Benchmarking in Wireless Networks

Experimentation is evolving as a viable and realistic performance analysis approach in wireless networking research. Realism is provisioned by deploying real software (network stack, drivers, OS), and hardware (wireless cards, network equipment, etc.) in the actual physical environment. However, the experimenter is more likely to be dogged by tricky issues because of calibration problems and bugs in the software/hardware tools. This, coupled with difficulty of dealing with multitude of controllable and uncontrollable hardware/software parameters and unpredictable characteristics of the wireless channel in the wild, poses significant challenges in the way of experiments repeatability and reproducibility. Furthermore, experimentation has been impeded by the lack of standard definitions, measurement methodologies and full disclosure reports that are particularly important to understand the suitability of protocols and services to emerging wireless application scenarios. Lack of tools to manage experiments, large amount of data and facilitate reproducible analysis further complicates the process. In this report, we present a holistic view of benchmarking in wireless networks; introduce key definitions and formulate a procedure complemented by step-by-step case study to help drive future efforts on benchmarking of wireless network applications and protocols

Building the Future Internet through FIRE

The Internet as we know it today is the result of a continuous activity for improving network communications, end user services, computational processes and also information technology infrastructures. The Internet has become a critical infrastructure for the human-being by offering complex networking services and end-user applications that all together have transformed all aspects, mainly economical, of our lives. Recently, with the advent of new paradigms and the progress in wireless technology, sensor networks and information systems and also the inexorable shift towards everything connected paradigm, first as known as the Internet of Things and lately envisioning into the Internet of Everything, a data-driven society has been created. In a data-driven society, productivity, knowledge, and experience are dependent on increasingly open, dynamic, interdependent and complex Internet services. The challenge for the Internet of the Future design is to build robust enabling technologies, implement and deploy adaptive systems, to create business opportunities considering increasing uncertainties and emergent systemic behaviors where humans and machines seamlessly cooperate

Performance and Security Enhancements in Practical Millimeter-Wave Communication Systems

Millimeter-wave (mm-wave) communication systems achieve extremely high data rates and provide interference-free transmissions. to overcome high attenuations, they employ directional antennas that focus their energy in the intended direction. Transmissions can be steered such that signals only propagate within a specific area-of-interest. Although these advantages are well-known, they are not yet available in practical networks. IEEE 802.11ad, the recent standard for communications in the unlicensed 60 GHz band, exploits a subset of the directional propagation effects only. Despite the large available spectrum, it does not outperform other developments in the prevalent sub-6 GHz bands. This underutilization of directional communications causes unnecessary performance limitations and leaves a false sense of security. For example, standard compliant beam training is very time consuming. It uses suboptimal beam patterns, and is unprotected against malicious behaviors. Furthermore, no suitable research platform exists to validate protocols in realistic environments. To address these challenges, we develop a holistic evaluation framework and enhance the performance and security in practical mm-wave communication systems. Besides signal propagation analyses and environment simulations, our framework enables practical testbed experiments with off-the-shelf devices. We provide full access to a tri-band router’s operating system, modify the beam training operation in the Wi-Fi firmware, and create arbitrary beam patterns with the integrated antenna array. This novel approach allows us to implement custom algorithms such as a compressive sector selection that reduces the beam training overhead by a factor of 2.3. By aligning the receive beam, our adaptive beam switching algorithm mitigates interference from lateral directions and achieves throughput gains of up to 60%. With adaptive beam optimization, we estimate the current channel conditions and generate directional beams that implicitly exploit potential reflections in the environment. These beams increase the received signal strength by about 4.4 dB. While intercepting a directional link is assumed to be challenging, our experimental studies show that reflections on small-scale objects are sufficient to enable eavesdropping from afar. Additionally, we practically demonstrate that injecting forged feedback in the beam training enables Man-in-the Middle attacks. With only 7.3% overhead, our authentication scheme protects against this beam stealing and enforces responses to be only accepted from legitimate devices. By making beam training more efficient, effective, and reliable, our contributions finally enable practical applications of highly directional transmissions

