Comparison of valence band x-ray photoelectron spectrum between Al-N-codoped and N-doped ZnO films

The valence band structures of Al-N-codoped [ZnO:(Al, N)] and N-doped (ZnO:N) ZnO films were studied by normal and soft x-ray photoelectron spectroscopy. The valence-band maximum of ZnO:(Al, N) shifts up to Fermi energy level by about 300 meV compared with that of ZnO:N. Such a shift can be attributed to the existence of a kind of Al-N in ZnO:(Al, N), as supported by core level XPS spectra and comparison of modified Auger parameters. Al-N increased the relative quantity of Zn-N in ZnO:(Al, N), while N-N decreased that of Zn-N in ZnO:N. (c) 2006 American Institute of Physics.

Fragmentación financiera y Unión Bancaria

De acuerdo a la normativa de TFEs el repositorio no puede dar acceso a este trabajo. Para consultarlo póngase en contacto con el tutor del trabajo. Puede acceder al resumen del mismo pinchando en el pdf adjunto

Nonlinear Acoustics in Underwater and Biomedical Applications: Array Performance Degradation and Time Reversal Invariance

This dissertation describes a model for acoustic propagation in inhomogeneous flu- ids, and explores the focusing by arrays onto targets under various conditions. The work explores the use of arrays, in particular the time reversal array, for underwater and biomedical applications. Aspects of propagation and phasing which can lead to reduced focusing effectiveness are described. An acoustic wave equation was derived for the propagation of finite-amplitude waves in lossy time-varying inhomogeneous fluid media. The equation was solved numerically in both Cartesian and cylindrical geometries using the finite-difference time-domain (FDTD) method. It was found that time reversal arrays are sensitive to several debilitating factors. Focusing ability was determined to be adequate in the presence of temporal jitter in the time reversed signal only up to about one-sixth of a period. Thermoviscous absorption also had a debilitating effect on focal pressure for both linear and nonlinear propagation. It was also found that nonlinearity leads to degradation of focal pressure through amplification of the received signal at the array, and enhanced absorption in the shocked waveforms. This dissertation also examined the heating effects of focused ultrasound in a tissue-like medium. The application considered is therapeutic heating for hyperther- mia. The acoustic model and a thermal model for tissue were coupled to solve for transient and steady temperature profiles in tissue-like media. The Pennes bioheat equation was solved using the FDTD method to calculate the temperature fields in tissue-like media from focused acoustic sources. It was found that the temperature-dependence of the medium's background prop- erties can play an important role in the temperature predictions. Finite-amplitude effects contributed excess heat when source conditions were provided for nonlinear ef- fects to manifest themselves. The effect of medium heterogeneity was also found to be important in redistributing the acoustic and temperature fields, creating regions with hotter and colder temperatures than the mean by local scattering and lensing action. These temperature excursions from the mean were found to increase monotonically with increasing contrast in the medium's properties.

On the Convergence of Statistical Techniques for Inferring Network Traffic Demands

Accurate knowledge of traffic demands in a communication network enables or enhances a variety of traffic engineering and network management tasks of paramount importance for operational networks. Directly measuring a complete set of these demands is prohibitively expensive because of the huge amounts of data that must be collected and the performance impact that such measurements would impose on the regular behavior of the network. As a consequence, we must rely on statistical techniques to produce estimates of actual traffic demands from partial information. The performance of such techniques is however limited due to their reliance on limited information and the high amount of computations they incur, which limits their convergence behavior. In this paper we study strategies to improve the convergence of a powerful statistical technique based on an Expectation-Maximization iterative algorithm. First we analyze modeling approaches to generating starting points. We call these starting points informed priors since they are obtained using actual network information such as packet traces and SNMP link counts. Second we provide a very fast variant of the EM algorithm which extends its computation range, increasing its accuracy and decreasing its dependence on the quality of the starting point. Finally, we study the convergence characteristics of our EM algorithm and compare it against a recently proposed Weighted Least Squares approach.

How Well Can TCP Infer Network State?

