Loading [MathJax]/extensions/MathMenu.js
Jointly Optimizing Content Caching and Recommendations in Small Cell Networks | IEEE Journals & Magazine | IEEE Xplore

Jointly Optimizing Content Caching and Recommendations in Small Cell Networks


Abstract:

Caching decisions typically seek to cache content that satisfies the maximum possible demand aggregated over all users. Recommendation systems, on the contrary, focus on ...Show More

Abstract:

Caching decisions typically seek to cache content that satisfies the maximum possible demand aggregated over all users. Recommendation systems, on the contrary, focus on individual users and recommend to them appealing content in order to elicit further content consumption. In our paper, we explore how these, phenomenally conflicting, objectives can be jointly addressed. First, we formulate an optimization problem for the joint caching and recommendation decisions, aiming to maximize the cache hit ratio under minimal controllable distortion of the inherent user content preferences by the issued recommendations. Then, we prove that the problem is NP-complete and that its objective function lacks those monotonicity and submodularity properties that would guarantee its approximability. Hence, we proceed to introduce a simpler heuristic algorithm that essentially serves as a form of lightweight control over recommendations so that they are both appealing to end-users and friendly to network resources. Finally, we draw on both analysis and simulations with real and synthetic datasets to evaluate the performance of the algorithm. We point out its fundamental properties, provide bounds for the achieved cache hit ratio, and study its sensitivity to its own as well as system-level parameters.
Published in: IEEE Transactions on Mobile Computing ( Volume: 18, Issue: 1, 01 January 2019)
Page(s): 125 - 138
Date of Publication: 30 April 2018

ISSN Information:

Funding Agency:


Contact IEEE to Subscribe

References

References is not available for this document.