Dogu Arifler

Capacity analysis of a diffusion-based short-range molecular nano-communication channel

Abstract Simulation-based and information theoretic models for a diffusion-based short-range molecular communication channel between a nano-transmitter and a nano-receiver are constructed to analyze information rates between channel inputs and outputs when the inputs are independent and identically distributed (i.i.d.). The total number of molecules available for information transfer is assumed to be limited. It is also assumed that there is a maximum tolerable delay bound for the overall information transfer. Information rates are computed via simulation-based methods for different time slot lengths and transmitter–receiver distances. The rates obtained from simulations are then compared to those computed using information theoretic channel models which provide upper bounds for information rates. The results indicate that a 4-input–2-output discrete channel model provides a very good approximation to the nano-communication channel, particularly when the time slot lengths are large and the distance between the transmitter and the receiver is small. It is shown through an extensive set of simulations that the information theoretic channel capacity with i.i.d. inputs can be achieved when an encoder adjusts the relative frequency of binary zeros to be higher (between 50% and 70% for the scenarios considered) than binary ones, where a ‘zero’ corresponds to not releasing and a ‘one’ corresponds to releasing a molecule from the transmitter.

SMAQ: a measurement-based tool for traffic modeling and queuing analysis. I. Design methodologies and software architecture

SMAQ is a measurement-based tool for integration of traffic modeling and queuing analysis. There are three basic components in SMAQ. In the design of the first component, statistic measurement, the most critical issues are to identify the important traffic statistics for queuing analysis in a finite buffer system and then to build a measurement structure to collect them. Our study indicates that both first- and second-order traffic statistics, measured within a given frequency-window, have a very significant impact on the queue length and loss rate performance. In the design of the second component, matched modeling, the focal point is to construct a stochastic model that can match a wide range of important statistics collected in various applications. New methodologies and fast algorithms are developed for such construction on the basis of a circulant modulated Poisson process (CMPP). For the third component, queuing solutions, the basic requirement is to provide numerical solutions of the queue length and loss rate for transport of given traffic in a finite buffer system. A fast and stable computation method, called a Folding algorithm, is applied to provide both steady-state and transient solutions of various kinds, including congestion control performance where arriving traffic are selectively discarded based on queue thresholds. We provide both design methodologies and software architectures of these three components, with discussion of practical engineering issues for the use of the SMAQ tool.

SMAQ: a measurement-based tool for traffic modeling and queuing analysis. II. Network applications

For pt. I see ibid. p.56-65 (1998). SMAQ is a measurement-based tool for integration of traffic modeling and queuing analysis. It can be used in a variety of network design areas. For instance, it can be used as a traffic generator to generate various traces for network testing. It also provides numerical solutions of the queue length and loss rate performance for transport of multimedia traffic. Several application modules are built into the tool for the evaluation of statistical multiplexing, buffer dimensioning, and link bandwidth allocation. Other examples include the evaluation of traffic shaping, local-congestion control, and the modeling of wireless channel dynamics. As one will find, the SMAQ tool indeed provides a solution technique for network engineers to solve many of the current design issues.

Modeling the self-similar behavior of packetized MPEG-4 video using wavelet-based methods

Video streaming has already been very popular on the Internet through services such as news bulletins from different parts of the world and on-demand music-video clips. With rapidly developing wireless technologies, video streaming to mobile devices will be very common. We investigate the self-similar scaling behavior that is present in variable bit rate (VBR) MPEG-4 video. As the usage of video services over packet-based wireless networks increases, new workload models will be necessary to study the quality of service aspects of video traffic. A key finding of our study is that MPEG-4 video encoder output traffic has fractal behavior and this behavior exists regardless of the compression ratio.

Network tomography based on flow level measurements

Internet traffic primarily consists of packets from elastic flows, i.e., Web transfers, file transfers (FTP), and e-mail, whose transfers are mediated via the transmission control protocol. We develop a conditional sampling technique to analyze throughput correlations among elastic flow classes based on flow level measurements from current network traffic monitoring tools. The primary contributions of the paper are: (1) a demonstration of throughput correlation among temporally overlapping flows on congested resources by using analytical/simulation models; (2) application of a multivariate statistical method (principal components) to infer network properties, such as the number of resources shared by flows in the network, from non-intrusive, flow level measurements collected at a single site. Our proposal for using flow level measurements to infer network properties differs significantly from previous network tomography research that has employed end-to-end packet level measurements for making inferences.

