17966983
Flexible Workflow Driven Job Shop Manufacturing Execution and Automation Based on Multi Agent System
Manufacturing automation with adoptability to the changing environment is a competitive advantage for shop floors. This paper presents a flexible workflow enacted job shop manufacturing execution and automation system. The manufacturing process sequence of each part is modeled as an abstract workflow and each manufacturing job resulting in a batch of the part items is recognized as corresponding workflow instance. The production schedule is generated to establish executable workflow instances to be enacted by the workflow engine and executed by the resources in the shop floor. Agent technology is applied to construct the system to take the advantage of distributed system architecture, reactivity, adaptability and cooperation. The proposed system can help to achieve production efficiency without huge investment on industrial automation system. The system architecture and implementation methods are discussed with demonstration and the performance of manufacturing shop floor is enhanced after the application.
14422830
Compiler-guided register reliability improvement against soft errors
With the scaling of technology, transient errors caused by external particle strikes have become a critical challenge for microprocessor design. As embedded processors are widely used in reliability-sensitive environments, it becomes increasingly important to develop cost-effective techniques to improve the processor reliability against soft errors. This paper focuses on studying the register file immunity against soft errors since modern processors typically employ a large number of registers, which are accessed very frequently. As a result, soft errors occurred in registers can easily propagate to functional units or the memory system, leading to silent data error (SDC) or system crash.To develop cost-effective techniques to fight soft errors for embedded processors, the first step is to understand the register file susceptibility to soft errors and its impact on the system reliability accurately. Toward this goal, this paper proposes the concept of register vulnerability factor (RVF) to characterize the probability that register transient errors can escape the register file and thus potentially impact the system reliability. Built upon the RVF concept, we then propose two cost-effective compiler-guided techniques to improve the register file reliability by lowering the RVF value. Our experiments indicate that on average, the RVF can be reduced to 9.1% and 9.5% by the hyperblock-based instruction re-scheduling and the reliability-oriented register assignment respectively, which can potentially lower the reliability cost significantly while protecting register files against transient errors.
43025995
Processing Probabilistic Range Query over Imprecise Data Based on Quality of Result
Sensors are employed in many applications to monitor entities such as environment temperature or illumination. Because of limited resources (e.g., battery power and wireless bandwidth), it is impractical for the database to track continuous changing readings from sensors at all times. Consequently, database may produce incorrect query results based on recorded data. However, if the error between the recorded value and the actual value is bounded, probabilistic approach can be applied to process queries over the imprecise data in database. The paper proposes a quality of result based probabilistic range query processing method. Two measures are defined to evaluate the quality of result. A probability model is proposed to estimate the quality of returned results. Based on the model, an algorithm is developed to choose the probability threshold according to user’s requirement on the quality of result.
17633305
The Impact of Cache Organization in Optimizing Microprocessor Power Consumption
In the recent years, power consumption has become increasingly an important design concern as silicon area and performance in modern computer systems design. Several factors have contributed to this trend. Perhaps the most visible have been the remarkable success and growth of Personal Digital Assistants (PDA’s), Cellular phones and pagers, etc .This work is an attempt to explore the impact of feature size shrinkage and cache configuration on optimizing power consumption in modern processors. The work studies two commercially known RISC microprocessors. The StrongARM and the Alpha-21064 microprocessors. The latter is the ancestor of the former and is therefore used here as the baseline in our analysis. Our analysis has illustrated quantitatively great power saving when technology is downsized and cache is well organized
26485902
Identification of Crosscutting Requirements Based on Feature Dependency Analysis
Identification of crosscutting concerns at the requirements level is important for the modularization and evolution of requirements, and has attracted many research interests. This paper proposes a feature-oriented approach to the identification of crosscutting requirements based on feature dependency analysis. In this approach, features are used as basic elements to organize the requirements space, and two kinds of dynamic dependencies (i.e. interactions and weavings) between features are analyzed to find out the candidate crosscutting requirements and their influence on other requirements. A case study is also used to illustrate the application of this approach
9354212
High-Performance Job-Shop Scheduling With A Time-Delay TD-lambda Network
Job-shop scheduling is an important task for manufacturing industries. We are interested in the particular task of scheduling payload processing for NASA's space shuttle program. This paper summarizes our previous work on formulating this task for solution by the reinforcement learning algorithm T D(). A shortcoming of this previous work was its reliance on hand-engineered input features. This paper shows how to extend the time-delay neural network (TDNN) architecture to apply it to irregular-length schedules. Experimental tests show that this TDNN-TD() network can match the performance of our previous hand-engineered system. The tests also show that both neural network approaches signiicantly out-perform the best previous (non-learning) solution to this problem in terms of the quality of the resulting schedules and the number of search steps required to construct them.
