Coordinating In-Network Caching in Content-Centric Networks: Model and Analysis

Li, Yanhua; Xie, Haiyong; Wen, Yonggang; Zhang, Zhi-Li

doi:10.1109/icdcs.2013.71

Cited by 62 publications

(46 citation statements)

References 33 publications

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“…Yanhua et al [6] have derived a model and give a solid analysis to determine how to divide caching capacity for conducting coordinated caching scheme in NDN. The decision is mainly based on tradeoff between cost of exchanging information among routers and the network performance.…”

Section: System Model and Methodologymentioning

confidence: 99%

“…The simulation is done on top of Abilene topology. Abilene is an educational backbone network established by Internet 2 group [24] and is also widely used for evaluating cache performance [5] [6]. The topology consists of 11 nodes all located in North America as shown in Figure 4.…”

Section: Environmentmentioning

confidence: 99%

“…By using this hybrid caching policy, we claim that it can avoid drawbacks and take advantages from both types of caching. For determining the capacity split ratio, Yanhua Li et al [6] gave an analysis by considering the trade-off between communication cost and routing performance. We consult their model and apply the concept in our study with modifications to decide the partitioning fraction.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

A Hybrid Coordination Approach of In-network Caching for Named Data Networking

Chang¹,

Chang²

2016

IJFGCN

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Section: System Model and Methodologymentioning

confidence: 99%

Section: Environmentmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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A Hybrid Coordination Approach of In-network Caching for Named Data Networking

Chang¹,

Chang²

2016

IJFGCN

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“…In order to reduce the computational complexity of the replication process, partially coordinated replication was introduced in [25]. Nodes use a fraction of their cache capacity to store content in a coordinated manner (CDN-like replication) and the remaining capacity is used to cache the locally most popular content.…”

Section: Reducing the Complexity Of Replication Processmentioning

confidence: 99%

Low complexity content replication through clustering in Content-Delivery Networks

et al. 2017

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Contemporary Content Delivery Networks (CDN) handle a vast number of content items. At such a scale, the replication schemes require a significant amount of time to calculate and realize cache updates, and hence they are impractical in highly-dynamic environments. This paper introduces cluster-based replication, whereby content items are organized in clusters according to a set of features, given by the cache/network management entity. Each cluster is treated as a single item with certain attributes, e.g., size, popularity, etc. and it is then altogether replicated in network caches so as to minimize overall network traffic. Clustering items reduces replication complexity; hence it enables faster and more frequent caches updates, and it facilitates more accurate tracking of content popularity. However, clustering introduces some performance loss because replication of clusters is more coarse-grained compared to replication of individual items. This tradeoff can be addressed through proper selection of the number and composition of clusters. Due to the fact that the exact optimal number of clusters cannot be derived analytically, an efficient approximation method is proposed. Extensive numerical evaluations of time-varying content popularity scenarios allow to argue that the proposed approach reduces core network traffic, while being robust to errors in popularity estimation.

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“…The cache decision scheme focuses on choosing appropriate caching locations in the network for particular contents to reduce the cache redundance and to improve the cache utilization. Recent cache decision studies mainly depend on the content popularity [14][15][16][17][18][19], node features, such as node capability and importance [20][21][22][23], and cache coordination [24][25][26]. In addition, a per-fetching based cache decision scheme specifically for adaptive video streaming is proposed in [27], which aims to maintain high quality video playback to the clients.…”

Section: Introductionmentioning

confidence: 99%

Request Expectation Index Based Cache Replacement Algorithm for Streaming Content Delivery over ICN

Nakazato

Ahmed

2017

Future Internet

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Abstract:Since the content delivery unit over Information-Centric Networking (ICN) has shifted from files to the segments of a file named chunks, solely either file-level or chunk-level request probability is insufficient for ICN cache management. In this paper, a Request Expectation Index (RXI) based cache replacement algorithm for streaming content delivery is proposed. In this algorithm, RXI is introduced to serve as a fine-grained and unified estimation criteria of possible future request probability for cached chunks. RXI is customized for streaming content delivery by adopting both file-level and chunk-level request probability and considering the dynamically varied request status at each route as well. Compared to prior work, the proposed algorithm evicts the chunk with the minimum expectation of future request to maintain a high cache utilization. Additionally, simulation results demonstrate that the RXI-based algorithm can remarkably enhance the streaming content delivery performance and can be deployed in complex network scenarios. The proposed results validate that, by taking fine-grained request probability and request status into consideration, the customized in-network caching algorithm can improve the ICN streaming content delivery performance by high cache utilization, fast content delivery, and lower network traffic.

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Coordinating In-Network Caching in Content-Centric Networks: Model and Analysis

Cited by 62 publications

References 33 publications

A Hybrid Coordination Approach of In-network Caching for Named Data Networking

A Hybrid Coordination Approach of In-network Caching for Named Data Networking

Low complexity content replication through clustering in Content-Delivery Networks

Request Expectation Index Based Cache Replacement Algorithm for Streaming Content Delivery over ICN

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