Algorithm 1. Pivot Point Generation Algorithm (implemented at each SH node).

Input: attrRangeTable (containing minimum, maximum, average and theta of each attribute), W (weights to different attributes based on their importance in the event description). Output: P (derived pivot point for each sector) 1: mapRec.minRange ← 0; mapRec.maxRange ← 0 2: m ← lengthof(attrRangeTable) 3: for each i from 1 to m do 4:  mapRec.minRange ← mapRec.minRange + (attrRangeTable[i].min/attrRangeTable[i].max) × W[i] 5:  mapRec.maxRange ← mapRec.maxRange + (attrRangeTable[i].max/attrRangeTable[i].max) × W[i] 6:  mapRec.com ← mapRec.com + (attrRangeTable[i].avg)/attrRangeTable[i].max) × W[i] 7:  mapRec.theta ← mapRec.theta + (attrRangeTable.theta)/attrRangeTable[i].max) × W[i] 8:  i ← i + 1 9: end for 10: comLowerLimit ← mapRec.com − mapRec.theta 11: comUpperLimit ← mapRec.com + mapRec.theta 12: // S is the total number of sectors 13: η ← (comUpperLimit − comLowerLimit)/(S − 1) 14: for each j from 0 to S do 15:  if j = 0 16:    then P[j] ← mapRec.minRange 17:  else if j = S 18:    then P[j] ← mapRec.maxRange 19:  else 20:    P[j] ← comLowerLimit + j × η 21:  end if 22:  j ← j + 1 23: end for