3005507
Iterative state-space reduction for flexible computation
Abstract Flexible computation is a general framework for decision making under limited computational resources. It enables an agent to allocate limited computational resources to maximize its overall performance or utility. In this paper, we present a strategy for flexible computation, which we call iterative state-space reduction . The main ideas are to reduce a problem space that is difficult to search to one that is relatively easy to explore, to use the optimal solution from the reduced space as an approximate solution to the original problem, and to iteratively apply multiple reductions to progressively find better solutions. The basic operation for state-space reduction is heuristic node pruning, which excludes the nodes that do not seem to lead to high-quality solutions from further examination. Iterative state-space reduction can be combined with a state-space search, such as best-first search or depth-first branch-and-bound (DFBnB). The resulting algorithm can run as an anytime algorithm, which provides a tradeoff between solution quality and computation. Based on an analytical modal, we analyze the probability that one iteration of the iterative process finds a solution. Furthermore, by combining it within DFBnB we apply iterative state-space reduction to three combinatorial problems, the maximum Boolean satisfiability, the symmetric TSP and asymmetric TSP. Our experimental results show that iterative state-space reduction is effective and efficient, making DFBnB find better solutions with less computation.
16936043
Complete Anytime Beam Search
Beam search executes a state-space search, but may abandon nonpromising search avenues in order to reduce complexity. Although it has existed for more than two decades and has been applied to many real-world problems, beam search still suffers from the drawback of possible termination with no solution or a solution of unsatisfactory quality. In this paper, we first propose a domain-independent heuristic for node pruning, and a method to reduce the possibility that beam search will fail. We then develop a complete beam search algorithm. The new algorithm can not only find an optimal solution, but can also reach better solutions sooner than its underlying search method. We apply complete beam search to the maximum boolean satisfiability and the symmetric and asymmetric Traveling Salesman Problems. Our experimental results show that the domain-independent pruning heuristic is effective and the new algorithm significantly improves the performance of its underlying search algorithm.
27074889
On pilot pattern design for PSAM-OFDM system
Pilot symbol assisted modulation (PSAM) of subcarriers is an attractive scheme for high data-rate OFDM transmission systems and has been widely used in broadcasting systems like DVB-T. In this paper, a new and simple pilot pattern for PSAM-OFDM system operated in the mobile communication environment is proposed and analyzed in terms of its bit error rate. Analytical and simulation results show that the proposed clustered pilot pattern for OFDM channel estimation gives a better performance than the conventional equally spaced pilot pattern in fading channel, yet without sacrificing the bandwidth efficiency.
43120880
Principle component analysis and its variants for biometrics
Principle component analysis (PCA) has been widely used for analyzing the statistics of data. While applied to biometrics as a classification scheme, PCA faces certain challenges. We present a number of modifications to PCA in order to meet these challenges. Using face recognition as an example, we show how eigenflow, PCA applied to optimal flow, enables us to measure the difference between two images while allowing expression changes and registration error. We show how PCA can be updated to model time-varying statistics. We also show that PCA can be used to model the surface reflectance of human faces and reduce illumination variation that defeats most existing face recognition algorithms. Finally, we present distinguishing component analysis (DCA) and apply it to multimodal biometric authentication.
10336575
Discovering accurate interclass test dependences
Knowledge of interclass test dependences is crucial to decide class test order, facilitating the design of an efficient integration test plan. In order to discover precise interclass test dependences, we proposed a semantic-based definition and designed a safe approximation algorithm to calculate the dependence according to the given definition. The algorithm propagates semantic dependences at method-level granularity and is parameterized by the precision of the corresponding program analysis. We have experimented with nine benchmarks and showed that the algorithm is rather accurate in that it discovers dependence cycles precisely in 6 out of 9 benchmarks (as evaluated by human inspection). The algorithm uncovers additional opportunities for concurrent testing in each of the benchmarks, with an on average expected 52.5% time savings over the ORD-based definition.