Events

SHIFT EVENT

[SHIFT] Seminar: 16 Nov, 2018

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    [SHIFT] 2015级本科生毕业设计课题

    欢迎同学踊跃报名!

    1. FaceID低功耗任务卸载: 随着物联网的发展,低功耗应用也越来越多。在一些需要识别和监控的地方,可能无法提供无限的能量供应而只能依靠电池运行。这里,我们就需要研究低功耗下如何更好完成任务。FaceID可以很好的识别用户,我们希望研究如何在低功耗终端节点,比如物联网节点,机器人节点等,和具有强计算能力的云雾中心进行任务卸载一方面降低终端节点的计算和传输功耗,一方面提供性能优秀的FaceID功能。

    2. 智慧交通信号管理: 现在城市一个中心问题就是交通拥堵。阿里巴巴的“城市大脑”也致力于解决这个问题。我们希望给予各个交通路口信号灯以智能处理能力,通过每个交通灯的个体智能实现相近路口的协同管理以充分降低拥堵,减少车辆路上通行时间。这个课题首先是搭建交通控制仿真平台,基于强化学习等工具,在此基础上探索如何为每个交通灯建立起最佳决策机制。

    3. 雾计算网络中的学习与博弈: 雾计算作为一种新兴的计算模式,通过将计算资源从云端到边缘连续分布实现无所不在的实时计算。在雾计算网络中,在卸载一个用户节点上的计算任务时,该用户节点需要做出如下决策:卸载到哪一个雾节点,卸载多少计算量到该雾节点。由于计算资源的异构和分布特性,用户很难提前知晓全局系统信息。为了做出好的决策,用户需要自己去有效地探索学习系统并根据已有信息做出合理决策。同时,在存在多用户是,用户之间以及雾计算节点之间的博弈都需要我们进行深入研究。

    4. 基于雾计算共享平台的视频渲染: 视频渲染需要极大量的计算资源。云计算模式可以满足计算的需求,可是一方面云计算成本较高,另一方面将大量的视频数据传输到云需要较大的网络带宽开销,有时候甚至成为不可完成对任务。一个选择是使用雾计算技术,将就近大量闲置的计算资源组织起来,供视频渲染使用。本课题拟研究如何组织就近的计算资源,以及管理和协调雾计算资源,高效地为视频渲染服务。

    5. 雾计算支持的智慧楼宇: 智慧楼宇需要大量的计算,其中有些需要处理大量数据,有些需要极低时延。因为应用众多,如果每一套智能系统均部署一套基础设施,将造成极大浪费。雾计算可以使能资源共享,数据共享,可以通过软件定义,灵活变化和部署服务。本课题研究雾计算支持的智慧楼宇比如能源管理,安全管理等应用。

    6. 多机器人联合定位制图: 单个移动机器人定位制图消耗时间相对较长,并且需要消耗本地的计算资源、存储资源和电池电量,另外制作高精度地图需要高精度传感器和高性能处理器,成本较高。利用基于雾计算的多机器人联合定位制图可以有效加快处理时间,将传感器数据处理和建图卸载到雾节点上完成,机器人的资源消耗将大力降低,使用精度稍低的传感器和处理器,通过多个机器人、雾节点协同处理可以提高地图精度,降低机器人成本。

    7. 基于雾计算的无人机导航: 无人机具有广阔的应用前景,其应用场景为典型时延和可靠性敏感型业务,比如控制飞行速度、高度、路线需要及时处理环境地理信息,涉及多种应用比如图像识别、目标跟逐、空间定位、实时检测等。雾计算能够协助无人机处理较大计算量的任务,本课题研究雾计算辅助下的无人机导航,能够按照设定,避开障碍物、精准快速地到达目的位置。

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    [SHIFT] Seminar

    Prof. Youlong Wu & Zhaowei Zhu, 16 Nov 2018

    Time: Nov 16, 11:00—13:00

    Location: Room 1C-502, SIST Building

    Part 1

    Title: Caching-Aided Communication and Computation

    Speaker: Prof. Youlong Wu

    Abstract: The Fog architecture has been recently attracted great attention since it could better satisfy the service requirements of the emerging Internet-of-Things (IoT). The main driving vision for Fog computing is to leverage the significant amount of dispersed computing resources at the edge of the network to provide much more user-aware, resource-efficient, scalable and low-latency services for IoT. This talk will consider a new way that using coding to exploits significantly reduce the communication load. An approximately optimal trade-off between the “computation load” and the “communication load” is analysed.

    Bio: Youlong Wu obtained his B.S. degree in electrical engineering from Wuhan University, Wuhan, China, in 2007. He received the M.S. degree in electrical engineering from Shanghai Jiaotong University, Shanghai, China, in 2011. In 2014, he received the Ph.D. degree at Telecom ParisTech, in Paris, France. In December 2014, he worked as a postdoc at the Institute for Communication Engineering, Technical University Munich (TUM), Munich, Germany. In 2017, he joined the School of Information Science and Technology at ShanghaiTech University. He obtained the TUM Fellowship in 2014 and is an Alexander von Humboldt research fellow. His research interests include information theory and wireless communication.

    Part 2

    Title: Leveraging Online Learning in Task Offloading

    Speaker: Zhaowei Zhu

    Abstract: 1. BLOT: Bandit Learning-based Offloading of Tasks in Fog-Enabled Networks
    2. Online optimal task offloading with one-bit feedback

    Bio: Zhaowei Zhu received the B.S. degree from the University of Electronic Science and Technology of China, Chengdu, China, in 2016. He is currently pursuing the M.S. degree with ShanghaiTech University, Shanghai, China, under the supervision of Prof. X. Luo. His research interests include the distributed machine learning and signal processing methods for mobile networks, fog computing, and signal processing on graph.

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    [SHIFT] Seminar

    Prof. Dengji Zhao & Zhaohui Yan, 9 Nov 2018

    Time: Nov 9, 11:00—13:00

    Location: Room 1C-502, SIST Building

    Part 1

    Title: Diffusion Mechanism Design in Social Networks

    Speaker: Prof. Dengji Zhao

    Abstract: The literature of mechanism design has traditionally assumed that the set of participants are fixed and are known to the mechanism (i.e. the market owner) in advance. However, in practice the market owner can only directly reach a small number of participants. In order to get more participants, the market owner often needs costly promotions via, e.g., Google, Facebook or Twitter, but the impact of the promotions is often unpredictable. That is, the revenue-increase that the market owner gets from the promotions may not cover the costs of the promotions. To solve this dilemma, we build the promotion inside the market mechanism without using any advertising platform. The promotion guarantees that the market owner will never lose and does not need to pay if the promotion is not beneficial to her. This is achieved by incentivizing people who are aware of the market to further propagate the information to their neighbors. They will be rewarded only if their diffusion effort is beneficial to the market owner, so the promotion is cost-free to some extent. This tutorial will discuss how to design such cost-free promotions, analyze some essential examples and show the rich challenges we still face.

    Bio: Dr. Dengji Zhao is an Assistant Professor at ShanghaiTech University, China. He received double Ph.D. (2012) degrees in Computer Science from University of Western Sydney and University of Toulouse, and received double M.Sc. (2009) degrees in Computational Logic from Technische Universität Dresden and Universidad Politécnica de Madrid. Before joining ShanghaiTech, he was a postdoc (2013-2014) working with Prof. Makoto Yokoo (the first AAAI Fellow in Asia) and a research fellow (2014-2016) working with Prof. Nick Jennings (the first Regius Professor of Computer Science, UK).

