Chinese Wall Security Policy

This project establishes a Chinese wall security policy model in the environment of cloud computing. In 1988 Brewer and Nash proposed a very nice commercial security policy in British financial world. Though the policy was well accepted, but the model was incorrect. A decade later, Dr. Lin provided a model in 2003 that meets Brewer & Nash’s Policy. One of the important components in Cloud computing is data center. In order for any company to store data in the center, a trustable security policy model is a must; Chinese wall security policy model will provide this assurance. The heart of the Chinese Wall Security Policy Model is the concept of Conflict of Interest (COI). The concept can be modeled by an anti-reflexive, symmetric and transitive binary relation. In this project, by extending Dr. Lin’s Model, we explore the security issues in the environment of cloud computing and develop a small system of the Chinese Wall Security Model

Load Balancing in the Non-Degenerate Slowdown Regime

We analyse Join-the-Shortest-Queue in a contemporary scaling regime known as the Non-Degenerate Slowdown regime. Join-the-Shortest-Queue (JSQ) is a classical load balancing policy for queueing systems with multiple parallel servers. Parallel server queueing systems are regularly analysed and dimensioned by diffusion approximations achieved in the Halfin-Whitt scaling regime. However, when jobs must be dispatched to a server upon arrival, we advocate the Non-Degenerate Slowdown regime (NDS) to compare different load-balancing rules. In this paper we identify novel diffusion approximation and timescale separation that provides insights into the performance of JSQ. We calculate the price of irrevocably dispatching jobs to servers and prove this to within 15% (in the NDS regime) of the rules that may manoeuvre jobs between servers. We also compare ours results for the JSQ policy with the NDS approximations of many modern load balancing policies such as Idle-Queue-First and Power-of-$d$-choices policies which act as low information proxies for the JSQ policy. Our analysis leads us to construct new rules that have identical performance to JSQ but require less communication overhead than power-of-2-choices.Comment: Revised journal submission versio

Electronic spectroscopy of transient molecules by mass-selected resonance enhanced multi-photon ionization

This work describes the experimental measurements and spectroscopic analyses of several transient molecules. These species are produced using pulsed laser ablation or electric discharge coupled with supersonic expansion and their electronic spectra are recorded using time-of-flight (TOF) based resonance enhanced multi-photon ionization (REMPI) spectroscopy. A combination of REMPI and TOF provides a powerful tool for unambiguous identification of the carrier of any spectral feature with a particular mass signature. Silver monosulfide (AgS) has been spectroscopically characterized in the gas phase for the first time and electronic transitions in the near-infrared region are assigned to the A2Σ+ − X2Πi electronic transition, based on a rotational analysis. The small difference in the rotational constant between the X2Π ground and A2Σ+ excited states indicates only a small change in Ag−S bond length on electron promotion. This is consistent with the dominant Frank-Condon factor for the 0−0 transition in the vibronic spectra. The electronic transition of titanium dioxide (TiO2) and zirconium dioxide (ZrO2) were observed in the visible and assigned to A1B2 − X1A1 system. There are many similarities in their spectra, such as a significant decrease in ω2 and ω3 and a slight decrease in ω1 upon excitation from the X 1A1 to A1B2 state. Also, long progressions are observed for both, suggesting a significant geometry change between the states. There is one striking difference; the observation of odd-ν3 quanta in the case of zirconium dioxide, which provides an evidence for vibronic coupling between A1B2 state and the next higher state, due to a breakdown of Born-Oppenheimer approximation. Silicon trimer (Si3) provides another interesting case for a breakdown of the Born-Oppenheimer approximation. The ground state electronic configuration of (Si3) in the high symmetry D3h geometry gives rise to 3A2´, 1A1´ and 1E´ lower states, amongst which 3A2´ is the least energetic state. However, due to Jahn-Teller and pseudo Jahn-Teller effects, the 1A1 component of the 1E´ term is stabilized and crosses the undistorted 3A2´ ground state to produce a global minimum of C2v geometry. The 3A2´ and 1A1 are nearly iso-energetic and both get populated, even under supersonic expansion conditions, giving rise to a complicated electronic spectrum in the visible region. Broad contours originating from the (2)3Σu− − X3Σg− transition of C6 and C8, and the 1Σu+ − X1Σg+ one for C7 and C9 have been identified in the ultraviolet using a 30 ps laser, indicating an excited state lifetime less than 30 ps (temporal width of the laser pulse). Spectroscopic measurements, other than providing information about the fundamental properties of molecules, can enrich our understanding of the universe. The gas phase spectra presented in this work provide a guide for detection of these molecules in stars, comets, dust clouds, etc. and to understand the molecular chemistry taking place in these environments

An Empirical Evaluation Of Attention And Pointer Networks For Paraphrase Generation

