Track Descriptions

ICCCN 2020 – Track Descriptions and TPC Lists

1. Cognitive, Ad Hoc, Mobile, and Mesh Networks (CAMM)
Anu Bourgeois
, Georgia State University, USA; abourgeois@cs.gsu.edu
Yunsheng Wang, Kettering University, USA; ywang@kettering.edu

With the proliferation of smart handheld devices, mobile data is projected to grow drastically in the next few years. Coupled with emerging machine-to-machine communications, there is a compelling need to significantly improve the current network capacity and architecture. To meeting this challenge, traditional cellular networks must be more adaptive and intelligent, e.g., adaptive to different types of spectrum (white space or dedicated) and traffic patterns. They must also interconnect with other coexisting wireless networks such as Wi-Fi, mobile ad hoc networks, wireless mesh network, femtocells and small cells, etc., to support a wide range of applications.

Track Topics:

  • Mobile Ad Hoc networks
  • Cellular networks
  • Seamless heterogeneous wireless networks
  • Dynamic spectrum access wireless networks
  • Cognitive radio networks
  • Wireless programming paradigms and middleware technologies
  • Mobility management and modeling
  • Wireless infrastructure planning and deployment
  • Lessons learned from long-term deployment experiences of wireless technologies
  • Radio access technologies and evolution
  • Wireless sensor networks
  • Wireless mesh networks
  • RFID technologies
  • Energy-efficient protocol design
  • Wireless MAC, routing and transport layer protocols
  • Cross-layer design and optimization
  • Wireless data offloading
  • Wireless network coding
  • Device to Device communication
  • Communication Interference control
  • Performance measurement

TPC List:

  • Violet R. Syrotiuk, Arizona State University, syrotiuk@asu.edu
  • Abhimanyu Gosain, Northeastern University, agosain@coe.neu.edu
  • Kewei Sha, University of Houston-Clear Lake, sha@uhcl.edu
  • Ning Wang, Rowan University, wangn@rowan.edu
  • Fei Qin, University of Chinese Academy of Sciences, fqin1982@ucas.ac.cn
  • Xiaohua Xu, Kennesaw State University, xxu6@kennesaw.edu
  • Kui Wu, University of Victoria, wkui@uvic.ca
  • Yingshu Li, Georgia State University, yili@gsu.edu
  • Bo Sheng, University of Massachusetts Boston, bo.sheng@umb.edu
  • Roberto Rojas-Cessa, New Jersey Institute of Technology, rojas@njit.edu
  • Wei Yu, Towson University, wyu@towson.edu
  • Kang Chen, Southern Illinois University, kchen@siu.edu
  • Mike P. Wittie, Gianforte School of Computing, Montana State University, mike.wittie@montana.edu
  • He Wang, Purdue University, hw@purdue.edu
  • Yan Huang, Kennesaw State University, yhuang24@kennesaw.edu
  • Guangzhi Qu, Oakland University, gqu@oakland.edu
  • Wei Gao, University of Pittsburgh, weigao@pitt.edu
  • Peng Liu, Hangzhou Dianzi University, perryliu@hdu.edu.cn
  • Yuben Qu, Shanghai Jiao Tong University, quyuben@sjtu.edu.cn
  • Huijuan Lu, China Jiliang University, hjlu@cjlu.edu.cn

2. Communication Networks Architectures, Algorithms, Measurement and Performance Evaluation (CAAME)
Weifa Liang
, Australian National University, Australia; wliang@cs.anu.edu.au
Chiara Petrioli, University of Rome 'La Sapienza', Italy; petrioli@di.uniroma1.it

Design of efficient network architectures and algorithms is one of the fundamental issues in computer networking. To this end, novel analytical, measurement, and simulation tools are required for evaluating the behavior and performance of complex communication networks. This track provides researchers, industry professionals and practitioners a forum to present the latest results in the rapidly evolving areas of network architectures, network algorithms, and performance evaluation. We solicit original and unpublished research work on theoretical, analytical, measurement, and simulation aspects of network architectures, network algorithms, and performance evaluation as well as efficient methods of algorithm design that apply to various areas of networking.

Track Topics:

  • Routing algorithms
  • Distributed algorithms
  • Congestion control algorithms
  • Error control algorithms
  • Algorithms for QoS support
  • QoS routing and scheduling
  • QoS analysis and modeling
  • Packet classification algorithms
  • Packet scheduling and buffer management
  • Address lookup algorithms
  • Admission control algorithms
  • Algorithms and protocols for traffic engineering
  • Capacity planning
  • Traffic modeling, engineering and control
  • Network coding
  • Reliability and survivability
  • Resource allocation and management
  • Algorithmic foundations of networking
  • Performance evaluation of web and social networking services
  • Analytical, measurement, and simulation techniques
  • Network design methodologies
  • Algorithms and optimization techniques for protocol design
  • Data center networking
  • Optical networks
  • UAV networks and scheduling
  • Resource allocation and scheduling for Mobile Edge Computing (MEC)
  • Virtualized Srvice Function (VNF) placement
  • Software-Defined Networking (SDN)

TPC List:

