Riverbed Technology, Inc.

Opnet Technologies, Inc.

Acintyo, Inc.

Anunta Technology Management Services Ltd.

Vinod Jeyachandran

Pradeep Singh

Alain J Cohen

Nitin Gupta

Vanko Vankov

James Mark Shaw

Raghavendra B Uppalli

Arun Pasupathy

Jerrold Stiffler

Pradeep Natarajan

Shobana Narayanaswamy

Nishant Gupta

Ankit Agarwal

Venuprakash Barathan

David Boyd

Ibrahim Utku Moral

Alejandro Talavera-Martinez

Poonam Singh

Sanjiv Dalal

David Manowitz

Kent Hundley

Yonghuan Cao

Ashish Deopura

Varun Gupta

Yu Lin

Aaditya Singh

Kritika Singh

Ananda Mukerji

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

The techniques described herein provides troubleshooting, monitoring, reporting and dynamic adjustments and virtualization to management of application delivery. A system can be completely external to an application delivery data path, or can be highly compatible for integration to the application delivery path. Entities can be billed on a per user, per application, per usage, or any combination of consumption-based billing.

Troubleshooting of cloud-based application delivery

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

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

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 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 will represent the 'ideal' routing tables that should be present in the routers of the actual network. 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 'ideal' can be identified.

First-order effects of hypothesized fault conditions are determined by propagating discrete test packets between select nodes and noting the change of path, if any, taken by the test packet under each condition relative to the fault-free path. Tools are provided to create classes of node pairs of interest, and test packets are created only for select classes. The network is analyzed to identify fault conditions that are likely to impact system performance, and only these fault conditions are simulated. By providing a methodology for selecting classes of node pairs to test, and prioritizing the faults to simulate, a first-order survivability analysis of large networks can be performed efficiently and effectively. The efficiency of this technique is also enhanced by providing test packets that are representative of a wide range of possible source-destination combinations, and by evaluating only the source-destination combinations that may be directly affected by each fault condition.

Traffic independent survivability analysis

A routing validation method and system identifies routers that are likely to be the cause of differences in forwarding tables associated with two versions of a network. Each destination sub-network prefix is processed to identify all the routers that exhibit differences in their forwarding table for this prefix. Each router exhibiting a difference is assessed to determine whether the difference may have been propagated to this router from another router. If the difference could not have been propagated from another router, this router is identified as a potential source of the observed difference. By eliminating routers that could have received the effects of the differences from another router, the task of identifying the root cause of the observed differences is substantially reduced in complexity.

Tracing routing differences

Traffic flows through an administered network from an off-network source and/or to an off-network destination are simulated and analyzed by selecting an ingress and/or egress node within the administered network, the ingress node capable of collecting traffic from an off-network source, and the egress node capable of routing traffic to an off-network destination. Traffic flow is mapped from the source or ingress node through the administered network to the egress node. The traffic flow may be simulated and analyzed. The ingress and/or egress nodes may be selected in a variety of ways.

Growing community of inventors

Rockville, MD, United States of America

Vinod Jeyachandran