NASA Scientific and Technical Aerospace Reports

A blackboard system consists of a set of knowledge sources, a blackboard data structure, and a control strategy used to
activate the knowledge sources. The blackboard model of problem solving is best described by Dr. H. Penny Nii of the
Stanford University AI Laboratory: ‘A Blackboard System can be viewed as a collection of intelligent agents who are gathered
around a blackboard, looking at pieces of information written on it, thinking about the current state of the solution, and writing
their conclusions on the blackboard as they generate them. ‘ The blackboard is a centralized global data structure, often
partitioned in a hierarchical manner, used to represent the problem domain. The blackboard is also used to allow
inter-knowledge source communication and acts as a shared memory visible to all of the knowledge sources. A knowledge
source is a highly specialized, highly independent process that takes inputs from the blackboard data structure, performs a
computation, and places the results of the computation in the blackboard data structure. This design allows for an opportunistic
control strategy. The opportunistic problem-solving technique allows a knowledge source to contribute towards the solution
of the current problem without knowing which of the other knowledge sources will use the information. The use of
opportunistic problem-solving allows the data transfers on the blackboard to determine which processes are active at a given
time. Designing and developing blackboard systems is a difficult process. The designer is trying to balance several conflicting
goals and achieve a high degree of concurrent knowledge source execution while maintaining both knowledge and semantic
consistency on the blackboard. Blackboard systems have not attained their apparent potential because there are no established
tools or methods to guide in their construction or analyze their performance.
Derived from text
Design Analysis; Data Structures; Computer Programs
20040121018 NASA Langley Research Center, Hampton, VA, USA
Modeling Personnel Turnover in the Parametric Organization
Dean, Edwin B.; [1991]; 9 pp.; In English; Thirteenth Annual Conference of the International Society of Parametric Analysis,
May 1991; No Copyright; Avail: CASI; A02, Hardcopy
A primary issue in organizing a new parametric cost analysis function is to determine the skill mix and number of
personnel required. The skill mix can be obtained by a functional decomposition of the tasks required within the organization
and a matrixed correlation with educational or experience backgrounds. The number of personnel is a function of the skills
required to cover all tasks, personnel skill background and cross training, the intensity of the workload for each task, migration
through various tasks by personnel along a career path, personnel hiring limitations imposed by management and the applicant
marketplace, personnel training limitations imposed by management and personnel capability, and the rate at which personnel
leave the organization for whatever reason. Faced with the task of relating all of these organizational facets in order to grow
a parametric cost analysis (PCA) organization from scratch, it was decided that a dynamic model was required in order to
account for the obvious dynamics of the forming organization. The challenge was to create such a simple model which would
be credible during all phases of organizational development. The model development process was broken down into the
activities of determining the tasks required for PCA, determining the skills required for each PCA task, determining the skills
available in the applicant marketplace, determining the structure of the dynamic model, implementing the dynamic model, and
testing the dynamic model.
Author
Cost Analysis; Dynamic Models; Computer Programs; Migration; Occupation
20040121021 Technische Hogeschool Twente, Enschede, Netherlands
Promote-IT: An Efficient Real-Time Tertiary-Storage Scheduler
Lijding, Maria Eva; Mullender, Sape; Jansen, Pierre; NASA/IEEE MSST 2004 Twelfth NASA Goddard Conference on Mass
Storage Systems and Technologies in cooperation with the Twenty-First IEEE Conference on Mass Storage Systems and
Technologies; April 2004, pp. 245-260; In English; See also 20040121020; No Copyright; Avail: CASI; A03, Hardcopy
Promote-IT is an efficient heuristic scheduler that provides QoS guarantees for accessing data from tertiary storage. It can
deal with a wide variety of requests and jukebox hardware. It provides short response and confirmation times, and makes good
use of the jukebox resources. It separates the scheduling and dispatching functionality and effectively uses this separation to
dispatch tasks earlier than scheduled, provided that the resource constraints are respected and no task misses its deadline. To
prove the efficiency of Promote-IT we implemented alternative schedulers based on different scheduling models and
scheduling paradigms. The evaluation shows that Promote-IT performs better than the other heuristic schedulers. Additionally,
Promote-IT provides response-times near the optimum in cases where the optimal scheduler can be computed.
Author
Data Storage; Heuristic Methods; Real Time Operation; Programming (Scheduling)
250