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  • ​KAUST-NSF Conference on


    Environmental Monitoring​​

    Conference Center Hall, Building 19, Level3​​
  • ​​KAUST-NSF Conference on


    Environmental Monitoring​​

    Conference Center Hall, Building 19, Level3​​​

​​​​About

The KAUST-NSF Research Conference is a tradition that started in 2014, led by faculty in the EE program at KAUST. The topic of this fifth cycle of the conference is environmental monitoring and sensing. These applications involve collecting and transferring data using sensor communication networks, analyzing data using signal processing, and making real-time decisions with the aid of high performance computing and machine actuation, thereby completing the cyber-physical systems cycle. Conference topics include the domains of urban, ocean, and agricultural applications, along with the foundational areas of communications and networking, signal processing, and control. The conference will engage internationally leading authorities, industry experts, fellow in-Kingdom researchers, and KAUST researchers.​​​​​​​​​​

The Conference is organized with financial support from the KAUST Office of Sponsored Research(OSR). Co-sponsored by National Science Foundation (NSF), United States of America, the KAUST Industry Collaboration Program (KICP) and the Computer Electrical Mathematical Science and Engineering (CEMSE) Division. ​

  • MondayNovember 6
  • TuesdayNovember 7
  • WednesdayNovember 8
9:00 AM

Welcome & Opening Remarks

9:15 AM

KEYNOTE: Simulating and Sensing Pedestrian Movements and Behaviors

From record-setting crowds at rallies, robot swarms in the field, to avatars in social virtual reality (VR), our world is experiencing a continuing rise of complex, distributed systems of independently moving humans in physical and virtual worlds. With potential applications such as predicting crowd panic, improving human-robot cooperation, enhancing social interactions, conceptualizing urban layout, computational models to analyze, understand, predict, reproduce, and control collective behaviors of complex human dynamical systems are becoming critically important. In this talk, we will present an overview of work on simulating as well as sensing movements of pedestrians as part of a crowd. These include new velocity-space models to compute cooperative motion paths and behaviors for a group of independent agents, sharing the same physical world or virtual space. These techniques include optimization-based strategies for distributed collision avoidance, the principle of least effort for simulating crowds, and data-driven models for capturing differences in personalities. Furthermore, we use these navigation along with Personality Trait Theory to characterize the personality of pedestrians from crowd videos and identify anomalies in their behaviors. We highlight their applications to modeling the behavior and movements of pilgrims during Hajj, Presidential Inauguration crowds, Social VR, human-robot interaction, visual surveillance, and architectural analysis. http://gamma.cs.unc.edu/research/crowds/

 Dinesh Manocha
University of North Carolina at Chapel Hill
10:15 AM

Coffee Break

10:30 AM

Crowd Sensing in Hajj and Umrah

The world population is growing and today more than ever infrastructures of societies such as roads, shopping malls and transport terminals are having to cope with ever more intense and complex flows of people. Recent tragic incidents of mass gathering has brought into attention the need to understand crowd behaviours and develop methods and technique to sense and monitor crowd in order to ensure crowd safety and security. Advanced technologies of from computer vision and ubiquitous technologies allows to sense and monitor huge crowds and to understand their behaviors. Cameras equipped with intelligent algorithms are capable of counting the number of people in scene and assessing their density distribution. Moreover, videos cameras can measure movement speed, direction as well as flow rate in Tawaf and Saee (Hajj & Umrah rituals). In this study we present the use of computer vision to sense crowd size and density as well as flow rate in different parts of Hajj and Umrah. In Ramadan we measured the number crowd performing Tawaf and their flow rate using four cameras with overlapping view mounted on the rooftop of Mattaf. On 27 of Ramadan 1437H at midnight, we recorded the presence of about 27800 people in Mattaf and completing 7 laps of Tawaf around Kabba took about 55 minutes. This is considered the most crowded date in Ramadan season. In the Hajj season we recorded the maximum number of people in Mattaf on 12 ZulHijah 1437 at 5PM, the number of people performing Tawaf was recorded at 26100 person and the required to complete Tawaf was 56 minutes. In Saee, the throughput of the ground floor was about 14650 person/hour on 12 Dul Hijah 1437. These measurements and readings has been verified by manual counting and Tawaf timing recorded from GPS devices simultaneously with camera recording. In Mina, we recoded the flow of people going toward Jamarat Bridge using cameras mounting on King Khalid Bridge facing streets 204 Souq-Al-Arab and Jowhara and we also recorded the inflow and out flow to and from Jamarat Bridge. On 10 Zul Hijah 1437H at 10PM, the inflow to Jamarat Bridge at the largest ramp was measured as 5.44 person/min while the outflow at the largest ramp was measured at 5.46 person/min. Visit ivul.kaust.edu.sa and www.bernardghanem.com for more details.

