The Experts below are selected from a list of 69 Experts worldwide ranked by ideXlab platform

Vikram Krishnamurthy - One of the best experts on this subject based on the ideXlab platform.

  • transmission control in cognitive radio as a Markovian Dynamic game structural result on randomized threshold policies
    IEEE Transactions on Communications, 2010
    Co-Authors: J W Huang, Vikram Krishnamurthy
    Abstract:

    This paper considers an uplink time division multiple access (TDMA) cognitive radio network where multiple cognitive radios (secondary users) attempt to access a spectrum hole. We assume that each secondary user can access the channel according to a decentralized predefined access rule based on the channel quality and the transmission delay of each secondary user. By modeling secondary user block fading channel qualities as a finite state Markov chain, we formulate the transmission rate adaptation problem of each secondary user as a general-sum Markovian Dynamic game with a delay constraint. Conditions are given so that the Nash equilibrium transmission policy of each secondary user is a randomized mixture of pure threshold policies. Such threshold policies can be easily implemented. We then present a stochastic approximation algorithm that can adaptively estimate the Nash equilibrium policies and track such policies for non-stationary problems where the statistics of the channel and user parameters evolve with time.

  • multi user scalable video transmission control in cognitive radio networks as a Markovian Dynamic game
    Conference on Decision and Control, 2009
    Co-Authors: Hassan Mansour, J W Huang, Vikram Krishnamurthy
    Abstract:

    This paper considers the multi-user bit-rate and latency control of scalable video content in a cognitive radio multimedia network. We consider a cognitive radio network where multiple secondary users attempt to access a spectrum hole according to a predefined time division multiple access (TDMA) access rule based on the primary user activities, the channel quality and the transmission delay of each user. Scalable video rate and distortion models are used in formulating the problem as a switching control Dynamic Markovian game. The video sources and channel behavior are modeled as independent Markov processes. However, the interaction between users is combined in the access rule thus resulting in a switching control game. We show that the proposed switching control game formulation results in an improvement in video quality over a myopic rate allocation scheme in video peak signal-to-noise ratio (PSNR).

Marcelo Dias De Amorim - One of the best experts on this subject based on the ideXlab platform.

  • performance of opportunistic epidemic routing on edge Markovian Dynamic graphs
    IEEE Transactions on Communications, 2011
    Co-Authors: John Whitbeck, Vania Conan, Marcelo Dias De Amorim
    Abstract:

    Connectivity patterns in intermittently-connected mobile networks (ICMN) can be modeled as edge-Markovian Dynamic graphs. We propose a new model for epidemic propagation on such graphs and calculate a closed-form expression that links the best achievable delivery ratio to common ICMN parameters such as message size, maximum tolerated delay, and link lifetime. These theoretical results are compared to those obtained by replaying a real-life contact trace.

Enrico Scalas - One of the best experts on this subject based on the ideXlab platform.

  • solvable non Markovian Dynamic network
    Physical Review E, 2015
    Co-Authors: Nicos Georgiou, Istvan Z Kiss, Enrico Scalas
    Abstract:

    Non-Markovian processes are widespread in natural and human-made systems, yet explicit modeling and analysis of such systems is underdeveloped. We consider a non-Markovian Dynamic network with random link activation and deletion (RLAD) and heavy-tailed Mittag-Leffler distribution for the interevent times. We derive an analytically and computationally tractable system of Kolmogorov-like forward equations utilizing the Caputo derivative for the probability of having a given number of active links in the network and solve them. Simulations for the RLAD are also studied for power-law interevent times and we show excellent agreement with the Mittag-Leffler model. This agreement holds even when the RLAD network Dynamics is coupled with the susceptible-infected-susceptible spreading Dynamics. Thus, the analytically solvable Mittag-Leffler model provides an excellent approximation to the case when the network Dynamics is characterized by power-law-distributed interevent times. We further discuss possible generalizations of our result.

