April 1999 CHAIMS1 Prof. Gio Wiederhold, Dr. Dorothea Beringer, Composing Autonomous Internet Services with CHAIMS CHAIMS Objective: Using and composing computational services offered by remote and autonomous megamodules. Approach: Develop and validate a composition-only language (CLAM), a protocol for large, distributed, heterogeneous and autonomous megamodules (CPAM), and a supporting system.

April 1999 CHAIMS2 Repository add information to e b CORBA / Process - Providing Megamodules writes CPAM compliant megamodules from scratch d MEGA Modules Megamodule Providers c Wrapper Templates a wrap legacy megamodules DCE / CPAM

April 1999 CHAIMS3 Process - Composing Megamodules CHAIMS Repository read Composers Megaprogram write Megaprogram written in CLAM CHAIMS Compiler generates Client Side Run Time compiled megaprograms information

April 1999 CHAIMS4 Process - Running a Megaprogram CPAM Protocol on top of Distribution System (CORBA, RMI, …) Client Side Run Time located on the client located on several servers b CORBA / e c a DCE / CPAM d MEGA Modules server side

April 1999 CHAIMS5 Advantages Advantages of using remote services: Knowledge »separation of concerns (provider - composer) »technical expertise »maintenance, newest algorithms Availability »pay per usage instead of pay per instance »lower barrier for clients to try out new modules »choice of several providers even at run-time Resources »access to computation intensive modules for everybody »minimal local resources possible Yet there are also challenges...

April 1999 CHAIMS6 Challenges - Services Computation intensive services: not free for a client execution time of a service transfer time for data fees for services Autonomy of megamodules: client has no control over availability of services and resources provided for services heterogeneity concerning languages, platforms as well as distribution protocols

April 1999 CHAIMS7 Characteristics CPAM Asynchronous: »pre-invocation primitives »invocation and result extraction primitives »termination primitives Cost-estimation »fee, execution time, data-volume of results Presetting of input parameters »for cost estimation »avoiding repeated transmission of same parameters Incremental result extraction »partial extraction of just those results that are ready »progressive extraction: repeated extraction of same result parameter with increasing accuracy Progress monitoring »individual result parameters and progress of invocation

April 1999 CHAIMS8 Challenges - Composition Composer is non-technical domain expert: expert in domain that uses these services, wants to focus on problem, e.g. scientist, assistant of a general not knowledgeable in middleware system, not an experienced programmer Purely Compositional Language: feasible? strengths? limits?

April 1999 CHAIMS9 Characteristics of CLAM Hiding technical details »all protocol related details generated from few high-level primitives Focus on composition: »no primitives for arithmetic ==> math megamodules »no primitives for input/output ==> general and problem-specific I/O megamodules »reduce complexity: not all facilities of a common language Focus on asynchrony - exploiting strengths of CPAM »reduction of complexity of call-statements by splitting up call-statement »parallelism by asynchrony in sequential program

April 1999 CHAIMS10 Upcoming Research Issues Applications, collaborations: »applying CHAIMS to a research system in bio-informatics »other collaborations? Composition: »automated optimization of a composition to exploit inherent parallelism of services, invocation scheduling at compile- as well as run-time »incremental composition, replacing compiler by interpreter with preprocessor »graphical composition Protocol: »using XML for CPAM primitives and CHAIMS repository »other distribution systems

April 1999 CHAIMS11 More Information C H A I M S