November 16, 2015


BLUE: Software-Defined Cyberinfrastructure to Enable Data-driven Smart Campus Applications

The BLUE project develops a new campus infrastructure to enable efficient and secure data-driven research and application development based on distributed IoT devices. BLUE addresses three main challenges for supporting innovative smart campus applications based on distributed IoT devices: (a) establishing a programable campus infrastructure to support distributed and ad hoc IoT services, (b) providing strong security and privacy protection of IoT data, and (c) constructing an edge-cloud infrastructure to provide computing, networking, and storage resources to support smart-campus applications. [Read More]

Generalized Caching-As-A-Service

Caching has been a consistent tool of designers of high-performance, scalable computing systems, but it has been deployed in so many ways that it can be difficiult to standardize and scale in cloud systems. This project elevates the use of caching in cloud-scale storage system to a “first-class citizen” by designing and implementing generalized Caching-as-a-Service (CaaS). The CaaS project supports a broad spectrum of applications that run in the private and public clouds. [Read More]

GEARS – An Infrastructure for Energy-Efficient Big Data Research on Heterogeneous and Dynamic Data

This project is developing the needed computational infrastructure to support GEARS (an enerGy-Efficient big-datA Research System) for studying heterogeneous and dynamic data using heterogeneous computing and storage resources. GEARS will be a one-of-kind, energy-efficient big-data research infrastructure based on cohesively co-designed software and hardware components. It enables a variety of important studies on heterogeneous and dynamic data and advances the scientific knowledge in computer science as well as other data-driven disciplines. [Read More]

DataStorm: A Data Enabled System for End-to-End Disaster Planning and Response

Natural disasters affect our society in profound ways. Data-driven models and computer simulations for disaster preparedness and response can play a key role in predicting the evolution of disasters and effectively managing emergencies through a diverse set of intervention measures. This project will enhance disaster response and community resilience through multi-faceted research to create a big data system to support data-driven simulations with the necessary volume, velocity, and variety and integrate and optimize the key aspects and decisions in disaster management. [Read More]

Discovering Context-Sensitive Impact in Complex Systems

Successfully tackling many urgent challenges in socio-economically critical domains (such as sustainability, public health, and biology) requires obtaining a deeper understanding of complex relationships and interactions among a diverse spectrum of entities in different contexts. This project establishes the foundations of big data driven Context-Sensitive Impact Discovery (CSID) in complex systems and fills an important hole in big data driven decision making in many critical application domains, including epidemic preparedness, biological pathway analysis, climate, and resilient water/energy infrastructures. [Read More]

NVM-enabled Host-side Caches

Non-volatile memory (NVM) is a transformative technology that is dramatically changing how data storage systems of the future are built. This technology allows an unprecedented combination of performance and persistence into a single device. This project will develop a suite of storage caching techniques for this transformative technology along four complementary dimensions. [Read More]

QoS-driven Resource Management for Big-data Computing Systems

Together with the increasing adoption of cloud computing is the emergence of data-intensive applications. Dubbed as ‘‘big data’’, these applications need to process and analyze massive amounts of data in parallel. As the demand of data-intensive computing continues to grow, it becomes increasingly common to use shared infrastructure to run such applications, while virtualization plays a key role to transparently and flexibly consolidate these applications. The objective of this proposed project is to address the resource management challenges for virtualized data-intensive computing and enable diverse applications to meet their desired QoS in such environments. [Read More]

Holistic Cloud Computing and Storage Resource Management

System virtualization is an increasingly powerful technology that enables the emerging computing paradigms such as public and private cloud systems. It allows applications to be conveniently deployed along with their required execution environments through virtual machine (VMs), and supports them to flexibly share the underlying physical resources with strong isolation. However, there exists an increasingly urgent need for virtualized systems to deliver strong Quality of Service (QoS) guarantees to their hosted applications. The objective of this project is to create a QoS-driven multi-type resource management system to support strong QoS guarantees for applications hosted on virtualized computing systems. [Read More]