  • Wei Bao, The University of Sydney, Australia
  • Sid Chau, Australian National University, Australia
  • Sajal Das, Missouri University of Science and Technology, USA
  • Qiangsheng Hua, Huazhong University of Science and Technology, China
  • Xiaohua Jia, City Univeristy of Hong Kong, China
  • Yao Liang, Indiann-Purdue University, USA
  • Yuben Qu, Shanghai Jiao Tong University, China
  • Michael Segal, Ben-Gurion University of the Negev, Israel
  • Jiugen Shi, Hefei University of Technology, China
  • Qiufen Xia, Dalian University of Technology, China
  • Kui Wu, University of Victoria, Canada
  • Wenzheng Xu, Sichaun University, China
  • Zichuan Xu, Dalian University of Technology, China
  • Yinlong Xu, University of Science and Technology of China
  • Xinming Zhang, University of Science and Technology of China
  • Bingbing Zhou, The University of Sydney, Australia
  • Wanlei Zhou, Univeristy of Technolody Sydney, Australia

3. Data Centers and Big Data Computing (DCBC)
Dawei Li
, Montclair State University, USA; dawei.li@montclair.edu
Xiao Luo, Indiana University - Purdue University Indianapolis, USA; luo25@iupui.edu

Datacenters constitute critical infrastructure for keeping up with the ever-increasing volume, velocity, and variety of big data. This track invites submissions describing novel ideas, techniques, and results in the general area of datacenter design and big data computing.

Track Topics:

  • Data center networks and infrastructure
  • Application of software defined techniques to datacenters
  • Traffic engineering and flow scheduling in data centers
  • Autonomic datacenter management
  • Green Datacenter
  • Big data processing and storage
  • VM placement and task scheduling for big data processing in data centers
  • Novel design paradigms and technologies for big data
  • Big data analytics
  • Case studies describing practical experience
  • Performance modeling and evaluation

TPC list:

  • Jiayin Wang, Montclair State University, USA; wangji@montclair.edu
  • Aparna Varde, Montclair State University, USA; vardea@montclair.edu
  • Michelle Zhu, Montclair State University, USA; zhumi@montclair.edu
  • Xin Li, Nanjin University of Aeronautics and Astronautics, P. R. China; lics@nuaa.edu.cn
  • Biyu Zhou, Institute of Information Engineering, Chinese Academy of Science, P. R. China; zhoubiyu@iie.ac.cn
  • Hongliang Li, Jilin University, P. R. China; lihongliang@jlu.edu.cn
  • Jiaqi Zheng, Nanjing University, P. R. China; jzheng@nju.edu.cn
  • Sadoon Azizi, University of Kurdistan, Iran; s.azizi@uok.ac.ir
  • Rafael Tolosana-Calasanz, Universidad de Zaragoza, Spain; rafaelt@unizar.es
  • Ivan Rodero, Rutgers University, USA; irodero@rutgers.edu
  • Varun Chandola, The State University of New York (SUNY) at Buffalo, USA; chandola@buffalo.edu
  • Chen Tian, Nanjing University, P. R. China; tianchen@nju.edu.cn
  • Shen Li, IBM Research, USA; cs.shenli@gmail.com
  • Shahrear Iqbal, National Research Council Canada, Canada; Shahrear.Iqbal@nrc-cnrc.gc.ca
  • Liting Hu, Florida International University, USA; lhu@cs.fiu.edu
  • Xiaonan Guo, Indiana University-Purdue University Indianapolis, USA; xg6@iu.edu
  • Zhengming Ding, Indiana University-Purdue University Indianapolis, USA; zd2@iu.edu
  • K. Anitha Kumari, PSG College of Technology, India; kak.it@psgtech.ac.in
  • Yunpeng Zhang, University of Houston, USA; yzhang119@uh.edu
  • Hongyu Liu, Santa Clara University, USA; yhliu@scu.edu

4. Green Networking and Sustainable Computing (GREEN)
Md Zakirul Alam Bhuiyan
, Fordham University, USA; mbjuiyan3@fordham.edu
Milos Stojmenovic, Singidunum University, Serbia; mstojmenovic@singidunum.ac.rs

Information and communication technology (ICT) is a multi-billion dollar domain that has incredible economic, social, and environmental effects. It has significantly improved our operations to solve society's sustainability issues. Green Information Networking Technology is used to promote innovations and social and economic restructuring globally to help reduce overall global carbon emissions. It has been estimated that by 2020, the ICT applications could help reduce global carbon emissions by 15%. This calls for energy-efficient and sustainable solutions for the ICT. This track focuses on novel contributions to green networking and sustainable computing by improving energy efficiency of end-hosts, data centers, cloud operations, Internet of things, cyber-physical system, and forthcoming additions to the ICT, and by developing novel strategies for sustainable integration with the grid. Developments are sought in hardware/software design, network architectures, protocols and algorithms that will lead to sustainable, reliable, trustworthy, and energy efficient networking infrastructure, as well as novel approaches that will improve the manageability, security, and reliability of the ICT as it is applied to solve global sustainability challenges.

