Search

Ritesh D Maheshwari

from Sunnyvale, CA
Age ~42
Get Report
Connected to:
Amit Maheshwary, 44Anisha Maheshwari, 30Arpita Maheshwari, 36Chetan Maheshwari, 34Kanika Maheshwari, 46Kavita Maheshwari, 61Ketan Maheshwari, 42Kritika Maheshwari, 35Mayank Maheshwari, 40Neelima Maheshwari, 53

Ritesh Maheshwari Phones & Addresses

  • Sunnyvale, CA
  • Cary, NC
  • Nashville, TN
  • Hermitage, TN
  • Antioch, TN
  • Mountain View, CA
  • Somerville, MA
  • Allston, MA
  • Centereach, NY

Publications

Us Patents

Client-Side Bottleneck Analysis Using Real User Monitoring Data

View page
US Patent:
20170346909, Nov 30, 2017
Filed:
May 31, 2016
Appl. No.:
15/169210
Inventors:
- Mountain View CA, US
David He - Cupertino CA, US
Ritesh Maheshwari - Mountain View CA, US
Swapnil Ghike - Sunnyvale CA, US
International Classification:
H04L 29/08
H04L 12/26
H04L 29/06
Abstract:
Techniques are provided for analyzing client-side performance data. In one technique, first client performance data and second client performance data is received. The first client performance data was generated by a first client device and indicates a first plurality of processing items that includes a first processing item that is associated with first item performance data. The second client performance data was generated by a second client device and indicates a second plurality of processing items that includes a second processing item that is associated with second item performance data. In response to determining that the first processing item is associated with the second processing item, an aggregate data value is computed based on the first item performance data and the second item performance data.

Compression-Based Detection Of Inefficiency In Local Storage

View page
US Patent:
20170336984, Nov 23, 2017
Filed:
May 20, 2016
Appl. No.:
15/160898
Inventors:
- Mountain View CA, US
Ritesh Maheshwari - Mountain View CA, US
Nicholas P. Baggott - Mountain View CA, US
Haricharan K. Ramachandra - Fremont CA, US
Badrinath K. Sridharan - Saratoga CA, US
Assignee:
LinkedIn Corporation - Mountain View CA
International Classification:
G06F 3/06
Abstract:
The disclosed embodiments provide a system for detecting and managing inefficiency in local storage. During operation, the system obtains a first snapshot of data in local storage of a computer system, wherein the first snapshot comprises a first set of data elements in the local storage at a first time. Next, the system applies a compression technique to the first snapshot to obtain a first set of inefficiency metrics for the first set of data elements. The system then outputs the first set of inefficiency metrics with additional attributes of the data to improve management of inefficiency in the data.

Compression-Based Detection Of Inefficiency In External Services

View page
US Patent:
20170336995, Nov 23, 2017
Filed:
May 20, 2016
Appl. No.:
15/160905
Inventors:
- Mountain View CA, US
Ritesh Maheshwari - Mountain View CA, US
Nicholas P. Baggott - Mountain View CA, US
Haricharan K. Ramachandra - Fremont CA, US
Badrinath K. Sridharan - Saratoga CA, US
Assignee:
LinkedIn Corporation - Mountain View CA
International Classification:
G06F 3/06
Abstract:
The disclosed embodiments provide a system for detecting and managing inefficiency in external services. During operation, the system obtains a snapshot of a data stream transmitted over an external service from a computer system at a first time. Next, the system applies a compression technique to the snapshot to obtain a set of inefficiency metrics for a set of data elements in the snapshot. The system then outputs the set of inefficiency metrics with additional attributes of the data stream to improve identification of inefficiency in the data stream.

Assigning Content Objects To Delivery Networks

View page
US Patent:
20160283480, Sep 29, 2016
Filed:
Mar 26, 2015
Appl. No.:
14/669910
Inventors:
- Mountain View CA, US
Ritesh Maheshwari - Mountain View CA, US
Haricharan K. Ramachandra - Fremont CA, US
Badrinath K. Sridharan - Saratoga CA, US
Assignee:
LINKEDIN CORPORATION - Mountain View CA
International Classification:
G06F 17/30
H04L 29/06
H04L 12/26
G06F 17/22
Abstract:
A system, method, and apparatus are provided for assigning or allocating multiple content objects, within a content page (e.g., web page) or other content collection (e.g., a set of pages), to different content delivery networks for delivery in response to a content request. The objects are ranked by importance (e.g., importance in rendering or presenting the page), and the networks are ranked by performance (e.g., throughput). In order of importance, the objects are assigned to the best-performing network that is “available.” Some or all networks are initially available, and a given network becomes “unavailable” after it has been assigned its portion of the objects (e.g., based on content, number of objects, amount of data, percentage). If a total accumulated cost of delivering the objects exceeds a target before all objects have been allocated, the allocation process may terminate early and the remaining objects may be assigned to the least-expensive network.

Systems And Methods For Evaluating A Change Pertaining To A Service Or Machine

View page
US Patent:
20150095892, Apr 2, 2015
Filed:
Sep 27, 2013
Appl. No.:
14/040470
Inventors:
- Mountain View CA, US
Christopher Coleman - Sunnyvale CA, US
Melvin Yueyang Du - Dublin CA, US
Thomas Goetze - Danville CA, US
Ritesh Maheshwari - Mountain View CA, US
Badrinath K. Sridharan - Saratoga CA, US
Cuong Tran - Los Altos CA, US
Assignee:
Linkedln Corporation - Mountain View CA
International Classification:
G06F 11/36
US Classification:
717127
Abstract:
Techniques for evaluating the performance of a service or machine after a change that pertains to the service or machine are described. For example, an indication of a change that pertains to a service or machine is received. In response to the receiving of the indication of the change, using at least one computer processor, a performance of the service or machine after the change is evaluated. The evaluation may be based on a particular rule for evaluating the performance of the service or machine after the change. An evaluation result is generated based on the evaluating of the performance of the service or machine after the change. The evaluation result indicates the quality of the performance of the service or machine after the change.
Control profile
Ritesh D Maheshwari from Sunnyvale, CA, age ~42 Get Report