Mobile Computing and Wireless Networking: Related Funding, Research Overview, Selected Papers Keynote on Wireless Networks

    Related Funding:
  1. CMMI 1436786: Collaboratve Research: Coordinated Real-Time Trafc Management based on Dynamic Informaton Propagation and Aggregaton under Connected Vehicle Systems, a three-year grant from the National Science Foundation. PI: Lili Du, Co-PI: Xiang-Yang Li, $240,000.
  2. NSF 1343306, EARS: Modeling and Analysis of Radar / Communications Spectrum Sharing Opportunities, a three-year grant from the National Science Foundation. PI: Dennis Roberson, Co-PI: Cindy Hood and Xiang-Yang Li, $512,169.
  3. NSF 1247944, EARS: Providing Predictable Service and Spectrum Access With Realtime Decision in Cognitive Multihop Wireless Networks, a three-year grant from the National Science Foundation. PI: Xiang-Yang Li, Co-PI: Erdal Eruklu. $498,122.
  4. PRC NSFC: China National Natural Science Foundation of Overseas Young Scholars Cooperation Research Fund (Outstanding Young Researcher-B). National Natural Science Foundation of China(Grant Nos.61228202). PI: Xiang-Yang Li, Co-PI: JiZhong Zhao. 2013.1.1-2014.12.30, RMB 200,000.
  5. USA NSF 1035894, CPS:Medium: The Study of and Methodology Development for Loosely Coupled Networked Control Systems with Disturbances, NSF CNS-1035894, PI: Xiang-Yang Li, Co-PIs: ShangPing Ren, Paul Anderson, and Fouad Teymour. 2010.09.15 - 2013.09.14. $750,000.00,
  6. USA NSF 0832120, NeTS-NECO: Some Fundamental Problems for Performance Study of Opportunistic Spectrum Utilization, NSF CNS-0832120, PI: Xiang-Yang Li, 2009.1.1 - 2011.12.30. $249,982.00,
  7. PRC NSFC: China National Natural Science Foundation of Overseas Young Scholars Cooperation Research Fund (Outstanding Young Researcher-B). National Natural Science Foundation of China(Grant Nos.60828003). PI: Xiang-Yang Li, Co-PI: Yong Qi. 2009.1.1-2010.12.30, RMB 200,000; 2010.12.30-2014.12.30, to be determined.
  8. HK RGC: Explore Business Models for Streaming Applications in Peer-to-Peer Environments. PI: Wei Lou, Co-PI: Xiang-Yang Li. CERG under Grant PolyU-5232/07E. 01-01-2008 to 31-12-2009, HK$ 378,400.
  9. HK RGC: Effective and Efficient Environment Monitoring in Wireless Sensor Networks, PI: YunHao Liu, Co-PI: Xiang-Yang Li. Hong Kong RGC CERG HKUST6169/07E, Sep. 1, 2007- Aug. 31, 2009. HK$ 489,445 (US$ 70K),
  10. HK RGC: A Microeconomic Approach for Digital Rights Management in P2P Networks, PI: XiaoWen Chu, Co-PI: Xiang-Yang Li. RGC HKBU 210406, from 01-09-2006 to 28-02-2009, HK$356,000.
  11. USA NSF: Prefix-Free Vertex Coloring for Channel Assignment in OVSF-CDMA Wire-less Ad Hoc Networks. PI: Peng-Jun Wan, Co-PI: Xiang-Yang Li. NSF Grant CCR-0311174. 2003-2006. $187,474.00.
  12. USA NSF: International Workshop on Theoretical Aspects of Wireless Ad Hoc, Sensor, and Peer-to-Peer Networks. PI: Xiang-Yang Li. 2003. $20,000.00

    Course Created and Taught at IIT:
  1. CS595: Foundations of Cyber-Physical Systems later renamed to regular course CS557: CYBER-PHYSICAL SYSTEMS: NETWORKING AND ALGORITHMS
  2. CS549: Cryptography and Network Security

    Research Overview:

     Understanding the science and engineering aspects of various networks (such as computer networks, social networks) has been attracting considerable research interests of scientists from different disciplines. The work conducted at Illinois Institute of Technology in the Wireless Networking Lab, led by Xiang-Yang Li, professor of computer science, is taking on the challenge of understanding the fundamental performance behaviors of large scale wireless networking, designing and implementing more energy efficient networking technologies under the most adverse technological challenges we ever faced, implementing mobile computing systems that will fulfill practical needs, and designing wireless networking protocols that will significantly enhance the performance. Overcoming these challenges will enable a new class of energy-conscious wireless networks that deliver high throughput networking and computing in a more environmentally-responsible manner. Li has been concentrating on investigating questions in various networks that have significant real world impact and that could contribute in fundamental ways to the advancement of networking science and related engineering disciplines. It involves both theoretical and empirical methods. Topics of his research projects include cyber-physical systems, wireless sensor networks, mobile computing, crowd-sourcing, and privacy issues in these networks. Li’s research is contributing and is supported in part by the National Science Foundation, through NeTS CPS, and the EARS program.