Track Topics:

  • Architectures, algorithms, and protocols
  • Applications of green networking technologies and principles
  • Cognitive networks for energy efficiency
  • Economy and pricing for green communication and services
  • Green communication in 5G systems
  • Green network monitoring and measurements
  • Green optical communications, switching and networking
  • Green traffic shaping and policy implementation
  • Energy cost models for network operators
  • Energy-efficient optimization for communications and computing
  • Energy-efficient routers and switches
  • Energy efficient scheduling and resource allocation
  • Energy harvesting, storage, and recycling
  • Energy minimization in core, metro, access and local area networks
  • Experimental testbeds for green communications and computing
  • Modeling the environmental footprint of communications
  • Sustainable integration of networking and computing into the grid
  • Networking processor and hardware designs
  • Non-energy based green issues and approaches
  • Standards and regulations for energy efficiency in networking
  • Sustainable storage and cloud computing
  • Theory, modeling, and performance analysis
  • Virtualization techniques for energy efficiency
  • Security, trust, and privacy in sustainable mobile computing and communications
  • Security in green networking and sustainable computing
  • Green networking in IoTs
  • Cyber-physical systems for sustainable computing
  • Efficient data management for sustainable mobile computing and communications
  • Big data processing for energy-efficient mobile computing
  • Energy-efficient networking for smart environments

TPC List:

  • Abbas Haider, National University of Sciences and Technology, Pakistan
  • Alejandro Canovas, Universitat Politecnica de Valencia, Spain
  • Aleksandar Jevremovic, Singidunum University, Belgrade, Serbia
  • Alireza Jolfaei, Federation University Australia, Australia
  • Arijit Karati, National Sun Yatsen University, Taiwan
  • Changqing Luo, Virginia Commonwealth University, USA
  • Haipeng Da, Nanjing University, China
  • Jose M. Jimenez, Universitat Politecnica de Valencia, Spain
  • Junggab Son, Kennesaw State University, USA
  • Kenichi Kourai, Kyushu Institute of Technology, Japan
  • Kouichi Sakurai, Kyushu University, Japan
  • Lorena Parra, Universitat Politecnica de Valencia, Spain
  • M. Kamruzzaman Sikder, Humber College, Canada, Canada
  • Mamoun Alazab, Australian National University, Australia
  • Miran Taha, University of Sulaimani, Kurdistan region, Iraq
  • Mohiuddin Ahmed, Edith Cowan University, Australia
  • Muhammad Alam, Xi'an Jiaotong-Liverpool University, China
  • Muhammad Imran, King Saud University, KSA
  • Naghmeh Moradpoor, Edinburgh Napier University, UK
  • Oscar Romero, Universitat Politecnica de Valencia, Spain
  • Paul Pang, Unitec Institute of Technology, New Zealand
  • Sandra Sendra, Universidad de Granada, Spain
  • Shaikh Arifuzzaman, University of New Orleans, USA
  • SK MD Mizanur Rahman, Centennial College, Canada, Canada
  • Varatharajan Ramachandran, Bharath University, India
  • Weizhi Meng, Technical University of Denmark, Demark
  • Xin-Wen Wu, Indiana University of Pennsylvania, USA
  • Yifan Zhang, SUNY Binghamton, USA
  • Yulei Wu, University of Exeter, UK
  • Zhiyuan Tan, Edinburgh Napier University, UK

5. Grid, Cloud, Internet and Middleware Computing and Communication (GCIM)
Rajkumar Buyya
, University of Melbourne, Australia; rbuyya@unimelb.edu.au
Antonio Fernandez, IMDEA Networks Institute, Spain; antonio.fernandez@imdea.org

The rapid advances in processing, communication and systems/middleware technologies are bringing about the explosive growth of online applications and services in Internet, and driving Grid, Cloud, and Edge to be dominating paradigms and platforms for computation and data in academia as well as industry. Social network services in Internet represent a simplified, managed (and walled-garden) version of the Web, providing identifiability of their participants between each other and serving the large-scale access to huge amounts of user generated content, images, and messages that their users share with their contacts in an efficient way. P2P technology effectively supports Internet Streaming and Content Distribution with high scalability and availability for such services. Grid enables the sharing of distributed computing and data resources such as processing, network bandwidth and storage capacity to create a cohesive resource environment for executing distributed applications, while Clouds provide elastic, on-demand as-a-service access to compute, data, and software resources. Edge computing moves the access to these resources closer to the final user when required for latency or data volume restrictions. The Grid, Cloud, Internet and Middleware Computing and Communication track of the ICCCN conference aims to the key issues underlying these paradigms, and welcomes paper submissions on innovative work from researchers in academia, industry and government describing original research. Topics of interest range from architectures and enabling technologies, programming models, systems and tools, management structures and policies, performance modeling and management, security and privacy, algorithms, network and storage, applications and experiences, and associated legal, regulatory, and social issues. We solicit original and unpublished research achievements in various aspects of this field, including, but not limited to, the following topics.

Track Topics:

  • Architectures & tools for integration of clouds and clusters
  • Service oriented architectures for HPC
  • Problem solving environments and portals
  • Cloud administration and manageability
  • Cloud data privacy and security
  • Cloud data services architectures
  • Cloud distributed and parallel query processing
  • Distributed and cloud networking
  • Cloud reliability and high availability
  • Cloud resource management and performance
  • Cloud provisioning and metering
  • Cloud infrastructure technologies
  • Cloud scheduling algorithms
  • Compute and storage cloud architectures
  • Cloud programming models and tools
  • Cloud service level agreements
  • Cloud federation models, policies and mechanism
  • Cloud interoperability mechanisms and standards
  • Governance structures and regulatory mechanism for Clouds
  • Scientific applications for clouds
  • Hybrid Grid/Cloud infrastructure and programming support
  • Hybrid Grid/Cloud usage modes and application scenarios
  • Energy management
  • Virtualization technologies
  • Virtual networks
  • Internet and mobile streaming
  • Content Distribution Network (CDN) and CDN federation
  • Network Function Virtualization
  • Cloud and content distribution using cloud
  • Content adaptation and sharing
  • Multimedia applications over wired and wireless/cellular networks
  • P2P based content streaming/distribution
  • Operating system middleware and network support
  • Future Internet and clean-slate design
  • Edge/fog computing services and infrastructures
  • Edge/fog computing network architectures
  • Integration of edge/fog and cloud computing
  • Middleware for edge/fog computing applications
  • Architectures and systems design for social networks
  • Search strategies in social networks
  • Social Web Content Provisioning
  • Social Networking Platform Apps
  • Mobile social networks
  • Distributed Systems enabled by Social Networks