The Transmission Control Protocol (TCP) has been the protocol of choice for many Internet applications requiring reliable connections. The design of TCP has been challenged by the extension of connections over wireless links. We ask a fundamental question: What is the basic predictive power of TCP of network state, including wireless error conditions? The goal is to improve or readily exploit this predictive power to enable TCP (or variants) to perform well in generalized network settings. To that end, we use Maximum Likelihood Ratio tests to evaluate TCP as a detector/estimator. We quantify how well network state can be estimated, given network response such as distributions of packet delays or TCP throughput that are conditioned on the type of packet loss. Using our model-based approach and extensive simulations, we demonstrate that congestion-induced losses and losses due to wireless transmission errors produce sufficiently different statistics upon which an efficient detector can be built; distributions of network loads can provide effective means for estimating packet loss type; and packet delay is a better signal of network state than short-term throughput. We demonstrate how estimation accuracy is influenced by different proportions of congestion versus wireless losses and penalties on incorrect estimation.

On the Efficiency and Fairness of Transmission Control Loops: A Case for Exogenous Losses

We postulate that exogenous losses-which are typically regarded as introducing undesirable "noise" that needs to be filtered out or hidden from end points-can be surprisingly beneficial. In this paper we evaluate the effects of exogenous losses on transmission control loops, focusing primarily on efficiency and convergence to fairness properties. By analytically capturing the effects of exogenous losses, we are able to characterize the transient behavior of TCP. Our numerical results suggest that "noise" resulting from exogenous losses should not be filtered out blindly, and that a careful examination of the parameter space leads to better strategies regarding the treatment of exogenous losses inside the network. Specifically, we show that while low levels of exogenous losses do help connections converge to their fair share, higher levels of losses lead to inefficient network utilization. We draw the line between these two cases by determining whether or not it is advantageous to hide, or more interestingly introduce, exogenous losses. Our proposed approach is based on classifying the effects of exogenous losses into long-term and short-term effects. Such classification informs the extent to which we control exogenous losses, so as to operate in an efficient and fair region. We validate our results through simulations.

Exogenous-Loss Awareness in Queue Management: Toward Global Fairness

For a given TCP flow, exogenous losses are those occurring on links other than the flow's bottleneck link. Exogenous losses are typically viewed as introducing undesirable "noise" into TCP's feedback control loop, leading to inefficient network utilization and potentially severe global unfairness. This has prompted much research on mechanisms for hiding such losses from end-points. In this paper, we show through analysis and simulations that low levels of exogenous losses are surprisingly beneficial in that they improve stability and convergence, without sacrificing efficiency. Based on this, we argue that exogenous loss awareness should be taken into account in any AQM design that aims to achieve global fairness. To that end, we propose an exogenous-loss aware Queue Management (XQM) that actively accounts for and leverages exogenous losses. We use an equation based approach to derive the quiescent loss rate for a connection based on the connection's profile and its global fair share. In contrast to other queue management techniques, XQM ensures that a connection sees its quiescent loss rate, not only by complementing already existing exogenous losses, but also by actively hiding exogenous losses, if necessary, to achieve global fairness. We establish the advantages of exogenous-loss awareness using extensive simulations in which, we contrast the performance of XQM to that of a host of traditional exogenous-loss unaware AQM techniques.

Efficiently and Fairly Allocating Bandwidth at a Highly Congested Link

We consider the problem of efficiently and fairly allocating bandwidth at a highly congested link to a diverse set of flows, including TCP flows with various Round Trip Times (RTT), non-TCP-friendly flows such as Constant-Bit-Rate (CBR) applications using UDP, misbehaving, or malicious flows. Though simple, a FIFO queue management is vulnerable. Fair Queueing (FQ) can guarantee max-min fairness but fails at efficiency. RED-PD exploits the history of RED's actions in preferentially dropping packets from higher-rate flows. Thus, RED-PD attempts to achieve fairness at low cost. By relying on RED's actions, RED-PD turns out not to be effective in dealing with non-adaptive flows in settings with a highly heterogeneous mix of flows. In this paper, we propose a new approach we call RED-NB (RED with No Bias). RED-NB does not rely on RED's actions. Rather it explicitly maintains its own history for the few high-rate flows. RED-NB then adaptively adjusts flow dropping probabilities to achieve max-min fairness. In addition, RED-NB helps RED itself at very high loads by tuning RED's dropping behavior to the flow characteristics (restricted in this paper to RTTs) to eliminate its bias against long-RTT TCP flows while still taking advantage of RED's features at low loads. Through extensive simulations, we confirm the fairness of RED-NB and show that it outperforms RED, RED-PD, and CHOKe in all scenarios.