11:00 AM

UE4Sim: A Photo-Realistic Simulator for Computer Vision Applications

In this talk, I will present UE4Sim, a photo-realistic simulator based on the open source computer game engine, Unreal Engine (UE4). UE4Sim was developed by the Image and Video Understanding Lab (IVUL) at KAUST and it is designed to be a fully enclosed environment to train, validate, and evaluate methods developed for a multitude of computer vision, machine learning, and robotics tasks, including autonomous navigation, visual object tracking, action recognition, crowd understanding, to name a few. One important feature of UE4Sim is that it provides a desirable level of photo-realism, which can ultimately facilitate the transfer of models/knowledge acquired in the simulator to the real-world, thus, avoiding the need to retrain from scratch in the latter environment. I will highlight the merits of UE4Sim by focusing on three exciting applications: persistent aerial tracking, self-driving cars, and autonomous racing UAVs (unmanned aerial vehicles).

11:30 AM

Smart Infrastructure for Livable Communities

Today, more than half of the world’s population lives in cities with more than six devices per person connected to the Internet. This implies that billions of devices and systems are embedded in a city’s infrastructure. Smart city services rely on computation and communication resources and analysis of the tremendous data to enhance safety, efficiency, productivity and quality of life for its citizens. In this talk, we showcase our research towards the softwarization of networks and endowing them with intelligent services to manage their resources in support of smart city applications. We start by describing two new biologically inspired channel selection strategies for societies of secondary users in dynamic spectrum access networks. Such channel selection strategies can be utilized in support of a wide variety of applications including vehicular networks and the Internet of Things (IoT). Then we present our work on a versatile platform for the development of IoT applications that dynamically leases cloud resources to deliver services that maximize the revenue collected from the delivery process of sensory data to IoT application users given Quality of Service (QoS) guarantees. We finish our talk by summarizing our work on a smart white cane to enhance the safety and crossing abilities of pedestrians at wide and complex intersections. This system is composed of three subsystems, the veering adjustment system through RFID technology (D2I), vehicle alert system through D2D and the cloud (D2V & V2D), and the green time system where connection is established through WiFi with the signal controller (D2I).

 Ala Al-Fuqaha
Western Michigan University
12:10 PM

Lunch

1:30 PM

Optimization Techniques for Large Scale Data Science Problems

The alternating direction method of multipliers (ADMM) is widely used to solve large-scale linearly constrained optimization problems, convex or nonconvex, which arise in numerous data science applications. However there is a general lack of theoretical understanding of the algorithm when the objective function is nonconvex or if the algorithm is implemented distributedly. In this talk we discuss the design and convergence of ADMM type algorithms for solving nonconvex optimization problems and if distributed asynchronous implementation is required.

 Zhi-Quan (Tom) Luo
The Chinese University of Hong Kong, Shenzhen
2:00 PM

Gaussian Comparisons Meet Convexity: Precise Analysis of Structured Signal Recovery

Non-smooth convex optimization has emerged as a powerful tool for modern large-scale inference problems, in which the desired properties of the unknown signal lie in some low-dimensional structure. While the algorithms are fairly well established, rigorous and unifying frameworks for their precise analysis are only recently emerging. We present a framework to evaluate the performance of such recovery methods under Gaussian measurement ensembles and under different measurement models. For illustration, we obtain novel expressions for the symbol-error rate of the popular box relaxation decoder in massive MIMO systems. The exact formulae allow accurate comparisons to the matched-filter bound and to the zero-forcing decoder.At the heart of the analysis is a stronger and tight version of a classical Gaussian comparison inequality in the presence of additional convexity assumptions, which we call the convex gaussian min-max theorem (CGMT).

