  With an increasing number of web services, providing an end-to-end Quality of
Service (QoS) guarantee in responding to user queries is becoming an important
concern. Multiple QoS parameters (e.g., response time, latency, throughput,
reliability, availability, success rate) are associated with a service,
thereby, service composition with a large number of candidate services is a
challenging multi-objective optimization problem. In this paper, we study the
multi-constrained multi-objective QoS aware web service composition problem and
propose three different approaches to solve the same, one optimal, based on
Pareto front construction and two other based on heuristically traversing the
solution space. We compare the performance of the heuristics against the
optimal, and show the effectiveness of our proposals over other classical
approaches for the same problem setting, with experiments on WSC-2009 and
ICEBE-2005 datasets.
