Survey on the run‐time systems of enterprise application integration platforms focusing on performance

Companies are taking advantage of cloud computing to upgrade their business processes. Cloud computing requires interaction with many kinds of applications, so it is necessary to improve the performance of software tools that allow keeping information on all these applications consistent and synchronised. Integration platforms are specialised software tools that provide support to design, implement, run, and monitor integration solutions, which aim to orchestrate a set of applications so as to promote compatibility among their data or to develop new functionality on top of the current ones. The run‐time system is the part of the integration platform responsible for running the integration solutions, which makes its performance the uttermost important issue. The contribution of this article is two‐fold: a framework and an evaluation of integration platforms. The former is a framework composed of ten properties grouped into two dimensions to evaluate the run‐time systems focusing on performance. Using this framework as reference, the second contribution is an evaluation of nine open‐source integration platforms, which represent the state‐of‐the‐art, provide support to the integration patterns, and follow the pipes‐and‐filters architectural style. In addition, as a result of this work, we suggest open research directions that can be explored to improve the performance of the run‐time systems and at the same time may be useful to adapt them to the context of cloud computing.

[1]  Nico Ebert,et al.  Integration platform as a service in der Praxis : eine Bestandsaufnahme , 2016 .

[2]  Kimberly R Powell,et al.  Coverage and quality: A comparison of Web of Science and Scopus databases for reporting faculty nursing publication metrics. , 2017, Nursing outlook.

[3]  Kasun Indrasiri Introduction to WSO2 ESB , 2016 .

[4]  Kevin A. Gary,et al.  Curricular change management with Git and Drupal: A tool to support flexible curricular development workflows , 2017, 2017 IEEE 15th International Conference on Software Engineering Research, Management and Applications (SERA).

[5]  Poonam Singh,et al.  A review of task scheduling based on meta-heuristics approach in cloud computing , 2017, Knowledge and Information Systems.

[6]  Geetam Singh Tomar,et al.  The Performance Metric for Enterprise Service Bus (ESB) in SOA system: Theoretical underpinnings and empirical illustrations for information processing , 2017, Inf. Syst..

[7]  sajid Mehmood Prediction and Frequency Based Dynamic Thread Pool System , 2016 .

[8]  Rafael Z. Frantz,et al.  An EAI Based Integration Solution for Science and Research Outcomes Information Management , 2015, CENTERIS/ProjMAN/HCist.

[9]  Hee Yong Youn,et al.  A Novel Predictive and Self -- Adaptive Dynamic Thread Pool Management , 2011, 2011 IEEE Ninth International Symposium on Parallel and Distributed Processing with Applications.

[10]  Huifang Deng,et al.  Elastic Scheduling of Scientific Workflows under Deadline Constraints in Cloud Computing Environments , 2018, Future Internet.

[11]  Srikumar Venugopal,et al.  Elastic Business Process Management: State of the art and open challenges for BPM in the cloud , 2014, Future Gener. Comput. Syst..

[12]  Ilango Paramasivam,et al.  An Enterprise Oriented View on the Cloud Integration Approaches – Hybrid Cloud and Big Data☆ , 2015 .

[13]  Geoffrey C. Fox,et al.  Distributed and Cloud Computing: From Parallel Processing to the Internet of Things , 2011 .

[14]  F. Bahadur,et al.  FBOS: FREQUENCY BASED OPTIMIZATION STRATEGY FOR THREAD POOL SYSTEM , 2014 .

[15]  Jin-Sub Kim,et al.  A History-based Dynamic Thread Pool Method for Reducing Thread Creation and Removal Overheads , 2013 .

[16]  Christoph Emmersberger,et al.  Tutorial: open source enterprise application integration - introducing the event processing capabilities of apache camel , 2013, DEBS.

[17]  Ewa Deelman,et al.  Workflow overhead analysis and optimizations , 2011, WORKS '11.

[18]  Hao Luo,et al.  Model-based services convergence and multi-clouds integration , 2013, Comput. Ind..