TPC List:

  • Mohsen Amini-Salehi, University of Louisiana at Lafayette, USA, amini@louisiana.edu
  • Jordi Arjona-Aroca, ITI, Universidad Politecnica de Valencia, Spain, jarjona@iti.es
  • Chen Avin, Ben Gurion University, Israel, avin@CSE.BGU.AC.IL
  • Rami Bahsoon, University of Birmingham, UK, r.bahsoon@cs.bham.ac.uk
  • Themistoklis Charalambous, Aalto University, Finland, themistoklis.charalambous@aalto.fi
  • Jörg Domaschka, Universität Ulm, Germany, joerg.domaschka@uni-ulm.de
  • Claudio Fiandrino, IMDEA Networks Institute, Spain, claudio.fiandrino@imdea.org
  • Peter Garraghan, Lancaster University, UK, p.garraghan@lancaster.ac.uk
  • Sukhpal Singh Gill, University of London, UK, drsukhpalsinghgill@gmail.com
  • Souymya K. Ghosh, IIT Kharagpur, India, skg@cse.iitkgp.ac.in
  • Boris Koldehofe, TU Darmstadt, Germany, boris.koldehofe@kom.tu-darmstadt.de
  • Fangming Liu, Huazhong University of Science and Technology, China, fmliu@hust.edu.cn
  • Zhiyong Liu, ICT, CAS, China, zyliu@ict.ac.cn
  • Ignacio Martín Llorente, Universidad Complutense de Madrid, Spain, imllorente@ucm.es
  • Md. Redowan Mahmud, The University of Melbourne, Australia, md.redowan.mahmud@gmail.com
  • P-O Östberg, Umeå University, Sweden, p-o@cs.umu.se
  • George Pallis, University of Cyprus, Cyprus, gpallis@cs.ucy.ac.cy
  • Marta Patiño, Universidad Politecnica de Madrid, Spain, mpatino@fi.upm.es
  • Amir Payberah, KTH, Sweden, payberah@kth.se
  • Gabriel Scalosub, Ben Gurion University, Israel, sgabriel@bgu.ac.il
  • Maria Sossa, The University of Melbourne, Australia, maria.rodriguez@unimelb.edu.au
  • Lin Wang, Vrije University, Nederlands, lin.wang@vu.nl

6. Internet of Things (IoT)
Imad Jawhar
, Al Maaref University, Lebanon; imad.jawhar@mu.edu.lb
Sejun Song, University of Missouri-Kansas City, USA; songsej@umkc.edu

The Internet of Things (IoT) is considered as a key player in the network of the future, which can be used to support numerous smart-world systems. With new advancements in computing technology leading to more processing power, storage, and communication capacity with very small scale components, connecting the corresponding devices in an efficient manner using the IoT architecture becomes a very important part of networking research. Numerous efforts are focusing on systems and protocols to build a powerful IoT. However, partly due to the large variations on the "things" in the Internet, IoT is still in an initial state. IoT is generally characterized by limited computation and communication capacity, the presence of sensors in tiny objects, and the associated challenges, e.g., concerning security, energy efficiency, data caching, storage, and sharing. To address these, both theoretical and systems approaches are invaluable. In this track, we invite submissions of research works with novel contributions of either type.

Track Topics:

  • Security and trustworthiness in IoT
  • Secure operating environments for IoT
  • Attack and defense strategies for IoT
  • Energy-aware IoT hardware
  • Energy-efficient IoT networking
  • Power consumption and optimization in IoT
  • Routing and control protocols
  • Scalability and robustness for IoT
  • Programming abstractions and middleware for IoT
  • Cloud back-ends and resource management for IoT applications
  • Edge and Fog computing in IoT
  • Distributed storage, data fusion, and data sharing in IoT
  • Sensor data management, mining and analytics in IoT
  • Crowd-sensing, human centric sensing
  • Mobile and pervasive applications built atop IoT
  • IoT for smart grid, smart transportation, smart cities, and other smart-world applications
  • Formal foundations and theories for IoT
  • Green IoT: sustainable design and technologies
  • Analytic foundations and theory of IoT
  • Machine learning foundation and models for IoT and applications

TPC List:

  • Burak Kantarci, University of Ottawa
  • Honggang Wang, University of Massacusetts Dartmouth
  • Houbing Song, Embry-Riddle Aeronautical University
  • Sherali Zeadally, University of Kentucky
  • Lei Chen, Georgia Southern University
  • Guobin Xu, Frostburg State University
  • Weixiao Liao, Towson University
  • Yue Chao, Northumbria University
  • Dou An, Xi'an Jiaotong University
  • Yong Guan, Iowa State University
  • Anyi Liu, Oakland University
  • Hanlin Zhang, Qingdao University
  • Xinwen Fu, University of Central Florida
  • Melike Erol-Kantarci, University of Ottawa
  • Zhen Ling, Southeast University
  • Lucy Cherkasova, ARM Research
  • Dong Wang, Notre Dame University
  • Jie Lin, Xi'an Jiaotong University
  • Mi Zhang, Michigan State University
  • Liang He, University of Colorado Denver
  • He Wang, Purdue University

