Fei Li - US grants

The Internet is now the world's dominant information infrastructure. Numerous requests from Internet users and their applications compete for shared resources in multiple ways. It is therefore critical to efficiently allocate limited network resources in order to provide high quality services. Improving the performance of the Internet in this manner has the potential to have extremely broad impact.

Resource management becomes even more challenging when mobile devices connecting to the Internet are considered. Designing efficient algorithms is difficult mainly due to the following factors: (1) diverse and unpredictable resource requests; (2) physical limitations on Internet links, on buffer space in network switches, on capacity of wireless channels, and on battery power in mobile devices.

This project aims to provide solutions for several fundamental algorithmic problems in networked systems and applications. Robust and insightful online algorithms will be developed for network switches forwarding prioritized packets and energy management in mobile devices. The objective is to understand the mathematical structure of these problems, to design elegant and easy-to implement online algorithms, to provide rigorous analysis on their performance bounds, and to integrate these algorithms into the real systems to achieve better performance.

The substantial increase of energy consumption has brought up many serious engineering problems and economic concerns to our society. Many energy-saving scheduling algorithms have been proposed in the past decade to manage power consumption. However, energy-saving algorithms' impact on chip lifetime reliability, an important factor affecting overall system sustainability, has not been carefully examined by computer science theorists.

The goal of this EAGER proposal is to explore the theoretical groundwork of incorporating chip reliability in designing energy efficient scheduling algorithms for modern computing facilities. The PI proposes a new model that augments the existing energy-aware schedulers by enforcing additional chip lifetime reliability constraints which are modeled as functions of processor frequency changes. Novel scheduling algorithm design and analysis techniques are investigated to solve this problem.

The project outcome may potentially be transformative to a spectrum of related scheduling problems. In addition to studying the proposed theoretical problems, the PI empirically measures the performance of the developed algorithms by utilizing the FreeBSD operating system. This research suggests that through operating system kernel development, the practical implications of theoretical findings can be demonstrated.

Energy consumption is now emerging as a dominant performance measure in computer systems. In recent years, significant progress in improving energy efficiency has been accomplished by a combination of better hardware design and software tools. Yet the design of future energy-efficient computer systems will ultimately require the development of fundamental models and algorithmic tools that can be used to guide practical solutions.

This project is to study algorithmic methods for improving energy efficiency of data processing and storage in computer systems. The basic approach is to model the operation of various system components in the language of combinatorial optimization, with the objective function representing energy consumption, and to solve these problems using exact or approximate efficient algorithms. Many of those problems can be formulated in terms of task scheduling, where the objective is to optimize the CPU energy consumption required to complete a collection of tasks, while meeting some performance requirements. Other examples include minimizing energy consumption of memory systems, both the internal and external memories, by optimizing power levels and sophisticated paging or caching strategies. In addition to addressing some specific energy optimization problems, this work is expected to produce new algorithmic techniques, as well as deeper understanding of the adequacy of standard performance enhancement tools, like caching and load balancing, for improving energy efficiency. The study on energy complexity will also shed some light on the relation between computation and energy.

Some algorithms developed in the course of this research will be implemented, tested empirically on the FreeBSD-based platform, and made available to practitioners. The educational component includes research projects for graduate and undergraduate students, and developing a course on sustainable computing.

