For　the　on-line　version　of　the　closest　pair　problem,　the　points　become　available　one　after　another.　A　new　point　arrives　as　soon　as　the　insertion　of　the　previous　point　has　been　completed.　At　the　start　of　the　algorithm,　the　final　size　of　the　point　set　is　not　known.　To　solve　this　on-line　problem,　we　need　a　data　structure　that　maintains　the　closest　pair　in　the　current　point　set　in　Ed.　The　only　operation　to　be　supported　is　the　insertion　of　a　point.　After　an　insertion,　we　have　to　update　the　closest　pair.　In　high-dimension　cases,　a　data　structure　is　given　that　maintains　the　minimal　distance　in　amortized　O((log　n)d-1)　time,　using　O(n)　space.　This　leads　to　an　O(n　log　d-1　n)　time　algorithm　for　the　on-line　closest　pair　problem.　This　paper　presents　an　efficient　data　structure　for　the　on-line　closest　pair　problem　in　d　dimensional　space.　The　data　structure　maintains　the　closest　pair　of　the　current　point　set　in　d　dimensional　space　on-line　in　amortized　time　O(log　2　n),　using　O(n)　space.　©　2011　IEEE.