Browsing by Author "Hsu, Guo-Huang"

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A local diagnosability measure for multiprocessor systems
(2007-05-01)
Hsu, Guo-Huang
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Tan, Jimmy J. M.
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資訊工程學系
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Department of Computer Science
The problem of fault diagnosis has been discussed widely and the diagnosability of many well-known networks has been explored. Under the PMC model, we introduce a new measure of diagnosability, called local diagnosability, and derive some structures for determining whether a vertex of a system is locally t-diagnosable. For a hypercube, we prove that the local diagnosability of each vertex is equal to its degree under the PMC model. Then, we propose a concept for system diagnosis, called the strong local diagnosability property. A system G(V; E) is said to have a strong local diagnosability property if the local diagnosability of each vertex is equal to its degree. We show that an n-dimensional hypercube Q(n) has this strong property, n >= 3. Next, we study the local diagnosability of a faulty hypercube. We prove that Q(n) keeps this strong property even if it has up to n - 2 faulty edges. Assuming that each vertex of a faulty hypercube Q(n) is incident with at least two fault-free edges, we prove Q(n) keeps this strong property even if it has up to 3(n - 2) - 1 faulty edges. Furthermore, we prove that Q(n) keeps this strong property no matter how many edges are faulty, provided that each vertex of a faulty hypercube Q(n) is incident with at least three fault-free edges. Our bounds on the number of faulty edges are all tight.
Conditional diagnosability of hypercubes under the comparison diagnosis model
(2009-02-01)
Hsu, Guo-Huang
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Chiang, Chieh-Feng
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Shih, Lun-Min
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Hsu, Lih-Hsing
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Tan, Jimmy J. M.
Processor fault diagnosis plays an important role in multiprocessor systems for reliable computing, and the diagnosability of many well-known networks has been explored. Lai et al. proposed a novel measure of diagnosability, called conditional diagnosability, by adding an additional condition that any faulty set cannot contain all the neighbors of any vertex in a system. We make a contribution to the evaluation of diagnosability for hypercube networks under the comparison model and prove that the conditional diagnosability of n-dimensional Hypercube Q(n) is 3(n - 2) + 1 for n >= 5. The conditional diagnosability of Q. is about three times larger than the classical diagnosability of Q(n). (C) 2008 Elsevier B.V. All rights reserved.
Diagnosability of star graphs with missing edges
(2012-04-01)
Chiang, Chieh-Feng
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Hsu, Guo-Huang
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Shih, Lun-Min
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Tan, Jimmy J. M.
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資訊工程學系
In this paper, we study the system diagnosis on an n-dimensional star under the comparison model. Following the concept of local diagnosability [3], the strong local diagnosability property [7] is discussed; this property describes the equivalence of the local diagnosability of a node and its degree. We prove that an n-dimensional star has this property, and it keeps this strong property even if there exist n - 3 missing edges in it. (C) 2011 Elsevier Inc. All rights reserved.
V2PSense: Enabling Cellular-based V2P Collision Warning Service Through Mobile Sensing
(2018-01-01)
Li, Chi-Yu
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Salinas, Giovanni
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Huang, Po-Hao
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Tu, Guan-Hua
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Hsu, Guo-Huang
The C-V2X (Cellular Vehicle-to-Everything) technology is developing in full swing. One of its mainstream services can be the Vehicle-to-Pedestrian (V2P) service. It can protect pedestrians who are mostly vulnerable on the road. In this work, we seek to enable a V2P service that can identify which pedestrians may be nearby a dangerous driving event and then notify them of warning messages. To enable this V2P service, there are two major challenges. First, a low-latency V2P message transport is required for this infrastructure-based service. Second, the pedestrian's smartphone requires an energy-efficient outdoor positioning method instead of power-hungry GPS due to its limited battery life. We thus propose a novel solution, V2PSense, which trades off positioning precision for energy savings while achieving low-latency message transport with LTE high-priority bearers. It does a coarse-grained positioning by leveraging intermittent GPS information and mobile sensing data, which includes step count from the pedometer and cellular signal strength changes. Though the V2PSense's positioning is not as precise as the GPS, it can still ensure that all the pedestrians nearby dangerous spots can be notified. Our results show that it can achieve the average precision ratio 92.6% for estimating where the pedestrian is while saving 20.8% energy, compared with the GPS always-on case.