Collaboration-based intelligent service composition at runtime by end users

Abstract: In recent years, computing technologies have greatly advanced. This has resulted in a wide-spread use of services in order to improve the quality of our daily life. For example, a person with a mobile device can use services to plan and execute his or her travel, to connect to family and friends, to perform his or her search, or to manage his or her business. However, most of these services might only be available at some times, they may lack robustness, and some of these services are not aware of (or do not exploit) the mobility of the user. These services appear impermeable to the end users, i.e. the end users do not get to control or configure the services. We envisage that end users, with no programming knowledge, will have a hard time to find services of their choice and that it will be hard for these end users to derive substantial benefits from these services. Unguided automation is not the answer to this problem, as a particular service suggested automatically by a dynamic composition mechanism may not be suitable for a specific user at a certain point of time and in a given context. On the other hand explicit specification of service instances will mean that the user will be bogged down with the problem of runtime optimization in a dynamic environment where the services having the required functionality may or may not be available. In order to address this issue we introduce the notion of intelligent service composition where the end user will have a great degree of flexibility to define his or her own rules or conditions based on which an optimal composition will be generated automatically from a set of collaborative services by adaptation in a specific context and at a specific point in time. This is a step forward when compared to the present dynamic composition mechanisms which do not facilitate end users defining their own conditions dictating the selection of specific service instance at runtime. We have developed this solution to bring end users towards adaptive use of services. We validated our solution through a scenario-based evaluation approach with an implementation of a proof-of-concept prototype.