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Performance evaluation of epidemic content retrieval in DTNs with restricted mobility

Rashidi, L ; Sharif University of Technology | 2019

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  1. Type of Document: Article
  2. DOI: 10.1109/TNSM.2019.2909108
  3. Publisher: Institute of Electrical and Electronics Engineers Inc , 2019
  4. Abstract:
  5. In some applicable scenarios, such as community patrolling, mobile nodes are restricted to move only in their own communities. Exploiting the meetings of the nodes within the same community and the nodes within the neighboring communities, a delay tolerant network (DTN) can provide communication between any two nodes. In this paper, two analytical models based on stochastic reward nets (SRNs) are proposed to evaluate the performance of the epidemic content retrieval in such multi-community DTNs. Performance measures computed by the proposed models are the average retrieval delay and the average number of transmissions. The monolithic SRN model proposed in the first step is not scalable, in terms of the number of communities and nodes, due to the state space explosion in the underlying Markov chain. In order to solve the scalability problem of the monolithic model, an approximate model based on the folding technique is presented which allows us to evaluate the performance of large-scale DTNs. In order to cross-validate the results obtained from the proposed models, we extend the ONE simulator to support our network model. The analyticnumeric results indicate that both models have good accuracy, and the folded model reduces the state space highly, achieving good scalability without any significant loss of accuracy. © 2019 IEEE
  6. Keywords:
  7. Content retrieval ; Epidemic routing ; Performance evaluation ; Stochastic reward nets ; Epidemiology ; Information retrieval ; Markov processes ; Scalability ; Stochastic models ; Stochastic systems ; Wireless networks ; Performance measure ; Restricted mobilities ; Scalability problems ; State-space explosion ; Delay tolerant networks
  8. Source: IEEE Transactions on Network and Service Management ; Volume 16, Issue 2 , 2019 , Pages 701-714 ; 19324537 (ISSN)
  9. URL: https://ieeexplore.ieee.org/document/8681155