Opnet Technologies, Inc.

Riverbed Technology, Inc.

Acintyo, Inc.

Pradeep Singh

Alain J Cohen

Vinod Jeyachandran

Nitin Gupta

Ankit Agarwal

Arun Pasupathy

Venuprakash Barathan

Vanko Vankov

Stefan Znam

David Boyd

Ibrahim Utku Moral

James Mark Shaw

Raghavendra B Uppalli

Nishant Gupta

Paul Janes

Jerrold Stiffler

Karthikeyan Chandrashekar

Pradeep Natarajan

Poonam Singh

Shobana Narayanaswamy

Alejandro Talavera-Martinez

Mahesh Lavannis

Seth Martin

David Manowitz

Marius Popa

Aaditya Singh

Kritika Singh

Nick Bastin

Yu Lin

Ashish Deopura

Yonghuan Cao

Varun Gupta

Raymond Onley

Kent Hundley

Raghavendra Uppalli

James Shaw

David James Boyd

Embodiments of the present invention include a multi-user, multi-device alarm system, which, according to some embodiments, maintains the confirmation status of the alarm creator and participants, any communications between the alarm creator and participants, and user management functionality. Embodiments include systems and methods for configuring and executing different types of alarms, including personal alarms, group alarms, buddy alarms, and team alarms. The same or alternative embodiments may include cascading notifications to participants of an alarm until the alarm creator or one of the participants marks the alarm as done.

Social alarms and reminders

In a network that includes static bandwidth and dynamic bandwidth links, traffic flow at the OSI network layer is simulated at a traffic-flow level at interfaces to fixed bandwidth links, and simulated at a discrete-packet level at interfaces to dynamic bandwidth links. The resultant discrete-packet reception events at the receiving interface(s) of the dynamic bandwidth link are processed to determine the effective bandwidth/throughput of the link, as well as the allocation of this bandwidth among the individual flows through the link. The discrete-packet level receptions are used to reconstruct the parameters of the traffic flow at the network layer of the receiving interface, and this determined traffic flow is simulated accordingly at the next link, depending upon whether the next link is a static or dynamic bandwidth link.

Modeling and simulating flow propagation in dynamic bandwidth systems

The present system includes a system, method and device for inferring connectivity between unconnected network segments. In operation, unconnected network segments are identified. Configuration data related to the unconnected network segments may be examined to facilitate inferring configuration data for an external network connected between the unconnected network segments. The inferred configuration data may be rendered, such as exported or visualized. The inferred configuration data may be related to a communication protocol and/or may be related to network bandwidth. The examined configuration data may be captured directly from one or more of the unconnected network segments and/or may be retrieved from a configuration data file, such as a network configuration model.

Inferring connectivity among network segments in the absence of configuration information

A network analysis system invokes an application specific, or source-destination specific, path discovery process. The application specific path discovery process determines the path(s) used by the application, collects performance data from the nodes along the path, and communicates this performance data to the network analysis system for subsequent performance analysis. The system may also maintain a database of prior network configurations to facilitate the identification of nodes that are off the path that may affect the current performance of the application. The system may also be specifically controlled so as to identify the path between any pair of specified nodes, and to optionally collect performance data associated with the path.

Network path discovery and analysis

All of the transit services that each device is expected to provide are determined and contrasted with the transit configuration of each device. Because the transit configuration of each device may be state-dependent, the service items within each application service are processed in sequential order. Sequences of service items are associated with connection groups, and each of the routes associated with each connection group is determined based on the sequential order of the service items. The configuration of each device along each route is processed to determine the services that will be permitted or denied, based on its current configuration. Each desired transit service item is compared to the transit configuration provided by each device to identify any inconsistencies and/or violations.

Assessing network and device compliance with security policies

A security policy database identifies the intended security policies within a network, a traffic generator provides test traffic that is configured to test each defined security policy, and a simulator simulates the propagation of this traffic on a model of the network. The model of the network includes the configuration data associated with each device, and thus, if devices are properly configured to enforce the intended security policies, the success/failure of the simulated test traffic will conform to the intended permit/deny policy of each connection. Differences between the simulated message propagation and the intended security policies are reported to the user, and diagnostic tools are provided to facilitate identification of the device configuration data that accounts for the observed difference. Additionally, if a network's current security policy is unknown, test traffic is generated to reveal the actual policy in effect, to construct a baseline intended security policy.

