Hannover : Institutionelles Repositorium der Leibniz Universität Hannover
Doi
Abstract
In today’s computer networks, short-lived flows are predominant. Consequently,
transient start-up effects such as the connection establishment in
cellular networks have a significant impact on the performance. Although
various solutions are derived in the fields of queuing theory, available bandwidths,
and network calculus, the focus is, e.g., about the mean wake-up
times, estimates of the available bandwidth, which consist either out of a
single value or a stationary function and steady-state solutions for backlog
and delay. Contrary, the analysis during transient phases presents fundamental
challenges that have only been partially solved and is therefore
understood to a much lesser extent.
To better comprehend systems with transient characteristics and to explain
their behavior, this thesis contributes a concept of non-stationary
service curves that belong to the framework of stochastic network calculus.
Thereby, we derive models of sleep scheduling including time-variant
performance bounds for backlog and delay. We investigate the impact of
arrival rates and different duration of wake-up times, where the metrics
of interest are the transient overshoot and relaxation time. We compare
a time-variant and a time-invariant description of the service with an
exact solution. To avoid probabilistic and maybe unpredictable effects from
random services, we first choose a deterministic description of the service
and present results that illustrate that only the time-variant service curve can
follow the progression of the exact solution. In contrast, the time-invariant
service curve remains in the worst-case value.
Since in real cellular networks, it is well known that the service and sleep
scheduling procedure is random, we extend the theory to the stochastic
case and derive a model with a non-stationary service curve based on
regenerative processes.
Further, the estimation of cellular network’s capacity/ available bandwidth
from measurements is an important topic that attracts research, and
several works exist that obtain an estimate from measurements. Assuming
a system without any knowledge about its internals, we investigate
existing measurement methods such as the prevalent rate scanning and
the burst response method. We find fundamental limitations to estimate
the service accurately in a time-variant way, which can be explained by
the non-convexity of transient services and their super-additive network
processes.
In order to overcome these limitations, we derive a novel two-phase probing
technique. In the first step, the shape of a minimal probe is identified,
which we then use to obtain an accurate estimate of the unknown service.
To demonstrate the minimal probing method’s applicability, we perform
a comprehensive measurement campaign in cellular networks with sleep
scheduling (2G, 3G, and 4G). Here, we observe significant transient backlogs
and delay overshoots that persist for long relaxation times by sending
constant-bit-rate traffic, which matches the findings from our theoretical
model. Contrary, the minimal probing method shows another strength:
sending the minimal probe eliminates the transient overshoots and relaxation
times