With the increasing array of information and services being supported by distributed computing, we face a new challenge: How do we handle charges? Providers of information will want to receive "royalties", providers of computing services will want to receive payment for use of the service, and providers of the network will want to receive payment for the transmission. At some point, the users of the provided services will have to pay for this. What do we need to do in designing our distributed computing systems to support some form of charge/payment? This paper discusses these issues.

The performance analysis of a system in which storage is provided by a file server node on a network of client processors is discussed. The server controls a hierarchy of storage devices, and provides all the necessary file management functions. The clients are large mainframe systems that have their own local storage devices. The movement of files among the various storage levels is managed by a hierarchical storage management system. A closed queuing network model of the client-server storage system is used to analyze the performance of the system for various file movement criteria and to study the tradeoffs between recalling a file and accessing it by a distributed file system. Several network topologies (Ethernet, token ring, channel-to-channel) and their effect on performance are considered.>

The delay characteristics of the Datakit virtual circuit switch (VCS) are investigated, and its contribution to the overall end-to-end character echo response time delay on large mainframe UNIX (LMU) systems is evaluated. The end-to-end delay consists of the Datakit network, the device attached control unit (DACU), and host component delays. The echo response time is the amount of time it takes for a character to be echoed back by the host. To measure the end-to-end terminal-to-host delay and the Datakit contribution to the overall delay, two parallel experiments were set up. The first experiment provides direct dialing from a 3B2 computer into a LMU by passing Datakit, whereas the second test utilized the Datakit terminal-to-host network to access the LMU during the same time intervals. The experiments provide a considerable amount of data to evaluate the delay with and without the Datakit component. the 50th percentile echo response time clearly indicates that the Datakit contribution to the overall response time is around 50 ms with very little variance. The overall Datakit delay fluctuates between 35 ms and 70 ms.>

The authors propose models for defining the availability metric of a distributed computing environment. The metric is a meaningful indicator of a distributed computing environment's performance from the reliability point of view. The proposed models can also be used to efficiently design, engineer, and monitor a distributed computing environment's activities. The models are general and can be applied to any distributed computing environment for availability evaluation.>