    Part 2

    Title: Introduction to Deep Reinforcement Learning and a DQN-based offloading scheme in Ad-hoc Mobile Clouds

    Speaker: Zhaohui Yan

    Abstract: Introduction to fundamental of Deep Reinforcement Learning. Include:
    1. Introduction to Reinforcement Learning;
    2. Dynamic planning method;
    3. Basic ideas of Monte-Carlo method and Temporal-Difference method;
    4. Basic ideas of Value Function Approximation method, Q-learning, Deep Q-Learning;
    5. An example of application of DQN in the field of offloading scheme of edge computing.

    Bio: M.S. Student, SIST, ShanghaiTech University; Institute of Fog Computing Technology (SHIFT)

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    [SHIFT] Seminar

    Dr. Wuxiong Zhang & Youyu Tan, 2 Nov 2018

    Time: Nov 2, 11:00—13:00

    Location: Room 1C-502, SIST Building

    Part 1

    Title: 物联网应用机会与对信息技术需求的思考

    Speaker: Prof. Cunqing Hua

    Abstract: 物联网技术与应用发展日新月异,深刻改变了公共服务、工业生产、人们生活的方方面面。另一方面,区块链、人工智能等新技术不断涌现。如何发掘物联网行业应用需求,并将信息技术加以融合,从而提供更加有效的供给与服务,既是市场,也是科研院校要考虑的重要问题。本报告将对物联网应用与技术的互相促进与融合,提供一些有意义的思考与建议。

    Bio: 张武雄,博士,中国科学院上海微系统与信息技术研究所副研究员,福州物联网开放实验室有限公司副总裁,上海无线通信研究中心常务副主任。2008年获上海交通大学学士学位,2013年获得中国科学院大学博士学位,2011年在英国赫瑞.瓦特大学短期学术交流。主持/参与国家自然科学基金面上项目、国家科技重大专项、上海市科委、经信委重点项目二十余项。目前主要从事物联网与智慧城市关键技术研究与应用。发表学术论文40余篇,其中SCI/EI索引35篇,申报国内发明专利11项、国际PCT专利1项,获2015年中国通信学会自然科学二等奖1项、2016年中国通信学会技术发明奖一等奖1项。

    Part 2

    Title: Learning-Based Task Offloading for Dynamic Fog Network

    Speaker: Youyu Tan

    Abstract: Fog computing is a promising paradigm to address the latency issue in cloud computing, it enables provisioning resources and services closer to end devices. Limited by the computing and storage resources, end devices offload the computation-intensive tasks to the fog devices nearby. We consider a dynamic fog network with unpredictable arrival and departure and moving action of fog nodes. We rigorously formulate the task offloading problem for such a dynamic fog network as an online stochastic optimization problem, and design offload policies for stationary status and Non-stationary status aiming to minimize the average latency.

    Bio: M.S. Student, SIST, ShanghaiTech University; Institute of Fog Computing Technology (SHIFT)

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    [SHIFT] Seminar

    Prof. Cunqing Hua & Hanyu Zhu, 26 Oct 2018

    Time: Oct 26, 11:00—13:00

    Location: Room 1C-502, SIST Building

    Part 1

    Title: Delay Optimal Concurrent Transmission in Dual Connectivity Networks

    Speaker: Prof. Cunqing Hua

    Abstract: Dual Connectivity (DC) is one of the key technologies standardized in 3GPP Release 12, which attempts to increase the throughput of users by allowing the user equipment (UE) to maintain dual connections with MeNB and SeNB simultaneously. In this talk, we focus on the 3C scenario of the DC architecture whereby the downlink data is split at PDCP layer of the MeNB and transmitted to the UE via the associated MeNB and SeNB concurrently. In this case, an out-of-order packet delivery problem may occur at the UE due to the dynamic channel conditions over two links, as well as the delay over the non-ideal backhaul link between MeNB and SeNB, which will introduce an extra delay for the procedure for re-ordering the packets. We firstly introduce two packet dispatching schemes, the state-independent packet dispatching (SIPD) policy, and the state-dependent packet dispatching (SDPD) policy, which try to mitigate the packet out-of-order problem by proper traffic splitting across the MeNB and SeNB links based on their queueing states. We then propose a RaptorQ based concurrent transmission scheme (DCRQ), which can effectively eliminate the out-of-order problem since the UE can decode the original data while receiving enough encoded symbols from either MeNB or SeNB. We present the detailed protocol design for the DCRQ scheme, and theoretical results are derived to characterize the delay performance of the DCRQ scheme. The simulation results are provided to illustrate the performance of the proposed scheme.

    Bio: 化存卿,教授,博导。2000年7月获中国科学技术大学电子工程学系学士学位,2002年8月和2006年8月先后获香港中文大学讯息工程学系硕士和博士学位,2006年9月至2008年12月在美国德州休斯顿大学从事博士后研究工作,2008年12月至2011年6月担任浙江大学信息与电子工程学系副教授,2011年7月加入上海交通大学信息安全工程学院,目前是上海交通大学网络空间安全学院教授。研究方向主要涉及下一代无线通信系统(5G)、无线网络及安全、分布式机器学习等领域,已在IEEE Trans. on Mobile Computing, IEEE Trans. on Wireless Communication, IEEE Trans. on Vehicular Technology等国际期刊和IEEE INFOCOM, ICC, Globecom等国际会议上发表论文八十余篇论文,申请国际PCT及国内发明专利五项。现担任International Journal of Ad Hoc Networking Systems (IJANS)副主编,International Journal of Computer Networks (IJCN)编委,IEEE ICC, Globecom等国际会议技术委员会委员。先后承担了国家自然科学基金、国家973项目子课题、国家863项目子课题、国家重大专项子课题等项目,并与中国移动、国家电网、中国航天科技集团、华为、中兴等企业有多项合作项目。

    Part 2

    Title: Optimal Interconnection for Relative Calibration in Massive MIMO

    Speaker: Hanyu Zhu

    Abstract: When deploying massive multiple-input multiple-output in time-division duplex mode, it is necessary to calibrate all the M antennas at the base station (BS) to restore the end-to-end uplink/downlink channel reciprocity. We examine the relative self-calibration performance where different BS antennas are interconnected via hardware transmission lines. First, we study the relative calibration performance with an arbitrary interconnection. Next, with only (M-1) transmission lines, we obtain the closed-form expression for the Cramer-Rao Bound (CRB) in estimating the calibration coefficients associated with each antenna. Based on the derived CRB expression, we further prove that the star interconnection is optimal for relative self-calibration due to its lowest total CRB when some mild conditions are met.

    Bio: PhD Student, SIST, ShanghaiTech University; DIAL; Institute of Fog Computing Technology (SHIFT)

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    [SHIFT] Seminar

    Prof. Yuanming Shi & Fuqian Yang, 19 Oct 2018

    Time: Oct 19, 11:00—13:00

    Location: Room 1C-502, SIST Building

    Part 1

    Title: Nonconvex Demixing from Bilinear Measurements

    Speaker: Prof. Yuanming Shi

    Abstract: Demixing a sequence of source signals from the superposition of noisy bilinear measurements is a generalized mathematical model for blind demixing with blind deconvolution. It is prevalent across the areas of machine learning, data analysis, signal and image processing. However, state-of-the-art convex methods for blind demixing via semidefinite programming are computationally infeasible for large-scale problems. Although the existing nonconvex algorithms are able to address the scaling issue, they normally require proper regularization and careful initialization to establish optimality guarantees. To address the limitations of exiting methods, we develop a provable nonconvex demixing procedure via Wirtinger flow, much like vanilla gradient descent, to harness the benefits of regularization free, random initialization, fast convergence rate, as well as computational and statistical guarantees. This is achieved by exploiting the benign geometry of the high-dimensional statistical estimation problem, thereby revealing that Wirtinger flow enforces the regularization-free iterates in the region of strong convexity and qualified level of smoothness where the step size can be chosen aggressively. Time permitting, I will discuss how to develop the Riemannian trust-region algorithm with random initialization to solve the blind demixing problem with fast convergence rate and low iteration cost. This algorithm is guaranteed to converge to an approximate local minimum.

