Authors: Haowei Yuan, Tian Song, and Patrick Crowley Publisher: ICCCN 2012 Presenter: Chai-Yi Chu Date: 2013/05/22 1

 Introduction  The NDN Forwarding Plane  The CCNx Performance Study  Issues in Scalable NDN Forwarding  Design Principles 2

 An NDN software prototype, CCNx.  Present an experimental evaluation of the current CCNx implementation.  Description of the major data structures and algorithms used in CCNx.  Analyze and simplify the packet forwarding operations in CCNx and NDN. 3

 Decides what to do for each incoming packet.  Can be divided into multiple layers based on the functions: 1.The strategy layer  Selects forwarding strategies and impacts the forwarding decisions. 2.The data forwarding layer  Packet forwarding, pending Interest management and temporary content storing. 3.The transport layer  Handles network communication. 4

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 Study was conducted in the Open Network Laboratory (ONL)  The CCNx implementation evaluated in this work is ccnx-0.4.0, released on September 15, ◦ compiled using gcc with optimization level -O4. ◦ The core component, ccnd, is configured with all default environment variable values. ◦ The Content Store size is set at the default value of 50, 000 6

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 To generate CCNx traffic, the built-in ccncatchunks2 and our ccndelphi programs are used as the client program and server program. ◦ ccncatchunks2: generates a sequence of Interest packets to fetch a large file. ◦ ccndelphi: generates Data packets with random payloads, and it is designed to send back Data packets as soon as possible. 8

 Throughput values are sampled every 1 second. For each experimental configuration, we select top 20 throughput values to compute the average peak throughput and calculate a 90% confidence interval.  Two experimental configurations were used for measuring CCNx router peak throughput: 1.every client requests a different file  ccnx:/i/chunk, i = 0…15, chunk starts with value 0 and increases by 1 for each generated Interest request. 2.all clients request the same file  ccnx:/0/chunk 9

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 Use Gprof to profile the saturated ccnd daemon. ◦ ccnd daemon, which implements the packet forwarding plane. ◦ more than 60% of the time was taken by unctions related to packet name decoding. ◦ ccn_skeleton_decode function, which is the lowest level packet decoding function, takes 35.46%. 12

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 The logical FIB and PIT share a hash table named Name Prefix Hash Table (NPHT), which indexes the Propagating Entries(PEs) and Forwarding Info Entries (FIEs). ◦ the structures storing detailed pending Interest information and forwarding information  Each bucket in the NPHT has pointers pointing to PEs and FIEs 14

 The Propagating Hash Table (PHT) is keyed by the nonce field ◦ which is unique for each Interest packet. ◦ Stores all the nonce field of the Interest packets presented in PIT (in the form of PEs). 15

 For Content Store, each Data packet is assigned a unique accession number  The cached Data packets are stored in an array named Content Array (CA) indexed by the accession numbers.  Old but popular Data packet whose accession number is out of the range that CA supports. ◦ These packets are stored in the Straggler Hash Table (SHT) to save space 16

 Two data structures summarize the Content Store, namely 1. Content Hash Table (CHT) ◦ a hash table keyed by the Data packet full name 2. Content Skip List (CSL) ◦ a standard implementation of the skip list data structure 17

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 Simplified Data Structures and Operational Flows 22

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 Key Issues to Be Solved ◦ Exact string matching with fast updates  In PIT & CS ◦ Longest prefix matching for variable-length and unbounded names  In FIB ◦ Large-scale flow maintenance  similar to IP network per-flow monitoring  {name, incoming interfaceID, outgoing interfaceID} 24

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 Aim for constant-time operations  URL-format for Optimization ◦ names in NDN have a format similar to HTTP URLs  Simple Data Structures for Fast Updates ◦ include hash tables, d-left hash tables and counting bloom filters.  Efficient Packet Encoding/Decoding ◦ a complicated XML format to encode packets  develop a quickly and efficiently packet decoding algorithm  Different Content Store Policies 27