The maximum flow problem: a real-time approach

The dynamic version of the maximum flow problem allows the graph underlying the flow network to change over time. The graph receives corrections to its structure or capacities and consequently the value of the maximum flow is modified. Several correction types are treated: edge capacity corrections and constant degree vertex additions/deletions. These corrections arrive in real time. In this paper, parallel and sequential solutions to the real-time maximum flow problem are developed on the reconfigurable multiple bus machine model and on the random access machine model, respectively. The parallel solution successfully meets the deadlines imposed in real time, while the sequential one fails to do so.The two solutions are then applied to a real-time process scheduler, an extension of Stone's static two-processor allocation problem. The scheduler allows processes to be created and destroyed, the amount of communication between two processes to change with time, and so on. The parallel algorithm is always able to compute the optimal schedule, while the solution obtained sequentially is only an approximation. The sequential solution gets worse with each new deadline to be met. In fact, after a sufficient number of steps, the quality improvement provided by the parallel approach over the sequential one is superlinear in the number of processors used by the parallel model.

[1]  Harold N. Gabow,et al.  Scaling algorithms for network problems , 1983, 24th Annual Symposium on Foundations of Computer Science (sfcs 1983).

[2]  Andrew V. Goldberg,et al.  A Parallel Algorithm for Finding a Blocking Flow in an Acyclic Network , 1989, Inf. Process. Lett..

[3]  Andrew V. Goldberg,et al.  A new approach to the maximum flow problem , 1986, STOC '86.

[4]  Ramachandran Vaidyanathan,et al.  On the power of segmenting and fusing buses , 1993, [1993] Proceedings Seventh International Parallel Processing Symposium.

[5]  Andrew V. Goldberg,et al.  Beyond the flow decomposition barrier , 1997, Proceedings 38th Annual Symposium on Foundations of Computer Science.

[6]  Selim G. Akl,et al.  Parallel Real-Time Optimization: Beyond Speedup , 1999, Parallel Process. Lett..

[7]  Selim G. Akl,et al.  Parallel real-time numerical computation: beyond speedup. III , 2000, Proceedings International Conference on Information Technology: Coding and Computing (Cat. No.PR00540).

[8]  Selim G. Akl,et al.  A Case Study in Real-Time Parallel Computation: Correcting Algorithms , 2001, J. Parallel Distributed Comput..

[9]  Selim G. Akl,et al.  The Characterization of Data-Accumulating Algorithms , 2000, Theory of Computing Systems.

[10]  Selim G. Akl,et al.  On the Data-Accumulating Paradigm , 2001 .

[11]  Selim G. Akl,et al.  Improving A Solution's Quality Through Parallel Processing , 2004, The Journal of Supercomputing.

[12]  D. R. Fulkerson,et al.  Maximal Flow Through a Network , 1956 .

[13]  S. Akl,et al.  Pursuit and Evasion on a Ring: An Infinite Hierarchy for Parallel Real-Time Systems , 2001, Theory of Computing Systems.

[14]  Uzi Vishkin,et al.  An O(n² log n) Parallel MAX-FLOW Algorithm , 1982, J. Algorithms.

[15]  Ramachandran Vaidyanathan,et al.  Constant Time Graph Algorithms on the Reconfigurable Mutliple Buss Machine , 1997, J. Parallel Distributed Comput..

[16]  Selim G. Akl Superlinear Performance in Real-Time Parallel Computation , 2004, The Journal of Supercomputing.

[17]  Takao Asano,et al.  RECENT DEVELOPMENTS IN MAXIMUM FLOW ALGORITHMS , 2000 .

[18]  Selim G. Akl,et al.  Towards a meaningful formal definition of real-time computations , 2000, Computers and Their Applications.

[19]  Selim G. Akl,et al.  Parallel real-time computation: sometimes quantity means quality , 2000, Proceedings International Symposium on Parallel Architectures, Algorithms and Networks. I-SPAN 2000.

[20]  Selim G. Akl,et al.  On the Necessity of Formal Models for Real-Time Parallel Computations , 2001, Parallel Process. Lett..

[21]  Robert E. Tarjan,et al.  A faster deterministic maximum flow algorithm , 1992, SODA '92.

[22]  Selim G. Akl,et al.  Real-Time Computation: A Formal Definition And Its Applications , 2003 .

[23]  Amnon Naamad,et al.  An O(EVlog²V) Algorithm for the Maximal Flow Problem , 1980, J. Comput. Syst. Sci..

[24]  Selim G. Akl,et al.  Nonlinearity, Maximization, and Parallel Real-Time Computation , 2000 .

[25]  Andrew V. Goldberg,et al.  Recent Developments in Maximum Flow Algorithms (Invited Lecture) , 1998, SWAT.

[26]  Selim G. Akl,et al.  Parallel Real-Time Cryptography: Beyond Speedup II , 2000, PDPTA.

[27]  Harold S. Stone,et al.  Multiprocessor Scheduling with the Aid of Network Flow Algorithms , 1977, IEEE Transactions on Software Engineering.

[28]  Uzi Vishkin,et al.  A Parallel Blocking Flow Algorithm for Acyclic Networks , 1992, J. Algorithms.

[29]  Selim G. Akl,et al.  The characterization of data-accumulating algorithms , 1999, Proceedings 13th International Parallel Processing Symposium and 10th Symposium on Parallel and Distributed Processing. IPPS/SPDP 1999.

[30]  Richard M. Karp,et al.  Theoretical Improvements in Algorithmic Efficiency for Network Flow Problems , 2001, Combinatorial Optimization.

[31]  Selim G. Akl,et al.  Real-time computation: a formal definition and its applications , 2001, Proceedings 15th International Parallel and Distributed Processing Symposium. IPDPS 2001.