    Bio: Dr. Yuanming Shi received the B.S. degree in electronic engineering from Tsinghua University, Beijing, China, in 2011. He received the Ph.D. degree in electronic and computer engineering from The Hong Kong University of Science and Technology (HKUST), in 2015, under the supervision of Prof. Khaled B. Letaief. Since September 2015, he has been with the School of Information Science and Technology in ShanghaiTech University, as a tenure-track Assistant Professor. He visited University of California, Berkeley, CA, USA, from October 2016 to February 2017, hosted by Prof. Martin J. Wainwright. Dr. Shi is a recipient of the 2016 IEEE Marconi Prize Paper Award in Wireless Communications, and the 2016 Young Author Best Paper Award by the IEEE Signal Processing Society. His research interests include learning, optimization, statistics and their applications to data analysis, mobile AI and intelligent IoT.

    Part 2

    Title: Optimal Interconnection Strategy for Self-Calibration in Massive MIMO System.

    Speaker: Fuqian Yang

    Abstract: In time-division duplexing (TDD) massive multiple-input multiple-output (MIMO) systems, the base station (BS) can rely on the channel reciprocity to obtain the downlink (DL) channel state information (CSI) with the acquired uplink (UL) CSI. In practice, the transmit and receive branches consists of different analog circuits, which break the end-to-end channel reciprocity. Calibration is thus necessitated to restore the channel reciprocity and enable efficient massive MIMO operation in TDD. This paper studies the interconnection strategy for self-calibration at the BS where different antennas are interconnected via hardware transmission lines. First, we show that a complex interconnection network can be decomposed into a set of daisy chain interconnection subnetworks. Then we derive closed-form Cramer-Rao lower bounds (CRLBs) for the unknown calibration coefficients under general conditions for full calibration. From the derived CRLBs, on the one hand, we prove the star interconnection is optimal when the total number of measurements is limited. On the other hand, we further show that the daisy chain interconnection outperforms the star interconnection when the time resources are limited. Numerical results corroborate our theoretical analyses.

    Bio: PhD Student, SIST, ShanghaiTech University; DIAL; Institute of Fog Computing Technology (SHIFT)

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    [SHIFT] Seminar

    Prof. Jun Wang & Xiaoyu Zhang, 12 Oct 2018

    Time: Oct 12, 11:00—13:00

    Location: Room 1C101 & 1C-502, SIST Building

    Part 1

    Title: 论机器意识的可能和实现 (On the Rise of Machine Consciousness)

    Speaker: Prof. Jun Wang

    Abstract: 在人类历史上,我们现在可以首次构建一个由算法驱动的社会。在这个社会中,许多人工智能实体会在一起“生活”,并相互学习、互动,最重要的是,它们会与人类交互。在本次演讲中,我将回顾狭义人工智能和机器学习研究的最新进展,并讨论我对通用人工智能路线图的个人观点。我将快速回顾近期的认识科学中对人类意识研究的现状,并指出当前的机器学习方法对智能化决策的优点与不足。在演讲最后部分,我会提出两个学科之间的潜在联系,并给出我们在强化学习研究中的一些最新尝试和行业应用。
    In this presentation, Professor Wang will review the latest development in AI and Machine Learning, and discuss his views on the general AI roadmap. He will look back the current status of human consciousness research in cognitive science and point out the advantages and disadvantages of current Machine Learning methods of intelligent decision making. In the final part of the presentation, he will present the potential links between two disciplines and give some latest attempts and industry applications in reinforcement learning research.

    Bio: 汪军,伦敦大学学院(UCL)计算机系教授,互联网科学与大数据分析专业主任。主要研究智能信息系统,主要包括数据挖掘、计算广告学、 推荐系统、机器学习、强化学习、生成模型等,已发表了100多篇学术论文, 多次获得最佳论文奖,在信息检索领域的权威出版物Foundation and Trends of Information Retrieval上出版两本学术专著。是国际公认的计算广告学 和智能推荐系统专家。2007年,在美国获得了由微软“超越搜索—语义计算 和互联网经济学奖”。此外,他还是2014年Yahoo! FREP的获奖者之一,ACM SIGIR/CIKM的领域主席,Springer Journal of Big Data的编委,也因在计 算广告数据科学的工业应用方面的突出成就,获得UCLB One-to-Watch Award 2016。
    Professor Jun Wang obtained his PhD degree in Delft University of Technology, the Netherlands; MSc degree in National University of Singapore, Singapore; and Bachelor degree in Southeast University, Nanjing, China. Currently, he is Chair Professor of Data Science, Computer Science, University College London, and Founding Director of MSc Web Science and Big Data Analytics. He is also Co-founder and Chief Scientist in MediaGamma Ltd, a UCL spin-out focusing on AI for intelligent audience decision making. His team won the first global real-time bidding algorithm contest with 80+ participants worldwide. He was a recipient of the Beyond Search Semantic Computing and Internet Economics award by Microsoft Research and also received Yahoo! FREP Faculty award. He has served as an Area Chair in ACM CIKM and ACM SIGIR. He was a technical advisor for startups such as Last.Fm, Passiv Systems, Massive Analytic, Context Scout, and Polecat, and had various projects with BT, Microsoft, Yahoo!, Alibaba etc.

    Part 2

    Title: MIDAR: Massive MIMO based Detection and Ranging -- Theoretical Analysis and Results

    Speaker: Xiaoyu Zhang

    Abstract: With the growing demand of location-based services in wireless communication systems, positioning has drawn increasing interest in both academia and industry. As one promising technology in 5G, massive multiple-input multiple-output (MIMO) can improve the spectral efficiency. Meanwhile, it is also an enabler to provide accurate localization. In some applications, e.g., autonomous driving and intelligent transportation systems, user behaviors including velocities and moving directions need to be detected in addition to positions. In this paper, we propose Massive MIMO based Detection and Ranging (MIDAR) to offer a solution for joint localization and behavior recognition by using the channel power spectrum in multiple domains.An angle-delay-Doppler power spectrum (ADD-PS) in tensor form is extracted from a mass of channel state information (CSI) as the 3-D fingerprint of a particular position with a certain behavior. On the one hand, by matching this fingerprint to a data set of pre-collected reference points, we can obtain improved localization performance and detect the user behavior at the same time. Two similarity criteria named direction cosine (DC) and chordal distance based kernel (CDBK) are considered. In particular, the CDBK metric based on tensor analysis can take full advantage of the geometrical structure of the multi-dimensional ADD-PS. On the other hand, by regarding the problem as a non-linear regression, we can apply deep learning techniques with 3-D convolution neural networks (CNNs) to obtain the inherent relationship from the ADD-PS to the location and behavior. Numerical results corroborate the feasibility of above schemes in MIDAR for joint localization and behavior recognition.

    Bio: PhD Student, SIST, ShanghaiTech University; DIAL; Institute of Fog Computing Technology (SHIFT)

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    FOG WORLD CONGRESS 2018

    San Francisco, October 1-3, 2018

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    Fog World Congress is back for its second year! Join members of the OpenFog Consortium and other fog computing leaders in the only multi-day conference on fog computing & networking. This year’s conference features a pre-conference day for tutorials and research papers, then two full days of keynotes; technical, industry and innovation tracks; an expanded expo area and plenty of networking.

    For more information, click here please.

