Scalable Request Routing with Next-Neighbor Load Sharing in Multi-Server Environments
Chung‐Min Chen, Yibei Ling, Marcus Pang, Wai Chen, Shengwei Cai, Yuuichi Suwa, O. Altintas
Abstract
Chung‐Min Chen, Yibei Ling, Marcus Pang, Wai Chen, Shengwei Cai, Yuuichi Suwa, O. Altintas
Abstract
Load balancing for distributed servers is a common issue in many applications and has been extensively studied. Several distributed load balancing schemes have been proposed that proactively route individual requests to appropriate servers to best balance the load and shorten request response time. These schemes do not require a centralized load balancer. Instead, each server is responsible for determining, for each request it receives from a client, to which server in the pool the request should be forwarded for processing. We propose a new request routing scheme that is more scalable to increasing number of servers and request load than the existing schemes. The method combines random server selection and next-neighbor load sharing techniques that together prevent the staleness of load information from building up when the number of servers increases. Our simulation shows that it outperforms existing schemes under a piggyback-based load update model.
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Load balancing for distributed servers is a common issue in many applications and has been extensively studied. Several distributed load balancing schemes have been proposed that proactively route individual requests to appropriate servers to best balance the load and shorten request response time. These schemes do not require a centralized load balancer. Instead, each server is responsible for determining, for each request it receives from a client, to which server in the pool the request should be forwarded for processing. We propose a new request routing scheme that is more scalable to increasing number of servers and request load than the existing schemes. The method combines random server selection and next-neighbor load sharing techniques that together prevent the staleness of load information from building up when the number of servers increases. Our simulation shows that it outperforms existing schemes under a piggyback-based load update model.
Key concepts: Round-robin DNS, Server, Computer science, Scalability, Load balancing (electrical power), Load sharing, Computer network, Distributed computing