    Wireless Network Capacity: A Tale of Cognitive Radio and Coexistence: Understanding asymptotic network behavior has been one of the heavily investigated scientific problems that are instrumental to network design and planning. The majority of the past efforts have been focusing on a single technology network. In the recent years, Li’s research group has investigated the impact of two new technologies, i.e., cognitive radio and coexistence of cross-technology networks, on some fundamental network performance limits. In the last decade, we witnessed a boom of various wireless technologies, especially mobile networking and short range communication technologies such as WiFi, Zigbee, Bluetooth, NFC, and RFID. Urban area wireless networks (including sensor networks, WiFi networks and mesh networks) are also becoming vitally important for nowadays “smart city” programs. These grand engineering works (e.g., CitySee Project, co-led by Li), typically using Zigbee networking technology, heavily depend on sensor nodes and efficient network connections for monitoring environment and collecting data for further study. Network designers are desperately searching for technology solutions that can make the most of, and increase their existing network capacity. To better utilize network resources, and for better network planning, design and deployment, we need a thorough understanding of the network capacity and other performance limits. Unfortunately, with crowded wireless devices and wireless communication technologies, the spectrum available for devices to build high quality communication links has been exhausted, and wireless interferences are more severe due to both the same technology interference and the cross-technology interference. In the last decade, several new innovative solution paradigms have been proposed to alleviate the negative impact of the spectrum scarcity and wireless interference. They include, but are not limited to, cognitive radio networking technology and harmony coexisting technology. However, classical network capacity results cannot fully reflect the advancement brought by these new paradigms.
    Cognitive Radio: First, available spectrum is being exhausted, while a lot of frequency bands are extremely underutilized. As a promising solution to improve dynamic allocation of the under-utilized spectrum, cognitive radio technology allows secondary users to opportunistically access vacant channels in temporal and spatial domain when the primary user is idle. However, due to resource and hardware constraints, at a given time, cognitive radios (CR) can sense only a part of the available heterogeneous channels with unknown quality before transmission. Thus, it is vital for secondary users to learn and select the best possible channels to access. Li’s group has developed a sequence of spectrum channel sensing, probing, and accessing methods that will theoretically guarantee that the average network throughput achieved under these methods will be asymptotically optimum, i.e., the difference between the throughput achieved by these methods and the optimum goes to zero over a time-horizon. Several recent results are proposed to tackle the dynamic spectrum sharing problem as the multi-armed bandits problem, and attempt to find a dynamic channel access policy that results in almost optimal expected throughput (or zero-regret), compared with the optimal fixed channel policy. Dynamic channel access in multihop cognitive radio networks demands more sophisticated formulation that considers constraints of general interference among users. A naive extension of formulation from the single-hop case to multihop case will lead to regret, time and space complexity that is exponential with the number of users in the learning process. Efficient channel access under multihop networks also requires decentralized design with low computation and communication. Previous decentralized MAB methods pay little attention to these practical challenges around multihop networks. We recently designed methods for achieving maximum expected throughput through a decentralized learning process with low computation and communication cost. This problem involves competition among adjacent users, and cooperation for maximum throughput network wide. We formulate the problem into a linearly combinatorial MAB problem. This novel formulation facilitates us to utilize a zero-regret learning policy where it only costs time and space complexity O(MN) for a network with M channels and N secondary users.
    Coexisting Cross-Technology Networks: Recent studies show that in urban areas, WiFi interference is pervasive and possibly the primary factor leading to ZigBee throughput degradation. Existing approaches for dealing with such interferences often modify either the ZigBee nodes or WiFi nodes. However, massive deployment of ZigBee nodes and uncooperative WiFi users call for innovative cross-technology coexistence without intervening legacy systems. In most of the previous studies, WiFi is often the signal of interest, and other mixed signals are eliminated as interference.