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    [SHIFT] Seminar

    Prof. Xiliang Luo & Yang Liu, 28 Sep 2018

    Time: Sept 26, 11:00—13:00

    Location: Room 1C-502, SIST Building

    Part 1

    Title: DIAL雾计算研究探索

    Speaker: Prof. Xiliang Luo

    Abstract:
    1. MIDAR: Massive MIMO based Detection and Ranging
    2. Learn and Pick to Offload
    3. Intelligent Traffic Control

    Bio: Xiliang Luo received his Bachelor of Science degree in Physics from the Peking University, Beijing, China, in 2001, and his Master of Science and Doctor of Philosophy degrees in Electrical Engineering from the University of Minnesota at Minneapolis in 2003 and 2006, respectively. Xiliang Luo was with SPiNCOM research group led by Prof. Georgios B. Giannakis. After finishing his PhD studies, he joined Qualcomm and carried out cutting edge researches in Qualcomm Research at different posts: senior engineer (2006), staff engineer (2010), and then senior staff engineer (2013). His work in Qualcomm included: system design, analyses, and standardization of 3GPP LTE starting from initial Rel-8 till Rel-11. He was the designer of various enhancements to Qualcomm’s current LTE solutions and he led the designs of Qualcomm’s next generation LTE modem for heterogeneous networks from initial concepts to final completion. In August 2014, Xiliang Luo joined the ShanghaiTech University as an Associate Professor in the School of Information Science and Technology. His general research interests lie in signal processing, communications, and information theory. In particular, he is interested in researches combining information theory and signal processing theory that can shape and guide the designs of next generation wireless networks and information processing. Till now, Xiliang Luo has published more than 70 research papers in top journals and conferences. Meanwhile, he is the (co)-inventor of more than 70 US and international patents, majority of which have been adopted into the LTE and LTE-Advanced standards. He is currently the Co-Director of Shanghai Institute of Fog Computing Technology (SHIFT). He is also serving as an Editor for the IEEE Transactions on Wireless Communications.

    Part 2

    Title: AAMT: Anti-multipath Acoustic-based Motion Tracking using Extreme Learning Machine

    Speaker: Yang Liu

    Abstract: Motion tracking is attractive in what concerns a smart city environment, where citizens have to interact with Internet of Things (IoT) devices spread all around one particular city. In past years, motion tracking provides natural ways for users to interact with the IoT devices, such as the ability to recognize of a wide range of hand motion in real-time. Compared with dedicated hardware devices, mobile phones use reliable speakers and microphones, and can serve as ubiquitous devices for cheap acoustic-based motion tracking solutions, which are appropriate for low-power and low-cost IoT applications. However, for complex indoor environments, it is very difficult for acoustic-based methods to achieve accurate motion tracking due to multipath fading and limited sampling rate at mobile devices. In this paper, a new method called Combating Acoustic Multipath using Extreme Learning Machine (CAME) is proposed to mitigate the effects of multipath fading on received signals. Based on CAME, a novel fine-grained motion tracking method is developed to calculate the moving distance based on the phase change of acoustic signals, and track the corresponding motion in two-dimensional plane by using multiple speakers. An Anti-multipath Acoustic Motion Tracking (AAMT) method is then proposed and implemented on standard Android smartphones. Experiment results show, without any specialized hardware, AAMT can achieve an impressive millimeter-level accuracy for localization and motion tracking applications in multipath fading environments. Specifically, the measurement errors are less than 2 mm and 4 mm in one-dimensional and two-dimensional scenarios, respectively.

    Bio: PhD Student, Shanghai Institute of Microsystem and Information Technology (SIMIT),CAS; Institute of Fog Computing Technology (SHIFT)

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    [SHIFT] Seminar

    Ming-Tuo Zhou & Zening Liu, 21 Sep 2018

    Time: Sept 21, 11:00—13:00

    Location: Room 1C-502, SIST Building

    Part 1

    Title: The Deployment and Application of FastNet (Fog as a Service Technology Network)

    Speaker: Ming-Tuo Zhou

    Abstract: The Deployment and Application of FastNet (Fog as a Service Technology Network) at ShanghaiTech University.

    Bio: Ming-Tuo Zhou received his BSc degree from Hunan University in 1997, MEng degree from Chongqing University of Posts and Telecommunications in 2000, and PhD degree from Asian Institute of Technology in 2003. He joined Shanghai Institute of Microsystem and Information Technology (SIMIT), Chinese Academy of Sciences (CAS) in September 2016, and now is the vice-chief technology officer and the head of the Application & Test Department. He was a senior research scientist at the Smart Wireless Laboratory of the (Japan) National Institute of Information and Communications Technology (NICT) Singapore Representative Office during July 2004 to August 2016, and a research specialist of the Finland Government Program, Asian Institute of Technology during January to June 2004. He has co-authored about 70 technical papers, 6 book chapters, and co-edited two technical books. He was the Technical Co-Editor of IEEE 802.16n and IEEE 802.16.1a, a voting member and technical contributor of IEEE 802.11, 802.15, and 802.16 Working Groups, and a member of the Test and Certification Working Group of Wi-SUN Alliance. He has served as Technical Program Committee member, Finance Chair, Local Arrangement Chair, and Session Chair at more than 40 international conferences including ICC, GLOBECOM, and PIMRC. His current research interests include fog computing, wireless sensor networks, industrial Internet of things, Industry 4.0, cyber-physical systems, 5G, advanced channel modeling, and big data/machine learning applications in wireless communications.

    Part 2

    Title: DOCT: Distributed Offloading of Computation Tasks in Heterogeneous Fog Networks

    Speaker: Zening Liu

    Abstract: Fog computing, which enables low-latency, high reliability and privacy-preservation services along the cloud-to-things continuum, has risen as a promising architecture for Internet of Things (IoT) and future intelligent networks. For a typical fog network consisting of many heterogeneous fog nodes (FNs), some of them have different computation tasks while some have spare computation resources. How to effectively map multiple computation tasks into multiple helper nodes (HNs) in a distributed manner to minimize every task’s delay is a fundamental challenge. To tackle this problem, the multi-task multi-helper (MTMH) mapping challenge is formulated as a game for distributed offloading of computation tasks (DOCT). The existence of nash equilibrium (NE) is proven for the general DOCT game with non-splitable tasks, as well as splitable tasks. Considering these cases, two effective DOCT algorithms are proposed for achieving the NE in the DOCT game and the efficiency of solutions is also analyzed, i.e., price of anarchy (PoA). Analytical and simulation results show the proposed algorithms can offer much better performance, in terms of system-wide average service delay and individual satisfaction level, comparing to other computation offloading schemes.

    Bio: PhD Student, SIST, ShanghaiTech University; University of Chinese Academy of Sciences; Institute of Fog Computing Technology (SHIFT)

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    Security in Blockchain
    &
    Blockchain based Cloud Computing and iExec Blockchain Ecosystem

    Speaker: Dr. Lei Zhang & Victor Bonhomme
    Date: 2018/07/09

    Speaker:   Dr. Lei Zhang & Victor Bonhomme

    Time:   July 8, 13:30—14:30

    Location:   Room 1C-502, SIST Building

    Contact:   Dr. Mingtuo Zhou

    Abstract:

    The presentation (from the team iExec) will focus on Blockchain technology, the involved security mechanisms, as well as the Blockchain based iExec ecosystem.

    Bio:

    Lei ZHANG, PhD, expert on Blockchain and Security, security director. He is currently leading the security team to build a Blockchain based cloud computing at iExec Blockchain Tech, France. He is a member of IEEE, key member of OpenFog Consortium, EEA (Enterprise Ethereum Alliance), and co-chairman of OCWG (blockchain Offchain Computing Working Group) to push the standardization of Blockchain based off-chain computing. His expert covers Blockchain, Security, Internet of Things, and Cloud Computing. He worked previously for Intel, and has multiple US / International Patents on Security and Wireless Communications. He also has a strong research background, he worked as a researcher in INRIA (Institut National de Recherche en Informatique et en Automatique), France; and an invited researcher in NICTA (National ICT of Australian). He received his Ph.D. degree in Computer Science from Universite de Toulouse and NICTA (National ICT of Australia) in 2009. He received his engineering degrees in Automation and Computer Science from Polytech'Lille, France (2005). He participates and coordinates several International and European projects on Internet of Things, Cloud computing and Cyber-Security.

