28662296
A Service Oriented Implementation of Distributed Status Monitoring and Fault Diagnosis Systems
The service-oriented architecture (SOA) can greatly improve the collaboration of devices in a distributed environment. With this architecture, human can be liberated from the burdensome configuration and management of distributed systems, especially when the nodes of the systems are dynamically changed. In this paper, we present a method to implement service-oriented distributed systems in industry. As a case study, we present a service-oriented Status Monitoring and Fault Diagnosis Systems (SMFDS) for large equipment. Our work is based on the UPnP (Universal Plug and Play) technology. Through abstracting the interfaces of devices and providing service middleware in an independent thread or process, the SOA can be easily implemented on an existing system with the least modifications. This characteristic is very useful when upgrading an existing system, for cost and risk consideration.
206594316
An OSEK COM Compliant Communication Model for Smart Vehicle Environment
Smart Vehicle Environment (SVE) is an important application of the idea of smart spaces. This paper presents Smart Vehicle Multi-Agent System (SVMAS) to achieve the goal of SVE and put forwards a commutation model for SVMAS based on SmartOSEK COM [1] to support data exchange. The paper also presents an approach to encapsulate the message to transport by CAN bus, and bring forward a simulator model for SVMAS. Finally the paper gives an example of the communication model which implements a dialogue between two agents and analyzes the performance. The contribution of our work is threefold. First, we adopt Knowledge Query and Manipulation Language (KQML) to describe the communication in vehicles. Second, we develop SmartOSEK COM to implement communication in vehicles. Third, we define the ACLcan protocol to transform the message from SmartOSEK COM to CAN frame.
17996623
Fault tolerant scheduling for fixed-priority tasks with preemption threshold
Fixed-priority with preemption threshold (FPPT) is an important form of real-time scheduling algorithm, which fills the gap between fixed-priority preemptive (FPP) and fixed-priority non-preemptive (FPNP). However, this scheduling scheme together with the requirements of fault tolerance makes the prediction of a real-time system's behaviors more difficult than traditional scheduling scheme. The major contribution of this work is twofold. First, we present an appropriate schedulability analysis, based on response time analysis, for supporting fault-tolerant FPPT scheduling in hard real-time systems. The error-recovery techniques are considered to be used to carry out fault tolerance. Second, we propose the optimal priority assignment algorithm which can be used, together with the schedulability analysis, to improve system fault resilience.
9419059
TLDFS: A Distributed File System based on the Layered Structure
This paper presents a novel distributed file system TLDFS, which consists of two layers. One is the block device layer, which makes the distributed file system manage the consistency of data easily by choosing an appropriate granularity of lock. We implement the distributed interfaces and the new data organization at the block level, which is different from most distributed file systems. The other is the file system layer that consists of three parts: interconnecting module, locking module and distributed file system module. Our prototype system proves the feasibility of the two-layered structure and the experiments show several advantages of TLDFS.
15857389
A novel genetic algorithm based on immunity
A novel algorithm, the immune genetic algorithm (IGA), is proposed based on the theory of immunity in biology which mainly constructs an immune operator accomplished by two steps: 1) a vaccination and 2) an immune selection. IGA proves theoretically convergent with probability 1. Strategies and methods of selecting vaccines and constructing an immune operator are also given. IGA is illustrated to be able to restrain the degenerate phenomenon effectively during the evolutionary process with examples of TSP, and can improve the searching ability and adaptability, greatly increase the convergence rate.
45515067
Evaluation Mode Research on Particle Swarm Optimization Algorithm
16050541
Energy-efficiency bounds for deep submicron VLSI systems in the presence of noise
In this paper, we present an algorithm for computing the bounds on energy-efficiency of digital very large scale integration (VLSI) systems in the presence of deep submicron noise. The proposed algorithm is based on a soft-decision channel model of noisy VLSI systems and employs information-theoretic arguments. Bounds on energy-efficiency are computed for multimodule systems, static gates, dynamic circuits and noise-tolerant dynamic circuits in 0.25-/spl mu/m CMOS technology. As the complexity of the proposed algorithm grows linearly with the size of the system, it is suitable for computing the bounds on energy-efficiency for complex VLSI systems. A key result presented is that noise-tolerant dynamic circuits offer the best trade off between energy-efficiency and noise-immunity when compared to static and domino circuits. Furthermore, employing a 16-bit noise-tolerant Manchester adder in a CDMA receiver, we demonstrate a 31.2%-51.4% energy reduction over conventional systems when operating in the presence of noise. In addition, we compute the lower bounds on energy dissipation for this CDMA receiver and show that these lower bounds are 2.8/spl times/ below the actual energy consumed, and that noise-tolerance reduces the gap between the lower bounds and actual energy dissipation by a factor of 1.9/spl times/.
14748707
Training One-class Support Vector Machines in the Primal Space
In this paper, we proposed a novel Newton-type solver for one-class support vector machines in the primal space directly. Firstly, utilizing reproducing property of kernel and Huber regression function, original constrained quadratic programming is transformed into approximate unconstrained one, which is continuous and twice differentiable. Then, we give a Newton-type training algorithm to solve it. Further analysis shows the computation complexity of our algorithm is identical with theoretical lower bound for solving one-class support vector machines. In the end, experiments on 9 UCI datasets are done to validate the affectivity of proposed algorithm, and when comparing with dual method (LIBSVM),its produces comparative testing accuracy, better training speed, and less support vectors.