A hybrid agent architecture for modeling autonomous agents in SAGE

This paper highlights the Hybrid agent construction model being developed that allows the description and development of autonomous agents in SAGE (Scalable, fault Tolerant Agent Grooming Environment) - a second generation FIPA-Compliant Multi-Agent system. We aim to provide the programmer with a generic and well defined agent architecture enabling the development of sophisticated agents on SAGE, possessing the desired properties of autonomous agents - reactivity, pro-activity, social ability and knowledge based reasoning. © Springer-Verlag Berlin Heidelberg 2005.

FREP: A Soft-Error Resilient Pipelined RISC Architecture

Soft error has become one of the major areas of attention with the device scaling and large scale integration. Lot of variants for superscalar architecture were proposed with focus on program re-execution, thread re-execution and instruction re-execution. In this paper we proposed a fault tolerant micro-architecture of pipelined RISC. The proposed architecture, Floating Resources Extended pipeline (FREP), re-executes the instructions using extended pipeline stages. The instructions are re-executed by hybrid architecture with a suitable combination of space and time redundancy.

Energy-efficient redundant execution for chip multiprocessors

Relentless CMOS scaling coupled with lower design tolerances is making ICs increasingly susceptible to wear-out related permanent faults and transient faults, necessitating on-chip fault tolerance in future chip microprocessors (CMPs). In this paper, we describe a power-efficient architecture for redundant execution on chip multiprocessors (CMPs) which when coupled with our per-core dynamic voltage and frequency scaling (DVFS) algorithm significantly reduces the energy overhead of redundant execution without sacrificing performance. Our evaluation shows that this architecture has a performance overhead of only 0.3% and consumes only 1.48 times the energy of a non-fault-tolerant baseline.

Modeling stochastic hybrid systems

Stochastic hybrid systems arise in numerous applications of systems with multiple models; e.g., air traffc management, flexible manufacturing systems, fault tolerant control systems etc. In a typical hybrid system, the state space is hybrid in the sense that some components take values in a Euclidean space, while some other components are discrete. In this paper we propose two stochastic hybrid models, both of which permit diffusion and hybrid jump. Such models are essential for studying air traffic management in a stochastic framework.

A Hybrid Five-Level Inverter With Common-Mode Voltage Elimination Having Single Voltage Source for IM Drive Applications

A new hybrid five-level inverter topology with common-mode voltage (CMV) elimination for induction motor drive is proposed in this paper. This topology has only one dc source, and different voltage levels are generated by using this voltage source along with floating capacitors charged to asymmetrical voltage levels. The pulsewidth modulation (PWM) scheme employed in this topology balances the capacitor voltages at the required levels at any power factor and modulation index while eliminating the CMV. This inverter has good fault-tolerant capability as it can be operated in three-or two-level mode with CMV elimination, in case of any failure in the H-bridges. More voltage levels with CMV elimination can be realized from this topology but only in a limited range of modulation index and power factor. Extensive simulation is done to validate the PWM technique for CMV elimination and balancing of the capacitor voltages. The experimental verification of the proposed inverter-fed induction motor is carried out in the linear modulation and overmodulation regions. The steady-state and transient operations of the drive are verified. The dynamics of the capacitor voltage balancing is also tested. The experimental results demonstrate that the proposed topology can be considered for industrial drive applications.

On the secret key capacity of the harary graph PIN model

A pairwise independent network (PIN) model consists of pairwise secret keys (SKs) distributed among m terminals. The goal is to generate, through public communication among the terminals, a group SK that is information-theoretically secure from an eavesdropper. In this paper, we study the Harary graph PIN model, which has useful fault-tolerant properties. We derive the exact SK capacity for a regular Harary graph PIN model. Lower and upper bounds on the fault-tolerant SK capacity of the Harary graph PIN model are also derived.

Lattice quantum codes and exotic topological phases of matter

This thesis addresses whether it is possible to build a robust memory device for quantum information. Many schemes for fault-tolerant quantum information processing have been developed so far, one of which, called topological quantum computation, makes use of degrees of freedom that are inherently insensitive to local errors. However, this scheme is not so reliable against thermal errors. Other fault-tolerant schemes achieve better reliability through active error correction, but incur a substantial overhead cost. Thus, it is of practical importance and theoretical interest to design and assess fault-tolerant schemes that work well at finite temperature without active error correction.

In this thesis, a three-dimensional gapped lattice spin model is found which demonstrates for the first time that a reliable quantum memory at finite temperature is possible, at least to some extent. When quantum information is encoded into a highly entangled ground state of this model and subjected to thermal errors, the errors remain easily correctable for a long time without any active intervention, because a macroscopic energy barrier keeps the errors well localized. As a result, stored quantum information can be retrieved faithfully for a memory time which grows exponentially with the square of the inverse temperature. In contrast, for previously known types of topological quantum storage in three or fewer spatial dimensions the memory time scales exponentially with the inverse temperature, rather than its square.