In computer vision, one of the common practice to augment the image dataset is by creating new images using geometric transformation, which preserves the similarity. This data augmentation was one of the most significant factors to win the Image Net competition in 2012 with vast neural networks. Similarly, in speech recognition, we saw similar results by augmenting the signal by noise, slowing signal or accelerating it, and spectrogram modification. Unlike in computer vision and speech data, there haven not been many techniques explored to augment data in natural language processing (NLP). The only technique explored in text data is by lexical substitution, which only focuses on replacing words by synonyms. In this thesis, we investigate the use of different pointer networks with the sequence to sequence models, which have shown excellent results in neural machine translation (NMT) and text simplification tasks, in generating similar sentences using a sequence to sequence model and of the paraphrase dataset (PPDB). The evaluation of these paraphrases is carried out by augmenting the training dataset of IMDb movie review dataset and comparing its performance with the baseline model. We show how these paraphrases can affect downstream tasks. Furthermore, We train different classifiers to create a stable baseline for evaluation on IMDb movie dataset. To our best knowledge, this is the first study on generating paraphrases using these models with the help of PPDB dataset and evaluating these paraphrases in the downstream task

Measurement-Driven Algorithm and System Design for Wireless and Datacenter Networks

The growing number of mobile devices and data-intensive applications pose unique challenges for wireless access networks as well as datacenter networks that enable modern cloud-based services. With the enormous increase in volume and complexity of traffic from applications such as video streaming and cloud computing, the interconnection networks have become a major performance bottleneck. In this thesis, we study algorithms and architectures spanning several layers of the networking protocol stack that enable and accelerate novel applications and that are easily deployable and scalable. The design of these algorithms and architectures is motivated by measurements and observations in real world or experimental testbeds. In the first part of this thesis, we address the challenge of wireless content delivery in crowded areas. We present the AMuSe system, whose objective is to enable scalable and adaptive WiFi multicast. AMuSe is based on accurate receiver feedback and incurs a small control overhead. This feedback information can be used by the multicast sender to optimize multicast service quality, e.g., by dynamically adjusting transmission bitrate. Specifically, we develop an algorithm for dynamic selection of a subset of the multicast receivers as feedback nodes which periodically send information about the channel quality to the multicast sender. Further, we describe the Multicast Dynamic Rate Adaptation (MuDRA) algorithm that utilizes AMuSe's feedback to optimally tune the physical layer multicast rate. MuDRA balances fast adaptation to channel conditions and stability, which is essential for multimedia applications. We implemented the AMuSe system on the ORBIT testbed and evaluated its performance in large groups with approximately 200 WiFi nodes. Our extensive experiments demonstrate that AMuSe can provide accurate feedback in a dense multicast environment. It outperforms several alternatives even in the case of external interference and changing network conditions. Further, our experimental evaluation of MuDRA on the ORBIT testbed shows that MuDRA outperforms other schemes and supports high throughput multicast flows to hundreds of nodes while meeting quality requirements. As an example application, MuDRA can support multiple high quality video streams, where 90% of the nodes report excellent or very good video quality. Next, we specifically focus on ensuring high Quality of Experience (QoE) for video streaming over WiFi multicast. We formulate the problem of joint adaptation of multicast transmission rate and video rate for ensuring high video QoE as a utility maximization problem and propose an online control algorithm called DYVR which is based on Lyapunov optimization techniques. We evaluated the performance of DYVR through analysis, simulations, and experiments using a testbed composed of Android devices and o the shelf APs. Our evaluation shows that DYVR can ensure high video rates while guaranteeing a low but acceptable number of segment losses, buffer underflows, and video rate switches. We leverage the lessons learnt from AMuSe for WiFi to address the performance issues with LTE evolved Multimedia Broadcast/Multicast Service (eMBMS). We present the Dynamic Monitoring (DyMo) system which provides low-overhead and real-time feedback about eMBMS performance. DyMo employs eMBMS for broadcasting instructions which indicate the reporting rates as a function of the observed Quality of Service (QoS) for each UE. This simple feedback mechanism collects very limited QoS reports which can be used for network optimization. We evaluated the performance of DyMo analytically and via simulations. DyMo infers the optimal eMBMS settings with extremely low overhead, while meeting strict QoS requirements under different UE mobility patterns and presence of network component failures. In the second part of the thesis, we study datacenter networks which are key enablers of the end-user applications such as video streaming and storage. Datacenter applications such as distributed file systems, one-to-many virtual machine migrations, and large-scale data processing involve bulk multicast flows. We propose a hardware and software system for enabling physical layer optical multicast in datacenter networks using passive optical splitters. We built a prototype and developed a simulation environment to evaluate the performance of the system for bulk multicasting. Our evaluation shows that the optical multicast architecture can achieve higher throughput and lower latency than IP multicast and peer-to-peer multicast schemes with lower switching energy consumption. Finally, we study the problem of congestion control in datacenter networks. Quantized Congestion Control (QCN), a switch-supported standard, utilizes direct multi-bit feedback from the network for hardware rate limiting. Although QCN has been shown to be fast-reacting and effective, being a Layer-2 technology limits its adoption in IP-routed Layer 3 datacenters. We address several design challenges to overcome QCN feedback's Layer- 2 limitation and use it to design window-based congestion control (QCN-CC) and load balancing (QCN-LB) schemes. Our extensive simulations, based on real world workloads, demonstrate the advantages of explicit, multi-bit congestion feedback, especially in a typical environment where intra-datacenter traffic with short Round Trip Times (RTT: tens of s) run in conjunction with web-facing traffic with long RTTs (tens of milliseconds)

Addressing Diabetes Education in Chittenden County

The percent of adults in Chittenden County with diabetes who have received diabetes education was short of national goals. To gather more information about the problem, a NP and 2 diabetic patients were interviewed. A educational handout was created to address some of the concerns brought up that reflect some of the unmet educational needs