SOTAVerified

Service Composition

Let T be the task that the service composition needs to accomplish. The task T can be granulated to T 1 , T 2 , T 3 , T 4 , … , T n . i.e. T = {T 1 , T 2 , T 3 , T 4 , … , T n } . For each task T i , a set of service S i = S i 1 , S i 2 , S i 3 , … , S i m is discovered during the service discovery process such that all services in a set S i perform the same function and have the same input and output parameters (See Figure 2). S 1 = {S 11 , S 12 , S 13 , … , S 1m } , S 2 = {S 21 , S 22 , S 23 , … , S 2m } , S 3 = {S 31 , S 32 , S 33 , … , S 3m } , … , S n = {S n 1 , S n 2 , S n 3 , … , S n m } We need to select one service from each set S i in order to compose the big service such that the overall QoS attributes of the big service are optimal. The total number of the possible distinct service composition is n m . Let k be the the number of QoS attributes. Then the total num- ber of comparisons required are kn m . We need at least kn m comparisons to find whether the solution is optimal, thus making the problem as NP-Hard.

Papers

Showing 3140 of 45 papers

TitleStatusHype
Multi-service collaboration and composition of cloud manufacturing customized production based on problem decomposition0
Optimization of Resource Service Composition in Cloud Manufacture Based on Improved Genetic and Ant Colony Algorithm0
QoS aware Automatic Web Service Composition with Multiple objectives0
Relational Model for Parameter Description in Automatic Semantic Web Service Composition0
Representing and Reasoning with Qualitative Preferences for Compositional Systems0
Retrieval-Augmented Generation for Service Discovery: Chunking Strategies and Benchmarking0
Service Choreography, SBVR, and Time0
Service Composition in the ChatGPT Era0
Service Composition Scenarios for Task-Oriented Translation0
Social-Sensor Composition for Tapestry Scenes0
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