 Christos Thrampoulidis
Massachusetts Institute of Technology (MIT)
2:30 PM

From Statics to Dynamics and from Convexity to Nonconvexity: the Scaling Limit of Iterative Algorithms for High-Dimensional Inference

This talk presents our recent work on analyzing, in the high-dimensional limit, the exact dynamics of iterative algorithms for solving nonconvex optimization problems that arise in signal estimation. For concreteness, we will focus on the prototypical problem of sparse principal component analysis in the talk. We show that the time-varying empirical measures of the estimates given by the algorithms will converge weakly to a deterministic “limiting process” in the high-dimensional limit. Moreover, this limiting process can be characterized as the unique solution of a nonlinear PDE, and it provides exact information regarding the asymptotic performance of the algorithms. For example, performance metrics such as the MSE, the cosine similarity and the misclassification rate in sparse support recovery can all be obtained by examining the deterministic limiting process. A steady-state analysis of the nonlinear PDE also reveals interesting phase transition phenomena related to the performance of the algorithm. Although our analysis is asymptotic in nature, numerical simulations show that the theoretical predictions are accurate for moderate signal dimensions. We will conclude the talk by briefly presenting the application of similar analysis techniques to other nonconvex optimization problems such as phase retrieval, subspace tracking, low-rank matrix estimation, and dictionary learning. Joint work with Chuang Wang (Harvard University) and Jonathan Mattingly (Duke University)

3:00 PM

Coffee Break

3:30 PM

Sensing and Observing the Marine Environment using Integrated Mobile Platforms and Coupled Ocean Modeling

Modern advances in autonomous surface and underwater vehicles, coupled with innovative sensor technologies have enabled a new level of capability that has yet to be fully exploited in understanding and imaging the three-dimensional ocean. By merging together various types of autonomous platforms, including animal platforms, new insights into how the marine environment functions are now possible. While no single capability is a sufficient in itself, by coupling these various capabilities and linking them to a “smart” modeling

4:00 PM

Exploring the Frontier of Cooperative Marine Robotics: Navigation and Control of Networked Autonomous Vehicles

The last decade has witnessed tremendous progress in the development of marine technologies that are steadily affording scientists advanced equipment and methods for ocean exploration and exploitation. Recent advances in marine robotics, sensors, computers, communications, and information systems are being applied to the development of sophisticated technologies that will lead to safer, faster, and far more efficient ways of exploring the ocean frontier, especially in hazardous conditions. As part of this trend, there has been a surge of interest worldwide in the development of autonomous marine robots capable of roaming the oceans freely and collecting data at the surface of the ocean and underwater on an unprecedented scale. Representative examples are autonomous surface craft (ASC) and autonomous underwater vehicles (AUVs). The mission scenarios envisioned call for the control of single or multiple AUVs acting in cooperation to execute challenging tasks without close supervision of human operators. This talk addresses the general topic of cooperative motion navigation and control of marine vehicles, both from a theoretical and a practical perspective. The presentation builds upon practical developments and experiments. Examples of scientific missions with ASCs and AUVs, acting alone or in cooperation, set the stage for the main contents of the presentation. Especial emphasis is placed on the problem of operating groups of vehicles for scientific ocean studies, habitat mapping in complex 3D scenarios, geotechnical surveying, and sustained presence at sea in hazardous environments. From a theoretical standpoint, a number of challenging problems are addressed in the area of cooperative motion control and navigation of groups of autonomous vehicles. The connections with advanced methods for navigation, including geophysicalbased navigation, are also briefly discussed. The results obtained are illustrated with videos from actual field tests with multiple marine robots exchanging information over acoustic networks. * The core material presented in the talk was obtained in the scope of the following EC-funded projects: • CO3AUVs (http://www.co3-auvs.org), • MORPH (http://cordis.europa.eu/project/rcn/101726_en.html), • CADDY (http://www.caddy-fp7.eu/), and • WiMUST (http://www.wimust.eu/)projects of the EC.

