Cisco Technology, Inc.

Carlos M Pignataro

Nagendra Kumar Nainar

Rajiv Asati

Joseph Michael Clarke

James Neil Guichard

David Delano Ward

Gonzalo A Salgueiro

David John Zacks

Paul M Quinn

Jerome Henry

Frank Brockners

Shwetha Subray Bhandari

K Tirumaleswar Reddy

Pascal Thubert

Clarence Filsfils

Robert E Barton

Prashanth Patil

Jaganbabu Rajamanickam

Eric Albin Voit

Thomas Szigeti

Domenico Ficara

Alon Shlomo Bernstein

Shree N Murthy

Zafar Ali

Bart A Brinckman

Benoit Claise

Syed Kamran Raza

Stefano Benedetto Previdi

Robert Edgar Barton

Stewart Frederick Bryant

George Swallow

Hugo Latapie

Enzo Fenoglio

Akram Ismail Sheriff

Rakesh Gandhi

Ahmed Refaat Bashandy

Rajesh Kumar

David C White, Jr

Ijsbrand Wijnands

Timothy Peter Stammers

Keyur Patel

Antonio Nucci

Muthurajah Sivabalan

Om Prakash Suthar

Luca Muscariello

Jim Guichard

Reshad Rahman

Javed Asghar

Srinath Gundavelli

Vimal Srivastava

Walter Theodore Hulick, Jr

John Matthew Swartz

Vinay Saini

Surendra M Kumar

Nitesh Trikha

Ram Mohan Ravindranath

Naiming Shen

Shankar Ramanathan

Michel Khouderchah

Rajesh Indira Viswambharan

Mark Grayson

Charles Calvin Byers

Kent Kinchu Leung

Sami Boutros

Daniel George Wing

Kyle Andrew Donald Mestery

Aeneas Sean Dodd-Noble

Alvaro E Retana

Jay Kemper Johnston

Mankamana Prasad Mishra

Magnus Mortensen

Ian James Wells

Giovanna Carofiglio

Cedell Adam Alexander, Jr

Aamer Saeed Akhter

Plamen Nedeltchev

Jianxin Wang

Arghya T Mukherjee

Chandrasekar Krishnamurthy

Matthew Aaron Silverman

John T Chapman

Vivek Agarwal

Nitin Kumar

Louis Gwyn Samuel

Malcolm Muir Smith

Yi Yang

Ardalan Alizadeh

Prakash C Jain

John Michael Lake

Milind R Naphade

Tarek Saad

Peter Psenak

Rex Emmanuel Fernando

Amine Choukir

Salvatore Valenza

Pradosh Mohapatra

Ammar Rayes

L Alexander Clemm

Darren Russell Dukes

Enke Chen

Devices, systems, methods, and processes for dynamically reducing the size of a video transmission are described herein. An energy-saving video transmission device can include a controller, a memory, a communication port coupled with at least a second device, and a virtual meeting logic configured to establish a virtual meeting with a video transmission. The video transmission is transmitted to at least the second device. The virtual meeting logic can determine a virtual meeting configuration and collect sustainability attributes data. Based on the collected data, an energy-saving video transmission rate can be selected. Often, this can indicate how often to capture and transmit keyframes of the video transmission instead of the entire video transmission. Finally, based on the energy-saving video transmission rate, a reduced size video transmission can be transmitted over a network. Subsequently, additional events can be detected that allow for the dynamic adjustment of the energy-saving video transmission rate.

Dynamic energy-saving video transmissions for sustainable collaboration

A system and methods by which a reconfigurable intelligent surface device is dynamically configured to control the reflection of transmissions made between an access point and one or more client devices so as to protect the transmissions from being properly received by an unauthorized device. These methods may be used to maintain data confidentiality, particularly for remote workers. The positions of the access point and client devices are used to configure the reconfigurable intelligent surface device to reflect the transmissions inward and avoid/minimize leakage outside a physical space.

