Traffic engineering for information-centric networks

Martin J. Reed, IEEE ICC 2012 - Next-Generation Networking Symposium

9761133 劉立恆

Abstract• Information-centric

network (ICN)

• Intra-domain traffic engineering (TE)

Information-centric network (ICN)

› publish-subscribe Internet routing paradigm (PSIRP)

› Bloom filter (BF)A source routing methodAnother method mentioned is Multi-Protocol Label Switch (MLPS)

› line speed publish-subscribe inter-networking (LIPSIN)LIPSIN = PSIRP + BF

Bloom filter (BF)

› Hash

› False positive

› Forwarding Identifier (FID) in header (routing information)

› Link Identifiers (LID) for each link

Publish-Subscribe Internet Routing Paradigm (PSIRP) with BF = LIne speed Publish-Subscribe Inter-Networking (LIPSIN)

Intra-domain traffic engineering (TE)

› Loss Rate

› Throughput

› MFMC 是 TE 的其中一個目的 (resource reservation)– 降低使用律 ( 最大化沒用到的傳輸能力 )– 應付未來可能增加的需求

• Multicommodity Flow with Minimum Congestion (MFMC)

x(p): path p 的流量 , u(e): edge e 的容量 , ΓL: 剩餘容量d : 需求量

1. 流量小於 edge 的容量 ( 容量已扣除保留的部分 )

2. flow 須滿足需求

• Integer Multicommodity Flow with Minimum Congestion (IMFMC)

對 IP based network ( 同一個 link 不可不同 path)

1. 流量小於 edge 的容量 ( 容量已扣除保留的部分 )

2. flow 須滿足需求每一個 demand (d) 對應一個 path (p)不可將 demand 分割成多條 path

• Maximum Concurrent Flow (MCF)

令 MCFC 等於 MCF 的變體

The Garg and Konemann algorithm

› Lagrange dual problem

› Iterative processing

› ϵ step, ϵ-optimize

› Run time :

Network simulation

› Degree: Weibull distribution ( k=0.42 )

› Edge generation: Viger and Latapylognormal distribution ( μ = 16.6 and σ = 1.04 )

MFMC v.s. Shortest Path Route (SPR)

15 個 nodes20 個虛擬情境

低負載=1

高負載=0

MFMC v.s. IMFMC

高負載=0

低負載=1

15 個 nodes20 個虛擬情境

Variance of IMFMC

高負載=0.1

NPC algorithm

Conclusion

IMFMC MFMC

pros可以使用現有 IP

架構 演算法速度快

cons演算法為 NPC

計算時間差異大無法使用 IP 當

底層架構

延伸討論› Information-Centric

Network 的應用？› IMFMC 的實際架構？› 20 個模擬情境？› MFMC 與理想狀況的

差距？