Embodiments of this application disclose a service resource preconfiguration method and device, and a system. The method includes establishing a first working path, sending a first path message from a first node to a second node, the first path message including an instruction to the second node to preconfigure a second channel resource; and preconfiguring the second channel resource based on the first path message. Fast automatic service recovery can be implemented, and fault recovery performance can be improved.

The portable peripheral (1001) of communication with a data storage peripheral and a data network utilizing the internet protocol, comprises: a connector to mechanically connect and establish a removable wired connection between the peripheral and a portable terminal, a first means of wired bidirectional communication with the portable terminal, a second means of bidirectional communication with a data storage peripheral or a data network and a security unit protecting the communication between the portable terminal and the data storage peripheral or the data network, this communication being established between the first and the second means of communication.

A Wi-Fi device includes a controller coupled to a writeable memory implementing a MAC and PHY layer and to a transceiver. Connection data stored in the writeable memory includes Wi-Fi connection parameters including ≥1 router MAC level information or a most recently utilized (MRU) channel used, and IP addresses including ≥1 of an IP address of the Wi-Fi device, IP address of the MRU router, an IP address of a MRU target server, and an IP address of a network connected device. An accelerated reconnecting to a Wi-Fi network algorithm is implemented by the processor is for starting from being in a network disconnected state, establishing current connection parameters for a current Wi-Fi network connection using the Wi-Fi connection parameters for at least one MAC layer parameter for the MAC layer.

Described are systems and methods for jointly optimizing Wide Area Network (WAN) and Local Area Network (LAN) network communications. In one embodiment, a management device communicatively interfaced with a WAN and a LAN includes a collection module to collect LAN information from the LAN and WAN information from the WAN; an analysis module to jointly analyze the collected WAN information and the collected LAN information to identify an operational condition; and an implementation nodule to initiate a management event responsive to the operational condition being identified. In one embodiment, the management event includes generating and transmitting a diagnostics report responsive to a fault being identified. The management device may further generate and execute instructions to remedy the diagnosed fault.

Entity models are used to evaluate potential risk of entities, either individually or in groups, in order to evaluate suspiciousness within an enterprise network. These individual or aggregated risk assessments can be used to adjust the security policy for compute instances within the enterprise network. A security policy may specify security settings such as network speed, filtering levels, network isolation, levels of privilege, and the like.

A partitioned virtual space supports logical networking of IoT devices. Agents of the devices are assigned to interest-based cells in a virtual space, and can travel among the cells. Within the cells, pairs of devices are tested for similarity, based on device profiles, and for detected affinity. Agents of devices having affinity are connected in a logical network. Some attributes can be based on a personality model and can reflect the personality of a user or other principal associated with a device. Such attributes can influence requests for affinity testing, calculation of similarity, and further behavioral effects incorporated in affinity determination. Evaluation of recommendations can lead to updating of similarity scores or changes in affinity determination. Disclosed embodiments provide scalable, distributed, autonomous, and unsupervised device-to-device connectivity, free of prior constraints. Embodiments can be implemented in the cloud, with privacy protection.

A method includes defining a first specification for a first network slice, determining a first equilibrium value for a first time period for the first network slice offering, receiving a first bid price for the first network slice for the first time period from a first customer, comparing the first equilibrium value to the first bid price; and providing services using the network slice to the customer during the time period in accordance with the first specification and the bid price if the bid price meets or exceeds the equilibrium value.

Methods, systems, and computer readable media for performing metadata-driven data collection are disclosed. In some examples, a method includes receiving a request for system status data for components of a distributed computing system while the distributed computing system is in operation. The request includes metadata specifying a data collection sequence for collecting component-level system status data. The components include compute components, network components, and storage components. The method includes obtaining, using the metadata, the component-level system status data by querying protocol-based data collectors in an order, one after the other, as specified by the data collection sequence specified by the metadata. The method includes assembling the component-level system status data into assembled status data and storing the assembled status data in memory and/or a repository.

An apparatus in one embodiment comprises a processing platform that includes a plurality of processing devices each comprising a processor coupled to a memory. The processing platform is configured to implement at least a portion of at least a first cloud-based system. The processing platform comprises a modelling language extension module configured to implement artificial intelligence-based decision points into a process flow and compile context attributes associated with the artificial intelligence-based decision points based on data from artificial intelligence systems. The processing platform also comprises a process engine configured to convert the artificial intelligence-based decision points and context attributes to input to a process optimization algorithm, and an optimization engine configured to determine, by applying the process optimization algorithm to the converted input, an overall execution path within the process flow, and output a decision to a first of the artificial intelligence-based decision points based on the overall execution path.

Described herein are systems and methods to manage blacklists and duplicate addresses in software defined networks (SDNs). In one implementation, a method includes, in a control plane and data plane of an SDN environment, obtaining a blacklist for a logical port in the SDN environment. The method further includes deleting realized address bindings in a realized address list for the logical port that match the one or more address bindings in the blacklist and preventing subsequent address bindings that match the one or more address bindings in the blacklist from being added to the realized address list.