Nippon Telegraph and Telephone Corporation

Tatsuaki Kimura

Ken Nishimatsu

Akio Watanabe

Tsuyoshi Toyono

Masahiro Kobayashi

Keisuke Ishibashi

Shigeaki Harada

Yoichi Matsuo

Daisuke Ikegami

Takuto Kimura

Arifumi Matsumoto

Yuka Komai

Takehiro Kawata

Rie Tagyo

A control device of the present invention is for calculating allocation information regarding the allocation of wireless resources of a plurality of base stations to a plurality of user devices. The control device includes: information managing means for storing request data amounts of the user devices; calculating means for calculating an estimated waiting time for each of the user devices by dividing the request data amount by an available bandwidth, and, using the maximum transmission power of the base stations as a constraint, calculating the allocation information regarding the allocation of the wireless resources of the base stations to the user devices so as to minimize the estimated waiting time of the user device having the highest estimated waiting time; and outputting means for outputting the allocation information that was calculated by the calculating means.

Control apparatus, resource allocation method and program

A moving image control apparatus is a control device that realizes bitrate control in a moving image streaming service, which includes a calculation means for calculating a quality target value used for the bitrate control such that a utility function including a predetermined engagement index value is optimized through Bayesian optimization.

Control apparatus, control method, and program

A prediction apparatus includes, a first calculation unit configured to calculate, for traffic in a past time period between a plurality of users and a plurality of services, statistics of the traffic in units of combinations of the users, the services, and time zones, an extraction unit configured to extract, based on the statistics, a plurality of patterns from the traffic, a classification unit configured to classify, by pattern, at least one of each user or each service into groups, a second calculation unit configured to calculate, based on the classification result from the classification unit and the statistics, per-time-zone statistics for each group, and a third calculation unit configured to apply a prediction technique to the per-time-zone statistics for each group, to calculate, for each group, a prediction value of the statistics for a time period later than the past time period, resulting improved accuracy of traffic prediction.

Prediction apparatus, prediction method and program

A failure effects estimating device includes an input unit that inputs a log and a traffic amount obtained from a communication system when an abnormality occurs, an estimating unit that estimates a failure effects amount in the communication system, on the basis of the log and the traffic amount, and an output unit that outputs the failure effects amount estimated by the estimating unit.

Failure influence estimation apparatus, failure influence estimation method and program

Techniques for extracting a set of highly correlated logs without user's prior knowledge of generation rules of logs generated by a machine. A log analysis apparatus includes: a template storage unit configured to store templates for log messages; a template determination unit configured to determine templates corresponding to log messages provided from a to-be-monitored host from the stored templates; an event candidate extraction unit configured to detect templates determined for log messages provided from the same host from the determined templates and extract a sequence of the detected templates as an event candidate; and an event extraction unit configured to extract a sequence of frequently occurring templates as an event from the extracted event candidate.

Log analysis apparatus, log analysis system, log analysis method and computer program

A monitoring device information analyzing device calculates a log variation amount from a log variation amount of a monitoring target device h and a log variation amount of the monitoring target device on another day, by referring to a template information storage unit storing a time at which a log message arises, the log message arising in the past, a template that is associated with an ID of the monitoring target device, and a template ID of the template to calculate the log variation amount of the monitoring target device and to obtain the log variation amount of the monitoring target device on the other day at the same time zone; obtains the log variation amount that is to be a sample; executes verification according to a statistical method, and determines the sample as an advance log, if a test statistic is greater than a predetermined threshold value.

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Musashino, Japan

Tatsuaki Kimura