Jono Vanhie-Van Gerwen

Efficient global optimization of multi-parameter network problems on wireless testbeds

A large amount of research focuses on experimentally optimizing the performance of wireless solutions. Finding the optimal performance settings typically requires investigating all possible combinations of design parameters, while the number of required experiments increases exponentially for each considered design parameter. The aim of this paper is to analyze the applicability of global optimization techniques to reduce the optimization time of wireless experimentation. In particular, the paper applies the Efficient Global Optimization (EGO) algorithm implemented in the SUrrogate MOdeling (SUMO) toolbox inside a wireless testbed. Moreover, to cope with the unpredictable nature of wireless testbeds, the paper applies an experiment outlier detection which monitors outside interference and verifies the validity of conducted experiments. The proposed techniques are implemented and evaluated in a wireless testbed using a realistic wireless conferencing scenario. The performance gain and experimentation time of a SUMO optimized experiment is compared against an exhaustively searched experiment. In our proof of concept, it is shown that the proposed SUMO optimizer reaches 99.79% of the global optimum performance while requiring 8.67 times less experiments compared to the exhaustive search experiment.

Experimental assessment of tradeoffs among spectrumsensing platforms

This paper reports experimental results comparing the performance of four platforms employed in spectrum sensing and dynamic spectrum access research: a sensing engine developed at imec and built around a prototype RFIC; the Universal Software Radio Peripheral (USRP) with the Iris software defined radio (SDR) solution; the TelosB sensor network platform; and the Wi-Spy low cost spectrum sensor solution targeted at the ISM band. We use experimental data to derive the receiver operating characteristics (ROC) of each of the four platforms. We observe that for low signal powers, narrow bandwidth signals, high shadowing, or stringent probability of false alarm (PFA) requirements tradeoffs among the platforms tested are most pronounced, whereas for high signal powers, large bandwidths, stable environments, and more flexible PFA requirements less expensive, commercial-off-the-shelf equipment performs sufficiently well.

Real-Life Performance of Protocol Combinations for Wireless Sensor Networks

Wireless sensor networks today are used for many and diverse applications like nature monitoring, or process and wireless building automation. However, due to the limited access to large testbeds and the lack of benchmarking standards, the real-life evaluation of network protocols and their combinations remains mostly unaddressed in current literature. To shed further light upon this matter, this paper presents a thorough experimental performance analysis of six protocol combinations for TinyOS. During these protocol assessments, our research showed that the real-life performance often differs substantially from the expectations. Moreover, we found that combining protocols is far from trivial, as individual network protocols may perform very different in combination with other protocols. The results of our research emphasize the necessity of a flexible generic benchmarking framework, powerful enough to evaluate and compare network protocols and their combinations in different use cases.

Various Detection Techniques and Platforms for Monitoring Interference Condition in a Wireless Testbed

Recently the constant growth of the wireless communication technology has caused a huge demand for experimental facilities. Hence many research institutes setup public accessible experimental facilities, known as testbeds. Compared to the facilities developed by individual researchers, a testbed typically offers more resources, more flexibilities. However, due to the fact that equipments are located remotely and experiments involve more complex scenarios, the required complexity for analysis is also higher. A deep insight on the underlying wireless environment of the testbed becomes necessary for comprehensive analysis.

Applying a methodology for the design, delivery and evaluation of learning resources for remote experimentation

Remote labs and online experimentation offer a rich opportunity to learners by allowing them to control real equipment at distance in order to conduct scientific investigations. Remote labs and online experimentation build on top of numerous emerging technologies for supporting remote experiments and promoting the immersion of the learner in online environments recreating the real experience. This paper presents a methodology for the design, delivery and evaluation of learning resources for remote experimentation. This methodology has been developed in the context of the European project FORGE, which promotes online learning using Future Internet Research and Experimentation (FIRE) facilities. FORGE is a step towards turning FIRE into a pan-European educational platform for Future Internet. This will benefit learners and educators by giving them both access to world-class facilities in order to carry out experiments on e.g. new internet protocols. In turn, this supports constructivist and self-regulated learning approaches, through the use of interactive learning resources, such as eBooks.

Efficient multi-objective optimization of wireless network problems on wireless testbeds

A large amount of research focuses on experimentally optimizing performance of wireless solutions. Finding the optimal performance settings typically requires investigating all possible combinations of design parameters, while the number of required experiments increases exponentially for each considered design parameter. The aim of this paper is to analyze the applicability of global optimization techniques to reduce the optimization time of wireless experimentation. In particular, the paper applies the Efficient Global Optimization (EGO) algorithm implemented in the SUrrogate MOdeling (SUMO) toolbox inside a wireless testbed. The proposed techniques are implemented and evaluated in a wireless testbed using a realistic wireless conference network problem. The performance accuracy and experimentation time of an exhaustively searched experiment is compared against a SUMO optimized experiment. In our proof of concept, the proposed SUMO optimizer reaches 99.51% of the global optimum performance while requiring 10 times less experiments compared to the exhaustive search experiment.

Distributed spectrum sensing in a cognitive networking testbed

In this demonstration, we show how the IBBT w-iLab.t wireless testbed, combined with multiple spectrum sensing engines designed by imec, can be used for experimentally-supported design and evaluation of cognitive networking protocols. Functionalities include the advanced characterization of the behavior of a cognitive solution under test, and characterization of the wireless experimentation environment itself.

FORGE Enabling FIRE Facilities for the eLearning Community

Many engineering students at third-level institutions across the world will not have the advantage of using real-world experimentation equipment, as the infrastructure and resources required for this activity are too expensive. This paper explains how the FORGE (Forging Online Education through FIRE) FP7 project transforms Future Internet Research and Experimentation (FIRE) testbed facilities into educational resources for the eLearning community. This is achieved by providing a framework for remote experimentation that supports easy access and control to testbed infrastructure for students and educators. Moreover, we identify a list of recommendations to support development of eLearning courses that access these facilities and highlight some of the challenges encountered by FORGE.