Traffic and user aware physical layer shielding for secure teleworker using reconfigurable intelligent surface device

Techniques to add environmental-impact and energy sustainability criteria and support to service function chains (SFCs). These techniques enabling steering of network traffic that carries energy sustainability related metadata within in an SFC based on energy sustainability or 'green criteria.' This allows for achieving, for example, so-called “green Operations, Administration and Maintenance (OAM)”, whether realized with Network Service Header (NSH), Segment Routing, Multi-protocol Label Switching (MPLS), etc. In other words, these techniques enhance service functions (SFs) and SFCs to allow for finding an energy sustainable or green path in an SFC, and to allow for conveying environmental information as in-line metadata.

Sustainability-based service function chain branching

A network of devices can be stabilized by administering an energy-aware topology that corresponds to a desired state derived in part from one or more sustainability metrics. Devices suitable for stabilization can include a processor, a memory, a plurality of elements, a communication port coupled with one or more neighboring devices, and an energy-aware topology logic. The energy-aware topology logic can monitor incoming traffic from one or more neighboring devices, receive current state data associated with the plurality of elements, and receive update data from the one or more neighboring devices via a sustainability-related augmented IGP. Also, the energy-aware topology logic can generate a desired state for the device based on at least the received current state data and update data. One or more of the plurality of elements may be modified in response to the generated desired state, wherein the modification involves changing one or more sustainability-related capabilities.

Energy-aware topology

Techniques for ultra-short-term resource forecasting for a network device are described. A selection of a time series algorithm from a set of time series algorithms for determining capacity right-sizing of a local resource is received, the is selection based at least in part on current local traffic conditions. Based on current local traffic conditions, parameter values to be used in the algorithm are determined, the parameters are associated with the time series algorithm selection. A number of data points for input to the time series algorithm are determined, the data points are a sequence of values representing an amount of the local resource used by the network device at a point in time and are collected at predetermined time intervals. Based on a calculation of the time series algorithm using the number of data points and parameter values, the right-size capacity of the local resource for the network device is determined and provided.

Seasonal parameter provisioning for ultra-short-term forecasts

Devices, systems, methods, and processes for managing network devices through generated predictions and associated confidence levels are described herein. Networks within a floorplan can be operated at full capacity all day in an inefficient way when not adjusted due to traffic patterns and seasonality changes. Data related to the topology of the network, along with historical data can be utilized to generate predictions of various network needs. For example, the overall network throughput capacity needs may be predicted for a series of points in the future. An associated confidence level can be generated as well including one or more confidence intervals. These can be utilized to select a future need for the network and generate a corresponding sustainable network configuration for the network devices and/or their transceivers that can provide sufficient network needs while minimizing the overall power used. This can be automated over time once trust has been established.

Client-aware floorplan management with predicted confidence levels

Techniques for determining an optimal connection path by a NHNaaS are described. The techniques may include receiving a registration from an IPS that includes service ISP service parameters, and storing the registration in a NaaS database. A request to connect to a remote service from a user device, including user parameters required is received. ISPs having respective service parameters compatible with the user parameters are identified in the NaaS database. Multiple paths offered by the service providers between the user device and the remote service are determined. Network performance data for each path is received from a network monitoring service. Using the network performance data, an optimal path for establishing the connection is identified. A request to instantiate a tunnel between the user device and remote service is transmitted to the service providers along the optimal path and the tunnel information is transmitted to the user device.

End-to-end neutral host network-as-a-service

A method, computer system, and computer program product are provided for decentralized machine learning. A plurality of computing networks are identified by determining that each computing network of the plurality of computing networks satisfies a predetermined number of criteria. A decentralized learning agent is provided to each computing network, wherein the decentralized learning agent is provided with input parameters for training and is trained using training data associated with a computing network to which the decentralized learning agent is provided. A plurality of learned parameters are obtained from the plurality of computing networks, wherein each learned parameter of the plurality of learned parameters is obtained by training the decentralized learning agent provided to each respective computing network. A global model is generated based on the plurality of learned parameters.

Decentralized machine learning across similar environments

A method is described that involves a method for application performance in a cross-domain network using multi-controller coordination. The method includes receiving a request at a first controller from an application within an enterprise network, wherein the request seeks to monitor a network path. The first controller identifies one or more additional controllers within the enterprise network capable of monitoring the network path. These additional controllers include a first one within the same domain as the first controller (first domain) and a second one within a different domain (second domain). A token, encompassing authentication details and monitoring requirements linked to the request, is sent to the second additional controller from the first domain. Subsequently, direct communication is established with a resource of the second controller, allowing monitoring of the request and its associated operation.

