Abstract
The pay-as-you-go service model impels cloud customers to reduce the usage cost of bandwidth. Traffic Redundancy Elimination (TRE) has been shown to be an effective solution for reducing bandwidth costs, and has recently captured significant attention in the cloud environment. By studying the TRE techniques with a trace driven approach, we found that solely using either sender-based TRE or receiver-based TRE cannot simultaneously capture traffic redundancy in both short-term (time span of seconds) and long-term (time span of hours or days) data redundancy, which concurrently appear in the traffic. Additionally, the TRE efficiency of existing receiver-based TRE solution is susceptible to data changes compared to historical data in the cache. In this paper, we propose a sender and receiver Cooperative end-to-end TRE solution (CoRE) for efficiently identifying and removing both short-term and long-term redundancy. Through a two-layer redundancy detection design and one single pass algorithm for chunking and fingerprinting, CoRE efficiently carries out cooperative operations between the sender and the receiver. By extensive evaluation with several real traces, we show that CoRE is able to identify both short-term and longterm redundancy with low additional cost, while ensuring TRE efficiency from data changes.
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