Abstract

The in-network caching is a considerably significant feature of Information-Centric Networking (ICN), especially the heterogeneous-cached ICN has been widely investigated since it accords with the actual network deployment. For the heterogeneous-cached ICN, although there have been many proposals to improve network performance, it is very difficult for these approaches to reach the optimal network performance with multiple metrics consideration. Therefore, in this paper, we propose a heuristic transferring strategy which selects some Content Routers (CRs) and combines them to facilitate the optimal network performance under a constrained total cache budget. At first, we quantify energy consumption, CR load, cache hit ratio and throughput, because the optimal network performance depends on four objects, i.e., minimizing energy consumption and CRs load as well as maximizing cache hit ratio and throughput. Then, based on the given network constraints and objects, we convert the CR transferring problem into 0-1 Knapsack Problem (KP01). Finally, in order to effectively obtain the optimal solution, we propose a heuristic approach based on Ant Colony Optimization (ACO) and expectation efficiency to solve KP01. The simulation is driven by the real YouTube dataset from campus network measurement over GTS and Deltacom topologies, and the experimental results demonstrate that the proposed strategy is more efficient compared to three baselines.

Highlights

  • Information-Centric Networking (ICN) has attracted much attention from the global research communities in the past decade (2009-2019) due to its clean-slate architecture [1], [2]

  • This paper investigates CRs Transferring Problem (CTP) in ICN, and the main contributions are summarized as follows. (i) We quantify energy consumption, Content Routers (CRs) load, cache hit ratio and throughput and use them as four evaluation metrics of the optimal network performance. (ii) Based on minimizing energy consumption and CR load as well as maximizing cache hit ratio and throughput, we convert the multiple-objective optimization problem into KP01. (iii) We propose a heuristic approach based on Ant Colony Optimization (ACO) and expectation efficiency to solve KP01 so that the optimal solution can be obtained effectively

  • SETUP The proposed Heuristic transferring strategy based on ACO and Expectation Efficiency (HAEE) is implemented via two parts: one is the implementation of CTP based on NS3 [40] and the other one is the implementation of KP01 based on Visual Studio, running on a personal computer with Intel(R) core(TM)i5-6200u, CPU2.92 GHZ, 4GB RAM

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Summary

INTRODUCTION

Information-Centric Networking (ICN) has attracted much attention from the global research communities in the past decade (2009-2019) due to its clean-slate architecture [1], [2]. A CR with 10TB cache can cost 30,0000 dollars and consume 500W at the full work [8] It means that the research on cache allocation and CRs transferring is more significant than that on the other two problems. By reviewing the above statements, CRs Transferring Problem (CTP) is described as: selecting some CRs from all CRs and combining them to facilitate the optimal network performance under a constrained total cache budget. The exact approach can always produce the optimal solution, it performs the poor convergence when deploying the large-scale ICN network. Under such context, the heuristic approach is usually employed to solve KP01.

RELATED WORK
CTP FORMALIZATION
METRICS QUANTIFICATION
HEURISTIC STRATEGY
PRELIMINARY
ACO FOR INITIAL CRs
CONCLUSION
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