    Victor is a software engineer, graduated from INSA of Lyon. Thanks to many years of working experience as the former CTO in a startup revolutionizing the entertainment industry in China, he knows best how to bootstrap projects facing thousands of users, meeting high requirements in terms of user experience and scalability. Lately, when in charge of the software stack of a quantitative hedge fund in Shenzhen, he developed an expertise in building robust and heavy-load resistant software that you can entrust with the delicate task of moving millions of dollars around, day and night, and still getting a peaceful sleep.

    For more information, click here please.

    For more information, click here please.

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    Business Finland uncovered: A new governmental company for innovation, export an invest in

    Speaker: Dr. Mika Klemettinen
    Date: 2018/07/02

    Speaker:   Dr. Mika Klemettinen

    Time:   July 2, 14:00—15:00

    Location:   Room 1C-502, SIST Building

    Contact:   Dr. Kunlun Wang

    Abstract:

    In my talk, I will introduce the new Business Finland organisation and its targets, including the digitalisation area that I am responsible for. I will also give updates on national digitalisation, artificial intelligence and platforms economy activities.

    Bio:

    Mika is a Digitalization Director at Business Finland with responsibilities covering 5G, Industrial Internet, Artificial Intelligence, Platforms Economy, New Space Economy and Smart Mobility programs as well as digitalization strategy. Mika holds a PhD degree in Data Mining and has more than 20 years of academic and industrial experience, e.g., from Nokia and EU collaboration as well as from wireless communications, IoT, BigData, MyData, artificial intelligence, intelligent solutions, cyber security and global collaboration. Mika is, e.g., a member of minister Lintilä’s national artificial intelligence and digitalization steering group in Finland with the responsibility of facilitating the data and platform economy subgroup. Additionally, he is responsible for the Finnish government’s national data policy preparation through running the artificial intelligence and data group.

    For more information, click here please.

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    2018 Summer School on “Fog Computing”

    2018 Summer School on “Fog Computing” will be held in Shanghai, on ShanghaiTech University campus, from June 26 to 29, 2018.

    2018 Summer School on “Fog Computing” will be held in Shanghai, on ShanghaiTech University campus, from June 26 to 29, 2018. The goal of this summer school is to bring together the world-class researchers in Fog Computing with undergraduate, graduate students and interested researchers from academia and engineers from industry, to educate the audience on both basics and recent advancements in Fog Computing overview, IoT, Optimization, Big Data, and Deep Learning, and to encourage collaborations on related topics. This summer school would also include a 24 hours’ hackathon after the two-days’ classes on Fog Computing, to encourage the students gather to collaborate and challenge themselves to build a project about Fog Computing from start to finish. It is an invaluable opportunity for the participants to gain coding experience, learn fog computing, and win awesome prizes.

    Hackathon

    • Fog Enabling Intelligent IoT
        - First Prize: US$5000
        - Second Prize: US$1000

    Highlights

    • Comprehensive Tutorials on Fog, IoT, Learning, and Optimization
    • Free registration
    • Complimentary banquet, meals, and coffee breaks
    • Reimbursements to 6 teams participating in Fog Hackathon (Per-student, only for IEEE ComSoc student members)
        - Students from Shanghai: US$80
        - Students from other mainland China: US$220(lodging) + US$80(travel)
        - Other students: US$220(lodging) + US$250(travel)
    • Certificates issued by:
        - IEEE Communications Society
        - OpenFog Consortium

    Dates and Location

    • Registration Deadline
        - Students from mainland China: May 15, 2018
        - Other students:: April 30, 2018
    • Dates: June 26-29, 2018
    • Location: ShanghaiTech University, 393 Middle Huaxia Road, Pudong, Shanghai, 201210

    For more information, click here please.

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    Efficient Information Dissemination of 3D Mapping Data for Autonomous Vehicles

    Speaker: Prof. Ivan Wang-Hei Ho
    Date: 2018/06/29

    Speaker:   Prof. Ivan Wang-Hei Ho

    Time:   June 29, 14:00—15:00

    Location:   Room 1C-502, SIST Building

    Contact:   Dr. Kunlun Wang

    Abstract:

    Information exchanges play a vital role in enabling autonomous driving by overcoming the limitation of perception and decision of a single autonomous vehicle. For assuring safety, facilitating regulations, and enhancing intelligent decisions, it is critical to enable a detailed global view of mapping data (that describes the road environments and roadside objects) to be synchronized and exchanged dynamically among autonomous vehicles, roadside infrastructure, and traffic control center. Central to autonomous driving is the mapping data in form of 3D point cloud that is commonly utilized by LIDAR (laser-based) perception systems, which can accurately represent physical objects in 3D space, but usually takes up a large volume of data. Therefore, the efficiency of 3D point cloud mapping data dissemination is crucial to practical realization of autonomous driving. In this paper, we present 3D-MADS, an efficient information dissemination system of 3D point cloud mapping data for autonomous vehicles, roadside units and a mapping data repository, considering heterogeneous transmission options, such as cellular network unicast and short-range local broadcast transmissions.

    Bio:

    Ivan Wang-Hei Ho is currently a Research Assistant Professor at the Department of Electronic and Information Engineering, The Hong Kong Polytechnic University. He received the B.Eng. and M.Phil. degrees in Information Engineering from The Chinese University of Hong Kong, and the Ph.D. degree in Electrical and Electronic Engineering from Imperial College London, UK. He worked on the MESSAGE project funded by EPSRC and Department for Transport, UK, and the ITA project funded by the US Army Research Laboratory and UK Ministry of Defence during his Ph.D. studies. In 2007, Ivan spent a summer working at the IBM T. J. Watson Research Center, Hawthorne, NY, USA. After his Ph.D. graduation, he was with the System Engineering Initiative at Imperial College as a Postdoctoral Research Associate. In Sept 2010, he co-founded P2 Mobile Technologies Limited at Hong Kong Science Park and served as the Chief R&D Engineer. He primarily invented the MeshRanger series wireless mesh embedded system, which won the Silver Award in Best Ubiquitous Networking at the Hong Kong ICT Awards 2012. Ivan is an Associate Editor for IEEE Access and IEEE Transactions on Circuits and Systems II, and TPC member for IEEE conferences (ICC, WCNC, PIMRC, etc.). His research interests are in wireless communications and networking, specifically in vehicular ad-hoc networks (VANET), intelligent transportation systems (ITS), Internet of things (IoT), and physical-layer network coding.

    For more information, click here please.

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    Meshee – An SDK Platform to Actualize Fog Computation

    Speaker: Dr. Ye Wu
    Date: 2018/05/30

    Speaker:   Dr. Ye Wu

    Time:   May 30, 11:00—12:00

    Location:   Room 1C-502, SIST Building

    Contact:   Prof. Xiliang Luo

    Abstract:

    Fog computation is rising rapidly due to its unrivaled advantages over cloud computation. Meanwhile, diverse smart terminals powered by operating systems (e.g., Android, iOS and Windows), as in cloud computation economy, will be the most valuable networking units in fog computation economy. Therefore, enabling fog computation functionality on smart terminals is more and more becoming the key factor to make fog computation a real success. It is exactly what Meshee SDK platform offers. Meshee SDK platform is capable of building a free Meshee network, which can cover an area of 400-hundred-meter-diameter, interconnect ~100 smart terminals and support end-to-end bandwidth up to ~100Mbps. Endowed with the aforementioned networking capabilities, using Meshee SDK to actualize fog computation, e.g., fog sharing of live videos and files, will become impressively easy. Furthermore, large coverage of lots of connected terminals and high bandwidth of Meshee networking are also very useful to smart IoT applications. In order to make fog computation readily useful for everybody/everything and industrialize fog computation more rapidly, Meshee SDK platform is open to developers to actualize their own fog computation Apps.