4:30 PM

Sensing and Control in Underwater Robotics: Challenges, Some Solutions and Experiments

During the last decades, underwater robotics has known a widespread interest from different research and industrial communities (Design, sensing actuation, dynamics, control, localization and mapping, etc.) given the multiple tasks they can accomplish. Indeed, their applications are multipole, such as dams inspection, oil and gas industry, fish farms, wind parks, hydroelectric power stations, underwater archeology, ocean cartography, air crash and environmental investigations, etc. An underwater vehicle is a submersible platform equipped with actuators, required to allow reliable vehicle motions; and sensors, to acquire data from the ocean environment. This talk will be organized in two parts. The first one will be focused on a technological review about the main sensors used in underwater monitoring in terms of localization, perception and communication. The initial sensors used in underwater robotics were mainly made by a simple integration of existing sensors, used in other fields of robotics, while considering underwater constraints. Nowadays, it has been recognized the need of developing of new sensing systems based on the constraints imposed by the underwater vehicle. This has stimulated the development of new sensors, specific for underwater vehicles (smarter, lower energy, more reliable, etc.) and enabling the cooperation between different vehicles to acquire the needed data and achieve successfully the mission. The second part of the talk will be focused on control of underwater vehicles for inspection applications, illustrating the use of sensors in feedback control. All the proposed control solutions will be illustrated through real-time experiments showing their effectiveness and robustness.

 Ahmed Chemori
University of Montpellier
9:00 AM

Welcome & Opening Remarks

9:15 AM

KEYNOTE: Diffusion Learning Over Weak Graphs

Interactions among networked agents influence the beliefs of agents about the state of nature. For example, in deciding whether the state of nature, denoted by θ, is either θ = 1 or θ = 0, an agent observes some data whose probability distribution is dependent on the unknown θ and, additionally, consults with its neighboring agents about their opinion on the most plausible value for θ. By combining their local measurements with the information from their neighbors, agents update their belief about θ continuously. In this work, we examine social learning and the diffusion of information over weakly-connected graphs where the flow of information is asymmetric. This scenario is common over social networks. For example, it is not unusual for some influential agents (such as celebrities) to have a large number of followers, while the influential agent may not be following most of them. A similar effect arises when social networks operate in the presence of stubborn agents, which insist on their opinion regardless of the evidence provided by observations or by neighboring agents. It turns out that weak graphs influence the evolution of the agents’ learning in an interesting manner and facilitate the spread of false information. Under some circumstances, a scenario arises where the influential agents in the network drive the learning behavior and determine the limiting state for all agents regardless of their local observations. For example, some agents may be driven to believe erroneously that “it is raining” although they are observing “sunny conditions.” At the same time, the graph topology endows non-influential agents with a resistive mechanism where they cannot be driven to any arbitrary belief. This presentation examines these patterns of behavior over multi-agent inference networks analytically and illustrates the results with examples and simulations.

10:15 AM

Coffee Break

10:30 AM

Autonomous Aerial Manipulation

Advances in unmanned aerial vehicle (drone) technologies have encouraged people to explore more sophisticated applications than aerial photography. In particular, unmanned aerial vehicles equipped with robotic manipulators can perform useful tasks such as inspection, maintenance, transportation, disaster recovery, and precision farming. This talk describes effective methodologies for aerial manipulation using (potentially multiple) autonomous unmanned aerial vehicles. Key ingredients including motion planning together with collision avoidance strategies, control algorithms for dexterous manipulation, distributed coordination, and vision-based detection and navigation algorithms will be discussed, along with their integration.

 Hyoun 'Jin' Kim
Seoul National University
11:00 AM

Planning Algorithm and Multi-Vehicle Formation for Environmental Monitoring by Using Low-Cost UAVs

Environmental monitoring using autonomous low-cost Unmanned Ariel Vehicles (UAVs) have been emerged as an efficient and unique robotic application. Inspecting large terrains (e.g. natural reservers, water reservoirs ) is considered an intensive task for humans and critical by its nature since missing any detail could affect nature ecosystems and its integrity. Furthermore, natural environments inspection is a time and resource intensive task that should be performed as eciently and accurately as possible. In this talk, it is proposed a coverage planning algorithm for inspecting large terrais that maybe include complex natural structures, using low-cost UAVs. The proposed method follows a model based coverage path planning approach which generates an optimized path that passes through a set of admissible waypoints sampled uniformly to cover a relative complex environments. The algorithm provides a prediction of the relative coverage of the regions by using “a priori” representations or maps. A search space coverage path planner technique is proposed that uses UAV's on-board sensors' models to generate optimal paths that maximize coverage and accuracy and minimize travelled distance. In addition, a pattern formation for use of multi-uav systems is proposed to achieve geometric patterns and overlook the visibility limitation in UAVs. A methodology to reach a complete coordinate agreement is adopted to achieve a desired pattern. In this talk, a decentralized approach for circle formation is highlighted. Simulation results have validated the robustness of the proposed algorithm, where the pattern has been successfully constructed in a self-organized manner an UAV swarm.

