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DTSTART;TZID=America/Denver:20231112T160000
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UID:submissions.supercomputing.org_SC23_sess436_ws_ia112@linklings.com
SUMMARY:A Parallel Algorithm for Updating a Multi-Objective Shortest Path 
 in Large Dynamic Networks
DESCRIPTION:Arindam Khanda, S. M. Shovan, and Sajal K. Das (Missouri Unive
 rsity of Science and Technology)\n\nIn dynamic networks, where continuous 
 topological changes are prevalent, it becomes paramount to find and update
  different graph properties without the computational burden of recalculat
 ing from the ground up. However finding or updating a multi-objective shor
 test path (MOSP) in such a network is challenging, as it involves simultan
 eously optimizing multiple (conflicting) objectives. \n\nIn light of this,
  we focus on shortest path search and proposes parallel algorithms tailore
 d specifically for large incremental graphs. We first present an efficient
  algorithm that updates the single-objective shortest path (SOSP) whenever
  a new set of edges are introduced. Leveraging this SOSP update algorithm,
  we also devise a novel heuristic approach to adaptively update a MOSP in 
 large networks. Empirical evaluations on both real and synthetic increment
 al networks with shared memory implementations attest to the scalability a
 nd efficacy of the proposed algorithms.\n\nTag: Algorithms, Applications, 
 Architecture and Networks\n\nRegistration Category: Workshop Reg Pass\n\nS
 ession Chairs: Sanjukta Bhowmick (University of North Texas), Vito Giovann
 i Castellana (Pacific Northwest National Laboratory (PNNL)), John Feo (Pac
 ific Northwest National Laboratory (PNNL)), Marco Minutoli (Advanced Micro
  Devices), and Antonino Tumeo (Pacific Northwest National Laboratory (PNNL
 ))\n\n
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