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Adaptive Interest Packet Lifetime Due to Pending Interest Table Overflow

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 رائد نصر كاظم العبيدي
20/10/2018 08:33:07
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Pending Interest Table (PIT) is a novel data structure for forwarding processes in Content-Centric Networking/Named Data Networking (CCN/NDN). It brings CCN/NDN significant features, such as multipath routing, communicating without the knowledge of consumers or publishers, better security, loop, and packet loss detection,. However, despite the numerous advantages of PIT, hardware challenges, including PIT are still progenerated in respect to CCN/NDN implementation in terms of memory efficiency. It is submitted that the benefits are achieved in fast time accessing and a large packet storing. With the current trend of Internet activities through access speed required for data traversing, entries and the possibilities offered in this sense of current memory technologies. A tendency for the PIT to overflow with consequent service disruption and possible network collapse is always feasible. The PIT problem of overflow could be subjected due to the massive usage of long Interest Lifetimes, which would further increase the number of simultaneous entries in the PIT. The objective of this paper to propose a smart scheme named Adaptive LifeTime (ALT) in order to manage the Interest Lifetime at content routers that will adapt Lifetimes as a function of the network load: leading a CCN/NDN node to grant larger Lifetime values in case of low traffic and in the event that the PIT is not full. Conversely, to implement a sort of Lifetime shaping when PIT overflow occurs for incoming Interest packets. With such a scheme, we would break down the hypothesis that states that intermediate nodes do not manage Lifetime values. The results from the performance analysis show that ALT result is considerably better in performance for the metrics average PIT Lifetime to compare with an original PIT.

  • وصف الــ Tags لهذا الموضوع
  • Content Centric Networking, Named Data Networking, Pending Interest Table, Interest Lifetime. 1.