Online Learning Models for Content Popularity Prediction in Wireless Edge Caching

Garg, Navneet; Sellathurai, Mathini; Bettagere, Bharath; Bhatia, Vimal; Ratnarajah, Tharmalingam

doi:10.1109/ieeeconf44664.2019.9048682

Cited by 6 publications

(4 citation statements)

References 37 publications

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“…In addition, to understand the benefits of multipoint multicast caching, we compare to single point caching. In [6], [24], each user is served by its nearest caching BS, and bandwidth is not allocated among files. Hence, for any file request, all BSs which cache that file, except the nearest BS, interfere with the desired signal.…”

Section: Simulation Results and Discussionmentioning

confidence: 99%

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Cellular Network Caching Based on Multipoint Multicast Transmissions

Amidzadeh

Al-Tous

Tirkkonen

et al. 2020

GLOBECOM 2020 - 2020 IEEE Global Communications Conference

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We consider an optimal cache-placement-anddelivery-policy using Network-level Orthogonal Multipoint Multicasting (OMPMC) for wireless networks. The placement of files in caches of Base Station (BS) is based on a probabilistic model, with controlled cache placement probabilities. File delivery is based on multipoint multicast and network-based orthogonal transmission; all BSs in the network caching a file transmit it synchronously in dedicated radio resources. If the average signal-to-noise ratio associated to a file at a requesting user is less than a threshold, the request is in outage. We derive a closed-form expression for the outage probability for a network modeled as a Poisson Point Process. An optimal caching policy is solved from an optimization problem, and compared to a threshold-based policy, suboptimal partial solutions, and single-point cache delivery. Simulation results show that exploiting OMPMC with optimal cache and bandwidth allocation significantly improves the overall outage probability as compared to single point delivery.

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Section: Simulation Results and Discussionmentioning

confidence: 99%

“…In this case each BS can simultaneously transmit several files in disjoint radio resources, so L can be greater than one. Using the outage probability expression in [24], the overall outage probability and its corresponding optimization problem can be formulated and used to obtain the optimum cache policy.…”

Section: Simulation Results and Discussionmentioning

confidence: 99%

Cellular Network Caching Based on Multipoint Multicast Transmissions

Amidzadeh

Al-Tous

Tirkkonen

et al. 2020

GLOBECOM 2020 - 2020 IEEE Global Communications Conference

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“…We denote this policy by Non-Orthogonal Single-Point (NOSP). Based on [38], the overall outage probability for this policy is:…”

Section: Single-point Multicastmentioning

confidence: 99%

Caching in Cellular Networks Based on Multipoint Multicast Transmissions

Amidzadeh

Al-Tous

Caire

et al. 2023

IEEE Trans. Wireless Commun.

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We consider cellular network caching with networkwide Orthogonal Multipoint Multicast (OMPMC) delivery. We apply a probabilistic model for content placement at the Base Stations (BSs). Content is delivered with multipoint multicast operating in file-specific orthogonal resources: all BSs caching a distinct file synchronously multicast it to requesting users in a dedicated resource. For a network modeled as a Poisson Point Process (PPP), an expression for the outage probability is derived. The outage-minimizing cache policy is found from a joint constrained optimization problem over cache placement and resource allocation. We devise principles by which the solution in one propagation environment can be generalized to another. To reduce computational complexity, we obtain a sub-optimal solution based on convex relaxation. We obtain an upper bound of the gap between the optimal and sub-optimal solutions. We compare the outage performance of OMPMC with delivery polices from the literature. Simulation results show that exploiting OMPMC with optimal cache placement and resource allocation outperforms single point cache delivery policies with a wide margin.

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“…Content update statistics evolved to become a fundamental component in the design and study of any communication network where caching and prefetching play a central role, such as content delivery networks (CDNs) and Information-centric networks (ICNs) [3][4][5], 5G networks [6][7][8][9], and wireless networks [10]. Indeed, accurate estimation of inter-update distribution is an important issue.…”

Section: Introductionmentioning

confidence: 99%

Analysis of Data Persistence in Collaborative Content Creation Systems: The Wikipedia Case

et al. 2019

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A very common problem in designing caching/prefetching systems, distribution networks, search engines, and web-crawlers is determining how long a given content lasts before being updated, i.e., its update frequency. Indeed, while some content is not frequently updated (e.g., videos), in other cases revisions periodically invalidate contents. In this work, we present an analysis of Wikipedia, currently the 5th most visited website in the world, evaluating the statistics of updates of its pages and their relationship with page view statistics. We discovered that the number of updates of a page follows a lognormal distribution. We provide fitting parameters as well as a goodness of fit analysis, showing the statistical significance of the model to describe the empirical data. We perform an analysis of the views-updates relationship, showing that in a time period of a month, there is a lack of evident correlation between the most updated pages and the most viewed pages. However, observing specific pages, we show that there is a strong correlation between the peaks of views and updates, and we find that in more than 50% of cases, the time difference between the two peaks is less than a week. This reflects the underlying process whereby an event causes both an update and a visit peak that occurs with different time delays. This behavior can pave the way for predictive traffic analysis applications based on content update statistics. Finally, we show how the model can be used to evaluate the performance of an in-network caching scenario.

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Online Learning Models for Content Popularity Prediction in Wireless Edge Caching

Cited by 6 publications

References 37 publications

Cellular Network Caching Based on Multipoint Multicast Transmissions

Cellular Network Caching Based on Multipoint Multicast Transmissions

Caching in Cellular Networks Based on Multipoint Multicast Transmissions

Analysis of Data Persistence in Collaborative Content Creation Systems: The Wikipedia Case

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