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C. Midoglu, L. Wimmer, P. Svoboda:
"Server Link Load Modeling and Request Scheduling for Crowdsourcing-Based Benchmarking Systems";
Talk: The 12th International Wireless Communications & Mobile Computing Conference (IWCMC 2016), Paphos; 2016-09-05 - 2016-09-09; in: "The 12th International Wireless Communications and Mobile Computing Conference Proceedings", IEEE, 978-1-5090-0304-4 (2016), ISBN: 978-1-5090-0304-4; 988 - 994.

Crowdsourcing-based network benchmarking is a
novel method of large-scale performance evaluation, which allows
for the collection of measurements from end nodes in order
to estimate overall network performance. For accuracy and
fairness, the measurement server and its communication links
must not constitute the bottleneck in the overall benchmarking
system. In this paper, we focus on performance optimization
through efficient request scheduling. We present a modular
approach to model the load on the server-side communication
links analytically, allowing for the combination of simulation
parameters with real measurement results, and demonstrate the
potential benefit of scheduling measurement requests with a
discrete time-based approach. We show that efficient scheduling
algorithms are as important as hardware improvements (such as
upgrading the communication links to higher capacity), in order
for benchmarking systems to cope with the increasing number
of measurements and ever growing data rates in both fixed and
mobile technologies.

Crowdsourcing-based network benchmarking is a
novel method of large-scale performance evaluation, which allows
for the collection of measurements from end nodes in order
to estimate overall network performance. For accuracy and
fairness, the measurement server and its communication links
must not constitute the bottleneck in the overall benchmarking
system. In this paper, we focus on performance optimization
through efficient request scheduling. We present a modular
approach to model the load on the server-side communication
links analytically, allowing for the combination of simulation
parameters with real measurement results, and demonstrate the
potential benefit of scheduling measurement requests with a
discrete time-based approach. We show that efficient scheduling
algorithms are as important as hardware improvements (such as
upgrading the communication links to higher capacity), in order
for benchmarking systems to cope with the increasing number
of measurements and ever growing data rates in both fixed and
mobile technologies.

benchmarking; bottleneck analysis; crowdsourcing; link utilization; network performance measurements; request scheduling; slotted ALOHA