Conveying operator intent to remote agents in an administrative-constrained cross-domain multi-controller FSO network

Devices and methods that incorporate sustainability data within a header of a data packet to allow for the generation of sustainable configurations for various network devices are disclosed. Power efficiency is obtained at a node-level by including metadata to existing network flows, in an in-band/in-situ configuration. This information may be used for optimum flow placement. Received data packets may be formatted with sustainability data within a metadata shim. The received data packets are processed, and a sustainable configuration is generated for the one or more network devices. The generated sustainable configuration is transmitted to the one or more network devices to enable efficient and effective management of network devices by incorporating sustainability data into the data packets.

In-band sustainable packet management

A method of orchestrating one or more radio resources among various services executing within a container. The method includes obtaining, by an orchestration engine executing on a network device, a request, from a first service of a plurality of services, for use of a physical/hardware resource that connects a container running on the network device to a network. The request from the first service has a particular priority. The plurality of services execute within the container. The method further includes determining whether to connect the first service to the network via the physical/hardware resource based on the priority and an availability status of the physical/hardware resource and establishing, at a kernel level, a connection between the first service and the physical/hardware resource based on the determining.

Resource orchestration for multiple services

In one embodiment, a service chain data packet is instrumented as it is communicated among network nodes in a network providing service-level and/or networking operations visibility. The service chain data packet includes a particular header identifying a service group defining one or more service functions, and is a data packet and not a probe packet. A network node adds networking and/or service-layer operations data to the particular service chain data packet, such as, but not limited to, in the particular header. Such networking operations data includes a performance metric or attribute related to the transport of the particular service chain packet in the network. Such service-layer operations data includes a performance metric or attribute related to the service-level processing of the particular service chain data packet in the network.

Segment routing network signaling and packet processing

Described herein are devices, systems, methods, and processes for optimizing network traffic distribution across multiple paths in a manner that is energy-efficient and environmental sustainability-aware. This may be achieved by leveraging time-series analytics and capacity planning based on seasonalities. Data associated with the Layer 3 topology of the network can be collected. Bandwidth can be pre-reserved on an energy-aware traffic engineering tunnel. The time-series data can be used to build a capacity plan based on the seasonalities. Nodes may be clustered based on usage patterns and network utilization seasonality. The data can be used to make decisions about when and where to combine or shut down paths for energy efficiency, while maintaining optimal network performance. A hysteresis mechanism may be incorporated to avoid oscillation when changing active links. Power savings can be achieved by fully turning off or depowering certain network components when they are not needed.

Sustainable network-wide optimization service

Methods are provided in which a cloud portal, serving as an orchestrator device, obtains a request for diagnostics data to monitor performance of a cloud-based service executing in a provider cloud network and accessed by a client device in an enterprise network and obtains service information about a plurality of assets involved in providing the cloud-based service. The plurality of assets are managed by at least a first cloud-based management entity and a second cloud-based management entity. The methods further include collecting the diagnostics data about the plurality of assets based on the service information, aggregating the diagnostics data to form a multi-cloud diagnostics data, and determining the performance of the cloud-based service based on the multi-cloud diagnostics data.

Case deflection using visibility into multi-product clouds

A method is performed by a network controller that is configured to control routers configured to forward a multicast flow downstream from a first hop router that is a root of a multicast tree formed by the routers to last hop routers that terminate branches of the multicast tree, respectively. The method includes collecting operational configuration information from the routers and constructing a topological view of the multicast tree based on the operational configuration information; causing the routers to forward multicast probes downstream from the first hop router along all of the branches toward the last hop routers to trace the multicast tree; receiving, from particular ones of the last hop routers that received the multicast probes, indications that the multicast probes were received; and detecting failures in the multicast tree based on the indications and the topological view.

In-situ operations, administration, and maintenance extension to trace multicast tree and identify failure node

Growing community of inventors

Cary, NC, United States of America

Carlos M Pignataro