by Naval Postgraduate School, Available from the National Technical Information Service in Monterey, Calif, Springfield, Va .
Written in English
|Statement||by Karen K. Lehman|
|Contributions||Shukla, Shridhar B., Yang, Chyan|
|The Physical Object|
|Pagination||98 p. ;|
|Number of Pages||98|
Execution times of dynamic distributed real-time systems are affected by variables that originate in external envi-ronments, and this leads to a new class of task allocation problems. CiteSeerX - Document Details (Isaac Councill, Lee Giles, Pradeep Teregowda): Some distributed real-time systems interact with external environments that change dynamically, and it is necessary to take the external variables into account when performing task allocation. We developed an approximation algorithm for task allocation, and it finds allocations that are maximally robust against. Gu, D., Drews, F., Welch, L.: Robust task allocation for dynamic distributed real-time systems subject to multiple environmental parameters. In: The 25th International Conference On Distributed Computing Systems (ICDCS), Columbus, Ohio (June ) Google ScholarAuthor: Dazhang Gu, Lonnie Welch. The allocation generated by these techniques will be robust with respect to changes in the environment during run time. Task allocation in real-time systems in order to meet certain deadlines is known to be an NP-hard problem (Ibarra and Kim, ).
Optimization of task allocation and priority assignment in hard real-time distributed systems December ACM Transactions on Embedded Computing Systems 11(4) The study of distributed robust optimization remains wide open. Most methods designed for the types of problem discussed in this paper do not consider uncertainty in their solutions. Thus, the main contribution here is the successful design and implementation of a robustness module for use with general, distributed task allocation algorithms. The considered distributed system is expected to operate in an environment where the input workload is likely to change unpredictably, possibly invalidating a resource allocation that was based on. Robust optimization is an emerging area in research that allows addressing different optimization problems and specifically industrial optimization problems where there is a degree of uncertainty in some of the variables involved. There are several ways to apply robust optimization and the choice of form is typical of the problem that is being solved. In this paper, the basic concepts of.
This paper summarizes some of our research in the area of robust static resource allocation for distributed computing systems operating under imposed quality of service (QoS) constraints. Often, these systems are expected to function in a physical environment replete with uncertainty, which causes the amount of processing required over time to fluctuate substantially. REAL-TIME MANAGEMENT OF RESOURCE ALLOCATION SYSTEMS focuses on the problem of managing the resource allocation taking place within the operational context of many contemporary technological applications, including flexibly automated production systems, automated railway and/or monorail transportation systems, electronic workflow management systems, and business transaction . The focus of this paper is the design of a static heuristic that: (a) determines a robust resource allocation, i.e., a resource allocation that maximizes the allowable increase in workload until a. An objective function can be derived by modifying the terms present in general model,which inturn depend on characteristics of the system concerned ex. Distributed computing system,distributed.