N. S. V. Rao. Computational complexity issues in operative diagnosis of graph-based systems. IEEE Transactions on Computers, vol. 42, pp. 447--457, April 1993.  Home/Search   Document Not in Database   Summary   Related Articles   Check

....by a unique set of sensors; the location detection analog of this would be to designate special sensor nodes in such a way that every node in the graph is within communication range of a unique set of sensors. The problem of nding an optimal identifying code for an arbitrary graph is NP complete [5]. Instead, we propose a novel greedy algorithm, called ID CODE, that produces irreducible identifying codes. An identifying code is irreducible if no codeword can be removed while still keeping every position uniquely identi able. Our numerical results show that the solution produced by our ....

....in [4] as a means of uniquely identifying faulty processors in a multiprocessor system. These codes, which are described in detail in Section 4, have enjoyed much attention in the coding theory literature. In general, nding an optimal identifying code is known to be an NP complete problem [5]. The available constructions in the literature have so far been restricted to regular graphs such as hypercubes, meshes, and trees [17] The works in [18, 19] suggest the use of these known identifying codes for surveillance purposes in an outdoor setting, but they require a regular, mesh ....

[Article contains additional citation context not shown here]

Nageswara S. V. Rao, \Computational complexity issues in operative diagnosis of Graph-Based systems," IEEE Transactions on Computers, vol. 42, no. 4, pp. 447-457, April 1993.

....a unique set of sensors; the location detection analog of this would be to designate special sensor nodes in such a way that every node in the graph is within communication range of a unique set of sensors. The problem of finding an optimal identifying code for an arbitrary graph is NP complete [5]. Instead, we propose a novel greedy algorithm, called ID CODE, that produces irreducible identifying codes. An identifying code is irreducible if no codeword can be removed while still keeping every position uniquely identifiable. Our numerical results show that the solution produced by our ....

....in [4] as a means of uniquely identifying faulty processors in a multiprocessor system. These codes, which are described in detail in Section IV, have enjoyed much attention in the coding theory literature. In general, finding an optimal identifying code is known to be an NP complete problem [5]. The available constructions in the literature have so far been restricted to regular graphs such as hypercubes, meshes, and trees [17] The works in [18, 19] suggest the use of these known identifying codes for surveillance purposes in an outdoor setting, but they require a regular, mesh ....

[Article contains additional citation context not shown here]

Nageswara S. V. Rao, "Computational complexity issues in operative diagnosis of Graph-Based systems," IEEE Transactions on Computers, vol. 42, no. 4, pp. 447--457, April 1993.

....can be expressed as follows: SDomain (5) V. F AULT LOCATION ALGORITHM (FLA) Time to locate the failure(s) is critical, and the FLA must locate failures as quickly as possible. Unfortunately, the multiple fault location problem has been shown to be NP complete already in the ideal scenario [1]. Nevertheless, the computation that has to be carried out when a new alarm reaches the manager can be kept short despite the potentially large size of the network, if we follow Rao s approach to precompute, as much as possible, the functions that can be executed independently of the received ....

....FLA. A more detailed study can be found in [17] Time complexity is critical for a fast diagnosis phase, whereas space complexity is critical if we have memory space limitations. Let us begin with time complexity. As mentioned earlier, the problem of identifying multiple failures is NP complete [1]. However, the computationally intensive part is carried out offline, in the precomputation phase (PCP) where all the codewords, including those accounting for nonideal scenarios, are determined. As a result, the computation time of the on line diagnosis part is kept minimal, proportional to the ....

N. S. V. Rao, "Computational complexity issues in operative diagnosis of graph-based systems," IEEE Trans. Computers, vol. 42, pp. 447--457, Apr. 1993.

....there are two or more simultaneous failures, the number of alarms considerably increases, the alarms arrive intermingled to the management system and the problem of locating the failures becomes even more difficult. The problem of locating multiple failures has been shown to be NP hard by Rao [Rao93] The location of the failure(s) must be fast and efficient (by efficient, we mean that the set of faulty candidates must be as small as possible) so that the faulty element(s) is (are) clearly identified before start digging or sending a technician to repair it(them) Such a task is expensive, ....

N. S. V. Rao. Computational Complexity Issues in Operative Diagnosis of graph-based Systems. IEEE Transactions on Computers, 42(4):447--457, April 1993.

....This lack of understanding is not altogether surprising because the sensor deployment combines the hitherto unexplained interaction of target location with optimal placement of sensors. The sensor placement problem for target location is closely related to the alarm placement problem described in [6]. The latter refers to the problem of placing alarms on the nodes of a graph G such that a single faults in the system (corresponding to a single faulty node in G) can be diagnosed. The alarms are therefore analogous to sensors in a sensor field. It was shown in [6] that the alarm placement ....

....placement problem described in [6] The latter refers to the problem of placing alarms on the nodes of a graph G such that a single faults in the system (corresponding to a single faulty node in G) can be diagnosed. The alarms are therefore analogous to sensors in a sensor field. It was shown in [6] that the alarm placement problem is NP complete for arbitrary graphs. However, we show that for restricted topologies, e.g. a set of grid points in a sensor field, a coding theory framework can be used to efficiently determine sensor placement. The sensor locations correspond to codewords of an ....

N. S. V. Rao. Computational complexity issues in operative diagnosis of graph-based systems. IEEE Transactions on Computers, vol. 42, pp. 447--457, April 1993.

....and fault tolerance [8] There are, however, a number of differences in what the graphs really represent in the various studies. In this paper, we are interested in operative diagnosis of faults arising in a wide variety of systems such as chemical plants, aircrafts, and medical diagnosis [6, 11, 12]. In these applications, the system under consideration consists of a number of components, some of which may become faulty. The fault at a component will result in the faulty or abnormal behavior of not only that component but also a few others. This manifestation is called fault propagation. ....

N. S. V. Rao, "Computational complexity issues in operative diagnosis of graph-based systems," IEEE Trans. Comput., vol. 42, no. 4, pp. 447457, Apr. 1993.

....f1,3,4,5g, f2,3,4,5g and f1,2,3,4,5g are all solutions for the alarm placement problem. The first three are also optimal solutions for the minimum alarm set problem. Several practical systems for which the graph model under consideration is applicable can be seen in [10,11,18 20] In [18] and [19], Rao investigated several fault diagnosis algorithms and their complexities. He also presented NP completeness results for the alarm placement and multiple fault diagnosis problems. The intractability result for the alarm placement problem in this paper is based on a reduction from the vertex ....

....algorithms and their complexities. He also presented NP completeness results for the alarm placement and multiple fault diagnosis problems. The intractability result for the alarm placement problem in this paper is based on a reduction from the vertex cover problem different from that in [19]. Our reduction allows proof of intractability of the problem even for very simple directed graphs. In Sections 2 and 3, we present some formal definitions and preliminary results. In Section 4, we show that the alarm placement problem is intractable, i.e. it is NP complete, even when restricted ....

N. S. V. Rao, Computational complexity issues in operative diagnosis of graphbased systems, IEEE Trans. Comput. 42 (1993) 447--457.

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N. S. V. Rao. Computational complexity issues in operative diagnosis of graph-based systems. IEEE Transactions on Computers, vol. 42, pp. 447--457, April 1993.

No context found.

N.S.V. Rao, "Computational Complexity Issues in Operative Diagnosis of Graph-Based Systems," IEEE Trans. Computers, vol. 42, no. 4, pp. 447-457, Apr. 1993.

No context found.

N. S. V. Rao. Computational complexity issues in operative diagnosis of graph-based systems. IEEE Transactions on Computers, vol. 42, pp. 447-457, April 1993.

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