HighThroughput and LowLatency Distributed Management Proxy for KeyValue Store Over 100Gbps Ethernet on FPGA Keyvalue store (KVS) is one of the most important NoSQL databases. To satisfy the demand for growing data in the era of big data, distributed KVS systems that enhance the scalability of storage systems are widely used in recent years. Hence, highperformance distributed management that implements functions such as data partitioning and message distribution is indispensable. In this paper, we present a highthroughput and lowlatency distributed management proxy (DMP) for keyvalue store over 100Gbps Ethernet (100GbE). The proxybased design which has flexibility and generality is fully implemented on FPGA. In the DMP, the consistent hashing algorithm is designed to partition KVS packets in pipeline. Then a hardware network offload engine is proposed to transmit network messages over 100GbE on FPGA to reduce the latency penalties caused by consistent hashing. Besides, in order to utilize the 100Gbps Ethernet bandwidth, four fully parallel and pipelined data paths are implemented in the DMP on an FPGA. The experimental results show that the peak throughput of the proposed DMP can reach 77.4 million queries per second (QPS), and the latency can achieve as low as 0.8xc2xb5s for the smallsize packets, which is 7.4x higher and 23x faster respectively than the software proxy implementation accelerated by Intelu0027s DPDK.

KVSwitch: An Innetwork Load Balancer for KeyValue Stores Todayxe2x80x99s cloudbased online services are underpinned by distributed keyvalue stores (KVSs). Keys and values are distributed across backend servers in such scaleout systems. One primary reallife performance bottleneck occurs when storage servers suffer from load imbalance under skewed workloads. In this paper, we present KVSwitch, a centralized selfmanaging load balancer that leverages the power and flexibility of emerging programmable switches. The balance is achieved through dynamically predicting the hot items and creating replication strategies according to KVS loading. To overcome the challenges in realizing KVSwitch given the limitations of the switch hardware, we decompose KVSwitchxe2x80x99s functions and carefully design them for the heterogeneous processors inside the switch. We prototype KVSwitch in a Tofino switch. Experimental results show that our solution can effectively keep the KVS servers balanced even under highly skewed workloads. Furthermore, KVSwitch only replicates 70% of hot items and consumes 9.88% of server memory rather than simply replicating all hot items to each server.