Load Balancing Memcached Traffic Using Software Defined Networking

2017 IFIP NETWORKING CONFERENCE (IFIP NETWORKING) AND WORKSHOPS(2017)

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摘要
Memcached is an in-memory key-value distributed caching solution, commonly used by web servers for fast content delivery. Keys with their values are distributed between Memcached servers using a consistent hashing technique, resulting in an even distribution (of keys) among the servers. However, as small number of keys are significantly more popular than others (a.k.a., hot keys), even distribution of keys may cause a significantly different request load on the Memcached servers, which, in turn, causes substantial performance degradation.Previous solutions to this problem require complex application level solutions and extra servers. In this paper, we propose MBalancer-a simple L7 load balancing scheme for Memcached that can be seamlessly integrated into Memcached architectures running over Software-Defined Networks (SDN). In a nutshell, MBalancer runs as an SDN application and duplicates the hot keys to many (or all) Memcached servers. The SDN controller updates the SDN switches forwarding tables and uses SDN ready-made load balancing capabilities. Thus, no change is required to Memcached clients or servers.Our analysis shows that with minimal overhead for storing a few extra keys, the number of requests per server is close to balanced (assuming requests for keys follows a Zipf distribution). Moreover, we have implemented MBalancer on a hardware-based OpenFlow switch. As MBalancer offloads requests from bottleneck Memcached servers, our experiments show that it achieves significant throughput boost and latency reduction.
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关键词
extra servers,simple L7 load balancing scheme,Memcached architectures,Software-Defined Networks,SDN,load balancing capabilities,Memcached clients,Zipf distribution,memcached traffic,in-memory key-value distributed caching solution,web servers,complex application level solutions,request load,SDN ready-made load balancing capabilities,Memcached servers,latency reduction
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