Brame groups relational tuples into workload-aware blocks and schedules block placement across cloud, edge, and terminal tiers, reporting improved query hit rates over data-aware baselines on two datasets.
An Adaptive Dynamic Replacement Approach for a Multicast based Popularity Aware Prefix Cache Memory System
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abstract
In this paper we have proposed an adaptive dynamic cache replacement algorithm for a multimedia servers cache system. The goal is to achieve an effective utilization of the cache memory which stores the prefix of popular videos. A replacement policy is usually evaluated using hit ratio, the frequency with which any video is requested. Usually discarding the least recently used page is the policy of choice in cache management. The adaptive dynamic replacement approach for prefix cache is a self tuning, low overhead algorithm that responds online to changing access patterns. It constantly balances between lru and lfu to improve combined result. It automatically adapts to evolving workloads. Since in our algorithm we have considered a prefix caching with multicast transmission of popular objects it utilizes the hard disk and network bandwidth efficiently and increases the number of requests being served.
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Brame: Hierarchical Data Management Framework for Cloud-Edge-Device Collaboration
Brame groups relational tuples into workload-aware blocks and schedules block placement across cloud, edge, and terminal tiers, reporting improved query hit rates over data-aware baselines on two datasets.