Intellectual Merit: In eukaryotes, DNA is packaged together with histone proteins into a highly complex structure called chromatin. Chemical modifications to DNA and histones play a key role in the control of chromatin structure and gene expression. These modifications, known as "epigenetic marks", can be faithfully inherited through many generations. During DNA replication, chromatin is disassembled ahead of the replication fork and then reassembled into its original epigenetic state behind the fork. Key questions on how epigenetic marks, particularly histone modifications, are inherited onto newly replicated chromatin, remain poorly understood. The goal of this project is to understand the fundamental principles underlying the inheritance of epigenetic marks. Fission yeast (Schizosaccharomyces pombe) will be used to address this important gap in knowledge. Fission yeast is a simple, genetically tractable model organism that contains many of the epigenetic components present in higher eukaryotes, and has thus recently emerged as a premier model for epigenetic study. In fission yeast, the methylation of histone H3 at lysine 9 (H3K9) is enriched in heterochromatin, the highly condensed and transcriptionally silent part of chromatin. This conserved epigenetic hallmark of heterochromatin is stably inherited from generation to generation, and provides a valuable framework for understanding the mechanisms behind epigenetic inheritance in eukaryotes. In this project, a combination of approaches, including genetics, biochemistry, and cytology, will be used to determine the role of proteins involved in DNA replication in the inheritance of H3K9 methylation. These findings will identify a key mechanistic link between DNA replication and the inheritance of H3K9 methylation, and provide important insights into how these two processes are coupled. This research will contribute to the understanding of the molecular mechanisms governing the inheritance of epigenetic information.

Broader Impacts: The epigenetic mechanisms found in S. pombe will likely apply to multicellular eukaryotes. Defects in the regulation of epigenetic marks often result in genomic instability and developmental disorders in both plants and animals. This study thus has important implications for agriculture, ecology and economy. This project will train post-doc researchers, graduate students, and undergraduates in cell biology, genetics, and biochemistry. The PI will continue to recruit underrepresented minority and women students to participate in research. This project will also serve as a teaching resource for courses that the PI teaches at New York University and for an outreach program aimed at encouraging K-12 students to consider careers in science.

PROJECT SUMMARY/ABSTRACT Vesicular glutamate transporters (VGLUTs) package the major excitatory neurotransmitter glutamate into synaptic vesicles, thus play a critical role in quantal release and neurotransmission. Despite decades of research, the mechanism of glutamate transport by the VGLUTs and its regulation under different ionic and pH conditions during exocytosis and endocytosis remains poorly understood. The lack of molecular level understanding of the structure and function of VGLUTs severely hinders our ability to understand their role in normal brain function, as well as in many psychiatric and neurological conditions where malfunction of VGLUTs has been implicated. This proposal aims to bridge this gap by providing a molecular blue print of a mammalian VGLUT protein with atomic details. Specifically, the candidate Dr. Fei Li will determine high-resolution structures of the rat VGLUT1 (rVGLUT1) by cryo electronmicrosocpy (cryo-EM) (Aim 1, mentored) and characterize its function by electrophysiology (Aim 2, mentored). Dr. Fei Li will further determine the structure of the native synaptic vesicle by cryo electrontomography (cryo-ET) (Aim 3A, mentored) and to reveal the higher order organization and interactions of synaptic vesicle membrane proteins (Aim 3B, independent). The goal of this K99/R00 Pathway to Independence Award proposal is to enhance Dr. Li?s knowledge in neuroscience and to provide opportunity of additional training in several key techniques that are critical to launching her independent research career focusing on the structure and function of neuronal membrane proteins in a leading research institution. The proposed aims allow Dr. Li to explore new biological questions that she can continue to investigate in her independent career while providing opportunities for training at the same time. Dr. Li has a strong interest in membrane protein structure and function in the context of brain physiology, and a strong background in membrane protein and X-ray crystallography. To guide the proposed project and to enhance her career prospects, Dr. Li has selected three leading scientists in, respectively, membrane proteins (Dr. Robert Stroud), electron microscopy (Dr. Yifan Cheng), as well as electrophysiology and neuroscience (Dr. Robert Edwards) as her co-mentors. Training through this project will allow Dr. Li to build a highly versatile and integrative skill set extending her background in membrane proteins and X-ray crystallography to the state-of-the-art cryo-EM and cryo-ET technology. Skills in electrophysiology will provide her with the tools required for functional analysis. Together, the research project and training program proposed in this award will play a critical role in preparing Dr. Li for a successful independent research career.