7. Multimedia and Real-Time Networking (MRN)
Yu Chen
, Binghamton Univ, State Univ of New York, USA; ychen@Binghamton.edu
Christian Poellabauer, University of Notre Dame, USA; cpoellab@nd.edu

With the rapid deployment of all IP networks as well as the wide adoption of smart mobile devices, various modern multimedia applications such as movies on demand, video streaming and conferencing, and IPTV are increasingly being offered over heterogeneous networks. The major challenge for these applications is to meet the high Quality of Service requirements for real-time content over limited-bandwidth connections. Network traffic management technologies are critical to enabling fair use of network resources among different types of traffic, while still achieving efficient and robust content delivery. This track focuses on the latest challenges, opportunities, and recent advances and developments in the broad areas of multimedia services and real-time networking. We seek original research contributions in various aspects of these fields, including, but not limited to the following topics.

Track Topics:

  • Real-time multimedia systems
  • Multimedia services, transport, and sharing protocols
  • Multimedia support for mobile and wireless networks
  • Mobile multimedia services and location-based systems
  • Cloud storage and computing
  • Content or information-aware network design and optimization
  • Network security for multimedia communication services
  • Real-time network architectures and protocols
  • Resource-constrained systems and mission-critical applications
  • Massive multiplayer online gaming
  • Analysis and modeling of mobile and social media networks
  • Network modeling, analysis, and simulation
  • Internet measurement and modeling
  • Real-time management for wired, wireless, ubiquitous, and hybrid networks
  • AR/VR systems in mobile and wireless networks
  • Visual Layer Attacks on Real-Time Multimedia Systems
  • Multimedia System as an Edge Service

TPC List:

  • Zheng Dong, Wayne State University, USA
  • Ziqian Dong, New York Institute of Technology, USA
  • Carsten Griwodz, University of Oslo, Norway
  • Chin-Tser Huang, University of South Carolina, USA
  • Wei Jiang, UESTC, China
  • Hyoseung Kim, University of California at Riverside, USA
  • Lisimachos Kondi, University of Ioannina, Greece
  • Linghe Kong, Shanghai Jiaotong University, China
  • Sunil Kumar, San Diego State University, USA
  • Jian Li, Binghamton University, USA
  • Jing Li, New Jersey Institute of Technology, USA
  • Yaoqing Liu, Fairleigh Dickinson University, USA
  • Gowri Sankar Ramachandran, University of Southern California, USA
  • Kaliappa Ravindran, City University of New York, USA
  • Yusuf Sarwar, University of Missouri – Kansas City, USA
  • Sachin Shetty, Old Dominion University, USA
  • Ali Tekeoglu, SUNY Polytechnic Institute, USA
  • Sudip Vhaduri, Fordham University, USA
  • Feng Wang, University of Mississippi, USA
  • Shuai Wang, Southeast University, China
  • Xin Wang, Fudan University, China
  • Alexander Wijesinha, Towson University, USA
  • Kecheng Yang, Texas State University, USA
  • Desheng Zhang, Rutgers University, USA
  • Dakai Zhu, University of Texas at San Antonio, USA

8. Security, Privacy, Trust and Incentives (SPTI)
Qin Liu
, Hunan University, China; gracelq628@hnu.edu.cn
Sachin Shetty, Old Dominion University, USA; sshetty@odu.edu

Recent advances in computer communications and networking techniques in technologies such as, Internet of Things, 5G, AI, etc., has resulted in emerging challenges in realizing security, privacy, trust and incentives. There is a need to develop protocols and systems that can preserve security and trust, without violating privacy and providing incentives to participate and collaborate. The 'Security, Privacy, Trust and Incentives' (SPTI) track of the 29th International Conference on Computer Communications and Networks (ICCCN), welcomes submissions of original papers from researchers and practitioners working in the fields of security, privacy, and trusted systems as well as incentive mechanisms. The track seeks novel contributions on algorithm and system design, implementation, and evaluations.

Track Topics:

  • Anonymization and privacy
  • Blockchain based decentralized trust management
  • Cloud security
  • Computer and network forensics
  • Data and application security
  • Information hiding and watermarking
  • Incentives and game theory
  • IoT Security
  • Private information retrieval
  • Privacy-preserving trust management
  • Smart cards and secure hardware
  • Trust and reputation models
  • Vulnerability, exploitation tools, and virus/worm analysis

TPC List:

  • Deepak Tosh, University of Texas at El Paso, USA
  • Uttam Ghosh, Vanderbilt University, USA
  • Amin Hassanzadeh, Accenture Technology Lab, USA
  • Lei Ding, Accenture Technology Lab, USA
  • Kaiqi Xiong, University of South Florida, USA
  • Sarada Prasad, Old Dominion University, USA
  • Mohammad Wazid, Mainpal Institute of Technology, India
  • Danda Rawat, Howard University, USA
  • Charles Kamhoua, Army Research Lab, USA
  • Kimberly Gold, Naval Surface Warfare Center, USA
  • Saman Zonouz, Rutgers University, USA
  • Saad Bani-Mohammad, Al al-Bayt University, Jordan
  • Anupam Chattopadhyay, Nanyang Technological University, Singapore
  • Alfredo Cuzzocrea, University of Calabria, Italy
  • Sabrina De Capitani di Vimercati, University of Milan, Italy
  • Ryan Ko, University of Queensland, Australia
  • Giovanni Livraga, University of Milan, Italy
  • Günther Pernul, University of Regensburg, Germany
  • Vincenzo Piuri, University of Milan, Italy
  • Luis Javier García Villalba, Universidad Complutense de Madrid, Spain
  • Muneer Masadeh Bani Yassein, Jordan Univ of Science and Technology, Jordan
  • Xin Liao, Hunan University, China
  • Tao Peng, Guangzhou University, China
  • Xin Yao, Central South University, China

