Abstract
Available bandwidth parameter is a crucial characteristic in terms of networking and data transmission. The beforehand knowledge of its value and use of this parameter in various traffic engineering algorithms and QoS calculations is a key for high-efficient multigigabit data transport in nowadays networks. The challenge in available bandwidth estimations is not only in its accuracy and processing speed but also in the reduction of the amount of probe traffic injected into the network by keeping an adequate level of estimation accuracy. In this paper we extend existing active probing measurement algorithms for end-to-end available bandwidth estimation along with methods to reduce estimation times and amount of injected traffic while keeping measurement accuracy constant and even reducing the uncertainty of estimations. The main goal of this research was to detect a sufficient ratio of MTU, packet train size with the link capacity and available bandwidth (AvB) in up to 10 Gbps networks. In order to explore measurement accuracy under different conditions, a new tool for the AvB estimation named Kite2 has been developed and is presented in the paper. Comparative performance of AvB estimations using Kite2, Kite and Yaz is presented. Finally we calculate with statistical means dependency between the estimation error probability, measurement probing overhead and the measurement time.
Highlights
Accuracy of available bandwidth (AvB) estimation heavily relies on the method of packet probing and the mathematical assumptions concluded from the delay distribution of the probe packets [1]
Available bandwidth of the end-to-end path defines the instantly unused capacity of the path in a contrary to the overall capacity, which is defined by the physical parameters of the link, so AvB depends on the instant traffic load and has almost unpredictable character
Approach of Kite2 is based on the Probe Rate Model (PRM) of the active probing measurement and basically uses analysis of inter-packet interval deviation on the receiver side (IpIr) in order to detect whether the sending rate of probe packets meets the available bandwidth limits of the link between the sender and the receiver
Summary
Accuracy of available bandwidth (AvB) estimation heavily relies on the method of packet probing and the mathematical assumptions concluded from the delay distribution of the probe packets [1]. As active measurement tools raise traffic load in the network, one of its significant flaws is related to the intrusion caused by the measurement traffic which can result in a QoS deterioration, and provide biased available bandwidth measuring results. If an active measurement tool operates with a small probing amount, it provides shorter execution times, which are significant for the highly dynamic traffic of the most networks. In order to investigate measurement performance under the different probing intensity, a new tool called Kite is proposed here. It extends the capabilities of Kite which was used for AvB estimations before [4].
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