NOMS 2016 - 2016 IEEE/IFIP Network Operations and Management Symposium 2016
DOI: 10.1109/noms.2016.7502845
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Automatic fault detection and diagnosis in cellular networks using operations support systems data

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Cited by 37 publications
(27 citation statements)
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“…Information technology is becoming a vital part of human life [1][2][3][4][5]. Increasing data production and the rapid growth of information technology over the past two decades have led to the production of a considerable amount of data in various formats from 1 3 various sources such as RFID tag [6], weblogs, data on scientific researches such as healthcare [7][8][9] and network management [10][11][12][13][14][15]. Several studies have been conducted to model data and partition the query loads on several hosts [14,[16][17][18].…”
Section: Introductionmentioning
confidence: 99%
“…Information technology is becoming a vital part of human life [1][2][3][4][5]. Increasing data production and the rapid growth of information technology over the past two decades have led to the production of a considerable amount of data in various formats from 1 3 various sources such as RFID tag [6], weblogs, data on scientific researches such as healthcare [7][8][9] and network management [10][11][12][13][14][15]. Several studies have been conducted to model data and partition the query loads on several hosts [14,[16][17][18].…”
Section: Introductionmentioning
confidence: 99%
“…Failure detection of network elements is one of the main concerns of mobile network operators. Several papers in literature treat the problem using real network operator data at the BS level, [7] [8] [9] [10] [11] . Such an approach produces very accurate results for the specific networks but the solutions are not easily generalized due to the difficulty in retrieving real cellular networks data.…”
Section: State Of the Artmentioning
confidence: 99%
“…First, the current approach needs to rely on an assumption that all the participants are honest; for example, they will not fake a coughing/sneezing/runny nose event to disturb the network. This assumption may not be true in practice and needs to be relaxed by introducing flaw detection [12]. Second, the current design is purely centralized, and is good for a small-scale application (e.g., a local community, small town/ city), in which a few central servers are enough to handle all the participants.…”
Section: Differentiating Dry and Wet Coughsmentioning
confidence: 99%