29 research outputs found
Analysis of Uplink Scheduling for Haptic Communications
While new mechanisms and configurations of the 5G radio are offering step
forward in delivery of ultra-reliable low latency communication services in
general, and haptic communications in particular, they could inversely impact
the remainder of traffic services. In this paper, we investigate the uplink
access procedure, how different advances in this procedure enhance delivery of
haptic communication, and how it affects the remainder of traffic services in
the network. We model this impact as the remainder of service, using stochastic
network calculus. Our results show how best the tradeoff between faster or more
resource efficient uplink access can be made depending on the rate of haptic
data, which is directly relevant to the application domain of haptic
communication.Comment: 8 pages, 14 figures, conference pape
A Basic Result on the Superposition of Arrival Processes in Deterministic Networks
Time-Sensitive Networking (TSN) and Deterministic Networking (DetNet) are
emerging standards to enable deterministic, delay-critical communication in
such networks. This naturally (re-)calls attention to the network calculus
theory (NC), since a rich set of results for delay guarantee analysis have
already been developed there. One could anticipate an immediate adoption of
those existing network calculus results to TSN and DetNet. However, the
fundamental difference between the traffic specification adopted in TSN and
DetNet and those traffic models in NC makes this difficult, let alone that
there is a long-standing open challenge in NC. To address them, this paper
considers an arrival time function based max-plus NC traffic model. In
particular, for the former, the mapping between the TSN / DetNet and the NC
traffic model is proved. For the latter, the superposition property of the
arrival time function based NC traffic model is found and proved. Appealingly,
the proved superposition property shows a clear analogy with that of a
well-known counterpart traffic model in NC. These results help make an
important step towards the development of a system theory for delay guarantee
analysis of TSN / DetNet networks
Branching processes, the max-plus algebra and network calculus
Branching processes can describe the dynamics of various queueing systems, peer-to-peer systems, delay tolerant networks, etc. In this paper we study the basic stochastic recursion of multitype branching processes, but in two non-standard contexts. First, we consider this recursion in the max-plus algebra where branching corresponds to finding the maximal offspring of the current generation. Secondly, we consider network-calculus-type deterministic bounds as introduced by Cruz, which we extend to handle branching-type processes. The paper provides both qualitative and quantitative results and introduces various applications of (max-plus) branching processes in queueing theory
An End-to-End Stochastic Network Calculus with Effective Bandwidth and Effective Capacity
Network calculus is an elegant theory which uses envelopes to determine the
worst-case performance bounds in a network. Statistical network calculus is the
probabilistic version of network calculus, which strives to retain the
simplicity of envelope approach from network calculus and use the arguments of
statistical multiplexing to determine probabilistic performance bounds in a
network. The tightness of the determined probabilistic bounds depends on the
efficiency of modelling stochastic properties of the arrival traffic and the
service available to the traffic at a network node. The notion of effective
bandwidth from large deviations theory is a well known statistical descriptor
of arrival traffic. Similarly, the notion of effective capacity summarizes the
time varying resource availability to the arrival traffic at a network node.
The main contribution of this paper is to establish an end-to-end stochastic
network calculus with the notions of effective bandwidth and effective capacity
which provides efficient end-to-end delay and backlog bounds that grows
linearly in the number of nodes () traversed by the arrival traffic, under
the assumption of independence.Comment: 17 page