9. Sensor/Embedded Networks and Pervasive Computing (SNPC)
Xiao Chen
, Texas State University, USA; xc10@txstate.edu
Kazuya Sakai, Tokyo Metropolitan University, Japan; ksakai@tmu.ac.jp

The modern computing technologies are becoming increasingly pervasive and ubiquitous in every facet of our lives which is redefining how we use technology, how technology can augment our capabilities, and how technology can solve the most crucial problems of 21st century. The disruptive new innovations in the areas of Sensor/Embedded Networks and Pervasive Computing are at the core of this innovation cycle. This year, In ICCCN 2020, the Sensor/Embedded Networks and Pervasive Computing (SNPC) track seeks novel, innovative and exciting submissions broadly related to the sensor and embedded systems, sensor networks, mobile sensing, pervasive and ubiquitous computing.

Track Topics:

  • Innovative hardware and software systems for sensing and sensor networks
  • Innovative communication and networking technologies for embedded and/or wearable sensors
  • New applications of sensing and networking technologies
  • Design and implementation of mobile phone, wearable and/or novel embedded systems based computing platforms
  • Integration of multimodal data from different sensor streams
  • Novel signal processing or machine learning techniques for different pervasive and ubiquitous computing applications
  • Off-body, wireless and remote sensing
  • Energy and resource efficient implementation of mobile and embedded systems

TPC List:

  • Ashwin Ashok, Georgia State University, USA
  • Qijun Gu, Texas State University, USA
  • Daniel Graham, University of Virginia, USA
  • Meng Jin, Tsinghua University, China
  • Wenzhong Li, Nanjing University, China
  • Yantao Li, Chongqing University, China
  • Liu Peng, Hangzhou Dianzi University, China
  • Muhammad Shahzad, North Carolina State University, USA
  • Bo Sheng, University of Massachusetts Boston, USA
  • Bin Tang, California State University, Dominguez Hills, USA
  • Jiliang Wang, Tsinghua University, China
  • Shuangquan Wang, William and Mary, USA
  • Yibo Wu, Google, USA, yibowu@google.com
  • Jie Xiong, University of Massachusetts, Amherst, USA
  • Kaiqi Xiong, University of South Florida, USA
  • Qing Yang, University of North Texas, USA
  • Zhicheng Yang, PingAn Tech., USA
  • Xiaojun Zhu, Nanjing University of Aeronautics and Astronautics, China

10. Software Defined Networks and Network Virtualization Technologies (SDN/NFV)
Bo Ji
, Temple University, USA; boji@temple.edu
Ori Rottenstreich, Technion, Israel; or@cs.technion.ac.il

Software-Defined Networking (SDN) and Network Function Virtualization (NFV) are key enablers of an unprecedented paradigm shift, which is impacting deeply Telecom and ICT industries and ultimately leads to their full convergence. By separating control and data planes and decoupling network functionalities from purpose-built equipment, the trend in network softwarization has the potential of efficiently handling heterogeneous resources, spanning networks and data center domains, and easily and flexibly deploying new services. Software-Defined Infrastructures (SDI) are conducive to intriguing opportunities in novel network architectures, management frameworks, advanced networking and computing services, while raising outstanding challenges in security, scalability, reliability. Considered the game changer for the deployment of fifth-generation (5G) systems, SDN and NFV are expected to deliver end-to-end sliced softwarized infrastructures to dramatically transform vertical industries, such as automotive, energy, healthcare, city management, manufacturing. This track is aimed to encourage fruitful discussion of core challenges and proposals towards the realization of SDN and NFV, both from theoretical and practical perspectives, welcoming work-in-progress as well as consolidated research results.

Track Topics:

  • Software-Defined Infrastructures (SDI)
  • SDN/NFV architecture and implementation
  • SDN/NFV standardization updates
  • SDN/NFV orchestration and management frameworks
  • SDN testing approaches
  • SDN/NFV application scenarios (e.g., IoT, smart cities, automotive, industry 4.0)
  • SDN/NFV enablers for fog/mobile edge computingSDN/NFV in 5G systems
  • SDN/NFV enablers for network slicing
  • SDN/NFV "as-a-Service" paradigms
  • SDN/NFV in multi-domain scenarios
  • SDN/NFV optimization algorithms
  • SDN/NFV interplay with machine learning and artificial intelligence
  • SDN/NFV modeling and performance analysis
  • SDN/NFV security analysis and design
  • SDN/NFV emulation/simulation/experimental platforms and testing approaches
  • SDN/NFV pilots
  • Programmable switches
  • Network telemetry

TPC List:

