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Analysis and Enhancement of Distributed Timely Computations Regarding Age of Information

Khani, Zeynab | 2023

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 57290 (05)
  4. University: Sharif University of Technology
  5. Department: Electrical Engineering
  6. Advisor(s): Ashtiani, Farid
  7. Abstract:
  8. Edge computing networks are ideal for emerging applications that require computation-intensive and timely processing, as they enable complex computation tasks to be offloaded and computed in parallel and distributed manner. However, for many applications that the calculations are of one type, such as determining the location of an object, it is crucial to insure the freshness of the information. Age of Information (AoI) metric is employed to measure freshness. This research focuses on identifying an appropriate model for calculating the average AoI in distributed computing systems and determining the optimal decision-making policy to enhance it. In essence, the primary objective is to address the choice between discarding completed subtasks to work on new tasks or working on existing tasks while discarding incoming tasks, at each node of the system and stage of computation, to enhance AoI. To achieve this, a (3,2) coded distributed computing system with heterogeneous Geometric service times and Bernoulli i.i.d. arrival tasks is analyzed. The study explores two scenarios: one without buffers and the other with a single buffer, in order to determine the system’s average AoI and derive the optimal policy for each node of the system to minimize AoI. The obtained methods and findings can be extended to other distributed computing systems with different encoding schemes. The primary approach used to determine the average AoI is based on Phase-Type distribution. Numerical findings indicate that the identified policies outperform the always preempting and always dropping policies. Furthermore, incorporating a buffer enhances the freshness of information
  9. Keywords:
  10. Distributed Computing ; Phase-Type Distribution ; Edge Computing ; Information Age

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