Print Email Facebook Twitter Online Caching through Optimistic Online Mirror Descent Title Online Caching through Optimistic Online Mirror Descent Author Admiraal, Gijs (TU Delft Electrical Engineering, Mathematics and Computer Science) Contributor Iosifidis, G. (mentor) Mhaisen, N. (graduation committee) Degree granting institution Delft University of Technology Programme Computer Science and Engineering Project CSE3000 Research Project Date 2022-06-22 Abstract The advent of wireless networks such as content distribution networks and edge computing networks calls for more effective online caching policies. Traditional policies lose performance since these new networks deal with highly non-stationary requests and frequent popularity shifts. Consequently, a new framework called Online Convex Optimization (OCO), which does not assume the request pattern, has recently been used to tackle the online caching problem. Besides, in many practical scenarios, a request prediction of unknown quality is available. This paper will leverage that and proposes a new online caching policy that uses these predictions. This policy will use the Optimistic Online Mirror Descent (OOMD) algorithm to solve the OCO problem. The policy will still obtain the same regret bound as its non-optimistic counterpart up to some constant even if the predictions are not accurate. The performance of the proposed policy is evaluated and compared with previous OCO-based policies with the use of trace-driven numerical tests. Subject Caching policiesOnline Convex OptimizationRecommendations To reference this document use: http://resolver.tudelft.nl/uuid:a8c24164-67aa-4df3-bdf5-777450d8fd6d Part of collection Student theses Document type bachelor thesis Rights © 2022 Gijs Admiraal Files PDF Research_Project_Paper_Gi ... _final.pdf 1015.92 KB Close viewer /islandora/object/uuid:a8c24164-67aa-4df3-bdf5-777450d8fd6d/datastream/OBJ/view