    Recently, Li’s group has investigated the WiFi and ZigBee coexistence when ZigBee is the signal of interest. Mitigating short duration relatively high-power WiFi interference (called flash) in long duration relatively low-power ZigBee data packets (called smog) is challenging, especially when we cannot modify the WiFi APs and the massively deployed sensor nodes. Solutions that make the WiFi network aware of the existence of ZigBee or suppress subcarriers will lead to performance degradation. Modifying the Zigbee networks to adapt to WiFi networks requires heavy reprogramming and is not interoperable with legacy systems.
    Recently, Li’s group has developed a new technology, ZIMO, focused on the WiFi and ZigBee coexistence when ZigBee is the signal of interest. ZIMO is a sink-based MIMO design for harmonic coexistence of ZigBee and WiFi networks with the goal of protecting the ZigBee data packets. The key insight of ZIMO is to properly exploit opportunities resulted from differences between WiFi and ZigBee, and bridge the gap between data of interest and cross technology signals. An extensive evaluations of the ZIMO protocol under real wireless conditions has shown that ZIMO can improve up to 1.9x throughput for ZigBee network, with median gain of 1.5x, and 1.1x to 1.9x for WiFi network as byproduct in ZigBee signal recovery. Our design does not need make modifications and interventions on neither WiFi APs nor ZigBee transmitters.
    Cyber-Physical Systems: The recent explosive growth of ultra-small and energy-efficient sensors is reshaping the landscape of many engineering systems, including, but are not limited to, the smart electric grid, smart transportation, smart medical technologies, and advanced manufacturing. Cyber-physical systems are engineered systems that are built from and depend upon the synergy of computational and physical components.
    In the last decade, Li’s group has been developing the core system and networking science needed to engineer complex cyber-physical systems. In collaboration with Shangpin Ren, associate professor of computer science, Paul R. Anderson, professor of civil, architectural, and environmental engineering, and Fouad Teymour, Johnson Polymer professor of chemical and biological engineering, Li’s group studied the Chicago waterway systems by modeling it as loosely coupled networked control systems with external disturbances. The aim is to advance wastewater processing engineering procedures by taking advantages of available cyber technologies that can provide not only sufficient real-time accurate data collected from ground-based sensors, but also physics-based climate simulations to effectively predict the impact from nature on the wastewater processing. Li developed mathematical abstractions to accurately model loosely coupled networked control systems, such as the waterway system, developed online actuation decision models that takes into account delayed observability of actions and temporal and spatial dependencies among them based on the mathematical abstraction model, and to help uncover scientific and engineering principles that cross-cut many application sectors. Based on these models, we developed a set of algorithms and policies to optimize system performance with respect to applications' quality of service (QoS) requirements.
    Designing Large Scale Sustainable Sensor Networks: Sensor networks, a major component in cyber-physical systems, are envisioned to consist of hundreds or thousands of inexpensive nodes that can be readily deployed to collect useful information in a robust and autonomous manner. However, several obstacles need to be overcome before this vision becomes a reality. Collaborating with researchers from several institutions, Li’s group designed and deployed wireless sensor networks, CitySee and GreenOrbs, for environment monitoring and study. The deployed sensor network is used for air quality monitoring, motivated by fighting global warming. Global warming, i.e., the increase in the average temperature of Earth’s near-surface air and oceans and its projected continuation, has enormous physical, ecological, social and economic impacts. Most of the observed temperature increase has been caused by increasing concentrations of greenhouse gases (GHGs). Among the totally emitted GHGs, 72% is carbon dioxide (CO2). The concentration of CO2 has increased from about 280 ppm (parts per million) preindustrial to about 388 ppm recently. Thus, CO2 emissions are the most important cause of global warming.
    Multi-hop large scale WSN with CO2 sensors, consisting of thousands of inexpensive nodes, can be deployed to provide real-time, comprehensive monitoring in a robust and autonomous manner. The CitySee system, collaborated by Li’s group and research institutions from HongKong and China, is composed of more than 1200 nodes that continuously work for more than one year now. This is one of the largest sensor networking systems reported, to the best of our knowledge. A number of unique phenomena were discovered in this large system and a number of challenging questions are addressed to make it sustainable and reliable. The system and experience obtained shed light on designing sustainable, scalable, and reliable sensor networks that meet industrial standards, especially on designing sustainable sensor networking systems with limited energy, computing and communication resources available to the sensor nodes.