  • exactly solvable non Markovian Dynamic network
    arXiv: Probability, 2015
    Co-Authors: Nicos Georgiou, Istvan Z Kiss, Enrico Scalas
    Abstract:

    Non-Markovian processes are widespread in natural and human-made systems, yet explicit modelling and analysis of such systems is underdeveloped. In this letter we consider a Dynamic network with random link activation and deletion (RLAD) with non-exponential inter-event times. We study a semi-Markov random process when the inter-event times are heavy tailed Mittag-Leffler distributed, thus considerably slowing down the corresponding Markovian Dynamics and study the system far from equilibrium. We derive an analytically and computationally tractable system of forward equations utilizing the Caputo derivative for the probability of having a given number of active links in the network. As an example showing the effects of non-Markovianity, the Dynamic network is coupled with a susceptible-infected-susceptible (SIS) spreading Dynamics leading to more persistent epidemics. The convergence to equilibrium is discussed in terms of the mixing time of the embedded chain and the difference with the Markovian case is highlighted. The novelty of our approach lies in showing a rigorous route from a non-Markovian model to the corresponding Kolmogorov-like equations and their analytical treatment.

Li Qiu - One of the best experts on this subject based on the ideXlab platform.

  • edge Markovian Dynamic graph based performance evaluation for delay tolerant networks
    Wireless Communications and Networking Conference, 2012
    Co-Authors: Li Qiu, Pan Hui, Depeng Jin, Lieguang Zeng
    Abstract:

    Groups of people with mobile phones using short range connections like WiFi and Bluetooth to propagate messages can be modeled as, with regard to regular absence of end-to-end connection, Delay Tolerant Networks (DTNs). The study of message transmission speed in such kind of networks has attracted increasing attention in recent years. In this paper, we present a realistic framework to model the message propagation process, and give a detailed expression of average information dissemination delay based on message size, users' selfishness, number of involved subscribers and other related parameters. We apply our model to real-life traces to assess its reliability by comparing the theoretical results with measured statistics, and present extensive upshots to evaluate the influence of various parameters on system performance.

  • edge Markovian Dynamic graph based information dissemination model for mobile social networks
    Proceedings of The ACM CoNEXT Student Workshop, 2011
    Co-Authors: Li Qiu, Pan Hui
    Abstract:

    In this poster, we apply Edge-Markovian Dynamic Graphs to present an analysis framework to evaluate the average delay for the information dissemination in Mobile Social Networks. It is the first model to give a detailed expression of average information dissemination delay based on message size, transmission willingness and other parameters. Extensive simulation results reveal the influence of those parameters.

J W Huang - One of the best experts on this subject based on the ideXlab platform.

  • transmission control in cognitive radio as a Markovian Dynamic game structural result on randomized threshold policies
    IEEE Transactions on Communications, 2010
    Co-Authors: J W Huang, Vikram Krishnamurthy
    Abstract:

    This paper considers an uplink time division multiple access (TDMA) cognitive radio network where multiple cognitive radios (secondary users) attempt to access a spectrum hole. We assume that each secondary user can access the channel according to a decentralized predefined access rule based on the channel quality and the transmission delay of each secondary user. By modeling secondary user block fading channel qualities as a finite state Markov chain, we formulate the transmission rate adaptation problem of each secondary user as a general-sum Markovian Dynamic game with a delay constraint. Conditions are given so that the Nash equilibrium transmission policy of each secondary user is a randomized mixture of pure threshold policies. Such threshold policies can be easily implemented. We then present a stochastic approximation algorithm that can adaptively estimate the Nash equilibrium policies and track such policies for non-stationary problems where the statistics of the channel and user parameters evolve with time.

  • multi user scalable video transmission control in cognitive radio networks as a Markovian Dynamic game
    Conference on Decision and Control, 2009
    Co-Authors: Hassan Mansour, J W Huang, Vikram Krishnamurthy
    Abstract:

    This paper considers the multi-user bit-rate and latency control of scalable video content in a cognitive radio multimedia network. We consider a cognitive radio network where multiple secondary users attempt to access a spectrum hole according to a predefined time division multiple access (TDMA) access rule based on the primary user activities, the channel quality and the transmission delay of each user. Scalable video rate and distortion models are used in formulating the problem as a switching control Dynamic Markovian game. The video sources and channel behavior are modeled as independent Markov processes. However, the interaction between users is combined in the access rule thus resulting in a switching control game. We show that the proposed switching control game formulation results in an improvement in video quality over a myopic rate allocation scheme in video peak signal-to-noise ratio (PSNR).