  • Benjamin Aziz, University of Portsmouth
  • Chao Song, University of Electronic Science and Technology of China
  • Deniz Gurkan, University of Houston
  • Fangming Liu, Huazhong University of Science & Technology
  • Gino Carrozzo, Nextworks
  • Javier Rubio-Loyola, CINVESTAV
  • Jiao Zhang, Beijing University of Posts and Telecommunications
  • Jiaqi Zheng, Nanjing University
  • Jingya Zhou, Soochow University
  • Juliano Wickboldt, Federal University of Rio Grande do Sul (UFRGS)
  • Konstantinos Poularakis, Yale University
  • Lailong Luo, National University of Defense Technology
  • Nadir Shah, COMSATS University Islamabad, Wah Campus
  • Neta Rozen Schiff, Hebrew University of Jerusalem
  • Nicholas Race, Lancaster University
  • Praveen Tammana, Princeton University
  • Pu Wang, UNC Charlotte
  • Raajay Viswanathan, Uber Technologies Inc
  • Ramin Khalili, Senior researcher, Huawei Research Center, Munich
  • Salvatore D'Oro, Northeastern University
  • Shay Vargaftik, VMware Research
  • Shih-Chun Lin, North Carolina State University
  • Shiqiang Wang, IBM Research
  • Shir Landau Feibish, Princeton University
  • Ting He, Penn State University

11. Social Networks and Computing (SNC)
Pan Hui
, The Hong Kong Univ of Sci and Tech, Hong Kong; panhui@cse.ust.hk
Mingjun Xiao, Univ of Sci and Tech of China, China; xiaomj@ustc.edu.cn

In recent years, social network research has advanced rapidly, owing to explosive mobile smart devices and diverse applications. Social network computing is being combined with artificial intelligence, mobile big data, edge computing, crowdsourcing, blockchain, etc. This year, at ICCCN, we will continue with the track on Social Networks and Computing and look to bringing together researchers in the area of applying computing to social networks. Our scope will include mobile and socially-aware networks, sensing as part of social networks, big data on social networks, cloud integration of social networks, machine learning solutions for social networks, crowdsourcing applications for social networks, social Internet of vehicles, security, privacy and trust and issues in social networks, social-based routing protocols, novel architectures for social networks, and any other relevant areas related to social networking and computing. This track seeks original ideas and submissions and will follow the policies as per the main ICCCN conference policies.

Track Topics:

  • Mobile and socially-aware networks
  • Community detection and community-based collaborative computing
  • Sensing as part of social networks
  • Big data and machine learning solutions for social networks
  • Cloud-based social networks
  • Security, privacy and trust and issues in social networks
  • Novel architectures for social networks
  • Big data analytics for social networks
  • Crowdsourcing applications for social networks
  • Social Internet of Things
  • Social Internet of Vehicles
  • Social-based energy harvesting in social networks
  • Social-based resource identification, discovery, and profiling
  • Social-based routing protocols and architectures

TPC List:

  • Yong Li, Tsinghua University, China (liyong07@tsinghua.edu.cn)
  • Huber Flores, University of Tartu, Estonia (huber.flores@ut.ee )
  • Yang Chen, Fudan University, China (chenyang@fudan.edu.cn)
  • Tristan Braud, Hong Kong Univ of Sci and Tech, Hong Kong SAR (braudt@ust.hk)
  • Lik-Hang Lee, Oulu University, Finland (lhleeac@connect.ust.hk )
  • Sheng Zhang, Nanjing University, China (sheng@nju.edu.cn)
  • Benjamin Finley, University of Helsinki, Finland (benjamin.finley@helsinki.fi)
  • En Wang, Jilin University, China (wangen@jlu.edu.cn)
  • Ranjan Pal, University of Michigan Ann Arbor, USA (ranjanpal9@gmail.com)
  • Yanchao Zhao, Nanjing Univ of Aeronautics and Astronautics, China (yczhao@nuaa.edu.cn)
  • Nishanth Sastry, King’s College London, UK (nishanth.sastry@kcl.ac.uk)
  • Wenjun Jiang, Hunan University, China (jiangwenjun@hnu.edu.cn)
  • Chaker Abdelaziz Kerrache, University of Ghardaia, Algeria (kr.abdelaziz@gmail.com)
  • Sokol Kosta, Aalborg University, Denmark (sok@cmi.aau.dk)
  • Huan Zhou, China Three Gorges University, China (zhouhuan117@163.com)
  • Anna Maria Vegni, Roma Tre University, Italy (annamaria.vegni@uniroma3.it)
  • Eiko Yoneki, University of Cambridge, UK (eiko.yoneki@cl.cam.ac.uk)
  • Franca Delmastro, National Research Council, Italy (franca.delmastro@iit.cnr.it)

12. Game, AI, and ML aided Network Design and Application (GAM)
Lin Chen
, Univ. Paris-Sud, France; chen@lri.fr
Mingming Lu, Central South University, China; mingminglu@csu.edu.cn

Recently, along with the upsurge of deep learning, the success application of AI/ML to various networking fields has aroused a lot of interests in AI/ML aided network design and applications. These interests can trace back to the long-term dream of autonomous or self-driving networks, where network management and control decisions are made in an automated fashion. Building such a self-driving network is one of the “grand challenges” of networking research today. It is worth noting that network design and application are different from standard AI/ML applications, because network agents (nodes) are by natural distributed decision makers that usually have their own interests to maximize their own utilities, such as transmission bandwidth, delay, and throughput. In this regard, game theory plays an important role in modeling the interactions among independent network agents with potentially mutual conflicting objectives. Thus, the combination of game and AI/ML can help network researchers to design network protocols/applications, where network nodes can adapt their behaviors according to their self-interests and the observed network status. In this optic, this track seeks contributions related to game, AI, and ML aided network design and application.

