Main Reference PaperCaching Transient Data for Internet of Things: A Deep Reinforcement Learning Approach, IEEE Internet of Things Journal, 2018 [Java]
  • To solve the formulated problem a deep reinforcement learning (DRL) based caching policy was proposed, which can determine the caching policy without any assumptions explicit about the operating environment.

+ Description
  • To solve the formulated problem a deep reinforcement learning (DRL) based caching policy was proposed, which can determine the caching policy without any assumptions explicit about the operating environment.

  • To solve the formulated problem based on a novel deep reinforcement learning (DRL) approach

  • To minimize the long-term cost of fetching IoT data

  • To achieve multiple equilibria and avoid reduplicative caching

+ Aim & Objectives
  • To solve the formulated problem based on a novel deep reinforcement learning (DRL) approach

  • To minimize the long-term cost of fetching IoT data

  • To achieve multiple equilibria and avoid reduplicative caching

  • A technique is contributed to further improve the performance of the overall network.

+ Contribution
  • A technique is contributed to further improve the performance of the overall network.

  • Operating System : Ubuntu 12.04 LTS 64bit

  • Simulator: Cooja, Instant Contiki-3.0 and Vmware Player 12.5.6

  • Language: C

+ Software Tools & Technologies
  • Operating System : Ubuntu 12.04 LTS 64bit

  • Simulator: Cooja, Instant Contiki-3.0 and Vmware Player 12.5.6

  • Language: C

  • M.E / M.Tech/ MS / Ph.D.- Customized according to the client requirements.

+ Project Recommended For
  • M.E / M.Tech/ MS / Ph.D.- Customized according to the client requirements.

  • No Readymade Projects-project delivery Depending on the complexity of the project and requirements.

+ Order To Delivery
  • No Readymade Projects-project delivery Depending on the complexity of the project and requirements.

Professional Ethics: We S-Logix would appreciate the students those who willingly contribute with atleast a line of thinking of their own while preparing the project with us. It is advised that the project given by us be considered only as a model project and be applied with confidence to contribute your own ideas through our expert guidance and enrich your knowledge.

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