We study a model of a competing population of N adaptive agents, with similar capabilities, repeatedly deciding whether to attend a bar with an arbitrary cutoff L. Decisions are based upon past outcomes. The agents are only told whether the actual attendance is above or below L. For L-> N/2, the game reproduces the main features of Challet and Zhang's minority game. As L is lowered, however, the mean attendances in different runs tend to divide into two groups. The corresponding standard deviations for these two groups are very different. This grouping effect results from the dynamical feedback governing the game's time-evolution, and is not reproduced if the agents are fed a random history.

Minority game with arbitrary cutoffs

Mobile data offloading based on minority game theoretic framework

Software Defined Networking (SDN) has been preferred over traditional networking due to its dynamic nature in adapting the network structure This agile nature of SDN imparts non-stationarity in traffic In this work, we characterize the SDN traffic and study its behavior under dynamic conditions using Augmented Dickey Fuller (ADF) test Later, we model the SDN under non-stationary conditions using queueing model and solve for average queue length at both controller and switch using Pointwise Stationary Fluid Flow Approximation (PSFFA) The analytical results have been validated through simulations We develop congestion control algorithm based on (a) Proportional Integral Derivative (PID) control mechanism and (b) Dynamic Random Early Detection (DRED) control mechanism for SDN controller using the fluid flow model Finally we demonstrate their effectiveness in stabilizing the queue length at the switch and controller under non-stationary conditions In nut shell our work brings out the importance of the non-stationary behaviour of the traffic in the design and analysis of SDN and its control algorithms

Modeling & analysis of software defined networks under non-stationary conditions

The increasing use of Software-Defined Networks brings the need for their performance analysis and detailed analytical and numerical models of them. The primary element of such research is a model of a SDN switch. This model should take into account non-Poisson traffic and general distributions of service times. Because of frequent changes in SDN flows, it should also analyze transient states of the queues. The method of diffusion approximation can meet these requirements. We present here a diffusion approximation of priority queues and apply it to build a more detailed model of SDN switch where packets returned by the central controller have higher priority than other packets.

Diffusion Model of Preemptive-Resume Priority Systems and Its Application to Performance Evaluation of SDN Switches

In the domain of wireless networking, there have been several attempts to design, and analyze resource allocation problems using Game theoretic techniques (such as, random access game for contention control). In the current paper, a Medium Access Control (MAC) protocol based on Minority Game(MG) theory is proposed for channel supporting Multipacket Reception (MPR). Several performance metrics of the protocol (like, mean of Attendance, Volatility, System Throughput and Energy Expenditure) are studied through extensive simulation. The behaviour of the protocol is also analyzed from the perspective of Crowd-Anticrowd Theory, a popular tool from econophysics literature.

Wireless MAC Protocol based on Crowd-Anticrowd Theory

Software Defined Networking (SDN) is a trending technology and its popularity can be attributed to its speed and agility in deploying new applications. Realistic modeling of SDN traffic is crucial in designing control algorithms and in provisioning network resources. The purpose of this paper is to model and characterize the SDN traffic. To this end, we have created an SDN environment using the mininet emulator and OpenDayLight (ODL) controller using which we have collected the SDN traffic data traces. The quantiles of inter-arrival times of SDN data traffic have been plotted against the quantiles of theoretical distributions. Then the Kolmogorov Smirnov (KS) test has been applied to model the SDN traffic and to capture its distribution characteristics effectively. From the KS test, it has been inferred that the inter arrival times of SDN traffic follows the Generalized Extreme Value (GEV) distribution. These findings indicate that traditional Poisson models for SDN traffic may not be suitable for evaluating the performance of Software Defined Networks.

Traffic Modeling & Characterization of Software Defined Networks

Successive Interference Cancellation (SIC) is one of the important techniques to decode multiple packets at the receiver and improve the system throughput. However, the IEEE 802.11 standard MAC protocol for Wi-Fi networks does not support multi-packet transmission. In this paper, we propose a modification to the IEEE 802.11 random access scheme for Wireless LAN (WLAN) that supports multi-packet transmission by leveraging the SIC technique at the Access Point (AP). The proposed random access scheme adapts to ongoing traffic conditions while decrementing the backoff counter value. Further, it utilizes the Channel State Information (CSI) to decide the backoff stage of the node. Extensive simulation has been carried out to validate the proposed protocol. Simulation results for the packet transmission probability, packet decoding probability, and throughput have been analyzed.

Navya Vuppalapati

Papers

Wireless MAC Protocol based on Crowd-Anticrowd Theory

Modeling & analysis of software defined networks under non-stationary conditions

Traffic Modeling & Characterization of Software Defined Networks

SIC and CSI-based Random Channel Access protocol for WLAN supporting Multi packet transmission

An Analytical Framework for Cooperative Cognitive Radio Network for Spectrum Leasing/Sharing