Trust Model for Optimized Cloud Services

Cloud computing with its inherent advantages draws attention for business critical applications, but concurrently expects high level of trust in cloud service providers. Reputation-based trust is emerging as a good choice to model trust of cloud service providers based on available evidence. Many existing reputation based systems either ignore or give less importance to uncertainty linked with the evidence. In this paper, we propose an uncertainty model and define our approach to compute opinion for cloud service providers. Using subjective logic operators along with the computed opinion values, we propose mechanisms to calculate the reputation of cloud service providers. We evaluate and compare our proposed model with existing reputation models

On Level Quantization for the Noncommutative Chern-Simons Theory

We show that the coefficient of the three-dimensional Chern-Simons action on the noncommutative plane must be quantized. Similar considerations apply in other dimensions as well.Comment: 6 pages, Latex, no figure

Secure communication using dynamic VPN provisioning in an Inter-Cloud environment

Most of the current cloud computing platforms offer Infrastructure as a Service (IaaS) model, which aims to provision basic virtualised computing resources as on-demand and dynamic services. Nevertheless, a single cloud does not have limitless resources to offer to its users, hence the notion of an Inter-Cloud enviroment where a cloud can use the infrastructure resources of other clouds. However, there is no common framework in existence that allows the srevice owners to seamlessly provision even some basic services across multiple cloud service providers, albeit not due to any inherent incompatibility or proprietary nature of the foundation technologies on which these cloud platforms are built. In this paper we present a novel solution which aims to cover a gap in a subsection of this problem domain. Our solution offer a security architecture that enables service owners to provision a dynamic and service-oriented secure virtual private network on top of multiple cloud IaaS providers. It does this by leveraging the scalability, robustness and flexibility of peer- to-peer overlay techniques to eliminate the manual configuration, key management and peer churn problems encountered in setting up the secure communication channels dynamically, between different components of a typical service that is deployed on multiple clouds. We present the implementation details of our solution as well as experimental results carried out on two commercial clouds

Dynamic virtual private network provisioning from multiple cloud infrastructure service providers

The Cloud infrastructure service providers currently provision basic virtualized computing resources as on demand and dynamic services but there is no common framework in existence that allows the seamless provisioning of even these basic services across multiple cloud service providers, although this is not due to any inherent incompatibility or proprietary nature of the foundation technologies on which these cloud platforms are built. We present a solution idea which aims to provide a dynamic and service oriented provisioning of secure virtual private networks on top of multiple cloud infrastructure service providers. This solution leverages the benefits of peer to peer overlay networks, i.e., the flexibility and scalability to handle the churn of nodes joining and leaving the VPNs and can adapt the topology of the VPN as per the requirements of the applications utilizing its intercloud secure communication framework

Hall effect in heavy-fermion metals

The heavy fermion systems present a unique platform in which strong electronic correlations give rise to a host of novel, and often competing, electronic and magnetic ground states. Amongst a number of potential experimental tools at our disposal, measurements of the Hall effect have emerged as a particularly important one in discerning the nature and evolution of the Fermi surfaces of these enigmatic metals. In this article, we present a comprehensive review of Hall effect measurements in the heavy-fermion materials, and examine the success it has had in contributing to our current understanding of strongly correlated matter. Particular emphasis is placed on its utility in the investigation of quantum critical phenomena which are thought to drive many of the exotic electronic ground states in these systems. This is achieved by the description of measurements of the Hall effect across the putative zero-temperature instability in the archetypal heavy-fermion metal YbRh$_2$Si$_2$. Using the Ce$M$In$_5$ (with $M =$ Co, Ir) family of systems as a paradigm, the influence of (antiferro-)magnetic fluctuations on the Hall effect is also illustrated. This is compared to prior Hall effect measurements in the cuprates and other strongly correlated systems to emphasize on the generality of the unusual magnetotransport in materials with non-Fermi liquid behavior.Comment: manuscript accepted in Adv. Phy

Neuromorphic In-Memory Computing Framework using Memtransistor Cross-bar based Support Vector Machines

This paper presents a novel framework for designing support vector machines (SVMs), which does not impose restriction on the SVM kernel to be positive-definite and allows the user to define memory constraint in terms of fixed template vectors. This makes the framework scalable and enables its implementation for low-power, high-density and memory constrained embedded application. An efficient hardware implementation of the same is also discussed, which utilizes novel low power memtransistor based cross-bar architecture, and is robust to device mismatch and randomness. We used memtransistor measurement data, and showed that the designed SVMs can achieve classification accuracy comparable to traditional SVMs on both synthetic and real-world benchmark datasets. This framework would be beneficial for design of SVM based wake-up systems for internet of things (IoTs) and edge devices where memtransistors can be used to optimize system's energy-efficiency and perform in-memory matrix-vector multiplication (MVM).Comment: 4 pages, 5 figures, MWSCAS 201

Biexciton recombination rates in self-assembled quantum dots

The radiative recombination rates of interacting electron-hole pairs in a quantum dot are strongly affected by quantum correlations among electrons and holes in the dot. Recent measurements of the biexciton recombination rate in single self-assembled quantum dots have found values spanning from two times the single exciton recombination rate to values well below the exciton decay rate. In this paper, a Feynman path-integral formulation is developed to calculate recombination rates including thermal and many-body effects. Using real-space Monte Carlo integration, the path-integral expressions for realistic three-dimensional models of InGaAs/GaAs, CdSe/ZnSe, and InP/InGaP dots are evaluated, including anisotropic effective masses. Depending on size, radiative rates of typical dots lie in the regime between strong and intermediate confinement. The results compare favorably to recent experiments and calculations on related dot systems. Configuration interaction calculations using uncorrelated basis sets are found to be severely limited in calculating decay rates.Comment: 11 pages, 4 figure