QoS-driven High-end Computing Storage Management

In today’s high-end computing (HEC) systems, the parallel file system (PFS) is at the core of the storage infrastructure. PFS deployments are shared by many users and applications, but currently there are no provisions for differentiation of service – data access is provided in a best-effort manner. As systems scale, this limitation can prevent applications from efficiently utilizing the HEC resources while achieving their desired performance and it presents a hurdle to support a large number of data-intensive applications concurrently. This NSF HECURA project tackles the challenges in quality of service (QoS) driven HEC storage management, aiming to support I/O bandwidth guarantees in PFSs. [Read More]

DM-CACHE – Dynamic Storage Caching for Cloud Computing Systems

Block-level distributed storage systems (e.g., SAN, iSCSI) are commonly used in the emerging cloud computing systems to provide virtual machine (VM) storage. They allow fast VM migration across different hosts and improved VM availability leveraging typical fault-tolerance measures (e.g., RAID) available in such storage systems. However, as the size of cloud systems and the number of hosted VMs rapidly grow, the scalability of shared block-level storage systems becomes a serious issue. This project proposes to address this issue by using client-side storage to implement block-level caching and exploit the data locality available in VM data accesses. By leveraging the capacity of fast storage devices such as SSD available on the VM hosts, this approach has the potential to substantially improve the performance of VMs and the load on the shared storage system. This approach is implemented upon dm-cache, a generic block-level caching utility. Our current prototype supports cache sharing across different co-hosted VMs in order to maximize cache utilization. [Read More]

vMoodle – Virtual Machine based Online Learning System

Web-based online learning environment (e.g., Moodle, Blackboard, WebCT) has become a widely used and important platform for educators to conveniently create and deliver course materials through the Internet and for students to easily use these materials in an interactive online learning environment. Meanwhile, system virtual machines (VMs, e.g., VMware, VirtualBox) are also emerging as a valuable tool for creating self-contained and portable educational modules that can be transparently replicated and deployed anywhere. Therefore, the combination of these two technologies has the potential to provide an even more powerful education software system, a VM-based online learning environment. The fundamental goal of this project is to develop a VM-based online learning system that allows educators and students to conveniently use VMs for creating and consuming course materials in an online learning environment. [Read More]

Streamlining High-end Computing with Software Persistent Memory

Currently, HEC applications manage persistent data largely by themselves and thus the developer involvement, and consequently, develpment time and cost, is high. Further, the developer needs to be intimately aware of the underlying persistent storage mechanisms to achieve high-performance, which typically requires a greater degree of expertise; this vertical development, unfortunately, also makes the application software less portable. The thesis of this NSF HECURA project is that a lightweight Software Persistent Memory (SoftPM) infrastructure is necessary for streamlining data management in next generation HEC applications and speeding up scientific discovery. [Read More]

A Research and Educational Framework to Advance Disaster Information Management in Computer Science PhD Programs

The objective of this proposal is to provide an integrated research and educational framework that will advance disaster information management in Florida International University’s (FIU) School of Computing and Information Sciences (SCIS) Computer Science PhD degree program. The outcomes are expected in three areas: (1) increased graduate degrees awarded with Homeland Security-related Science, Technology, Engineering, and Mathematics (HS-STEM) related knowledge and skills, (2) engaging early career faculty to pursue HS-STEM research and education activities leveraging senior faculty research agenda in disaster information management, and (3) to enhance our computer science (CS) doctoral degree program course curriculum in areas relevant to HS-STEM. The pursuit of these objectives combined will create a sustainable and replicable research and education program that will create notoriety for FIU in the area of HS-STEM related expertise and will promote further research study at other HS-STEM interested institutions. [Read More]

Cloud Hackathon

In collaboration with IBM, the FIU School of Computing and Information Sciences (external link) hosted a Cloud Hackathon. This event is offered as part of the Introduction to Cloud Computing course (CEN4083) and open to students who are not currently enrolled in the class. CEN4083 is a new course offered as a shared course to FIU, UCF, and USF. IBM supports the hackathon with free trial access to the IBM Bluemix (external link), an industry-leading PaaS platform. You will get exposure to cutting-edge cloud technologies and mentoring from cloud computing experts. Top projects will be publicized by IBM. The top four students with the best projects will also win a Raspberry Pi starter kit (sponsored by IBM)! [Read More]

Research Experience for Undergraduates

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Senior Capstone Project

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Past Projects

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