Cisco Technology, Inc.

Lavan Kumar Peechara

Prasenjeet Acharjee

Subramanian Karunanithi

Togis Thomas

Sanjeeth Kumar Ravindranath

Vingesh Shetty

Bhavadharini Krishnamoorthy

Sai Kishore Bhyri

A network node in an optical network dynamically generates a routing table based on attributes of the optical network. The network node obtains attributes characterizing the optical network, which includes multiple network nodes connected by optical links. The network node calculates cost values for sending data from the network node to one or more next hop nodes that are connected to the network node. Each particular cost value is associated with a probability of success of sending the data to a particular next hop node based on a particular permutation of the attributes characterizing the optical network. The network node generates a routing table correlating the permutations of the attributes with each next hop node based on the cost values.

Route selection in optical networks based on machine learning

Anomaly detection and filtering based on system logs is provided via receiving, at a first time, a first sequence of log entries from a networked system; generating, based on previously observed log entries including the first sequence of log entries, predicted log entries for a second time; receiving, at the second time, a second sequence of log entries from the networked system; determining whether the second sequence is anomalous based on comparing the second sequence with the predicted log entries; in response to determining that the second sequence is anomalous, determining whether the second sequence is noteworthy based on a function entropy of the first sequence and a sentiment polarity of the second sequence; and in response to determining that the second sequence is noteworthy, generating an anomaly report that includes the second sequence and a root cause.

Anomaly detection and filtering based on system logs

In one embodiment, a memory manager may identify allocators as either transient in nature or static in nature based on a length of time each one of the allocators held, holds, or both, onto requested memory blocks. The memory manager may also allocate memory blocks requested by allocators identified as transient in nature from one memory pool and allocate memory blocks requested by allocators identified as static in nature from another memory pool. In one example, the memory manager may also use a deferred splitting strategy to optimize allocation of free memory next to memory blocks reserved by the most transient allocators by not splitting such free memory if the free bytes are less than a maximum block size threshold.

Adaptive memory allocation

Growing community of inventors

Andhra Pradesh, India

Lavan Kumar Peechara