    Bio:

    Ye Wu now takes the role of CEO of Meshee Technology Ltd. He acquired the PhD degree in University of Liverpool, UK in 2008. In the same year, Dr. Wu received Chinese Government Award for Outstanding Self-financed Students Abroad due to his contribution for wireless communications. Before setting up Meshee Technology Ltd., Dr. Wu worked in NEC research lab and Huawei Technologies for over 9 years, where his research and development experience on wireless networking covers PHY layer and higher layer of diverse standards (e.g., 5G/LTE/802.1x/). In his research area, Dr. Wu has filed over 100 PCT/US/CN IPRs with half of them already granted. He also represented NEC and Huawei as the delegates in IEEE and 3GPP standardization organizations. Over the past 6 years, Dr. Wu had led several teams in Huawei and had

    For more information, click here please.

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    Introduction to the DESY test beam infrastructure and its new improvements

    Speaker: Dr. Mengqing Wu
    Date: 2018/05/25

    Speaker:   Dr. Mengqing Wu

    Time:   May 27, 13:00—14:00

    Location:   Room 1C-502, SIST Building

    Contact:   Dr. Wuxiong Zhang

    Abstract:

    DESY is one of the world’s leading accelerator centres and a member of the Helmholtz Association. DESY test beam facility operates three beam lines providing electron/position with energies from 1 to 6 GeV. Two of the three beam lines are equipped with an EUDET-type telescope based on the fine pitch Mimosa26 pixel sensor, requiring by ∼70% users.According to the test beam user community, a task to improve the DESY test beam infras-tructure is assigned within the EU Horizen2020 AIDA-2020 project, including building up a new silicon telescope at the third beam line to address the need of momentum measurements inside a 1T superconducting solenoid magnet, and an environmental slow control system to cover all the beam area. The new telescope is based on a 25μm pitch strip sensor of 10×10cm 2 , readout by two 1024-channel bumpbonded ASICs, and it is designed to provide a resolution better than 10μm in the bending direction, and a resolution better than 1mm along the magnetif field. This talk will give a brief introduction of the current DESY test beam infrastructure, with a focus on the R&D of the new telescope and the slow control system, and naturally a summary with perspectives will be given at the end.

    Bio:

    Currently working in FLC group, DESY as a Scientist (Postdoc)
    • Play a central role in the design, construction and installation of a silicon reference tracker within the AIDA2020 project at the test beam facility,
    • in charge of the commissioning of the read-out system and the installation of a monitoring system within the test beam DAQ.
    - 2012-2015 Ph.D. in Particle Physics - Université Joseph Fourier, France Graduated - July 30th, 2015
    Supervisors - Dr. Marie-Hélène GENEST and Dr. Faïrouz MALEK Thesis - Search for Supersymmetry and Dark Matter particles in the single photon final state with the ATLAS detector, CERN-THESIS-2015-122

    For more information, click here please.

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    Energy Digitization and Software Defined Battery Systems - From Bits to Watts

    Speaker: Prof. Song Ci
    Date: 2018/04/27

    Speaker:   Prof. Song Ci

    Time:       Apr 27, 15:00—16:00

    Location: Room 1C-502, SIST Building

    Contact:       Dr. Kunlun Wang

    Abstract:

    Battery has been widely used in many applications, such as consumer electronics, electric vehicles, back power systems and grid-level energy storage systems. However, it is challenging to design an efficient, cost-effective, reliable and safe battery systems due to the fundamental mismatch between battery cell variation and fixed series-parallel battery pack configuration. Furthermore, it is even harder to fulfill various user demands based on today’s limited types of battery technologies. Thus, energy digitization is proposed to overcome battery cell variation problems by utilizing the cutting-edge power electronics semiconductors, leading to a paradigm-shifting approach to battery system development and operation. Through energy digitization, traditional battery systems can be transformed from analog energy systems into digital, which allows to digitize and virtualize physical battery into digital energy assets and further to be seamlessly integrated with Internet ecosystem, leading to energy storage as a service to end users. In this talk, the design philosophy and the overarching system framework of energy digitization and battery virtualization will be discussed, and the effectiveness and efficiency of digital energy storage systems will be demonstrated by extensive experimental results and real-world case studies.

    Bio:

    Song Ci is an Associate Professor with the ECE Department, University of Nebraska-Lincoln, USA. He has authored more than 200 peer-reviewed articles in those areas, and his research has been support by NSF and other funding sources. His current research interests include large-scale dynamic complex system modeling and optimization, energy Internet and distributed energy management, green computing and communications, and mobile Internet. He is a member of ACM. He has served as an Editor or a Guest Editor in many journals, such as the IEEE Transactions on Circuits and Systems for Video Technology, the IEEE Journal on Selected Areas in Communications, the IEEE Access, and the IEEE Wireless Network.

    For more information, click here please.

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    Massive, Ultra-Dense, Delay, and Intelligence

    Speaker: Prof. Tony Q.S. Quek, SUTD
    Date: 2018/04/18

    Speaker: Prof. Tony Q.S. Quek, SUTD

    Time:       Apr 18, 10:00—11:00

    Location: Room 1A-200, SIST Building

    Host:       Prof. Xiliang Luo

    Abstract:

    In the future wireless systems, new services, applications and devices will drive requirements on data rate, ubiquity of data services, latency, cost, and reliability and further drive data traffic growth. To meet the above challenges, new technologies have been developed and investigated all around the world. Furthermore, the recent breakthrough in artificial intelligence and machine learning are providing us with technologies to perform tasks that once seemed impossible. In this talk, we will discuss a few key characteristics in future wireless networks and investigate related research problems to enhance our understanding of such networks.

    Bio:

    Dr. Quek has been actively involved in organizing and chairing sessions, and has served as a TPC member in numerous international conferences. He is serving as the Track Co-Chair for IEEE PIMRC 2018, Track Co-Chair for IEEE VTC Spring 2018, and TPC Co-Chair for IEEE WCSP 2018. He is currently an elected member of the IEEE Signal Processing Society SPCOM Technical Committee. He was an Executive Editorial Committee Member of the IEEE Transactions on Wireless Communications, an Editor of the IEEE Transactions on Communications, and an Editor of the IEEE Wireless Communications Letters. He is a co-author of the book “Small Cell Networks: Deployment, PHY Techniques, and Resource Allocation” published by Cambridge University Press in 2013 and the book “Cloud Radio Access Networks: Principles, Technologies, and Applications” by Cambridge University Press in 2016.

    Dr. Quek received the 2008 Philip Yeo Prize for Outstanding Achievement in Research, the IEEE Globecom 2010 Best Paper Award, the 2012 IEEE William R. Bennett Prize, the 2016 IEEE Signal Processing Society Young Author Best Paper Award, 2017 CTTC Early Achievement Award, 2017 IEEE ComSoc AP Outstanding Paper Award, and 2017 Clarivate Analytics Highly Cited Researcher. He is a Distinguished Lecturer of the IEEE Communications Society and a Fellow of IEEE.

    For more information, click here please.

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    Massive, Ultra-Dense, Delay, and Intelligence

    Speaker: Prof. Tony Q.S. Quek, SUTD
    Date: 2018/04/18

    Speaker: Prof. Tony Q.S. Quek, SUTD

    Time:       Apr 18, 10:00—11:00

    Location: Room 1A-200, SIST Building

    Host:       Prof. Xiliang Luo

    Abstract:

    In the future wireless systems, new services, applications and devices will drive requirements on data rate, ubiquity of data services, latency, cost, and reliability and further drive data traffic growth. To meet the above challenges, new technologies have been developed and investigated all around the world. Furthermore, the recent breakthrough in artificial intelligence and machine learning are providing us with technologies to perform tasks that once seemed impossible. In this talk, we will discuss a few key characteristics in future wireless networks and investigate related research problems to enhance our understanding of such networks.