 Jorge Dias
Khalifa University, Abu Dhabi.
11:30 AM

Integrated Actuation, Sensing and Sampling in Autonomous and Networked Systems

A wide range of current and emerging engineering applications address the development of novel autonomous systems with agile maneuvering and robust perception in dynamic, complex and unpredictable environments well beyond what is currently feasible in practice. Further, systems with a rich array of sensors but limited power and/or processing resources have more potential information available than they can use and are forced to subsample the data. In the work presented here, integration of the tasks of modeling, control, sensing and sensor selection for autonomous systems is considered. The lack of a separation principle between control and estimation in nonlinear systems is leveraged for improved system observability based on the idea of co-design of control and estimation. We build on observability analysis for general nonlinear systems to provide a basis for a framework to investigate dynamic sensor selection to optimize a measure of observability, specifically the condition number of an observability Gramian. These ideas will be discussed relative to both engineering applications in the form of motion planning for range and bearing only navigation in autonomous vehicles, vortex position and strength estimation from pressure measurements on airfoils, and effective strain sensor placement on insect wings for inertial measurements.

12:00 PM

Lunch & Poster Session

2:00 PM

Towards Sustainable Smart Desalination Systems

The rising population around the world is placing increased pressure on the already limited natural freshwater resources. To satisfy rising demands, many countries rely on seawater desalination to meet their fresh water needs. However, alternatives to the conventional energy intensive thermal desalination methods have to be developed for a sustainable future. Membrane distillation (MD) is an example of emerging technology for sustainable water desalination. In this talk, I will present feedback strategies that help in optimizing and controlling the MD process and also designing algorithms to automatically detect performance deterioration such as fouling.

2:30 PM

Harnessing a Revolution in Earth Observation: from CubeSats, UAVs and IoTs to Machine Learning and Big-Data Analysis

We are witnessing the emergence of new and exciting earth observing technologies with the potential to revolutionize how we undertake, and interpret, the sensing of our environment. From advanced shoe-box sized CubeSats, to the rise of unmanned aerial vehicles, monitoring the earth has never been more precise, or the data more attainable. Other technologies beckon, including stratospheric balloons and solar planes, as well as enhanced ground-based capabilities that include distributed networks of miniaturized sensors, and other internet enabled devices. Developing smart and efficient techniques to interpret this data deluge, together with approaches that extract the signal from the noise, has never been more important. Here we examine the application of some of these emerging sensing technologies and analysis techniques to the field of agriculture, highlighting how new observation platforms offer enhanced insights into crop health and condition, and enable the delivery of smart-farming approaches that provide farmers with actionable intelligence. When combined with more numerical modeling approaches, these observation streams will help to deliver needed improvements in the management of our global food and water resources.

3:00 PM

Coffee Break

3:15 PM

On Groundwater Usage: Theory and Evidence

We use game theory and individual-level data to study usage of groundwater. We propose a dynamic game theory model to describe how individuals behave when resource usage induces social costs, and how they anticipate their participation in resource depletion. The main prediction of the theory reflects the key issue underlying tragedy of the commons, namely, free-riding behavior. We test our predictions on a unique, large-scale dataset from one of the most agriculturally productive districts in the US where farmers irrigate crops from a common-groundwater resource. We study interaction effects and propose some new policy arguments.

3:45 PM

Imagineering the Cybernetics of Water Resource Management

Regions around the world are facing rapid large-scale environmental changes brought about by natural forces unleashed by climate change; historical forces driven by social, political and demographic changes; and global transitions triggered by new technologies. In South Asia, the impact of these changes is felt most in the water sector in poor management of irrigation networks, depleting groundwater, deterioration in water quality, poor sanitation and difficulties in preservation of eco-systems. To address these challenges, we have developed and deployed cyber physical systems and IoT inspired solutions for water management and precision agriculture in the Indus river basin in Pakistan.These include real-time flow monitoring systems, innovative schemes for demand-based and supply-driven irrigation delivery and the use of unmanned aerial vehicles (UAV) to inspect siltation of water channels. We demonstrate the effectiveness of such cybernetic technologies in scaling-up solutions for transparent and effective governance of water resources.