Providing Soft Bandwidth Guarantees Using Elastic TCP-based Tunnels

The best-effort nature of the Internet poses a significant obstacle to the deployment of many applications that require guaranteed bandwidth. In this paper, we present a novel approach that enables two edge/border routers-which we call Internet Traffic Managers (ITM)-to use an adaptive number of TCP connections to set up a tunnel of desirable bandwidth between them. The number of TCP connections that comprise this tunnel is elastic in the sense that it increases/decreases in tandem with competing cross traffic to maintain a target bandwidth. An origin ITM would then schedule incoming packets from an application requiring guaranteed bandwidth over that elastic tunnel. Unlike many proposed solutions that aim to deliver soft QoS guarantees, our elastic-tunnel approach does not require any support from core routers (as with IntServ and DiffServ); it is scalable in the sense that core routers do not have to maintain per-flow state (as with IntServ); and it is readily deployable within a single ISP or across multiple ISPs. To evaluate our approach, we develop a flow-level control-theoretic model to study the transient behavior of established elastic TCP-based tunnels. The model captures the effect of cross-traffic connections on our bandwidth allocation policies. Through extensive simulations, we confirm the effectiveness of our approach in providing soft bandwidth guarantees. We also outline our kernel-level ITM prototype implementation.

TCP Optimization through FEC, ARQ and Transmission Power Tradeoffs

TCP performance degrades when end-to-end connections extend over wireless connections-links which are characterized by high bit error rate and intermittent connectivity. Such link characteristics can significantly degrade TCP performance as the TCP sender assumes wireless losses to be congestion losses resulting in unnecessary congestion control actions. Link errors can be reduced by increasing transmission power, code redundancy (FEC) or number of retransmissions (ARQ). But increasing power costs resources, increasing code redundancy reduces available channel bandwidth and increasing persistency increases end-to-end delay. The paper proposes a TCP optimization through proper tuning of power management, FEC and ARQ in wireless environments (WLAN and WWAN). In particular, we conduct analytical and numerical analysis taking into "wireless-aware" TCP) performance under different settings. Our results show that increasing power, redundancy and/or retransmission levels always improves TCP performance by reducing link-layer losses. However, such improvements are often associated with cost and arbitrary improvement cannot be realized without paying a lot in return. It is therefore important to consider some kind of net utility function that should be optimized, thus maximizing throughput at the least possible cost.

A Bayesian Approach for TCP to Distinguish Congestion from Wireless Losses

(This Technical Report revises TR-BUCS-2003-011) The Transmission Control Protocol (TCP) has been the protocol of choice for many Internet applications requiring reliable connections. The design of TCP has been challenged by the extension of connections over wireless links. In this paper, we investigate a Bayesian approach to infer at the source host the reason of a packet loss, whether congestion or wireless transmission error. Our approach is "mostly" end-to-end since it requires only one long-term average quantity (namely, long-term average packet loss probability over the wireless segment) that may be best obtained with help from the network (e.g. wireless access agent).Specifically, we use Maximum Likelihood Ratio tests to evaluate TCP as a classifier of the type of packet loss. We study the effectiveness of short-term classification of packet errors (congestion vs. wireless), given stationary prior error probabilities and distributions of packet delays conditioned on the type of packet loss (measured over a larger time scale). Using our Bayesian-based approach and extensive simulations, we demonstrate that congestion-induced losses and losses due to wireless transmission errors produce sufficiently different statistics upon which an efficient online error classifier can be built. We introduce a simple queueing model to underline the conditional delay distributions arising from different kinds of packet losses over a heterogeneous wired/wireless path. We show how Hidden Markov Models (HMMs) can be used by a TCP connection to infer efficiently conditional delay distributions. We demonstrate how estimation accuracy is influenced by different proportions of congestion versus wireless losses and penalties on incorrect classification.