    Bio:

    Tony Q.S. Quek received the B.E. and M.E. degrees in Electrical and Electronics Engineering from Tokyo Institute of Technology, Tokyo, Japan, respectively. At Massachusetts Institute of Technology (MIT), Cambridge, MA, he earned the Ph.D. in Electrical Engineering and Computer Science. Currently, he is a tenured Associate Professor with the Singapore University of Technology and Design (SUTD). He also serves as the Associate Head of ISTD Pillar and the Deputy Director of SUTD-ZJU IDEA. His current research topics include wireless communications and networking, security, big data processing, network intelligence, and IoT.

    Dr. Quek has been actively involved in organizing and chairing sessions, and has served as a TPC member in numerous international conferences. He is serving as the Track Co-Chair for IEEE PIMRC 2018, Track Co-Chair for IEEE VTC Spring 2018, and TPC Co-Chair for IEEE WCSP 2018. He is currently an elected member of the IEEE Signal Processing Society SPCOM Technical Committee. He was an Executive Editorial Committee Member of the IEEE Transactions on Wireless Communications, an Editor of the IEEE Transactions on Communications, and an Editor of the IEEE Wireless Communications Letters. He is a co-author of the book “Small Cell Networks: Deployment, PHY Techniques, and Resource Allocation” published by Cambridge University Press in 2013 and the book “Cloud Radio Access Networks: Principles, Technologies, and Applications” by Cambridge University Press in 2016.

    Dr. Quek received the 2008 Philip Yeo Prize for Outstanding Achievement in Research, the IEEE Globecom 2010 Best Paper Award, the 2012 IEEE William R. Bennett Prize, the 2016 IEEE Signal Processing Society Young Author Best Paper Award, 2017 CTTC Early Achievement Award, 2017 IEEE ComSoc AP Outstanding Paper Award, and 2017 Clarivate Analytics Highly Cited Researcher. He is a Distinguished Lecturer of the IEEE Communications Society and a Fellow of IEEE.

    For more information, click here please.

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    Presentation of VTT and the research work on energy and spectral efficiencies in 5G during the exchange project with WiCO

    Speaker: Ilkka Harjula, and Sandrine Boumard
    Date: 2018/04/11

    Speaker:   Ilkka Harjula, and Sandrine Boumard

    Time:   Apr 11, 11:00—12:00

    Location:   Room 1C-502, SIST Building

    Host:   Prof. Kunlun Wang

    Abstract:

    In this presentation, we will first introduce our company, VTT, the Technical Research Center of Finland, its organisation and general research focuses, and then narrow down to the various research topics related the communication field. A key element in our research field is the 5G test network (5GTN), which allows for testing different ideas in real environments. After presenting the test network, we will present the ESEC project, which is the reason why we are visiting WiCO. A general introduction of the project will be followed by technical presentation of the research conducted within the project: Throughput and Energy Consumption Trade-Off in Traffic Splitting in Heterogeneous Networks with Dual Connectivity, Demonstration on resource allocation algorithms, Network energy and spectral efficiencies measurements, Vehicular communications energy and spectral efficiencies.

    Bio:

    Ilkka Harjula works as a senior scientist at VTT Technical Research Centre of Finland. He received his M.Sc. degree in telecommunications from the University of Oulu in 2002 and Licentiate of Technology in 2008, and is currently working towards a Ph.D., focusing on energy and spectrum efficient technologies for 5G and beyond communication systems. Ilkka has contributed to numerous national and international R&D projects studying the communication concepts associated with 5G systems as well as the functionalities of currently dominating commercial technologies.

    Sandrine Boumard received her Master of Advanced Studies (DEA) in Electronics, Systems, Radar and Radio communication and her M. Sc degree in Electronics and Communication Systems in 1998 from the INSA (National Institute of Applied Sciences) of Rennes, France. She has been working since then as a Research Scientist at VTT Oulu, and as a Senior Scientist since 2011. Her current position is a Senior Scientist in the Efficient Computing and Communications team in the Connectivity research area of the Knowledge Intensive Products and Services business area at VTT.

    For more information, click here please.

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    Multi-Agent Machine Learning: A Tutorial

    Speaker: Prof. Jun Wang, UCL
    Date: 2018/04/10

    Speaker:   Prof. Jun Wang, UCL

    Time:   Apr 10, 13:30—14:30

    Location:   Room 1C-502, SIST Building

    Host:   Prof. Kunlun Wang

    Abstract:

    Multi-agent learning arises in a variety of domains with the applications ranging from controlling a group of autonomous vehicles/robots/drones, military combats, collaborative bots in production lines to optimizing distributed sensor networks/traffic and to machine bidding in competitive e-commerce and financial markets, just to name a few. In this talk, I shall provide an up-to-date tutorial on the technique and algorithms of multi-agent AI, with a focus on competition, collaboration, and communications among intelligent agents. The studies in both game theory and machine learning will be examined and be presented in a unified treatment. At the end of the talk, I shall example our recent work on the subject including mean-field multi-agent reinforcement learning, generative adversarial nets, hierarchical reinforcement learning and their applications in various domains.

    Bio:

    Dr. Jun Wang obtained his PhD degree in Delft University of Technology, the Netherlands; MSc degree in National University of Singapore, Singapore; and Bachelor degree in Southeast University, Nanjing, China. Currently, he is Chair Professor of Data Science, Computer Science, University College London, and Founding Director of MSc Web Science and Big Data Analytics. He is also Co-founder and Chief Scientist in MediaGamma Ltd, a UCL spin-out focusing on AI for intelligent audience decision making. His team won the first global real-time bidding algorithm contest with 80+ participants worldwide. He was a recipient of the Beyond Search Semantic Computing and Internet Economics award by Microsoft Research and also received Yahoo! FREP Faculty award. He has served as an Area Chair in ACM CIKM and ACM SIGIR. He was a technical advisor for startups such as Last.Fm, Passiv Systems, Massive Analytic, Context Scout, and Polecat, and had various projects with BT, Microsoft, Yahoo!, Alibaba etc.

    For more information, click here please.

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    Automated Driving and Connected Vehicles

    Speaker: Prof. Xuemin (Sherman) Shen
    Date: 2018/04/02

    Speaker: Prof. Xuemin (Sherman) Shen

    Time:       Apr 2, 14:00—15:00

    Location: Room 1C-502, SIST Building

    Host:       Dr. Kunlun Wang & Ziqin Li

    Abstract:

    Modern society depends on faster, safer, and environment friendly transportation system. Vehicular communications network in terms of vehicle to vehicle, vehicle to infrastructure, vehicle to pedestrian, vehicle to cloud, and vehicle to sensor, can provide a solution to such transportation system. In this talk, we first introduce the all connected vehicles. We then present the applications, challenges and scientific research issues of vehicular communications network. We also explain the role of vehicular networking in the automated driving era. We conclude the talk by discuss the future Space-Air-Ground (SAG) Integrated vehicular networks.

