Abstract: A method, computer program product, and system identifying a probability of a medical condition in a patient. The method includes a processor obtaining data set(s) related to a patient population diagnosed with a medical condition and based on a frequency of features in the data set(s), identifying common features. The processor generates pattern(s) including a portion of the common features to generate a machine learning algorithm(s). The processor compiles a training set of data to use to tune the machine learning algorithm(s). The processor dynamically adjusts common features in the pattern(s) such that the machine learning algorithm(s) can distinguish patient data indicating the medical condition from patient data not indicating the medical condition. The processor applies the machine learning algorithm(s) to data related to the undiagnosed patient, to determine the probability.

Abstract: A method, computer program product, and system identifying a probability of a medical condition in a patient. The method includes a processor obtaining data set(s) related to a patient population diagnosed with a medical condition and based on a frequency of features in the data set(s), identifying common features. The processor generates pattern(s) including a portion of the common features to generate a machine learning algorithm(s). The processor compiles a training set of data to use to tune the machine learning algorithm(s). The processor dynamically adjusts common features in the pattern(s) such that the machine learning algorithm(s) can distinguish patient data indicating the medical condition from patient data not indicating the medical condition. The processor applies the machine learning algorithm(s) to data related to the undiagnosed patient, to determine the probability.

Abstract: An apparatus and method predict and detect network attacks by using a diverse set of indicators to measure aspects of the traffic and by encoding traffic characteristics using these indicators of potential attacks or anomalous behavior. The set of indicators is analyzed by supervised learning to automatically learn a decision rule which examines the temporal patterns in the coded values of the set of indicators to accurately detect and predict network attacks. The rules automatically evolve in response to new attacks as the system updates its rules periodically by analyzing new data and feedback signals about attacks associated with that data. To assist human operators, the system also provides human interpretable explanations of detection and prediction rules by pointing to indicators whose values contribute to a decision that there is an existing network attack or an imminent network attack. When such indictors are detected, an operator can take remediation actions.

Abstract: A communication node operable to estimate faults in a mobile ad hoc network and method of performing the same. In one embodiment, the communication node includes a processor and memory including computer program code configured to, with the processor, cause the communication node to monitor a set of observable parameters at the communication node, produce a fault estimate at the communication node from the set of observable parameters, and provide the fault estimate to a global fault detector at another communication node.

Abstract: A method for active learning using privileged information is disclosed. A processing device receives a set of labeled examples and a set of unlabeled examples. For each unlabeled example in the set of unlabeled examples, the processing device determines whether to query at least one of an oracle to obtain a label for the unlabeled example or a teacher to obtain privileged information about the unlabeled example. The processing device outputs a decision rule based on minimizing a number of queries to the oracle for a label and the teacher for privileged information. Minimizing the number of queries to the teacher and the oracle is based on a cost of querying the teacher or the oracle.

Abstract: A communication node operable to estimate faults in a mobile ad hoc network and method of performing the same. In one embodiment, the communication node includes a processor and memory including computer program code configured to, with the processor, cause the communication node to monitor a set of observable parameters at the communication node, produce a fault estimate at the communication node from the set of observable parameters, and provide the fault estimate to a global fault detector at another communication node.

Abstract: A solution to the problem of automated policy generation for mobile ad hoc networks includes an optimization-based, utility-driven approach aimed at generating optimal policies with respect to the given network objectives. The combination of optimization heuristics and network simulation is used to solve the problem. Specifically, the problem of automated generation of network management policies based on available network plans and related information is solved by converting the policy generation into the following optimization problem: given network information and objectives as input, generate optimal policies as output. The optimization process is guided by a utility function based on performance evaluation criteria reflecting the network objectives.

Abstract: An apparatus and method predict and detect network attacks by using a diverse set of indicators to measure aspects of the traffic and by encoding traffic characteristics using these indicators of potential attacks or anomalous behavior. The set of indicators is analyzed by supervised learning to automatically learn a decision rule which examines the temporal patterns in the coded values of the set of indicators to accurately detect and predict network attacks. The rules automatically evolve in response to new attacks as the system updates its rules periodically by analyzing new data and feedback signals about attacks associated with that data. To assist human operators, the system also provides human interpretable explanations of detection and prediction rules by pointing to indicators whose values contribute to a decision that there is an existing network attack or an imminent network attack. When such indictors are detected, an operator can take remediation actions.