itmBench: Generalized API for Internet Traffic Managers

Internet Traffic Managers (ITMs) are special machines placed at strategic places in the Internet. itmBench is an interface that allows users (e.g. network managers, service providers, or experimental researchers) to register different traffic control functionalities to run on one ITM or an overlay of ITMs. Thus itmBench offers a tool that is extensible and powerful yet easy to maintain. ITM traffic control applications could be developed either using a kernel API so they run in kernel space, or using a user-space API so they run in user space. We demonstrate the flexibility of itmBench by showing the implementation of both a kernel module that provides a differentiated network service, and a user-space module that provides an overlay routing service. Our itmBench Linux-based prototype is free software and can be obtained from http://www.cs.bu.edu/groups/itm/.

Exploiting the Transients of Adaptation for RoQ Attacks on Internet Resources

In this paper, we expose an unorthodox adversarial attack that exploits the transients of a system's adaptive behavior, as opposed to its limited steady-state capacity. We show that a well orchestrated attack could introduce significant inefficiencies that could potentially deprive a network element from much of its capacity, or significantly reduce its service quality, while evading detection by consuming an unsuspicious, small fraction of that element's hijacked capacity. This type of attack stands in sharp contrast to traditional brute-force, sustained high-rate DoS attacks, as well as recently proposed attacks that exploit specific protocol settings such as TCP timeouts. We exemplify what we term as Reduction of Quality (RoQ) attacks by exposing the vulnerabilities of common adaptation mechanisms. We develop control-theoretic models and associated metrics to quantify these vulnerabilities. We present numerical and simulation results, which we validate with observations from real Internet experiments. Our findings motivate the need for the development of adaptation mechanisms that are resilient to these new forms of attacks.

A randomized solution to BGP divergence

The Border Gateway Protocol (BGP) is an interdomain routing protocol that allows each Autonomous System (AS) to define its own routing policies independently and use them to select the best routes. By means of policies, ASes are able to prevent some traffic from accessing their resources, or direct their traffic to a preferred route. However, this flexibility comes at the expense of a possibility of divergence behavior because of mutually conflicting policies. Since BGP is not guaranteed to converge even in the absence of network topology changes, it is not safe. In this paper, we propose a randomized approach to providing safety in BGP. The proposed algorithm dynamically detects policy conflicts, and tries to eliminate the conflict by changing the local preference of the paths involved. Both the detection and elimination of policy conflicts are performed locally, i.e. by using only local information. Randomization is introduced to prevent synchronous updates of the local preferences of the paths involved in the same conflict.

Safe Compositional Specification of Networking Systems

The Science of Network Service Composition has clearly emerged as one of the grand themes driving many of our research questions in the networking field today [NeXtworking 2003]. This driving force stems from the rise of sophisticated applications and new networking paradigms. By "service composition" we mean that the performance and correctness properties local to the various constituent components of a service can be readily composed into global (end-to-end) properties without re-analyzing any of the constituent components in isolation, or as part of the whole composite service. The set of laws that would govern such composition is what will constitute that new science of composition. The combined heterogeneity and dynamic open nature of network systems makes composition quite challenging, and thus programming network services has been largely inaccessible to the average user. We identify (and outline) a research agenda in which we aim to develop a specification language that is expressive enough to describe different components of a network service, and that will include type hierarchies inspired by type systems in general programming languages that enable the safe composition of software components. We envision this new science of composition to be built upon several theories (e.g., control theory, game theory, network calculus, percolation theory, economics, queuing theory). In essence, different theories may provide different languages by which certain properties of system components can be expressed and composed into larger systems. We then seek to lift these lower-level specifications to a higher level by abstracting away details that are irrelevant for safe composition at the higher level, thus making theories scalable and useful to the average user. In this paper we focus on services built upon an overlay management architecture, and we use control theory and QoS theory as example theories from which we lift up compositional specifications.