Google Inc.

Andras Erdei

Krzysztof Duleba

Luuk Van Dijk

Mark M Sandler

Nils Richard Ekwall

Provided is a method of correlating an Internet Protocol version 4 (IPv4) address with an Internet Protocol version 6 (IPv6) address. The method may include communicating, via the Internet, an IPv4-addressed signal transmitted to, or received from, an IPv4-capable computing device. The method may also include communicating, via the Internet, an IPv6-addressed signal transmitted to, or received from, an IPv6-capable computing device. The method may further include determining that the IPv4-capable computing device and the IPv6-capable computing device are the same computing device based on the IPv4-addressed signal and the IPv6-addressed signal, and storing in memory data indicating a correlation between at least part of the IPv4 address and at least part of the IPv6 address.

Apparatus and method for correlating addresses of different internet protocol versions

Apparatus and method for correlating addresses of different Internet protocol versions

Among other disclosed subject matter, a computer-implemented method includes receiving a first, a second and a third network address mapping. The method includes mapping each of the network addresses in the first, second and third network address mappings to respective first, second and third locations. The method includes determining, for each of the network addresses in the first, second and third network address mappings, location agreements. The method includes determining a first and second network address mapping agreement rate, a first and third network address mapping agreement rate, and a second and third network address mapping agreement rate, respectively based on location agreements determined for each of the network addresses. The method includes determining a confidence level associated with the first network address mapping based on the agreement rates.

Evaluating IP-location mapping data

Methods, systems, and implementations are disclosed to schedule a plurality of tasks on one or more processors. The tasks may be part of a larger job based on a user initiated query for information retrieval. One example method of operation may include estimating, based upon historical actual execution times of tasks of a respective corresponding type, an expected execution time for each task of the plurality of tasks. The method may further include scheduling the plurality of tasks for execution on the one or more processors based upon the estimated expected execution time of each task. The scheduling procedure utilized ultimately produces an optimized task execution schedule, and in turn, minimizes the expected job completion time.

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Zurich, Switzerland

Andras Erdei