9:15 AM

KEYNOTE: Optimal Mass Transport and the Robustness of Complex Networks

10:15 AM

Coffee Break

10:30 AM

From IoT to Ephemeral Computing: Understanding Cyber-Physical Interactions for Monitoring and Control

Networks of sensor devices are being embedded into the world around us, however to ensure their continuous operation requires new network protocols, data analytics and a strong understanding of how the physical world impacts on the cyber world. This short talk will introduce the work of the Julie McCann and Adaptive Embedded/Emergent Systems Engineering group in DoC showing what the future of such systems will look like and how this will bring about a world of Ephemeral Computers that can become what the user wishes.

11:00 AM

Designing Smart Cities: A Big Data Approach

Cities are arguably our most highly complex socio-technical systems. A city is, in fact, a system of systems. Its physical systems include communication, energy, mobility, urbanism (how people interact with the built environment), waste, and water. A city also includes a variety of social systems such as culture, education, economy, health, and labor. It is subject to environmental systems such as pollution and the weather, and they establish governance systems—administration and security—and function within those established by others. These systems are intertwined, integrating people, technology, and services, and producing interactions that give way to so-called emergent properties. The City Dynamics platform explores these systems and their interactions and what we can learn from the detailed, data-driven study of how they work. It explains the questions this understanding can answer and the city design challenges it can inform. The platform can help policymakers address the challenges of serving the current population and planning for the future by equipping them with a level of insight that was not attainable before the era of big data.

11:30 AM

Environment-Aware and User-Centric Internet of Things.

The Internet of Things (IoT) is expected to connect billions of objects and devices through global dynamic information exchange leading to diverse applications and services which will result in major cost savings, new revenues, and employee productivity enhancements. However, real-world deployment and use of IoT systems is very challenging mainly because of the Big Data generated, the large-scale deployment of sensors and devices, and the heterogeneity of IoT technologies. This talk will address these challenges and will present state-of-the-art strategies for building IoT architectures that are environment-aware, user-centric, and sustainable. The talk will discuss dynamic learning and adaptation strategies that are based on environment awareness and end user behavior. Several examples will be provided showing the impact of user-centric design on improving user experience and optimizing the IoT system performance (in terms of energy, bandwidth, sensing, computing, and data analytics).

 Mohamed Ibnkahla
Carleton University, Ottawa, Canada
12:00 PM

Lunch

1:30 PM

Towards a Flexible Software-Defined Network Ecosystem

The next generation of networks will need to offer capabilities far beyond the current Internet to accommodate the requirements for global-scale interconnection of Internet-of-Things devices and cyber-physical systems such as smart cities, smart grids, and autonomous automobiles. This requires a transformation of existing, rigid infrastructure into Software-Defined Infrastructure (SDI): deeply programmable, highly interconnected, virtualized systems spanning many administrative domains. Current technological trends such as Software-Defined Networking (SDN), Network Function Virtualization (SDN) and Programmable Dataplanes are key enablers to this transformation. Software-Defined eXchanges (SDXes) are emerging as interconnection points between multiple SDI domains and promise to significantly increase the flexibility and function of interdomain traffic delivery. This talk will present one particular approach, as embodied within the H2020 ENDEAVOUR project, to enable the next generation of programmatic network services in SDXes.

2:00 PM

Broadband Where You Need It

The increasing reliance on mobile devices like smart phones for managing critical tasks of our daily lives has made access to broadband more critical than ever. Unfortunately, the infrastructure for delivering broadband has not been able to keep up with the growing demand. Technologies that power broadband networks today are either expensive (fiber) or do not scale (copper/wireless). As a result, in the last ten years, we have witnessed a gap between the demand for data and the capacity offered by the current broadband infrastructure that continues to grow exponentially. At the same time, many regions, especially rural, continue to be underserved. In addition to the challenges associated with last mile fiber deployment, a large component of the data traffic is becoming increasingly mobile, leaving wireless as the only viable option to solve the broadband challenge. With recent advances by Tarana Wireless in radio design, wireless technology, as a fiber alternative for the last mile, has become a reality for the first time. Using wireless as a replacement to fiber not only reduces the cost of deployment, but also significantly increases network rollout speed. In this talk, we discuss the challenges of using wireless as a mechanism for delivering broadband, and how these challenges are overcome with Tarana technology. We also provide an overview of Tarana’s universal wireless transport system and discuss different applications where it can be used to support mobile data explosion in the coming decade.