This spin model exhibits a previously unexpected topological quantum order, in which ground states are locally indistinguishable, pointlike excitations are immobile, and the immobility is not affected by small perturbations of the Hamiltonian. The degeneracy of the ground state, though also insensitive to perturbations, is a complicated number-theoretic function of the system size, and the system bifurcates into multiple noninteracting copies of itself under real-space renormalization group transformations. The degeneracy, the excitations, and the renormalization group flow can be analyzed using a framework that exploits the spin model's symmetry and some associated free resolutions of modules over polynomial algebras.

Quantum error correction with biased noise

Quantum computing offers powerful new techniques for speeding up the calculation of many classically intractable problems. Quantum algorithms can allow for the efficient simulation of physical systems, with applications to basic research, chemical modeling, and drug discovery; other algorithms have important implications for cryptography and internet security.

At the same time, building a quantum computer is a daunting task, requiring the coherent manipulation of systems with many quantum degrees of freedom while preventing environmental noise from interacting too strongly with the system. Fortunately, we know that, under reasonable assumptions, we can use the techniques of quantum error correction and fault tolerance to achieve an arbitrary reduction in the noise level.

In this thesis, we look at how additional information about the structure of noise, or "noise bias," can improve or alter the performance of techniques in quantum error correction and fault tolerance. In Chapter 2, we explore the possibility of designing certain quantum gates to be extremely robust with respect to errors in their operation. This naturally leads to structured noise where certain gates can be implemented in a protected manner, allowing the user to focus their protection on the noisier unprotected operations.

In Chapter 3, we examine how to tailor error-correcting codes and fault-tolerant quantum circuits in the presence of dephasing biased noise, where dephasing errors are far more common than bit-flip errors. By using an appropriately asymmetric code, we demonstrate the ability to improve the amount of error reduction and decrease the physical resources required for error correction.

In Chapter 4, we analyze a variety of protocols for distilling magic states, which enable universal quantum computation, in the presence of faulty Clifford operations. Here again there is a hierarchy of noise levels, with a fixed error rate for faulty gates, and a second rate for errors in the distilled states which decreases as the states are distilled to better quality. The interplay of of these different rates sets limits on the achievable distillation and how quickly states converge to that limit.

Nonperturbative dynamical decoupling with random control

Parametric fluctuations or stochastic signals are introduced into the rectangular pulse sequence to investigate the feasibility of random dynamical decoupling. In a large parameter region, we find that the out-of-order control pulses work as well as the regular pulses for dynamical decoupling and dissipation suppression. Calculations and analysis are enabled by and based on a nonperturbative dynamical decoupling approach allowed by an exact quantum-state-diffusion equation. When the average frequency and duration of the pulse sequence take proper values, the random control sequence is robust, fault-tolerant, and insensitive to pulse strength deviations and interpulse temporal separation in the quasi-periodic sequence. This relaxes the operational requirements placed on quantum control devices to a great deal.

Uma infraestrutura para monitoramento de sistemas cientes do contexto.

Aplicações ubíquas e pervasivas são cientes do contexto dos recursos utilizados no que diz respeito à disponibilidade e qualidade. Esta classe de aplicações pode se beneficiar de mecanismos para descobrir recursos que atendam aos requisitos não-funcionais desejados, e mecanismos para monitorar a qualidade destes recursos. Neste trabalho é proposta uma arquitetura para dois serviços que deveriam ser incluídos na infra-estrutura de suporte a ser utilizada pelas aplicações mencionadas: um Serviço de Contexto, que provê acesso a informações de contexto, e um Serviço de Descoberta, que permite a descoberta dinâmica de recursos, levando em conta restrições de contexto a serem satisfeitas. Estes serviços se apóiam em Agentes de Recursos, que efetivamente monitoram os recursos e sensores. Uma implementação de referência foi desenvolvida, oferecendo os serviços mencionados na forma de Serviços Web e implementando os Agentes de Recursos empregando um padrão de projeto simples. Para avaliar os serviços estes foram utilizados como infra-estrutura para o desenvolvimento de um sistema tolerante a falhas e uma aplicação de assistência domiciliar remota (tele-saúde). O desempenho dos serviços também foi avaliado.

The design algorithm of an associative memory neural network

A design algorithm of an associative memory neural network is proposed. The benefit of this design algorithm is to make the designed associative memory model can implement the hoped situation. On the one hand, the designed model has realized the nonlinear association of infinite value pattern from n dimension space to m dimension space. The result has improved the ones of some old associative memory neural network. On the other hand, the memory samples are in the centers of the fault-tolerant. In average significance the radius of the memory sample fault-tolerant field is maximum.

一种无线传感器网络中事件区域检测的容错算法

特殊环境中的事件区域检测是无线传感器网络的一种重要应用.由于传感器的错误会导致事件区域检测的不准确,所以相关的容错算法成为近年来的研究热点.已有研究工作都仅考虑了事件的空间相关性,通过相邻传感器之间的数据交换实现容错.文中从事件的空间相关性和时间相关性入手,提出了一种以局部检测为主的分布式事件区域检测算法.该算法通过检验传感器本地采样值构成的时间序列与事件随机过程统计特征的符合程度实现容错.算法分析的结果表明,该算法可以减少传感器之间的数据交换,从而有效地利用传感器的能量.模拟实验表明,当有10%的传感器发生错误时,该算法可以检测到93%的事件区域和88%的错误传感器.