A factor analytic approach to inferring congestion sharing based on flow level measurements

Internet traffic primarily consists of packets from elastic flows, i.e., Web transfers, file transfers, and e-mail, whose transmissions are mediated via the Transmission Control Protocol (TCP). In this paper, we develop a methodology to process TCP flow measurements in order to analyze throughput correlations among TCP flow classes that can be used to infer congestion sharing in the Internet. The primary contributions of this paper are: 1) development of a technique for processing flow records suitable for inferring congested resource sharing; 2) evaluation of the use of factor analysis on processed flow records to explore which TCP flow classes might share congested resources; and 3) validation of our inference methodology using bootstrap methods and nonintrusive, flow level measurements collected at a single network site. Our proposal for using flow level measurements to infer congestion sharing differs significantly from previous research that has employed packet level measurements for making inferences. Possible applications of our method include network monitoring and root cause analysis of poor performance.

Monte Carlo Analysis of Molecule Absorption Probabilities in Diffusion-Based Nanoscale Communication Systems with Multiple Receivers

For biomedical applications of nanonetworks, employing molecular communication for information transport is advantageous over nano-electromagnetic communication: molecular communication is potentially biocompatible and inherently energy-efficient. Recently, several studies have modeled receivers in diffusion-based molecular communication systems as “perfectly monitoring” or “perfectly absorbing” spheres based on idealized descriptions of chemoreception. In this paper, we focus on perfectly absorbing receivers and present methods to improve the accuracy of simulation procedures that are used to analyze these receivers. We employ schemes available from the chemical physics and biophysics literature and outline a Monte Carlo simulation algorithm that accounts for the possibility of molecule absorption during discrete time steps, leading to a more accurate analysis of absorption probabilities. Unlike most existing studies that consider a single receiver, this paper analyzes absorption probabilities for multiple receivers deterministically or randomly deployed in a region. For random deployments, the ultimate absorption probabilities as a function of transmitter–receiver distance are shown to fit well to power laws; the exponents derived become more negative as the number of receivers increases up to a limit beyond which no additional receivers can be “packed” in the deployment region. This paper is expected to impact the design of molecular nanonetworks with multiple absorbing receivers.

Link layer modeling of bio-inspired communication in nanonetworks

Abstract Bio-inspired packet communication over a link between two nanogateways is considered. In the envisioned nanonetwork architecture, bacteria are employed as transporters of information packets between gateways and therefore, the link layer model must take into account the behavior of these transporters. With the unique features of this mode of communication integrated into a simulation software, single-hop delay and throughput performance measures are analyzed. The effects on performance of traffic generation intensity, source–destination separation distance, propagation time variability, packet lifetime, and the number of bacteria that can be processed concurrently at the nanogateway are presented. The primary contribution of this study is an assessment of the effects of congestion in nanonetworks through consideration of competition among bacteria for conjugation at a nanogateway.

Simulation Based Analysis of Spreading Dynamics of Malware in Wireless Sensor Networks

We analyze spreading dynamics of malware (malicious software) that can replicate itself on other nodes in a network of wireless sensing devices. Epidemic models have previously been employed by researchers to investigate the spreading dynamics of malware in the Internet. Most studies have generally ignored spatial deployment characteristics of nodes which are critical for a realistic analysis in wireless sensor networks. We consider random and localized attack strategies by malware that may be introduced by an adversary into a network with either completely random or clustered sensor deployment patterns. Results demonstrate that sensor networks face serious security threats, particularly in cases where sensors are deployed in clusters and when malware can carry out attacks to random targets. We recommend possible defense measures based on simple topology control that might slow down the spread of malware across the network and allow necessary measures to be taken for containing the spread when malware employs a localized attack strategy. Presented analysis has a significant impact on network security and defense industry since it provides an insight into potential threats to information and surveillance infrastructure consisting of wireless sensing devices.

Deterministic Model for Pulse Amplification in Diffusion-Based Molecular Communication

In molecular communication, molecules are used to transmit information from a nanotransmitter to a nanoreceiver. In many molecular communication applications, the primary aim is to send a single pulse to trigger a response at the receiver. As such, the transmitter can emit a “puff” of information molecules that will freely diffuse in a fluidic environment. In free-diffusion-based communication, the maximum achievable pulse level rapidly decreases with increasing distance. Therefore, signal conditioning is usually necessary for effective processing at a distant receiver. We use Ficks diffusion equation to model pulse amplification, which is an important stage in signal conditioning. We consider the existence of an intermediate amplifying nanodevice that reacts to a given particle concentration condition by emitting the same type of particles as the transmitter. Our development differs from an ordinary problem in partial differential equations with two independent instantaneous point sources; here, by coupling the activation of the amplifier to the operation of the transmitting source, we determine the required particle allocations at these devices for optimal signal reception.