A DETERMINISTIC LATENCY NAME RESOLUTION FRAMEWORK USING NETWORK PARTITIONING FOR 5G-ICN INTEGRATION

被引:13
作者
Liao, Yi [1 ,2 ]
Sheng, Yiqiang [1 ,2 ]
Wang, Jinlin [1 ,2 ]
机构
[1] Chinese Acad Sci, Inst Acoust, Natl Network New Media Engn Res Ctr, 21,North 4th Ring Rd, Beijing 100190, Peoples R China
[2] Univ Chinese Acad Sci, Sch Elect Elect & Commun Engn, 19 A,Yuquan Rd, Beijing 100049, Peoples R China
来源
INTERNATIONAL JOURNAL OF INNOVATIVE COMPUTING INFORMATION AND CONTROL | 2019年 / 15卷 / 05期
关键词
5G; ICN; Deterministic low latency; Name resolution; Network partitioning; ROUTING SCHEME; INFORMATION;
D O I
10.24507/ijicic.15.05.1865
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Achieving low latency is one of the goals of 5G networks and beyond. We consider Information-Centric Networking (ICN) as a candidate network architecture to realize 5G objectives. The trend of the future network is transformed from best-effort to deterministic transmission. In this paper, we introduce the concept of deterministic latency into the Name Resolution System (NRS) of ICN and propose a Deterministic Latency Name Resolution (DLNR) framework to provide name resolution service with deterministic low latency to satisfy the delay sensitive requirement of NRS. As one of the key techniques, firstly, a Latency-aware Hierarchical elastic area Partitioning (LHP) algorithm is designed to solve the problem of resolver placement with bounded and deterministic transmission latency conditions. Secondly, we design corresponding latency demand-aware name registration and resolution schemes so that constant forwarding hops can be realized. Simulation results show that deterministic low latency name resolution service is achieved by Enhanced NRS (ENRS), which is a system developed to realize the framework of DLNR. Furthermore, the average response latency of ENRS outperforms the Resolution Handler (RH) of DONA 25.2% at best. The query overhead of ENRS is stable due to the deterministic request-forwarding, and the single query overhead of ENRS is reduced by up to 30 times compared with KNN-DNRS.
引用
收藏
页码:1865 / 1880
页数:16
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