Combining Quality of Service and Social Information for Ranking Services

Qinyi Wu, Arun Iyengar, Revathi Subramanian, Isabelle Rouvellou, Ignacio Silva-Lepe, Thomas Mikalsen
http://www.research.ibm.com/people/i/iyengar/ICSOC2009.pdf

FROM BEFORE

The authors propose ServiceRank as a method to rank services based on the opinion of those using a service as well as local behavior of services, mainly response time and response failure.

Problems:

1. what is the proper answer response from a service? Does it have to match a value expected by the client or can it be just any response? How does the client know of the proper value for a computation prior to using a service? Does it then require to have knowledge about the service?
   
2. How does data from all services is collected? is there a single repository where the services publish the results their experiments with the services?

ServiceRank as a ranking algorithm to bring opinion of the community about using a service into consideration when deciding on the quality of service

Problems:

1. It is not clear how requesting services decide about the correctness of the returned data? is a response rated as correct when only a response is received, or when the correct response is returned. In the first case, how would the service be guaranteed as the proper service, and in the second case how are we going to know what is the returned value for the request?
2. How the cumulative data about the experience of other services gets collected? There are monitoring services that keep the record of all services. There are going to be multiple monitor services associated with the applications connected to the SOAlive. This is not a real case for the real world applications.
   

The paper also contains a set of experiments to demonstrate how a composition can be affected by quality of service and how the cumulative study for service composition.

The approach can be used as a method to provide cumulative study on service composition within a composition chain.