Faster than at-speed testing provides an effective way to detect small delay defects (SDDs). It requires test patterns to be delicately classified into groups according to the delay of sensitized paths. Each group of ...
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Faster than at-speed testing provides an effective way to detect small delay defects (SDDs). It requires test patterns to be delicately classified into groups according to the delay of sensitized paths. Each group of patterns is applied at certain frequency. In this paper, we propose to generate tests for faster than at-speed testing using path delay fault (PDF) model and single path sensitization criterion. An effective path selection and grouping method is introduced, which could quickly and accurately identify paths whose delay falls into a given delay span. Several techniques are used to improve the efficiency of the testable path selection procedure. Experimental results on ISCAS'89 benchmark circuits show that the proposed method could achieve high transition fault coverage and high test quality of SDDs with low CPU time.
Hybrid sensor network technology is a key component of future ITS applications. In this paper, we propose a hybrid architecture that combined VANETs and roadside WSNs for intelligent navigation. Different from traditi...
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Hybrid sensor network technology is a key component of future ITS applications. In this paper, we propose a hybrid architecture that combined VANETs and roadside WSNs for intelligent navigation. Different from traditional ITS application, Sensors in WSNs and VANETs are used to perceive and exchange roadside and vehicular information to support the intelligent navigating decision process. We firstly give the system and protocol architecture, and then we discuss the scenarios and use cases of our system in intelligent navigation. After that, we describe the software and hardware implementation of our prototype, conduct a simulation on the discussed scenarios, and present a detailed data communication experimental result to prove the feasibility of our prototype.
In this paper, we focus on generation of a universal path candidate set V that contains testable long paths for delay testing. Some strategies are presented to speed up the depth first search procedure of U generation...
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In this paper, we focus on generation of a universal path candidate set V that contains testable long paths for delay testing. Some strategies are presented to speed up the depth first search procedure of U generation, targeting the reduction of sensitization criteria checking times. Experimental results illustrate that our approach achieves an 8X speedup on average in comparison with the traditional depth first search approach.
As a primary method for functional verification of microprocessors, simulation-based verification has received extensive studies over the last decade. Most investigations have been dedicated to the generation of stimu...
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As a primary method for functional verification of microprocessors, simulation-based verification has received extensive studies over the last decade. Most investigations have been dedicated to the generation of stimuli (test cases), while relatively few has focused on explicitly reducing the redundant stimuli among the generated ones. In this paper, we propose an on-the-fly approach for reducing the stimuli redundancy based on machine learning techniques, which can learn from new knowledge in every cycle of simulation-based verification. Our approach can be easily embedded in traditional framework of simulation-based functional verification, and the experiments on an industrial microprocessor have validated that the approach is effective and efficient.
In this paper, we proposed a novel network coding method called local-directed network coding to improve the throughput of the vehicular ad-hoc network. Different from other vehicular network coding methods, we consid...
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In this paper, we proposed a novel network coding method called local-directed network coding to improve the throughput of the vehicular ad-hoc network. Different from other vehicular network coding methods, we consider the direction of packet transmission. In detail, the intermediate node selects one main packet and some sub-packets from forwards and backwards sending queues, and then encodes these packets into one packet to broadcast. Simulation results show that our approach can efficiently improve the throughput of application layer in vehicular networks.
Statistical background subtraction has proved to be a robust and effective approach for segmenting and extracting objects without any prior information of the foreground objects. This paper presents two contributions ...
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Statistical background subtraction has proved to be a robust and effective approach for segmenting and extracting objects without any prior information of the foreground objects. This paper presents two contributions on this topic. The first contribution of this paper proposes a novel approach which introduces the motion mask into the Gaussian Mixture Models to reduce the errors of classical GMMs, which always classifies the moving objects as background incorrectly, and affects the accuracy of the steps followed by, when the objects are still in long periods. The second contribution regards the connected component labeling based on the contour tracking algorithm. Experimental results validate the effectiveness of the proposed approach.
We attack the sensor network deployment problem. We define the deployment problem as the problem of deciding how many sensor nodes should be deployed in the sensor field over how many phases during its lifetime. We ta...
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We attack the sensor network deployment problem. We define the deployment problem as the problem of deciding how many sensor nodes should be deployed in the sensor field over how many phases during its lifetime. We target the optimal deployment strategy that meets user-defined availability requirement with minimum total cost taking into consideration node failures and changing field trip to sensor node cost ratio. We model WSN availability and total cost as functions of the deployment plan, then, we formalize the deployment problem as a 2D optimization problem. Our modeling enables us to explore cost-benefit tradeoffs, we believe, this is a solid step toward bringing cost as an explicit dimension in the design space of WSN protocols. We compare the performance of the optimized solution (denoted as pro-active) to more ad-hoc solutions: on-demand and at-front. The former strategy schedules future deployments only on demand. The latter strategy deploys all nodes at front with no later field trips. Using extensive simulations, we show that proactive outperforms at-front and on-demand in terms of total cost per availability unit in all application scenarios. For example, using pro-active costs $7 compared to $40 and $280 per total uptime in case of on-demand and at-front, respectively.
We study the capacity scaling laws for the cognitive network that consists of the primary hybrid network (PhN) and secondary ad hoc network (SaN). PhN is further comprised of an ad hoc network and a base station based...
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Critical path selection is very important in delay testing. Critical paths found by conventional static timing analysis (STA) tools are inadequate to represent the real timing of the circuit, since neither the testabi...
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In this paper a new blind watermarking algorithm based on DCT (discrete cosine transform) and DWT (discrete wavelet transform) was proposed. In order to enhance the security of watermarking, Arnold transform is carrie...
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