Ken R. Duffy

Modeling the 802.11 distributed coordination function in nonsaturated heterogeneous conditions

Analysis of the 802.11 CSMA/CA mechanism has received considerable attention recently. Bianchi presented an analytic model under a saturated traffic assumption. Bianchis model is accurate, but typical network conditions are nonsaturated and heterogeneous. We present an extension of his model to a nonsaturated environment. The models predictions, validated against simulation, accurately capture many interesting features of nonsaturated operation. For example, the model predicts that peak throughput occurs prior to saturation. Our model allows stations to have different traffic arrival rates, enabling us to address the question of fairness between competing flows. Although we use a specific arrival process, it encompasses a wide range of interesting traffic types including, in particular, VoIP

Modeling the 802.11 distributed coordination function in non-saturated conditions

Analysis of the 802.11 CSMA/CA mechanism has received considerable attention recently. Bianchi (2000) presents an analytic model under a saturated traffic assumption. Bianchis model is accurate, but typical network conditions are non-saturated. This paper presents an extension of Bianchis model to a non-saturated environment. Its predictions are validated against simulation and are found to accurately capture many interesting features of non-saturated operation.

Activation-Induced B Cell Fates Are Selected by Intracellular Stochastic Competition

Stochastic or Asymmetric Fate Determination? During an adaptive immune response, B lymphocytes rapidly divide and differentiate into effector cell populations, including antibody-secreting plasmablasts and memory B cells. Many also change the class of antibody they secrete, through a process called isotype switching. During this process, some cells die. Whether cells acquire these different fates in a stochastic or programmed manner, however, is unclear. Duffy et al. (p. 338, published online 5 January) used single-cell tracking to determine the times to division, differentiation into a plasmablast, isotype switching, and death of stimulated B lymphocytes. Statistical analysis and mathematical modeling revealed that these cell-fate decisions appear to be the result of random clocks: Which clock went off first (division, differentiation, or death), determined the fate of the cell. Barnett et al. (p. 342, published online 15 December) sought to determine whether asymmetrical cell division, which is thought to contribute to effector cell-fate decisions in T cells, may be at work in B lymphocytes. Indeed, factors important for the initiation and maintenance of germinal center B lymphocyte identity, along with an ancestral polarity protein, were asymmetrically distributed and maintained their asymmetry during cell division. Cell-fate decisions in activated B lymphocytes are determined by stochastic competition. In response to stimulation, B lymphocytes pursue a large number of distinct fates important for immune regulation. Whether each cell’s fate is determined by external direction, internal stochastic processes, or directed asymmetric division is unknown. Measurement of times to isotype switch, to develop into a plasmablast, and to divide or to die for thousands of cells indicated that each fate is pursued autonomously and stochastically. As a consequence of competition between these processes, censorship of alternative outcomes predicts intricate correlations that are observed in the data. Stochastic competition can explain how the allocation of a proportion of B cells to each cell fate is achieved. The B cell may exemplify how other complex cell differentiation systems are controlled.

Antigen affinity, costimulation, and cytokine inputs sum linearly to amplify T cell expansion

T cell responses are initiated by antigen and promoted by a range of costimulatory signals. Understanding how T cells integrate alternative signal combinations and make decisions affecting immune response strength or tolerance poses a considerable theoretical challenge. Here, we report that T cell receptor (TCR) and costimulatory signals imprint an early, cell-intrinsic, division fate, whereby cells effectively count through generations before returning automatically to a quiescent state. This autonomous program can be extended by cytokines. Signals from the TCR, costimulatory receptors, and cytokines add together using a linear division calculus, allowing the strength of a T cell response to be predicted from the sum of the underlying signal components. These data resolve a long-standing costimulation paradox and provide a quantitative paradigm for therapeutically manipulating immune response strength. T cells follow a linear calculation when integrating costimulatory and cytokine signals. Stimulatory signals add up for T cells T cell activation is a dynamic process. T cells encounter multiple input signals such as antigens, costimulatory molecules, and cytokines at different times and anatomical locations during an infection. But how do T cells integrate this information to determine the extent to which they divide? To find out, Marchingo et al. stimulated mouse T cells in culture with different combinations of inputs and also tracked antigen-specific T cell responses in mice infected with influenza virus. They found that T cells linearly sum the various stimulatory inputs they receive to determine their “division destiny.” Science, this issue p. 1123

