In　the　noisy　intermediate-scale　quantum　era,　scientists　are　trying　to　improve　the　entanglement　swapping　success　rate　by　researching　anti-noise　technology　on　the　physical　level,　thereby　obtaining　a　higher　generation　rate　of　long-distance　entanglement.　However,　we　may　improve　the　generation　rate　from　another　perspective,　which　is　studying　an　efficient　entanglement　swapping　strategy.　This　paper　analyzes　the　challenges　faced　by　existing　entanglement　swapping　strategies,　including　the　node　allocation　principle,　time　synchronization,　and　processing　of　entanglement　swapping　failure.　We　present　Parallel　Segment　Entanglement　Swapping　(PSES)　to　solve　these　problems.　The　core　idea　of　PSES　is　to　segment　the　path　and　perform　parallel　entanglement　swapping　between　segments　to　improve　the　generation　rate　of　long-distance　entanglement.　We　construct　a　tree-like　model　as　the　carrier　of　PSES　and　propose　heuristic　algorithms　called　Layer　Greedy　and　Segment　Greedy　to　transform　the　path　into　a　tree-like　model.　Moreover,　we　realize　the　time　synchronization　and　design　the　on-demand　retransmission　mechanism　to　process　entanglement　swapping　failure.　The　experiments　show　that　PSES　performs　superiorly　to　other　entanglement　swapping　strategies,　and　the　on-demand　retransmission　mechanism　can　reduce　the　average　entanglement　swapping　time　by　80%　and　the　average　entanglement　consumption　by　80%.　©　2024　IEEE.