Creating a Worldwide Network For the Global Environment for Network Innovations (GENI) and Related Experimental Environments

Many important societal activities are global in scope, and as these activities continually expand world-wide, they are increasingly based on a foundation of advanced communication services and underlying innovative network architecture, technology, and core infrastructure. To continue progress in these areas, research activities cannot be limited to campus labs and small local testbeds or even to national testbeds. Researchers must be able to explore concepts at scale—to conduct experiments on world-wide testbeds that approximate the attributes of the real world. Today, it is possible to take advantage of several macro information technology trends, especially virtualization and capabilities for programming technology resources at a highly granulated level, to design, implement and operate network research environments at a global scale. GENI is developing such an environment, as are research communities in a number of other countries. Recently, these communities have not only been investigating techniques for federating these research environments across multiple domains, but they have also been demonstration prototypes of such federations. This chapter provides an overview of key topics and experimental activities related to GENI international networking and to related projects throughout the world

Position Estimation of Robotic Mobile Nodes in Wireless Testbed using GENI

We present a low complexity experimental RF-based indoor localization system based on the collection and processing of WiFi RSSI signals and processing using a RSS-based multi-lateration algorithm to determine a robotic mobile node's location. We use a real indoor wireless testbed called w-iLab.t that is deployed in Zwijnaarde, Ghent, Belgium. One of the unique attributes of this testbed is that it provides tools and interfaces using Global Environment for Network Innovations (GENI) project to easily create reproducible wireless network experiments in a controlled environment. We provide a low complexity algorithm to estimate the location of the mobile robots in the indoor environment. In addition, we provide a comparison between some of our collected measurements with their corresponding location estimation and the actual robot location. The comparison shows an accuracy between 0.65 and 5 meters.Comment: (c) 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other work

Peer-to-Peer Based Trading and File Distribution for Cloud Computing

In this dissertation we take a peer-to-peer approach to deal with two specific issues, fair trading and file distribution, arisen from data management for cloud computing. In mobile cloud computing environment cloud providers may collaborate with each other and essentially organize some dedicated resources as a peer to peer sharing system. One well-known problem in such peer to peer systems with exchange of resources is free riding. Providing incentives for peers to contribute to the system is an important issue in peer to peer systems. We design a reputation-based fair trading mechanism that favors peers with higher reputation. Based on the definition of the reputation used in the system, we derive a fair trading policy. We evaluate the performance of reputation-based trading mechanisms and highlight the scenarios in which they can make a difference. Distribution of data to the resources within a cloud or to different collaborating clouds efficiently is another issue in cloud computing. The delivery efficiency is dependent on the characteristics of the network links available among these network nodes and the mechanism that takes advantage of them. Our study is based on the Global Environment for Network Innovations (GENI), a testbed for researchers to build a virtual laboratory at scale to explore future Internets. Our study consists of two parts. First, we characterize the links in the GENI network. Even though GENI has been used in many research and education projects, there is no systematic study about what we can expect from the GENI testbeds from a performance perspective. The goal is to characterize the links of the GENI networks and provide guidance for GENI experiments. Second, we propose a peer to peer approach to file distribution for cloud computing. We develop a mechanism that uses multiple delivery trees as the distribution structure, which takes into consideration the measured performance information in the GENI network. Files are divided into chunks to improve parallelism among different delivery trees. With a strict scheduling mechanism for each chunk, we can reduce the overall time for getting the file to all relevant nodes. We evaluate the proposed mechanism and show that our mechanism can significantly reduce the overall delivery time

Programming routing policies for video traffic

Making the network programmable simplifies network management and enables network innovations. The Recursive InterNetwork Architecture (RINA) is our solution to enable network programmability. ProtoRINA is a user-space prototype of RINA and provides users with a framework with common mechanisms so a user can program recursive-networking policies without implementing mechanisms from scratch. In this paper, we focus on how routing policies, which is an important aspect of network management, can be programmed using ProtoRINA, and demonstrate how ProtoRINA can be used to achieve better performance for a video streaming application by instantiating different routing policies over the GENI (Global Environment for Network Innovations) testbed, which provides a large-scale experimental facility for networking research.National Science Foundation (NSF grant CNS-0963974

Recursive InterNetworking Architecture (RINA) Boston University prototype programming manual (version 1.0)

The lack of a complete Internet architecture continues to dramatically increase the complexity and management cost of all distributed systems. Our Recursive InterNetwork Architecture (RINA) is a clean-slate solution that leverages recursion of scoped inter-process communication. Following the RINA specification handbook, we implemented a prototype. The prototype is tested on our Boston University campus network, and cross-debugged with two other RINA prototypes (IRATI and TRIA).We have also demonstrated our prototype on the Global Environment for Network Innovations (GENI) testbed. This manual describes the software architecture of our prototype, and guides users on how to use existing management policies and how to write new network applications over the built-in mechanisms.National Science Foundation (CNS-0963974), Global Environment for Network Innovation

Internet Predictions

More than a dozen leading experts give their opinions on where the Internet is headed and where it will be in the next decade in terms of technology, policy, and applications. They cover topics ranging from the Internet of Things to climate change to the digital storage of the future. A summary of the articles is available in the Web extras section

Managing NFV using SDN and control theory

Control theory and SDN (Software Defined Networking) are key components for NFV (Network Function Virtualization) deployment. However little has been done to use a control-theoretic approach for SDN and NFV management. In this paper, we describe a use case for NFV management using control theory and SDN. We use the management architecture of RINA (a clean-slate Recursive InterNetwork Architecture) to manage Virtual Network Function (VNF) instances over the GENI testbed. We deploy Snort, an Intrusion Detection System (IDS) as the VNF. Our network topology has source and destination hosts, multiple IDSes, an Open vSwitch (OVS) and an OpenFlow controller. A distributed management application running on RINA measures the state of the VNF instances and communicates this information to a Proportional Integral (PI) controller, which then provides load balancing information to the OpenFlow controller. The latter controller in turn updates traffic flow forwarding rules on the OVS switch, thus balancing load across the VNF instances. This paper demonstrates the benefits of using such a control-theoretic load balancing approach and the RINA management architecture in virtualized environments for NFV management. It also illustrates that GENI can easily support a wide range of SDN and NFV related experiments