Decentralised learning MACs for collision-free access in WLANs

By combining the features of CSMA and TDMA, fully decentralised WLAN MAC schemes have recently been proposed that converge to collision-free schedules. In this paper we describe a MAC with optimal long-run throughput that is almost decentralised. We then design two schemes that are practically realisable, decentralised approximations of this optimal scheme and operate with different amounts of sensing information. We achieve this by (1) introducing learning algorithms that can substantially speed up convergence to collision free operation; (2) developing a decentralised schedule length adaptation scheme that provides long-run fair (uniform) access to the medium while maintaining collision-free access for arbitrary numbers of stations.

Modeling the Impact of Buffering on 802.11

A finite load, large buffer model for the WLAN medium access protocol IEEE 802.11 is developed that gives throughput and delay predictions. This enables us to investigate the impact of buffering on resource allocation. In the presence of heterogeneous loads, 802.11 do not allocate transmission opportunities equally. It is shown that increased buffering can help this inequity, but only at the expense of possibly significantly increased delays

Modeling 802.11e for data traffic parameter design

This paper introduces a finite load multi-class 802.11e EDCF model that is simple enough to be explicitly solvable. The model is nevertheless flexible enough to model the impact of 802.11e parameters on the prioritization of realistic traffic. We emphasize that a modeling framework which allows nonsaturated sources is essential in the study of realistic traffic. We apply the model to a situation of practical interest: competing TCP flows in an infrastructure network. The model allows us to make a principled selection of 802.11e parameters to resolve problems highlighted in this scenario. Model predictions and parameter selections are validated against simulation and experiment. The model is shown to be accurate and the parameters effective.

On the validity of IEEE 802.11 MAC modeling hypotheses

We identify common hypotheses on which a large number of distinct mathematical models of WLANs employing IEEE 802.11 are founded. Using data from an experimental test bed and packet-level ns-2 simulations, we investigate the veracity of these hypotheses. We demonstrate that several of these assumptions are inaccurate and/or inappropriate. We consider hypotheses used in the modeling of saturated and unsaturated 802.11 infrastructure mode networks, saturated 802.11e networks, and saturated and unsaturated 802.11s mesh networks. In infrastructure mode networks, we find that even for small numbers of stations, common hypotheses hold true for saturated stations and also for unsaturated stations with small buffers. However, despite their widespread adoption, common assumptions used to incorporate station buffers are erroneous. This raises questions about the predictive power of all models based on these hypotheses. For saturated 802.11e models that treat differences in arbitration interframe space (AIFS), we find that the two fundamental hypotheses are reasonable. For 802.11s mesh networks, we find that assumptions are appropriate only if stations are lightly loaded and are highly inappropriate if they are saturated. In identifying these flawed suppositions, this work identifies areas where mathematical models need to be revisited and revised if they are to be used with confidence by protocol designers and WLAN network planners.

Complexity analysis of a decentralised graph colouring algorithm

Colouring a graph with its chromatic number of colours is known to be NP-hard. Identifying an algorithm in which decisions are made locally with no information about the graphs global structure is particularly challenging. In this article we analyse the complexity of a decentralised colouring algorithm that has recently been proposed for channel selection in wireless computer networks.

Intracellular competition for fates in the immune system

During an adaptive immune response, lymphocytes proliferate for five to 20 generations, differentiating to take on effector functions, before cessation and cell death become dominant. Recent experimental methodologies enable direct observation of individual lymphocytes and the times at which they adopt fates. Data from these experiments reveal diversity in fate selection, heterogeneity and involved correlation structures in times to fate, as well as considerable familial correlations. Despite the significant complexity, these data are consistent with the simple hypothesis that each cell possesses autonomous processes, subject to temporal competition, leading to each fate. This article addresses the evidence for this hypothesis, its hallmarks, and, should it be an appropriate description of a cell system, its ramifications for manipulation.