    Bio:

    Xuemin (Sherman) Shen is a University Professor, and Associate Chair for Graduate Study, Department of Electrical and Computer Engineering, University of Waterloo, Canada. Dr. Shen's research focuses on wireless resource management, wireless network security, smart grid and vehicular ad hoc and sensor networks. He is the Editor-in-Chief of IEEE IoT J. He serves as the General Chair for Mobihoc'15, the Technical Program Committee Chair for IEEE GC'16, IEEE Infocom'14, IEEE VTC'10, the Symposia Chair for IEEE ICC'10, the Technical Program Committee Chair for IEEE Globecom'07, the Chair for IEEE Communications Society Technical Committee on Wireless Communications. Dr. Shen is an elected member of IEEE ComSoc BoG, the chair of IEEE ComSoc Distinguish Lecturer selection committee, and a member of IEEE ComSoc Fellow evaluation committee. Dr. Shen received the Excellent Graduate Supervision Award in 2006, and the Premier's Research Excellence Award (PREA) in 2003 from the Province of Ontario, Canada. Dr. Shen is a registered Professional Engineer of Ontario, Canada, an IEEE Fellow, an Engineering Institute of Canada Fellow, a Canadian Academy of Engineering Fellow, a Royal Society of Canada Fellow, and a Distinguished Lecturer of IEEE Vehicular Technology Society and Communications Society.

    For more information, click here please.

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    From Autonomous Vehicles to Autonomous Mobility: Challenges and Opportunities

    Speaker: Dr. Tao Zhang
    Date: 2018/03/29

    Speaker: Dr. Tao Zhang, Cisco

    Time:       Mar 29, 14:00—15:00

    Location: Room 1C-502, SIST Building

    Host:       Prof. Yang Yang

    Abstract:

    Autonomous vehicles are coming. However, many more fundamental challenges remain to be addressed before self-driving vehicles can become practical in real-world environments. Furthermore, enabling vehicles to drive themselves is only the first step toward making them practical and realizing their full potential for advancing mobility and transportation. In addition, autonomous vehicles will bring profound disruptions to technology directions, business models, industry landscapes, policies and regulations. In this talk, I will discuss the challenges we face, the disruptions we may expect, and the opportunities we should seize now for the emerging world of mobility with autonomous vehicles.

    Bio:

    Dr. Tao Zhang, an IEEE Fellow, is a Distinguished Engineer / Senior Director of Cisco Corporate Strategic Innovation Group. He joined Cisco in 2012 as the Chief Scientist for Cisco’s Smart Connected Vehicles business, and has since also been leading initiatives to develop strategies, architectures, technology, and eco-systems for the Internet of Things (IoT) and Fog Computing. Prior to Cisco, he was Chief Scientist and Director of Mobile and Vehicular Networking at Telcordia Technologies (formerly Bell Communications Research or Bellcore). For over 25 years, Tao has been in various technical and executive positions, directing research and product development in vehicular, mobile, and broadband networks and applications. His leadership and technical work have led to ground-breaking results in fiber optic networks, all-IP cellular networks, mobile ad-hoc networks, and vehicular networks; resulting in new technology, standards, and products. Tao holds 50 US patents and has co-authored two books “Vehicle Safety Communications: Protocols, Security, and Privacy” (2012) and “IP-Based Next Generation Wireless Networks” (2004) published by John Wiley & Sons. Dr. Zhang co-founded, and is serving as a Board Director for, the Open Fog Consortium. He is the CIO and a Board Governor of the IEEE Communications Society (2016 and 2017).

    For more information, click here please.

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    A Cross-Layer Peer-to-peer System based on Device-to-device Communications

    Speaker: Dr. Xiaoli Chu
    Date: 2018/03/22

    Speaker: Dr. Xiaoli Chu

    Time:       Mar 22, 11:00—12:00

    Location: Room 1C-502, SIST Building

    Host:       Prof. Xiliang Luo

    Abstract:

    In this talk, I will introduce a peer-to-peer (P2P) system based on harvesting data in a community utilising multi-hop device-to-device (D2D) communications. The P2P system optimises D2D communications for P2P local file sharing, improves user experience, and offloads traffic from the base stations (BSs). The P2P system features cross-layer integration of: 1) a wireless P2P protocol based on the Bittorrent protocol in the application layer; 2) a simple centralised routing mechanism for multi-hop D2D communications; 3) an interference cancellation technique for conventional cellular (CC) uplink communications; and 4) a radio resource management scheme to mitigate the interference between CC and D2D communications that share the cellular uplink radio resources while maximising the throughput of D2D communications. Simulation results show that the D2D enabled P2P system can increase the cellular spectral efficiency, reduce the traffic load of BSs, and improve the data rate and energy saving for mobile users.

    Bio:

    Xiaoli Chu is a Reader in the Department of Electronic and Electrical Engineering at the University of Sheffield. She received the B.Eng. degree in Electronic and Information Engineering from Xi’an Jiao Tong University in 2001 and the Ph.D. degree in Electrical and Electronic Engineering from the Hong Kong University of Science and Technology in 2005. From 2005 to 2012, she was with the Centre for Telecommunications Research at King’s College London. Xiaoli is co-recipient of the IEEE Communications Society 2017 Young Author Best Paper Award. She is the lead editor/author of the book “Heterogeneous Cellular Networks – Theory, Simulation and Deployment” published by Cambridge University Press (May 2013) and the book “4G Femtocells: Resource Allocation and Interference Management” published by Springer (November 2013). She is Editor for the IEEE Communications Letters and the IEEE Wireless Communications Letters. She was Co-Chair of Wireless Communications Symposium for the IEEE International Conference on Communications (ICC) 2015, Workshop Co-Chair for the IEEE International Conference on Green Computing and Communications 2013, and has been Technical Program Committee Co-Chair of 6 workshops on heterogeneous and ultra-dense networks for IEEE ICC, GLOBECOM, WCNC, and PIMRC.

    For more information, click here please.

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    Wireless Road Infrastructure for Accurate and Reliable Vehicle Localization - A Roadmap to the Future

    Speaker: Proc. Guoqiang Mao, UTS
    Date: 2018/03/20

    Speaker: Prof. Guoqiang Mao, UTS

    Time:       Mar 20, 10:00—11:00

    Location: Room 1C-502, SIST Building

    Host:       Dr. Kunlun Wang & Ziqin Li

    Abstract:

    Connected and autonomous vehicles (CAVs) are set to completely disrupt countless aspects of daily personal life, business, and technology in the decades to come. The safe and efficient mass deployment of CAVs requires the support of revolutionary, next generation smart road infrastructure. Accurate and reliable localization anytime anywhere is a key requirement for the safe and efficient operations of CAVs. This talk will start with an introduction to our previous research projects in localization area. Then, it will introduce out future work plan to lay the theoretical foundation for establishing the wireless road infrastructure needed to support accurate and reliable localisation of connected and autonomous vehicles (CAVs), via the deployment and coordination of a large number of low-cost road beacons. The proposed solution complements existing satellite, and map-and-sensor, based localisation, and extends this technology to provide accurate CAV localisation in complex and dynamic environments, like urban canyons and tunnels.

    Bio:

    Guoqiang Mao received PhD in telecommunications engineering in 2002 from Edith Cowan University, Australia. He was with the School of Electrical and Information Engineering, the University of Sydney between 2002 and 2014. He joined the University of Technology Sydney in February 2014 as Professor of Wireless Networking and Director of Center for Real-time Information Networks. He has published over 200 papers in international conferences and journals, which have been cited around 6,000 times. He is an editor of the IEEE Transactions on Intelligent Transportation Systems, IEEE Transactions on Wireless Communications, IEEE Transactions on Vehicular Technology and received “Top Editor” award for outstanding contributions to the IEEE Transactions on Vehicular Technology in 2011, 2014 and 2015. He is a co-chair of IEEE Intelligent Transport Systems Society Technical Committee on Communication Networks. He has served as a chair, co-chair and TPC member in a large number of international conferences. His research interest includes intelligent transport systems, applied graph theory and its applications in telecommunications, Internet of Things, next generation mobile communication systems, and wireless localization techniques. He is a Fellow of IEEE and IET.

    For more information, click here please.