Intern-Content Delivery-Information
Huawei - Santa Clara, CA

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Job Description

Working with a team of networking experts and industry professionals in the development of analytical tools and innovative methods and protocols for content delivery in information-centric networks. The intern will be studying patterns in content disseminations and analyzing the performance of joint content coding and content placement in caches in the network to enhance content delivery and minimize the load at the server. The intern will be studying the performance of methods to disseminate content and to share content information over the network for efficient encoding at the source, and see how different encoding schemes influence the overall performance of the system (where performance means some metric such as capacity or delay). The intern will generalize the index coding problem to Information Centric Networks. The intern will design a model upon which to perform an analytical study, and validate the study with simulations. The intern will design innovative and patentable features.

Qualifications
  • Profound understanding of content delivery mechanisms
  • Capability to develop and promote new and better analytical tools to study network-wide performance metrics
  • Capability to develop innovative methods for content encoding and content placement analysis
  • Capability to validate results using either traces, analytical tools and/or simulation environments
  • Very effective communicator with proven track record of delivering high quality, on time projects
  • Ability to meet deadlines and commitments in a fast paced environment
  • Strong attention to details, and proactive, motivated and able to work as a team player
  • Student in a Ph. D program at a high quality institution or equivalent certifications plus experience
Experience
  • Essential analytical ability and demonstrated results in networking and in information theory
  • Solid understanding of information-centric networking
  • Solid understanding of content distribution mechanisms and content caching protocols
  • Solid ability with simulation environments
  • Fluency with trace based evaluation
  • Experience with queuing theoretic models, fluid models, probabilistic models
  • Track record of publication in high quality peer-referred conferences or journals
Required Skills
  • 2-5 years experience in network science
  • Fluent in one or more of: perl, matlab, NS3, opnet
  • 1+ years of experience in a research position

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