A technology is described for determining a trust score or trust metric used to determine whether to allow a connection to a high risk destination. In one example of the technology, a connection request to initiate a connection with a destination over a network may be received at a communication service. The communication service may identify a customer account associated with the connection request and obtain a trust score that indicates whether the connection request associated with the customer account may be allowed. The communication service may determine whether the connection request associated with the customer account is allowed to initiate the connection with the destination based on the trust score, and initiate the connection with the destination over the network when the trust score allows the connection request.

A method and apparatus are disclosed from the perspective of a first device for performing sidelink transmission in a sidelink resource pool. In one embodiment, the first device has a configuration of the sidelink resource pool, wherein the sidelink resource pool is enabled with resource reservation for different Transport Blocks (TBs). The first device also has a configuration of a list of reserved periods. Furthermore, the first device selects or determines a first reserved period from the list of reserved periods, wherein the first selected or determined reserved period is within a first set of reserved periods. In addition, the first device randomly selects a first integer in a first interval, wherein the first interval is based on a scaling factor and a second interval, and the scaling factor is derived based on a largest reserved period in the first set of reserved periods, and wherein the first integer indicates a number of transmission opportunities of different TBs with the first reserved period. The first device further performs sidelink transmission of one TB on one transmission opportunity from the number of transmission opportunities.

In some aspects, a computing system may use time series data and machine learning to determine an efficient time to send data to a blockchain. A machine learning model may use a variety of blockchain related data to predict a network usage costs for different times in the future. The predicted network usage costs may be used to determine when data should be sent for storing on the blockchain to reduce network resource costs for a computing system. For example, based on inputting the blockchain data into the machine learning model, a computing system may generate output indicating network usage costs for a future time period, with each network usage cost corresponding to a timestamp within the future time period. The computing system may determine a minimum network usage cost of the network usage costs and send data to a node in the blockchain network at the corresponding timestamp.

A network device may receive a request to connect to a network from a user equipment device and perform a first admission control procedure to determine whether to temporarily allow the user equipment device to connect to the network. The network device may receive information identifying a slice associated with the user equipment device in response to determining to temporarily allow the user equipment device to connect to the network. The network device may perform a second admission control procedure to determine whether to allow the user equipment device to connect to the network. The second admission control procedure is based on the slice associated with the user equipment device. The network device may allocate network resources to the user equipment device in response to determining to allow the user equipment device to connect to the network.

Methods and systems for migrating resources of a virtual private cloud across public cloud environments are described. The method performed by server system includes discovering a plurality of resources associated with a source cloud via an application programming interface (API) of the source cloud and generating resource models associated with the plurality of resources based, at least in part, on the discovered resources of the source cloud. The resource models include information of the plurality of resources and relationships between the plurality of resources. The method includes storing the resource models associated with the source cloud in a database and migrating the plurality of resources of the source cloud to a different region of the source cloud or a target cloud based, at least in part, on the resource models associated with the plurality of resources.

The subject technology selects a particular zone among multiple zones based on a target skew to meet a global balancing of cluster instances. The subject technology deploys a particular type of cluster instance to the particular zone. The subject technology, for each zone from the multiple zones, determines a respective number of cluster instances. The subject technology identifies a second particular type of cluster instance to add based on a total number of the second particular type of cluster instance in the multiple zones and a second total number of the particular type of cluster instance in the multiple zones. The subject technology adds the second particular type of cluster instance to a second particular zone to meet the global balancing of cluster instances in the multiple zones.

Described herein is a platform for providing a resource catalog local to an appliance device, such that the appliance device is able to generate a transaction related to one or more resources within the resource catalog. In some embodiments, the appliance device may receive resource information within streaming data. For example, the appliance device may receive an indication that a portion of streaming media data is related to a resource. Upon determining that a portion of streaming data is related to a resource, the appliance device may be configured to store the portion of data in relation to the identified resource. A user may retrieve and/or execute the portion of streaming data at a later date. In some embodiments, the user may request that a transaction be conducted with respect to the resource and a corresponding transaction request may be generated by the appliance device.

A method and apparatus are disclosed from the perspective of a first device for performing sidelink transmission in a sidelink resource pool. In one embodiment, the first device has a configuration of the sidelink resource pool, wherein the sidelink resource pool is enabled with resource reservation for different Transport Blocks (TBs). The first device also has a configuration of a list of reserved periods. Furthermore, the first device selects or determines a first reserved period from the list of reserved periods, wherein the first selected or determined reserved period is within a first set of reserved periods. In addition, the first device randomly selects a first integer in a first interval, wherein the first interval is based on a scaling factor and a second interval, and the scaling factor is derived based on a largest reserved period in the first set of reserved periods, and wherein the first integer indicates a number of transmission opportunities of different TBs with the first reserved period. The first device further performs sidelink transmission of one TB on one transmission opportunity from the number of transmission opportunities.

An improved buffer for networking and other computing devices comprises multiple memory instances, each having a distinct set of entries. Transport data units (“TDUs”) are divided into storage data units (“SDUs”), and each SDU is stored within a separate entry of a separate memory instance in a logical bank. One or more grids of the memory instances are organized into overlapping logical banks. The logical banks are arranged into views. Different destinations or other entities are assigned different views of the buffer. A memory instance may be shared between logical banks in different views. When overlapping logical banks are accessed concurrently, data in a memory instance that they share may be recovered using a parity SDU in another memory instance. The shared buffering enables more efficient buffer usage in a network device with a traffic manager shared amongst egress bocks. Example read and write algorithms for such buffers are disclosed.

A computer-implemented method and system for reducing time lag in data transfer are disclosed. The computer implemented method for reducing time lag in data transfer, the method includes sending a small packet of data at predetermined time from at least one device to a destination address to keep the network connection alive and network resources assigned, wherein the at least one device includes one or more of: a transmitting device, a receiving device or a combination thereof. The system for reducing time lag in data transfer, the system comprising at least one base station; at least one device, wherein the at least one device includes one or more of a transmitting device, a receiving device or a combination thereof; wherein the at least device sends a small packet of data at predetermined time to a destination address to keep the network connection alive and network resources assigned.