Track Topics:

  • Game aided network design
  • Game aided network application
  • Design and implementation of closed-loop systems (modular) that use monitoring to drive network control (e.g., congestion control, TE, QoE, QoS, etc.) with minimal human intervention
  • Algorithms to train learning models for inferring network attacks, device/service fingerprinting, congestion, failures, QoE metrics, etc. in (real time) at scale
  • Techniques to collect and analyze network data in a privacy-preserving manner
  • Learning models to capture the relationship between network events and control actions
  • Design data structures and algorithms for consistently and correctly updating the distributed states (e.g., forwarding table entries)
  • Examples of design choices informed by control-theoretic findings (e.g., hard limits, unavoidable tradeoffs)
  • New use cases for self-driving networks in wireless networks, cloud networks, CDNs, home networks, etc.
  • Case studies demonstrating (dis)advantages of choosing AI/ML techniques for networking over more traditional ones
  • New topology, algorithms, and network protocols for AI/ML applications
  • Techniques to optimize distributed AI, ML and graph processing algorithms/systems with new networking options

TPC List:

  • Thomas Bégin, Univ. Lyon 1, France
  • Xu Chen, Sun Yat-sen Univ., China
  • Marco Di Renzo, CNRS/LSS, France
  • Salvatore D'Oro, Northestern Univ., USA
  • Joecelyne Elias, Univ. Paris-Descartes, France
  • Anastasios Giovanidis, CNRS/LIP6, France
  • Isabelle Guerin-Lassous, Univ. Lyon 1, France
  • Hua Huang, Stonybrook Univ., USA
  • Wanchun Jiang, Central South Univ., China
  • Shan Lin, Stonybrook Univ., USA
  • Fabio Martignon, Univ. Bergamo, Italy
  • Lai Pan, Singapore Univ. Tech. Design
  • Stefano Paris, Nokia Bell Labs, France
  • Gang Wang,Beihang Univ., China
  • Kehao Wang, Wuhan Univ. Tech., China
  • Lusheng Wang, Hefei Univ. Tech., China
  • Chia-Mu Yu, National Chung Hsing Univ.
  • Jihong Yu, Beijing Inst. Tech., China
  • Jiaqi Zheng, Nanjing Univ., China
  • Meng Zheng, Shenyang Inst. Automation, Chinese Acad. Sci.

13. Hot Topics in Networking (HOT)
Marcelo Carvalho
, University of Brasília, Brazil; mmcarvalho@ene.unb.br
Pouya Ostovari, San Jose State University, USA; pouya.ostovari@sjsu.edu

The Track on Hot Topics in Networking will bring together researchers in information and communication technologies (ICT) and computer networks arena to engage in a lively debate on the practice and theory of networking. Furthermore, this track will provide a venue for discussing innovative ideas and debating future research agendas in the wide range of future computer networking topics. In addition to mature submission, we also encourage submissions of early-stage work on novel ideas with preliminary results, that may not be submitted to the other tracks that mostly focus on full fledge work. In addition, controversial and non-traditional papers that advocate new technologies, application areas, and research directions are also welcomed in this track. The submitted papers will be reviewed and evaluated based on their originality, technical merit, and innovation as well as their potential to stimulate interesting discussions and exchange of ideas.

Track Topics:
The authors are expected to share their new ideas, latest findings, and results on the following topics, but not limited to

  • Mobile and wireless networking
  • Unmanned aerial vehicle (UAV) or Unmanned underwater vehicle (UUV) Networks
  • Robotic networks
  • Internet of Things
  • Software Defined Networks and Virtualization
  • Tactile Internet
  • Information-Centric Networking
  • Fog and Edge computing/networking
  • Social networking
  • Data center networking
  • Network security and privacy
  • Novel applications in networking
  • Business perspective of applying Data Centric Approaches in Real-World Environment
  • Intelligent Transportation Systems and Networking
  • Big Data and Future Internet
  • Transport layer issues in Future Internet Architectures
  • Multimedia Applications and Feasibility with Future Internet architectures
  • Multimedia networking
  • Future Internet and Smart Cities
  • Sensor and Ad Hoc Networks
  • Wearable and human-centric networking
  • Nanonetworks
  • Crowdsensing, Crowdsourcing
  • Cooperative and opportunistic networking
  • AI/ML-based smart networking

TPC List:

  • Katia Obraczka, University of California Santa Cruz, USA
  • Rodolfo W. L. Coutinho, University of Ottawa, Canada
  • Marc Mosko, PARC, USA
  • Rolando Menchaca-Mendez, Instituto Politécnico Nacional, Mexico
  • Nadjib Aitsaadi, University Paris Est Creteil, France
  • Cintia Borges, University of São Paulo, Brazil
  • Yu Wang, Temple University, USA
  • Hamed Ahmadi, University of Essex, United Kingdom
  • Renato Mariz de Moraes, Federal University of Pernambuco, Brazil
  • Zhuozhao Li, University of Chicago, USA
  • Alireza Jolfaei, Federation University, Australia
  • Ning Wang, Rowan University, USA
  • Nazanin Rahnavard, University of Central Florida, USA
  • Md Zakirul Alam Bhuiyan, Fordham University, USA
  • Nizar Zorba, Qatar University, Qatar
  • Mario E. Rivero-Angeles, Instituto Politecnico Nacional, Mexico
  • Zhen Jiang, West Chester University, USA
  • Marco Spohn, Federal University of Fronteira Sul, Brazil
  • Tahiry Razafindralambo, Université La Réunion, LIM, France
  • Michele Nogueira, Federal University of Parana, Brazil
  • Ertan Onur, Middle East Technical University, Turkey