NeTS: Small: Design and Provisioning of Low-Carbon Optical Datacenter Networks

本项目重点关注动态骨干网和城域接入网的网络设计、供应和流量工程问题，以支持绿色云计算的“追随风/太阳”计算范式。这种模式是基于这样一种观察，即将数据和计算转移到具有本地绿色能源的站点比将绿色能源连接到电网然后将绿色电力传输到远程数据中心更节能。该项目将研究网络设计和交通工程，当产生交通负荷的元素的放置是一个可能的自由度。子问题包括：1)将数据中心放置在接近绿色能源的位置，并了解现有的网络部署；2)网络容量规划和速率容量分配，其中数据中心可能根据能源可用性动态上电/下电；3)根据网络考虑和绿色能源可用性估计将用户服务请求路由到数据中心。更广泛的影响：该项目将探索和量化数据中心更好地利用绿色可再生能源，数据中心是电力的重要消费者。该项目将为绿色数据中心的未来设计、布局和运营提供见解。pi将在能源管理的跨学科领域培训本科生（通过REU计划）和研究生。作为培训的一部分，pi将举行高度互动的每周会议，学生们在会上积极地相互学习。

This project focuses on the issues of network design, provisioning, and traffic engineering for dynamic backbone and metropolitan access networks needed to support a "follow the wind/sun" computing paradigm for green cloud computing. This paradigm is based on the observation that it is more energy efficient to move data and computations to a site with local green energy than it is to connect green energy sources to a power grid and then transmit the green power to distant data centers. The project will study network design and traffic engineering when placement of the elements generating the traffic load is a possible degree of freedom. The sub-problems include 1) placement of data centers to both be close to green energy and aware of existing network deployment, 2) network capacity planning and rate capacity assignment for networks where data centers may be dynamically powered up/down based on energy availability, 3) routing of user service requests to data centers based on network considerations and estimates of green energy availability.Broader Impact:This project will explore and quantify better use of green-renewable energy by data-centers, a significant consumer of electric power. The project will produce insights that assist industry in the future design, placement and operation of green data centers. The PIs will train undergraduate (via the REU program) and graduate students in the interdisciplinary area of energy management. As part of the training the PIs will hold highly-interactive weekly meetings in which students actively learn from each other.