《 Hierarchical Caching Management for Software Defined Content Network based on Node Value 》 Reporter ： Jing Liu ， China Affiliation ： University of Science and Technology of China ：

Background Users want the content instead of the IP address through the network The original host-host model in IP is not suitable any more !

Future Internet architecture: CCN: Content-Centric Network SDN :Software-Defined Network Background

Why SDCN ? The most existing CCN schemes are over the IP network Protocol-Oblivious Forwarding (POF) is the extension of OpenFlow proposed by HUA WEI. SDCN realizes CCN over SDN which does not rely on the IP

SDCN over POF Fig. SDCN Architecture

How to describe the value of Content Node ? Node Value : tends to be the minimum path length node centricity metric set a higher value for the center node which bears higher traffic

Node Value Node centricity(D i ): the reciprocal of the sum of shortest path distance to other nodes N is the number of nodes in network. Normalization process of D i

Node Value Node connectivity ( L i ): the number of nodes connected to node i

Node Value (V i ) : D i    L i Where  is the tradeoff between Node centricity and Node connectivity. Node Value

Hierarchical Cache Model Fig. Simple topology example For S1: the sum of the shortest path : =17

NodeSumDiLi  Li ViRank S S S S S S S S Hierarchical Cache Model Table 1. Calculation of Node Value (  is 0.02 )

The network with 8 nodes is divided into 3 layers. The total cache C is divided equally into each layer and each layer further divides the C/3 equally Hierarchical Cache Model Table 2. The allocation of total cache space C Cache size of LayernodesCache size of node Layer1 (10%)C/3S6C/3 Layer2 (30%)C/3S3, S5C/6 Layer3 (60%)C/3S1,S2,S4,S7,S8C/15

Hierarchical Cache Model Fig The Hierarchical Model

Cache Decision Strategy : NVD We assume the content popularity is known and set popularity threshold as T Algorithm 1 ： Node Value based cache Decision Strategies NVD 1: Input 2: Content: A data chunk D with popularity P 3: Begin 4: Check the value of each node along path 5: if P > T 6: Cache D on the node of V-max; 7: else 8: Cache D on the node of V-min; 9: end if 10: End

Experiment and analysis A topology with 50 nodes is built under Mininet. The total storage budget is 600 objects, and 1000 files. Content popularity is modelled with a Zipf distribution Content requests are modelled as Poisson process. The cache replacement policy is based on popularity

Experiment and analysis Fig. The average P_hit of each layer in four scenarios P_hit =  hit /  request

Experiment and analysis Fig. P_hit of each node using LCE_Model vs NVD_Model

Conclusion The proposed hierarchical cache model and cache policy can improve the performance of network caching, including hit ratio and average hops of each request. For further research, the study of node value considering more information such as link bandwidth will be required.

The End