Abstract: Network management for providing and managing Quality of Service (QoS) in converged networks, and particularly management of bursty, short-lived data loads, in an opaque network where knowledge of or control over network elements is not required. Preferential treatment is provided to some subset of the network users that require better QoS assurances from the underlying network by applying probabilistic admission control decisions in conjunction with estimated network state provides improved performance for high priority data with bursty data loads.

Abstract: Network management for providing and managing Quality of Service (QoS) in converged networks, and particularly management of bursty, short-lived data loads, in an opaque network where knowledge of or control over network elements is not required. Preferential treatment is provided to some subset of the network users that require better QoS assurances from the underlying network by applying probabilistic admission control decisions in conjunction with estimated network state provides improved performance for high priority data with bursty data loads.

Abstract: A solution to the problem of automated policy generation for mobile ad hoc networks includes an optimization-based, utility-driven approach aimed at generating optimal policies with respect to the given network objectives. The combination of optimization heuristics and network simulation is used to solve the problem. Specifically, the problem of automated generation of network management policies based on available network plans and related information is solved by converting the policy generation into the following optimization problem: given network information and objectives as input, generate optimal policies as output. The optimization process is guided by a utility function based on performance evaluation criteria reflecting the network objectives.

Abstract: Loads for a wireless network having a plurality of end nodes are predicted by constructing a computer data set of end-to-end pairs of the end nodes included in the network using a computer model of the network; constructing a computerized set of observables from social information about users of the network; developing a computerized learned model of predicted traffic using at least the data set and the observables; and using the computerized learned model to predict future end-to-end network traffic.

Abstract: Systems and methods for managing network congestion through detecting the closeness to network congestion. The network includes a plurality of network nodes, where each node has at least one neighboring node and each node has a buffer for a queue of packets from other nodes. The system measures queue length at a node and the node's neighboring nodes, processes the measured queue lengths to obtain patterns of fluctuations for the measured queue length. The system determines if one or more of the measured nodes are in a transition-onset status toward a phase transition point based on the obtained patterns of fluctuation and generates congestion control signals based on the determination to route network traffic away. The phase transition point corresponds to a change from a non-congestive phase of the measured nodes to a congestive phase of the measured nodes.

Abstract: A solution to the problem of automated policy generation for mobile ad hoc networks includes an optimization-based, utility-driven approach aimed at generating optimal policies with respect to the given network objectives. The combination of optimization heuristics and network simulation is used to solve the problem. Specifically, the problem of automated generation of network management policies based on available network plans and related information is solved by converting the policy generation into the following optimization problem: given network information and objectives as input, generate optimal policies as output. The optimization process is guided by a utility function based on performance evaluation criteria reflecting the network objectives.

Abstract: A method and apparatus for controlling ingress to a communications network to control quality of service is described. A request to admit a new communications flow is received. A polynomial and its coefficients representing a state of the network is determined and applied to the network state plus the new communications flow to determine whether admission of the new communications flow would cause the network to operate in a stable or unstable state. In response to determining that the network would operate in the unstable state, a communications flow for the ingress device is downgraded in its quality of service. By another approach, it is determined whether the new communications flow exceeds an allocated quota of bandwidth. Admission or rejection of the communications flow can be determined.

Abstract: A solution to the problem of automated policy generation for mobile ad hoc networks includes an optimization-based, utility-driven approach aimed at generating optimal policies with respect to the given network objectives. The combination of optimization heuristics and network simulation is used to solve the problem. Specifically, the problem of automated generation of network management policies based on available network plans and related information is solved by converting the policy generation into the following optimization problem: given network information and objectives as input, generate optimal policies as output. The optimization process is guided by a utility function based on performance evaluation criteria reflecting the network objectives.