The future high-speed networks are expected to support a variety of services such as data, voice, image, and video with diverse traffic flow characteristics and Quality-of-Service (QoS) requirements. Developing a framework for the design, control and management of wide area packet networks which can effciently support such QoS requirements is a fundamental challenge.
Conventional frameworks for the teletraffic analysis of networks and QoS guarantees are either deterministic or probabilistic. In the deterministic approach, the worst-case traffic envelopes are used. This most likely will lead to conservative resource allocation policies and inefficient usage of the network resources. In the standard probabilistic frameworks, the traffic is usually modeled as a variant of Poisson process, e.g., MMPP, MAP, etc. Such models are amenable to traditional teletraffic analysis but only capture simple and limited correlation structures in the data.
The researchers propose to significantly expand the analytical methodology in solving complex teletraffic problems arising in modern computer and communications networks. Their approach which is rooted in classical ballot theorem handles a large class of arrival processes including the standard Markovian processes, general periodic processes, processes described by time-series (auto-regressive and moving average), or even general processes described by the joint distribution of number of arrivals in equally-spaced non-overlapping discrete intervals. Special attention will be paid in deriving algorithmic solutions which are numerically robust and efficient even when the system utilization is high.
The researchers proposed approach is unifying, it avoids root-findings, and unlike the matrix analytical approach or recently introduced state-space spectral decomposition method, it does not involve potentially expensive iterations. Further, it is transform-free and may provide a simple form of solution amenable for further analytical studies such as tail behavior or asymptotic analysis.
The researchers general arrivals processes could be used for the end-to-end performance analysis once the departure process from a network node is appropriately approximated or probabilistically bounded. Since they are not limited to traditional Markovian models, such an approach appears to be viable.
The researchers propose to implement our general algorithms and make them available as a scientific package to the research community.
