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WebServices.pdf

By accumulating all the execution plans quality

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by accumulating all the execution plans' quality vectors: Q = 5 , 4 , 3 , 2 , 1 , 5 , 2 4 , 2 3 , 2 2 , 2 1 , 2 5 , 1 4 , 1 3 , 1 2 , 1 1 , 1 2 2 2 2 2 1 1 1 1 1 .. .. .. .. .. .. .. .. .. .. ) ( ) ( ) ( ) ( ) ( .. .. .. .. .. .. .. .. .. .. ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( n n n n n n rep n rel n av n du n price rep rel av du price rep rel av du price Q Q Q Q Q Q Q Q Q Q Q Q Q Q Q p Q p Q p Q p Q p Q p Q p Q p Q p Q p Q p Q p Q p Q p Q p Q (3) An additive weighting technique is used to select an optimal execution plan. Some of the criteria are negative: the higher the value, the lower quality, for example execution time and execution price. Others are positive criteria: the higher value, the higher quality. For negative criteria values are scaled according to Equation 4. V ij = - - - otherwise Q Q Q Q Q Q j j j j ij j , 1 0 , min max min max max j=1,2 (4)

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17 For positive criteria, values are scaled according to Equation 5. V ij = - - - otherwise Q Q Q Q Q Q j j j j j ij , 1 0 , min max min max min j=3,4,5 (5) In the above equations, max j Q is maximal value of a quality criterion in matrix Q (3): max j Q = Max( Q i;j ), 1 < i < n min j Q is minimal value of a quality criterion in matrix Q : min j Q = Min( Q i,j ); 1 < i < n In fact, computing max j Q and min j Q can be done without generating all possible execution plans. For example, in order to compute the maximum execution price ( max price Q ) of all the execution plans, the most expensive Web service for each task should be selected and sum up all these execution prices to compute max price Q . In order to compute the minimum execution duration ( min du Q ) of all the execution plans, the Web service that has shortest execution duration for each task should be selected and use CPA to compute min du Q . The computation cost of max j Q and min j Q is polynomial [1]. Using (5) and with help of the following formula end users can give their preference to compute the overall quality score for each execution plan: Score(p i ) = = 5 1 , ) * ( j j j i W V , (6) The W j [0,1] and = 5 1 j j W = 1 . W j represents the weight of each criterion. The global planner will choose the execution plan p i which has the maximal value of Score(p i ) . If there are more than one execution plans which have the same maximal value of Score(p) , then an execution plan could be selected from them randomly. 3.4. Linear Programming solution The approach of selecting an optimal execution plan requires the generation of all possible execution plans. Such an approach is impractical for large-scale composite services, where both the number of tasks in the composite services and the number of candidate Web services in communities are large. The method based on linear programming (LP) is used to allow selection of the optimal execution plan without generating all possible plans [21].
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• Winter '15
• MAhmoudali
• World Wide Web, Web Services, Business process modeling, Web Services Description Language

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