Grid Computing is a large set of geographically distributed heterogeneous resources for
solving problems in science and engineering. Resource selection is one of the important key …

Data transport infrastructures based on wavelength-routed optical networks are appealing to
the grid community because they can provide a reconfigurable and high-bandwidth network …

Scheduling many tasks in environments of millions of unreliable nodes is a challenging
problem. To our knowledge, no work in the literature has proposed a solution that also …

We address the problem of discovering frequent items in unstructured P2P networks which
is relevant for several distributed services such as cache management, data replication …

Resource discovery in large-scale Peer-to-Peer (P2P) networks is challenging due to lack of
effective methods for guiding queries. Based on the observation that the effectiveness of …

Meta-scheduling in lambda grids is often a complex task because it typically comprises the
discovery, monitoring, co-allocation, and orchestration of networking and computing …

Automated workflows are the key concept of big data pipelines in science, engineering and
enterprise applications. The performance analysis of automated workflows is an important …

In today's large-scale distributed cloud environments, there are usually multiple layers
involved when performing orchestration. It is important to decide what capability is visible at …

A meta-scheduler is used to efficiently assign tasks to distributed resources. Additionally, the
Internet is often used to share the data of tasks on the resources. Throughput prediction will …

Information aggregation is a method for reducing the information being exchanged between
Grid networks. Resource manager takes the scheduling decisions by using this aggregated …