Metaserver Locality and Scalability in a Distributed NFS

Abstract

The leveraging of existing storage space in a cluster is a desirable characteristic of a parallel file system. While undoubtedly an advantage from the point of view of resource management, this possibility may face the administrator with a wide variety of alternatives for configuring the file server, whose optimal layout is not always easy to devise. Given the diversity of parameters such as the number of processors on each node and the capacity and topology of the network, decisions regarding the locality of server components like metadata servers and I/O servers have a direct impact on performance and scalability. In this paper, we explore the capabilities of the dNFSp file system on a large cluster installation, observing how scalable the system behaves in different scenarios and comparing it to a dedicated parallel file system. Our obtained results show that the design of dNFSp allows for a scalable and resource-saving configuration for clusters with a large number of nodes.

An Evaluation Framework for Design-Time Context-Adaptation of Process Modelling Languages

“…Scenarios 1 4 6 7 Support for Context Modelling Support for interoperability [11] X X Support for use of external context [30,31] X Support for context fusion [31,32] X X Support for time constraint [33] X Support for Flexibility Support for sub-processes [8,10,34] X X X X Support for flexible activity execution [33] X Support for decision logic [8] X X X Support for routing logic [10,19,36] X X X Support for exception handling [16] X X Support for Scalability Support for Sub-processes [36] X X X X Support for Separation of Concerns [37] X X X Support for use of external context. In the domain of IoT, hardware sensors and virtual sensors are usually used to capture the external contexts by which process activities are triggered.…”