing intelligent beyond 5G (B5G) vehicular networks. The computation tasks of intelligent applications can be offloaded to and processed by near-end-user MEC servers to meet strict latency requirements. However, the latency of provided services is dependent on MEC processor scheduling and millimeter wave (mmWave) transmission conditions for the urban B5G vehicular networks. To alleviate the mmWave signal attenuation caused by buildings, Intelligent Reflecting Surface (IRS) has been regarded as efficient and prospective infrastructure. In this paper, we study the IRS-aided MEC-served vehicular networks and analyze the relationship between computation resource allocation and offloading policy at an intersection. Considering the vehicle mobility patterns, transmission conditions, and task sizes, we optimize the task scheduling by improving the allocation of limited processors and IRS resource. Moreover, the mutual interference among concurrent transmissions is taken into account. In this presentation, by assuming the moving directions available, a dynamic task scheduling algorithm is presented which considers both the communications and computations. The simulation results illustrate that the new scheme outperforms benchmark methods in terms of task offloading rate, computing rate, and finish rate for the IRS-aided MEC-served vehicular networks.

Prof. Yong Liang GUAN

Associate Vice President, Nanyang Technological University (NTU), Singapore; Professor, School of Electrical and Electronic Engineering, NTU, Singapore

Title: OAM Radio: A New Paradigm in Wireless Communication

Abstract – In contrast to the planewave radio of today which has a uniform wavefront of spatial phase distribution, Orbital Angular Momentum (OAM) radio has a vortex wavefront with spiralling spatial phase distribution. OAM radio offers new exciting wireless communication and sensing possibilities not achievable by planewave MIMO radio, such as increased data-carrying capacities in LOS channels, enhanced micro-Doppler detection capability, and angular separation of overlapped LOS signals by using meta-surface. However, OAM signals and transceivers are faced with their fair share of new challenges and limitations too.  In this talk, I will discuss some recent advances in OAM research in mitigating the challenges to realize the OAM promises.

Prof. ChangJun Jiang

Academician of the Chinese Academy of Engineering; Professor, Department of Computer Science and Technology, Tongji University, China

Title: 智能算网系统

报告摘要：

首先介绍了国家东数西算重大战略背景，分析了现状和问题；接着介绍了方舱计算的架构和特点，由此与东算西算固定网形成了舱网融合的智能算网系统，分析了它的创新优势，演示了同济智能算网系统；最后，指出了它的三步走计划及未来前景。