Today, companies and data centers are moving towards distributed and serverless storage systems instead of traditional file systems. As a result of such transition, allocating sufficient resources to users and parties to satisfy their service level demands has become crucial in distributed storage systems. The Quality of Service (QoS) is a research area that tries to tackle such challenges. The schedulability of system components and requests is of great importance to achieve the QoS goals in a distributed storage. Many QoS solutions are designed and implemented through request scheduling at different levels of system architecture.However, the bufferbloat phenomenon in storage backends can compromise the request schedulability of the system. In a storage server, bufferbloat happens when the server submits all requests immediately to the storage backend due to a too large buffer in the storage backend. In recent decades, many research works tried to solve the bufferbloat problem for network systems.Nevertheless, none of these works are suitable for storage system environments and workloads. This paper presents the SF_CoDel algorithm, an adaptive extension of the Controlled Delay (CoDel) algorithm, to mitigate the bufferbloat for different workloads in storage systems. SF_CoDel manages this purpose by controlling the amount of work submitted to the storage backend. The evaluation of our algorithm indicates that SF_CoDel can mitigate the bufferbloat in storage servers.