Inter-Chunk Popularity-Based Edge-First Caching in Content-Centric Networking

Lim, Sung-Hwa; Ko, Young-Bae; Jung, Gue-Hwan; Kim, Jae-Hoon; Jang, Myeong-Wuk

doi:10.1109/lcomm.2014.2329482

Cited by 34 publications

(13 citation statements)

References 9 publications

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“…In addition, a centrality-based caching algorithm through using the betweenness centrality is devised to improve the caching gain, where only part of the nodes are used to cache data. Based on this consideration, many researches have taken content popularity as a consideration in selective caching strategies [20,21]. In [20], WAVE strategy is proposed, which is a popularity-based cooperative caching strategy.…”

Section: Related Workmentioning

confidence: 99%

Mitigating Cache Pollution Attack in Information Centric Mobile Internet

2019

KSII TIIS

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Information centric mobile network can significantly improve the data retrieving efficiency by caching contents at mobile edge. However, the cache pollution attack can affect the data obtaining process severely by requiring unpopular contents deliberately. To tackle the problem, we design an algorithm of mitigating cache pollution attacks in information centric mobile network. Particularly, the content popularity distribution statistic is proposed to detect abnormal behavior. Then a probabilistic caching strategy based on abnormal behavior is applied to dynamically maintain the steady-state distribution for content visiting probability and achieve the purpose of defense. The experimental results show that the proposed scheme can achieve higher request hit ratio and smaller latency for false locality content pollution attack than the CacheShield approach and the baseline approach where no mitigation approach is applied.

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Section: Related Workmentioning

confidence: 99%

Mitigating Cache Pollution Attack in Information Centric Mobile Internet

2019

KSII TIIS

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“…As a first step, let us define f i (τ ) : [0; 1] → [0; 1] as a one-to-one function such that the permuted audience retention rate function R i (τ ) := R i (f −1 i (τ )) is non decreasing. The function f i is a permutation function that orders the video parts in order of decreasing popularity, such that f i (τ ) < f i (τ ) if and only if R i (τ ) > R i (τ ) 11 . Then, R i is the outcome of such permutation.…”

Section: B Proof Of Theoremmentioning

confidence: 99%

Adapting caching to audience retention rate

Maggi

Gkatzikis

Paschos

et al. 2018

Computer Communications

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“…When request received, the node with a hit will use the information to compute the optimal content placement policy. S. H. Lim et al [17] proposed Inter-chunk Popularity-based Edge-first Caching (IPEC). IPEC places popular contents at edge cache nodes with a pipeline fashion.…”

Section: Explicit Coordinationmentioning

confidence: 99%

“…Finally, we evaluate the fairness among all the contents by using the Jain"s fairness index as (17).…”

Section: Figure 9 Normalized Link Trafficmentioning

confidence: 99%