Simulation Intelligence: Towards a New Generation of Scientific Methods

The original "Seven Motifs" set forth a roadmap of essential methods for the field of scientific computing, where a motif is an algorithmic method that captures a pattern of computation and data movement. We present the "Nine Motifs of Simulation Intelligence", a roadmap for the development and integration of the essential algorithms necessary for a merger of scientific computing, scientific simulation, and artificial intelligence. We call this merger simulation intelligence (SI), for short. We argue the motifs of simulation intelligence are interconnected and interdependent, much like the components within the layers of an operating system. Using this metaphor, we explore the nature of each layer of the simulation intelligence operating system stack (SI-stack) and the motifs therein: (1) Multi-physics and multi-scale modeling; (2) Surrogate modeling and emulation; (3) Simulation-based inference; (4) Causal modeling and inference; (5) Agent-based modeling; (6) Probabilistic programming; (7) Differentiable programming; (8) Open-ended optimization; (9) Machine programming. We believe coordinated efforts between motifs offers immense opportunity to accelerate scientific discovery, from solving inverse problems in synthetic biology and climate science, to directing nuclear energy experiments and predicting emergent behavior in socioeconomic settings. We elaborate on each layer of the SI-stack, detailing the state-of-art methods, presenting examples to highlight challenges and opportunities, and advocating for specific ways to advance the motifs and the synergies from their combinations. Advancing and integrating these technologies can enable a robust and efficient hypothesis-simulation-analysis type of scientific method, which we introduce with several use-cases for human-machine teaming and automated science

Design and evaluation of a self-configuring wireless mesh network architecture

Wireless network connectivity plays an increasingly important role in supporting our everyday private and professional lives. For over three decades, self-organizing wireless multi-hop ad-hoc networks have been investigated as a decentralized replacement for the traditional forms of wireless networks that rely on a wired infrastructure. However, despite the tremendous efforts of the international wireless research community and widespread availability of devices that are able to support these networks, wireless ad-hoc networks are hardly ever used. In this work, the reasons behind this discrepancy are investigated. It is found that several basic theoretical assumptions on ad-hoc networks prove to be wrong when solutions are deployed in reality, and that several basic functionalities are still missing. It is argued that a hierarchical wireless mesh network architecture, in which specialized, multi-interfaced mesh nodes form a reliable multi-hop wireless backbone for the less capable end-user clients is an essential step in bringing the ad-hoc networking concept one step closer to reality. Therefore, in a second part of this work, algorithms increasing the reliability and supporting the deployment and management of these wireless mesh networks are developed, implemented and evaluated, while keeping the observed limitations and practical considerations in mind. Furthermore, the feasibility of the algorithms is verified by experiment. The performance analysis of these protocols and the ability to deploy the developed algorithms on current generation off-the-shelf hardware indicates the successfulness of the followed research approach, which combines theoretical considerations with practical implementations and observations. However, it was found that there are also many pitfalls to using real-life implementation as a research technique. Therefore, in the last part of this work, a methodology for wireless network research using real-life implementation is developed, allowing researchers to generate more reliable protocols and performance analysis results with less effort

Building the Future Internet through FIRE

The Internet as we know it today is the result of a continuous activity for improving network communications, end user services, computational processes and also information technology infrastructures. The Internet has become a critical infrastructure for the human-being by offering complex networking services and end-user applications that all together have transformed all aspects, mainly economical, of our lives. Recently, with the advent of new paradigms and the progress in wireless technology, sensor networks and information systems and also the inexorable shift towards everything connected paradigm, first as known as the Internet of Things and lately envisioning into the Internet of Everything, a data-driven society has been created. In a data-driven society, productivity, knowledge, and experience are dependent on increasingly open, dynamic, interdependent and complex Internet services. The challenge for the Internet of the Future design is to build robust enabling technologies, implement and deploy adaptive systems, to create business opportunities considering increasing uncertainties and emergent systemic behaviors where humans and machines seamlessly cooperate

Towards Complete Tracking of Provenance in Experimental Distributed Systems Research

International audienceRunning experiments on modern systems like supercomput-ers, cloud infrastructures or P2P networks became very complex, both technically and methodologically. It is difficult to rerun an experiment or understand its results even with technical background on the technology and methods used. Storing the provenance of experimental data, i.e., storing information about how the results were produced, proved to be a powerful tool to address similar problems in computational natural sciences. In this paper, we (1) survey provenance collection in various domains of computer science, (2) introduce a new classification of prove-nance types, and (3) sketch a design of a provenance system inspired by this classification