Theories and Models for Internet Quality of Service

We survey recent advances in theories and models for Internet Quality of Service (QoS). We start with the theory of network calculus, which lays the foundation for support of deterministic performance guarantees in networks, and illustrate its applications to integrated services, differentiated services, and streaming media playback delays. We also present mechanisms and architecture for scalable support of guaranteed services in the Internet, based on the concept of a stateless core. Methods for scalable control operations are also briefly discussed. We then turn our attention to statistical performance guarantees, and describe several new probabilistic results that can be used for a statistical dimensioning of differentiated services. Lastly, we review recent proposals and results in supporting performance guarantees in a best effort context. These include models for elastic throughput guarantees based on TCP performance modeling, techniques for some quality of service differentiation without access control, and methods that allow an application to control the performance it receives, in the absence of network support

Optimal channel choice for collaborative ad-hoc dissemination

Abstract—Collaborative ad-hoc dissemination of information has been proposed as an efficient means to disseminate information among devices in a wireless ad-hoc network. Devices help in forwarding the information channels to the entire network, by disseminating the channels they subscribe to, plus others. We consider the case where devices have a limited amount of storage that they are willing to devote to the public good, and thus have to decide which channels they are willing to help disseminate. We are interested in finding channel selection strategies which optimize the dissemination time across the channels. We first consider a simple model under the random mixing assumption; we show that channel dissemination time can be characterized in terms of the number of nodes that forward this channel. Then we show that maximizing a social welfare is equivalent to an assignment problem, whose solution can be obtained by a centralized greedy algorithm. We show empirical evidence, based on Zune data, that there is a substantial difference between the utility of the optimal assignment and heuristics that were used in the past. We also show that the optimal assignment can be approximated in a distributed way by a Metropolis-Hastings sampling algorithm. We also give a variant that accounts for battery level. This leads to a practical channel selection and reselection algorithm that can be implemented without any central control. I

Freshness and Reactivity Analysis in Globally Asynchronous Locally Time-Triggered Systems

International audienceCritical embedded systems are often designed as a set of real-time tasks, running on shared computing modules, and communicating through networks. Because of their critical nature, such systems have to meet timing properties. To help the designers to prove the correctness of their system, the real-time systems community has developed numerous approaches for analyzing the worst case times either on the processors (e.g. worst case execution time of a task) or on the networks (e.g. worst case traversal time of a message). However, there is a growing need to consider the complete system and to be able to determine end-to-end properties. Such properties apply to a functional chain which describes the behavior of a sequence of functions, not necessarily hosted on a shared module, from an input until the production of an output. This paper explores two end-to-end properties: freshness and reactivity, and presents an analysis method based on Mixed Integer Linear Programming (MILP). This work is supported by the French National Research Agency within the Satrimmap project

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

Last Encounter Routing under Random Waypoint Mobility

Last Encounter Routing (LER) algorithms for mobile ad hoc networks rely only on encounter histories at every node to route packets, and therefore do not need control traffic to track topology changes due to node mobility. LER exploits the fact that past information about a node`s mobility helps to locate that node in the future. As we have pointed out in earlier work \cite{mg}, the performance of LER algorithms depends on the mobility processes of nodes. In this paper, we ask whether LER can work under the random waypoint (RWP) mobility model. This question is important for several reasons. First, as shown in \cite{mg}, a good performance for the RWP model is harder to achieve than for another prominent mobility model, the random walk. This is because the RWP model has a much shorter relaxation time, i.e., a time-horizon over which past information is still useful. Also, the RWP model has a much less favorable ratio of number of encounters between nodes and the traveled distance. Second, in contrast to the random walk, the RWP model is predictable. This provides us with an opportunity to exploit additional information collected in an encounter (such as speed, direction, etc.) to improve routing. We formally define the RWP model, and compute the optimal predictors for several observation sets, i.e., observed parameters of node mobility. We develop a new LER algorithm tuned to the RWP model called GREASE-RWP, and present simulation results that demonstrate that an efficient and scalable LER for the RWP model is possible

Mean-Field Limits Beyond Ordinary Differential Equations

16th International School on Formal Methods for the Design of Computer, Communication, and Software Systems, SFM 2016, Bertinoro, Italy, June 20-24, 2016, Advanced LecturesInternational audienceWe study the limiting behaviour of stochastic models of populations of interacting agents, as the number of agents goes to infinity. Classical mean-field results have established that this limiting behaviour is described by an ordinary differential equation (ODE) under two conditions: (1) that the dynamics is smooth; and (2) that the population is composed of a finite number of homogeneous sub-populations, each containing a large number of agents. This paper reviews recent work showing what happens if these conditions do not hold. In these cases, it is still possible to exhibit a limiting regime at the price of replacing the ODE by a more complex dynamical system. In the case of non-smooth or uncertain dynamics, the limiting regime is given by a differential inclusion. In the case of multiple population scales, the ODE is replaced by a stochastic hybrid automaton

Upconversion assisted self-pulsing in a high-concentration erbium doped fiber laser

We report results on experimental and theoretical characterisation of self-pulsing in high concentration erbium doped fibre laser which is free from erbium clusters. Unlike previous models of self-pulsing accounting for pair-induced quenching (PIQ) on the clustered erbium ions, new model has been developed with accounting for statistical nature of the excitation migration and upconversion and resonance-like pumpto-signal intensity noise transfer. The obtained results are in a good agreement with the experimental data

A Domain-Specific Language for Incremental and Modular Design of Large-Scale Verifiably-Safe Flow Networks (Preliminary Report)

We define a domain-specific language (DSL) to inductively assemble flow networks from small networks or modules to produce arbitrarily large ones, with interchangeable functionally-equivalent parts. Our small networks or modules are "small" only as the building blocks in this inductive definition (there is no limit on their size). Associated with our DSL is a type theory, a system of formal annotations to express desirable properties of flow networks together with rules that enforce them as invariants across their interfaces, i.e, the rules guarantee the properties are preserved as we build larger networks from smaller ones. A prerequisite for a type theory is a formal semantics, i.e, a rigorous definition of the entities that qualify as feasible flows through the networks, possibly restricted to satisfy additional efficiency or safety requirements. This can be carried out in one of two ways, as a denotational semantics or as an operational (or reduction) semantics; we choose the first in preference to the second, partly to avoid exponential-growth rewriting in the operational approach. We set up a typing system and prove its soundness for our DSL.Comment: In Proceedings DSL 2011, arXiv:1109.032