1. 《 Hierarchical Caching Management for Software Defined Content Network based on Node Value 》 Reporter ： Jing Liu ， China Affiliation ： University of Science and Technology of China Email ： ljsmile@mail.ustc.edu.cn

2. 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 !

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

4. 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

5. SDCN over POF Fig. SDCN Architecture

6. 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

7. 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

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

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

10. Hierarchical Cache Model Fig. Simple topology example For S1: the sum of the shortest path : 2+1+3+2+2+3+4=17

11. NodeSumDiLi  Li ViRank S1170.83342210.020.8534226 S2170.83342210.020.8534227 S3111.28801540.081.3680152 S4160.88551110.020.9055115 S5131.08985920.041.1298593 S6101.41681740.081.4968171 S7150.94454520.040.9845454 S8200.70840810.020.7284088 Hierarchical Cache Model Table 1. Calculation of Node Value (  is 0.02 )

12. 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

13. Hierarchical Cache Model Fig The Hierarchical Model

14. 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

15. 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

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

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

18. 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.

19. The End