A global plan policy for coherent co-operation in distributed dynamic load balancing algorithms

Abstract

Distributed-controlled dynamic load balancing algorithms are known to have several advantages over centralized algorithms such as scalability, and fault tolerance. Distributed implies that the control is decentralized and that a copy of the algorithm (called a scheduler) is replicated on each host of the network. However, distributed control also contributes to the lack of global goals and lack of coherence. This paper presents a new algorithm called DGP (decentralized global plans) that addresses the problem of coherence and co-ordination in distributed dynamic load balancing algorithms. The DGP algorithm is based on a strategy called global plans (GP), and aims at maintaining all computational loads of a distributed system within a band called delta . The rationale for the design of DGP is to allow each scheduler to consider the actions of its peer schedulers. With this level of co-ordination, the schedulers can act more as a coherent team. This new approach first explicitly specifies a global goal and then designs a strategy around this global goal such that each scheduler (i) takes into account local decisions made by other schedulers; (ii) takes into account the effect of its local decisions on the overall system and (iii) ensures load balancing. An experimental evaluation of DGP with two other well known dynamic load balancing algorithms published in the literature shows that DGP performs consistently better. More significantly, the results indicate that the global plan approach provides a better framework for the design of distributed dynamic load balancing algorithms.