Analyzing security compliance within a network

A hybrid approach to populating forwarding tables in a virtual network obtains forwarding data both by simulating routing protocol behavior in the virtual network to build forwarding tables, and by importing operational forwarding data from corresponding physical nodes in a physical network. The use of operational forwarding data improves the fidelity of the simulation by closely conforming forwarding behavior in the simulation to that which occurs in the physical network.

Network simulation and analysis using operational forwarding data

The present system includes a system, method and device for inferring connectivity between network devices across a third party network. Configuration data related to the network devices is examined and configuration data about the network is inferred. The inferred configuration data may be related to a communication protocol, network bandwidth, and the like. A model representing the network is then created to indicate inferred interfaces and connections through the external network between network devices. The representation may be rendered in various forms, such as a display or data exported to another system. Various studies may also be performed using the model, such as traffic, routing, or planning studies.

System and method for modeling a system that comprises networks connected across a third party external network based on incomplete configuration data

Network survivability is quantified in such a way that failure cases can be compared and ranked against each other in terms of the severity of their impact on the various performance measures associated with the network. The degradation in network performance caused by each failure is quantified based on user-defined sets of thresholds of degradation severity for each performance measure. Each failure is simulated using a model of the network, and a degradation vector is determined for each simulated failure. A comparison function is defined to map the degradation vectors into an ordered set, and this ordered set is used to create an ordered list of network failures, in order of the network degradation caused by each failure.

Multi-variate network survivability analysis

A simulator simulates routing system protocols to build routing tables corresponding to a modeled network, and a comparator compares the routing tables in the actual network to these simulator-created routing tables. Because the modeled system represents a fault-free version of the actual system, and assuming that the modeled routing system protocols are representative of the algorithms used in the actual routers, these simulator-produced routing tables can represent steady-state routing tables that should be present in the routers of the actual network at steady state. By querying each router in the actual network for its routing table and comparing each routing table to the corresponding simulator-produced routing table, any differences from the steady state can be identified.

Routing validation

The embodiments relate to modeling wireless communications in a network. In wireless communications, the nodes share one or more wireless communication channels. When a node has data to transmit, it must contend with the other nodes for access to the wireless communication channel. In the embodiments, the model is configured to simulate the throughput effects of contention including delays caused by retransmissions due to interference and collisions, listen-and-backoff, unavailability of time slots, etc. The occurrence of failed/dropped transmissions due to buffer overflows, excessive retransmission attempts, and unintended collisions are modeled as well. In addition, the embodiments may simulate the effect of mobility by the nodes and the effect of the location of the nodes relative to each other.

Methods and system for modeling wireless communications in a network

A contextual and semantic analysis of network entities facilitates a mapping and comparison of the entities between network models. The system includes a plurality of refine handler and match handler pairs that use rules that are specific to the type of network entities being analyzed. The refine handler analyzes the network model to identify the entities for which its rules apply, and the match handler processes these identified entities to establish a pairing between corresponding entities in each model. A sequence of refine-match processes are applied to the network models, typically in accordance with a hierarchy of rules until each entity is identified as a matched, added, or removed entity. A difference handler processes the identified pairings to provide a difference analysis that facilitates a meaningful interpretation of the configuration changes, and a user interface provides an interactive environment to view the differences from different perspectives.

Identifying and analyzing network configuration differences

Simulation models of media access control and physical layer characteristics facilitate the simulation/emulation of a variety of phenomena that affect transmissions via a wireless media. Such phenomena include media access contention delays, packet drops, and retransmissions that are generally dependent upon changes in transmitter/receiver locations. Each wireless environment is characterized by a model of the communication channel that characterizes transmission effects based on the number of competing transmitters in the environment, which is dynamically determined based on the location of each node in the environment. Additionally, the location of nodes is used to simulate the effects of 'hidden nodes', nodes that are unknown to a transmitting node but can interfere with the reception of transmissions at a receiving node. Each device/node model in the wireless environment preferably accesses the same model of the communication channel, thereby minimizing the amount of detail required at each device model.

Wireless MAC and link-layer simulation modeling

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Arlington, VA, United States of America

Pradeep Singh