An autonomic network-aware scheduling architecture for grid computing

Grid technologies have enabled the aggregation of geographically distributed resources, in the context of a particular application. The network remains an important requirement for any Grid application, as entities involved in a Grid system (such as users, services, and data) need to communicate with each other over a network. The performance of the network must therefore be considered when carrying out tasks such as scheduling, migration or monitoring of jobs. Surprisingly, many existing QoS efforts ignore the network and focus instead on processor workload and disk access. Making use of the network in an efficient and fault tolerance manner, in the context of such existing research, leads to a significant number of research challenges. One way to address these problems is to make Grid middleware incorporate the concept of autonomic systems. Such a change would involve the development of "self-configuring" systems that are able to make decisions autonomously, and adapt themselves as the system status changes. We propose an autonomic network-aware scheduling infrastructure that is capable of adapting its behavior to the current status of the environment.