2:30 PM

Resource Sharing and Exchange of Services in Wireless Networks: Theory and Novel Realizations

The proliferation of mobile internet access poses new challenges to wireless service providers as the capacity growth of their networks cannot cope with the rate of increase of mobile wireless traffic. Alternate means are considered to deal with the excessive traffic demand, that exploit the proliferation of wireless networks in unlicensed parts of the spectrum as well as of handheld devices with multiple radio interfaces. Traffic off-loading from the cellular network to a wifi access point is possible for mobile users with wireless interfaces for both networks. We will present schemes that motivate operators, access point owners and users to cooperate in order to maximize use of available capacity in the different networks; the schemes are based on double auction mechanisms.In an alternate approach, a mobile user may gain internet access when another user with cellular internet connection is willing to relay its traffic received through a direct link between the users. We will present incentives mechanisms that facilitate the creation of such User Provided Networks (UPN) in a way that all participants gain in terms of access capacity as well as energy consumption. Finally will present a design and implementation of a novel cloud-controlled UPN that employs SDN support on mobile terminals,to dynamically apply data forwarding policies with adaptive flow-control.

3:00 PM

Coffee Break

3:30 PM

Optical Wiretap Channel with Input-Dependent Gaussian Noise Under Peak and Average Intensity Constraints

This paper studies the optical wiretap channel with input-dependent Gaussian noise, in which the main distortion is caused by an additive Gaussian noise whose variance depends on the current signal strength. Subject to non-negativity and peak intensity constraints on the channel input, we first evaluate the conditions under which this wiretap channel is stochastically degraded. We then study the secrecy capacity-achieving input distribution of this wiretap channel and prove it to be discrete with a finite number of mass points, one of them located at the origin. Moreover, we show that the entire rate-equivocation region of this wiretap channel is also obtained by discrete input distributions with a finite support. Similar to the case for Gaussian wiretap channel under a peak power constraint, here too, we observe that under non-negativity and peak intensity constraints, there is a tradeoff between the secrecy capacity and the capacity in the sense that both may not be achieved simultaneously. Furthermore, we prove the optimality of discrete input distributions in the presence of an additional average intensity constraint. Finally, we shed light on the asymptotic behavior of the secrecy capacity in the low and high intensity regimes. In the low intensity regime, the secrecy capacity scales quadratically with the peak intensity constraint. On the contrary, in the high intensity regime, secrecy capacity does not scale with the constraint.

4:00 PM

QoS for Internet of Things Crowdsourced Environmental Monitoring

Traditional wireless sensor networks and computer vision techniques were utilized to acquire real-time data of the world conditions. Such data collection is vital for the decision-making of many domains like dynamic urban planning, traffic management, public safety, and environmental monitoring. The emerging domain of Mobile Crowd Sensing proposes a new framework for data collection based on the power of sensors installed in smartphones, wearable devices, and sensor-equipped vehicles. Taking advantage of such sensor-enabled devices which reside at the edge of the Internet in more real-life disciplines will cause an evolution in the concept of Internet of Things (IoT). Soon up to several billions of IoT devices will push their sensing data across the Internet. The amount of data IoT promises to generate will challenge the existing networks that were initially built for human-centric interactions. Due to the dynamic and real-time nature of IoT, traditional network architectures become inadequate to provide this type of Quality of Service (QoS).In this talk, I will propose making the network intelligent enough to take some early on decisions to provide certain QoS for IoT crowdsourced environmental applications. Thus, I leverage the new paradigm of Software Defined Networks (SDN), along with the Hierarchical Token Bucket (HTB) queuing discipline to provide dynamic and within application QoS. We employed the well-known weather signal application as a use case for our experimental design. We implement our design through well-known open source SDN components and evaluate its effectiveness using real IoT sensor traces. Our results show that the proposed framework can provide higher QoS for IoT applications under the exact network resources and conditions.

Keynote Speakers

 Allen Tannenbaum

State University of New York

 Dinesh Manocha

University of North Carolina at Chapel Hill

Speakers

 Allen Tannenbaum

State University of New York

 Christos Thrampoulidis

Massachusetts Institute of Technology (MIT)

 Dinesh Manocha

University of North Carolina at Chapel Hill

 Mohamed Ibnkahla

Carleton University, Ottawa, Canada

 Zhi-Quan (Tom) Luo

The Chinese University of Hong Kong, Shenzhen