Network emulation focusing on QoS-Oriented satellite communication

This chapter proposes network emulation basics and a complete case study of QoS-oriented Satellite Communication

Don't Repeat Yourself: Seamless Execution and Analysis of Extensive Network Experiments

This paper presents MACI, the first bespoke framework for the management, the scalable execution, and the interactive analysis of a large number of network experiments. Driven by the desire to avoid repetitive implementation of just a few scripts for the execution and analysis of experiments, MACI emerged as a generic framework for network experiments that significantly increases efficiency and ensures reproducibility. To this end, MACI incorporates and integrates established simulators and analysis tools to foster rapid but systematic network experiments. We found MACI indispensable in all phases of the research and development process of various communication systems, such as i) an extensive DASH video streaming study, ii) the systematic development and improvement of Multipath TCP schedulers, and iii) research on a distributed topology graph pattern matching algorithm. With this work, we make MACI publicly available to the research community to advance efficient and reproducible network experiments

Unified radio and network control across heterogeneous hardware platforms

Experimentation is an important step in the investigation of techniques for handling spectrum scarcity or the development of new waveforms in future wireless networks. However, it is impractical and not cost effective to construct custom platforms for each future network scenario to be investigated. This problem is addressed by defining Unified Programming Interfaces that allow common access to several platforms for experimentation-based prototyping, research, and development purposes. The design of these interfaces is driven by a diverse set of scenarios that capture the functionality relevant to future network implementations while trying to keep them as generic as possible. Herein, the definition of this set of scenarios is presented as well as the architecture for supporting experimentation-based wireless research over multiple hardware platforms. The proposed architecture for experimentation incorporates both local and global unified interfaces to control any aspect of a wireless system while being completely agnostic to the actual technology incorporated. Control is feasible from the low-level features of individual radios to the entire network stack, including hierarchical control combinations. A testbed to enable the use of the above architecture is utilized that uses a backbone network in order to be able to extract measurements and observe the overall behaviour of the system under test without imposing further communication overhead to the actual experiment. Based on the aforementioned architecture, a system is proposed that is able to support the advancement of intelligent techniques for future networks through experimentation while decoupling promising algorithms and techniques from the capabilities of a specific hardware platform

An overview of link-level measurement techniques for wide-area wireless networks

By building wireless link-level measurement tools we hope to improvement the design, deployment and management of wide-area wireless community networks. This paper identifies existing link-level measurement techniques and discusses the advantages and disadvantages of each in the context of measuring and monitoring such networks. Finally, we make a case for the need for more sophisticated techniques and tools which will assist both day-to-day network operations as well as wireless network research

The New Grid

The New Grid seeks to provide mobile users with an additional method for off-grid communication, or communication without connection to Internet infrastructure. The motivation for this project was to find another alternative to Internet-dependent communication. Current Internet infrastructure is antiquated; it is expensive to maintain and expand, it has numerous vulnerabilities and high-impact points of failure, and can be rendered unusable for lengthy periods of time by natural disasters or other catastrophes. This current grid will eventually need to be replaced by a more modern, scalable, and adaptive infrastructure. The results of the projects research showed that implementing a library to allow for the creation of mobile peer-to-peer mesh networks could serve as a starting point for a transition from current Internet infrastructure to a more scalable, adaptive, and reliable Internet- independent network grid. Development of The New Grid largely followed the Rational Unified Process, in which the development process is split into four phases: requirements gathering, system design, implementation, and testing. Most of fall quarter was spent outlining functional requirements for the system, designing possible methods of implementation, and researching similar solutions that seek to transition mass mobile communication to a newer, more modern network grid. The New Grid differs from similar solutions because it has been implemented as a modular library. Current systems that allow for off-grid mobile connection exist as independent applications with a defined context and predetermined usability scope. We, the design team, found that implementing the system in the form of a modular library has multiple benefits. Primarily, this implementation would allow The New Grid to be deployed as widely as possible. Developers can both write applications around our library as well as include specific modules into existing applications without impacting other modules or introducing additional overhead into a system. Another benefit of deploying the system as a modular library is adaptability. The current, initial stable build of The New Grid uses Bluetooth Low Energy as its backbone for facilitating communication within large networks of mobile devices; however, this library could use any existing or future communication protocol to facilitate connection as long as a hook is written to allow The New Grid to interface with that protocol. Thus, The New Grid is not limited by which connection protocols currently exist, a property that other similar systems do not possess. The New Grid can be used in any application that requires connection between users. The most common applications would likely be messaging, file sharing, or social networking. While developers may find a variety of uses for The New Grid, its primary purpose is to facilitate reliable connection and secure data transfer in an environment with a large user base. Achieving this goal was proven feasible through research and testing the library with a small cluster of Android devices communicating solely with Bluetooth Low Energy. Expanding this group of a few phones to a larger mesh network of hundreds of devices was shown to be feasible through testing the librarys algorithms and protocols on a large network of virtual devices. As long as developers seek to create applications that allow users to communicate independent of Internet infrastructure, The New Grid will allow smartphone users to communicate off-grid and hopefully spur a switch from infrastructure-dependent mobile communication to user-centric, adaptive, and flexible connection

Why (and How) Networks Should Run Themselves

The proliferation of networked devices, systems, and applications that we depend on every day makes managing networks more important than ever. The increasing security, availability, and performance demands of these applications suggest that these increasingly difficult network management problems be solved in real time, across a complex web of interacting protocols and systems. Alas, just as the importance of network management has increased, the network has grown so complex that it is seemingly unmanageable. In this new era, network management requires a fundamentally new approach. Instead of optimizations based on closed-form analysis of individual protocols, network operators need data-driven, machine-learning-based models of end-to-end and application performance based on high-level policy goals and a holistic view of the underlying components. Instead of anomaly detection algorithms that operate on offline analysis of network traces, operators need classification and detection algorithms that can make real-time, closed-loop decisions. Networks should learn to drive themselves. This paper explores this concept, discussing how we might attain this ambitious goal by more closely coupling measurement with real-time control and by relying on learning for inference and prediction about a networked application or system, as opposed to closed-form analysis of individual protocols