Service-Aware Optimal Caching Placement for Named Data Networking

Zhang, Ran; Liu, Jiang; Xie, Renchao; Huang, Tao; Yu, Feng

doi:10.1109/globecom38437.2019.9013161

Cited by 2 publications

(3 citation statements)

References 21 publications

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“…Authors in DPCP proposed to cache a content at alternative routers, which avoids homogenous caching to some extent. Service‐aware caching 82 and DPWCS 83 use popularity measures to cache a content.…”

Section: Literature Reviewmentioning

confidence: 99%

A source‐driven probabilistic forwarding and caching strategy in NDN and SDN‐based NDN

Iqbal

Asaduzzaman

Hoque

2022

Int J Communication

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Summary NDN forwarding strategies are mainly developed receiver‐driven, where Interest forwarding and Data (content) delivery are controlled from the consumers' viewpoint. The receiver‐driven strategies are greedy by nature and emphasize optimizing the Interest forwarding, which is far from the performance bottleneck as an Interest is of tiny size in compared with a content's size. Thus, optimizing the content delivery can improve the forwarding performance. Moreover, source‐driven optimization of content delivery can alleviate the greedy nature of its counterpart. In this work, a source‐driven forwarding strategy is proposed where the content sources respond to Interest requests in a distributed manner. The content requests hit all the sources, but the sources respond probabilistically such that the content retrieval overhead and latency are minimized. The strategy consents the nearer sources to set a high probability of reacting with the matching content. On the contrary, the distant sources answer with an Offer to save transmission overhead. Besides, a caching strategy is proposed, an integral part of the source‐driven scheme, that caches diverse contents considering the gap between successive copies and content availability while admitting new contents. Next, we extend the source‐driven probabilistic forwarding strategy to operate in SDN‐based NDN architecture. The SDN‐based solution controls the content delivery phase using the global knowledge of NDN cache states. Simulation study conducted using ndnSIM reveals that the proposed forwarding and caching strategy improves user satisfaction and network performance in terms of different performance metrics such as transmission overhead, latency, and cache hit.

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Section: Literature Reviewmentioning

confidence: 99%

A source‐driven probabilistic forwarding and caching strategy in NDN and SDN‐based NDN

Iqbal

Asaduzzaman

Hoque

2022

Int J Communication

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“…In [23], the cache allocation was formalized as a multi-objective optimization problem by minimizing both the average distance from which contents are retrieved and the peering links utilization. In [24], a service-aware caching model framework was proposed, in which the caching service matrix was used to describe the position where each user's request was served for each piece of content.…”

Section: A Homogeneous Cache Allocationmentioning

confidence: 99%

“…Although [15]- [24] increase cache utilization rate and decrease redundant content copies, they do not consider the heterogeneous cache allocation which can not only balance node load but also further increase cache utilization rate and decrease redundant content copies.…”

Section: A Homogeneous Cache Allocationmentioning

confidence: 99%

Heterogeneous CCN Cache Allocation Strategy With Collaboration Support

Jiang

2021

IEEE Access

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Content-Centric Networking (CCN) is regarded as a promising network architecture which has received the distinct interest from many global research communities thanks to its friendly structure, especially its caching technology has attracted the most widespread attention. However, the current caching strategies have some limitations, such as redundant content copies, low cache utilization rate and unbalanced node load. In order to further optimize cache, this paper investigates the classical cache allocation problem, i.e., distributing the cache capacity across some Content Routers (CRs) under a constrained and fixed total cache budget. At first, both topology information and traffic characteristics as two factors to determine the importance of CR, where the evaluation of network topology depends on degree centrality, betweenness centrality and closeness centrality while that of traffic characteristics depends on node load and interest preference. In particular, given the data redundancy due to the high-dimensional feature, increasing the complexity of computation, t-distributed Stochastic Neighbor Embedding (t-SNE) is used to reduce the dimensions of data. Then, for the CR with cache capacity, its Content Store (CS) is divided into collaborative region and non-collaborative region by a heuristic algorithm to facilitate the optimal performance, and the CS with collaboration needs to interact the cached information with its neighborhoods. Finally, the performance evaluation is driven by the real dataset over GTS-CE topology. The experimental results reveal that the proposed collaboration-supported cache allocation strategy is more efficient than two baselines, i.e., increasing cache hit ratio by 7.79%, increasing cache utilization rate by 11.31%, decreasing routing delay by 49.38% and decreasing load balance by 50.98%.

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Service-Aware Optimal Caching Placement for Named Data Networking

Cited by 2 publications

References 21 publications

A source‐driven probabilistic forwarding and caching strategy in NDN and SDN‐based NDN

A source‐driven probabilistic forwarding and caching strategy in NDN and SDN‐based NDN

Heterogeneous CCN Cache Allocation Strategy With Collaboration Support

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