컨텐트 중심 네트워킹을 위한 효율적인 라우팅 및 캐시 관리 기법
DC Field | Value | Language |
---|---|---|
dc.contributor.advisor | 고영배 | - |
dc.contributor.author | Lee, Sung Won | - |
dc.date.accessioned | 2018-11-08T08:10:16Z | - |
dc.date.available | 2018-11-08T08:10:16Z | - |
dc.date.issued | 2014-02 | - |
dc.identifier.other | 16233 | - |
dc.identifier.uri | https://dspace.ajou.ac.kr/handle/2018.oak/11081 | - |
dc.description | 학위논문(박사)--아주대학교 일반대학원 :컴퓨터공학과,2014. 2 | - |
dc.description.tableofcontents | CHAPTER I INTRODUCTION 1 I.A. Background 1 I.B. Summary of the Thesis 2 CHAPTER II RELATED WORK 6 II.A. Taxonomy in Content-Centric Networking 6 II.B. In-network Caching 8 II.C. Content-based Routing 11 II.D. Position of Proposed Schemes 12 CHAPTER III LIGHTWEIGHT PREFIX-BASED ROUTING 13 III.A. Introduction 13 III.B. Problem Definition 15 III.C. Lightweight Prefix-based Routing (LPR) 18 III.C.1. Neighbor Discovery 18 III.C.2. Lightweight Route Discovery 20 III.C.3. FIB Construction and Prefix-based Routing 22 III.D. Performance Evaluation 24 III.D.1. Simulation Environments 24 III.D.2. Simulation Results 26 CHAPTER IV PHEROMONE-BASED CACHE REPLACEMENT AND FORWARDING 29 IV.A. Introduction 29 IV.B. Problem Definition 30 IV.C. Pheromone-based CCN (P-CCN) 33 IV.C.1. Pheromone Estimation and Propagation 34 IV.C.2. Pheromone-based Cache Replacement 36 IV.C.3. Pheromone-based Forwarding 38 IV.D. Performance Evaluation 43 IV.D.1. Simulation Environments 43 IV.D.2. Simulation Results 45 CHAPTER V CACHE CAPACITY-AWARE CCN 48 V.A. Introduction 48 V.B. Problem Definition 49 V.C. Cache Capacity-aware CCN (CC-CCN) 54 V.C.1. Cache Capacity Estimation 54 V.C.2. Selective Caching 57 V.C.3. Cache-aware Routing 59 V.D. Performance Evaluation 61 V.D.1. Simulation Environments 61 V.D.2. Simulation Results 62 CHAPTER VI CONCLUSION AND FUTURE WORKS 68 APPENDIX: OPNET CCN SIMULATOR 72 A. Introduction 72 B. Problem Definition 72 C. OPNET CCN Simulator 74 1. Node Models 75 2. System Parameter Management 78 3. CCN Topology Generation 79 D. Verification of OPNET CCN Simulator 80 1. CCN Traffic Generator 80 2. CCN Route Support and Forwarding Engine 82 3. Content Store (Cache Management) 83 | - |
dc.language.iso | eng | - |
dc.publisher | The Graduate School, Ajou University | - |
dc.rights | 아주대학교 논문은 저작권에 의해 보호받습니다. | - |
dc.title | 컨텐트 중심 네트워킹을 위한 효율적인 라우팅 및 캐시 관리 기법 | - |
dc.title.alternative | Sung-Won Lee | - |
dc.type | Thesis | - |
dc.contributor.affiliation | 아주대학교 일반대학원 | - |
dc.contributor.alternativeName | Sung-Won Lee | - |
dc.contributor.department | 일반대학원 컴퓨터공학과 | - |
dc.date.awarded | 2014. 2 | - |
dc.description.degree | Doctoral | - |
dc.identifier.localId | 609821 | - |
dc.identifier.url | http://dcoll.ajou.ac.kr:9080/dcollection/jsp/common/DcLoOrgPer.jsp?sItemId=000000016233 | - |
dc.subject.keyword | 컨텐트 중심 네트워킹 | - |
dc.subject.keyword | 라우팅 | - |
dc.subject.keyword | 캐시 관리 | - |
dc.subject.keyword | Content Centric Networking | - |
dc.subject.keyword | Routing | - |
dc.subject.keyword | Forwarding | - |
dc.subject.keyword | Cache Management | - |
dc.description.alternativeAbstract | Content-Centric Networking (CCN) is a new, redesigned communication networking architecture of the Internet to replace traditional host-centric communication with content-centric communication. CCN proposes an architecture which is centered on the content itself, without regard to where it is physically located. The CCN architecture includes an in-network caching and a content-based routing as main features where every content has its own name as an identifier. Although content-centric networking embraces caching and content-based routing, there is little work on the comprehensive interaction between them. Most ongoing research on content-centric networking is centered on independent research item among emerging contents analysis, content naming, caching technology, and content-oriented routing. Therefore, we have an aim for synergy between cache management and content-based routing. To reliably evaluate CCN performances, we developed OPNET CCN Simulator which is easy to configure diverse network environments. It covers most functionality of existing CCN simulators and overcome their drawbacks by providing GUI-based configuration, heterogeneous cache management and CCN topology generator software that allows users to generate diverse Internet-like topologies with node naming. Then, we propose the lightweight prefix-based routing protocol with a consideration of the complexity of the longest-prefix matching in CCN. The proposed scheme limits the area of route discovery to reduce the number of entries in the routing table and FIB with aggregation mechanism. Furthermore, the LPR provides a method of using inter-hierarchical connections to reduce overall route lengths. As an interactive mechanism between cache replacement and cache-aware routing, the pheromone-based cache replacement and forwarding algorithm is proposed with a new metric, pheromone. This metric represents a degree of content concentration for a particular category. In addition, the metric is utilized to diverse the cached contents in the local area and to forward Interest to a router which has been expected to cache the required content. Then, the forwarding algorithm leads to concentrate contents of the particular category in the router even if cache miss occurs. In addition, the cache capacity-aware content centric networking is proposed for an interaction between cache replication and cache-aware routing. This proposal considers cache capacity as a main metric which is a supportable caching space and can be defined with a willingness degree by the previous proposal. The proposed scheme is composed of a selective caching and a cache-aware routing algorithm which provides deterministic cache-awareness without any control message. Then, with analysis about CCN performance under flash crowd, the CC-CCN mechanism is extended with flash crowd detection and related confrontational procedures to reduce network impact by flash crowd. Simulation studies for each proposed scheme show that content-based routing mechanisms in both sides of server-aware and cache-aware routing need little control overhead and help cache hit ratio to be improved. In addition, a synergy effect between the proposed cache management algorithms and the cache-aware routing makes significant caching performance improvement and network load reduction even in flash crowd effect. | - |
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