Title : 
Neural networks for the design of distributed, fault-tolerant, computing environments
         
        
            Author : 
Geist, Robert ; Suggs, Darrell
         
        
            Author_Institution : 
Dept. of Comput. Sci., Clemson Univ., SC, USA
         
        
        
        
        
        
            Abstract : 
Binary optimization models for the design of distributed, fault-tolerant computing systems are considered, with a focus on the task allocation and file assignment modeling schema proposed by J. Bannister and K. Trivedi (Proc. Second Symp. on Reliability in Distributed Software and Database Systems, 1982). It is shown that R. Graham´s (1969) partitioning algorithm, S, when applied to this schema can, in the case of finite resources, yield allocations that are arbitrarily poor with respect to the optimum allocation. This contrasts sharply with the case of ample resources, where S provides allocations that are provably close to the optimum. Two alternative allocation algorithms are suggested. Both are seen to deliver allocations preferable to those provided by S, but at some additional computational expense
         
        
            Keywords : 
distributed processing; fault tolerant computing; neural nets; optimisation; binary optimisation models; distributed systems; fault-tolerant computing; file assignment modeling; optimum allocation; partitioning algorithm; system design; task allocation; Computer networks; Design optimization; Distributed computing; Fault tolerance; Fault tolerant systems; Hopfield neural networks; Neural networks; Resource management; Shape control; Simulated annealing;
         
        
        
        
            Conference_Titel : 
Reliable Distributed Systems, 1992. Proceedings., 11th Symposium on
         
        
            Conference_Location : 
Houston, TX
         
        
            Print_ISBN : 
0-8186-2890-1
         
        
        
            DOI : 
10.1109/RELDIS.1992.235127