[19]  Fabricia Roos-Frantz,et al.  Task Scheduling Optimization on Enterprise Application Integration Platforms Based on the Meta-heuristic Particle Swarm Optimization , 2017, SBES.

[20]  Marinos Themistocleous,et al.  Evaluating the Adoption of Enterprise Application Integration in Health-Care Organizations , 2006, J. Manag. Inf. Syst..

[21]  Wu He,et al.  Integration of Distributed Enterprise Applications: A Survey , 2014, IEEE Transactions on Industrial Informatics.

[22]  Anil Sethi MULTICORE PROCESSOR TECHNOLOGY- ADVANTAGES AND CHALLENGES , 2015 .

[23]  Rodney T. Ogawa,et al.  Towards Rigor in Reviews of Multivocal Literatures: Applying the Exploratory Case Study Method , 1991 .

[24]  Benoît Eynard,et al.  Towards a PLM Interoperability for a Collaborative Design Support System , 2014 .

[25]  Konstantinos Manikas,et al.  Revisiting software ecosystems Research: A longitudinal literature study , 2016, J. Syst. Softw..

[26]  Fabricia Roos-Frantz,et al.  Cloud Configuration Modelling: a Literature Review from an Application Integration Deployment Perspective , 2015 .

[27]  P. Mell,et al.  The NIST Definition of Cloud Computing , 2011 .

[28]  Won Woo Ro,et al.  Virtual Thread: Maximizing Thread-Level Parallelism beyond GPU Scheduling Limit , 2016, 2016 ACM/IEEE 43rd Annual International Symposium on Computer Architecture (ISCA).

[29]  Jing Deng,et al.  Parallel Computing for Geocomputational Modeling , 2018 .

[30]  Kostyantyn Myroshnychenko Maturidade de plataformas SOA Open Source vs proprietários , 2013 .

[31]  Barbara Ann Kitchenham Evaluating software engineering methods and tools, part 7: planning feature analysis evaluation , 1997, SOEN.

[32]  Mark Fisher,et al.  Spring Integration in Action , 2012 .

[33]  Victor Romero,et al.  Mule in Action , 2009 .

[34]  Lin Ma,et al.  A Memory Access Model for Highly-threaded Many-core Architectures , 2012, 2012 IEEE 18th International Conference on Parallel and Distributed Systems.

[35]  K S Bauer,et al.  Designing the Search Service for Enterprise Portal based on Oracle Universal Content Management , 2017 .

[36]  Ahmad Ashari,et al.  Service orchestration using enterprise service bus for real-time government executive dashboard system , 2015, 2015 International Conference on Data and Software Engineering (ICoDSE).

[37]  Saurabh Anand,et al.  Working with Cassandra Database , 2018 .

[38]  Barbara Kitchenham,et al.  DESMET: a methodology for evaluating software engineering methods and tools , 1997 .

[39]  Arvind Sudarsanam,et al.  Resource estimation and task scheduling for multithreaded reconfigurable architectures , 2004, Proceedings. Tenth International Conference on Parallel and Distributed Systems, 2004. ICPADS 2004..

[40]  Pamela Jordan Basics of qualitative research: Grounded theory procedures and techniques , 1994 .

[41]  Norman May,et al.  Optimization Strategies for Integration Pattern Compositions , 2018, DEBS.

[42]  Rajkumar Buyya,et al.  Article in Press Future Generation Computer Systems ( ) – Future Generation Computer Systems Cloud Computing and Emerging It Platforms: Vision, Hype, and Reality for Delivering Computing as the 5th Utility , 2022 .

[43]  Rafael Corchuelo,et al.  An Efficient Orchestration Engine for the Cloud , 2011, 2011 IEEE Third International Conference on Cloud Computing Technology and Science.

[44]  Fabricia Roos-Frantz,et al.  A Study of Petri Nets, Markov Chains and Queueing Theory as Mathematical Modelling Languages Aiming at the Simulation of Enterprise Application Integration Solutions: A First Step , 2016, CENTERIS/ProjMAN/HCist.

[45]  Marcos José Santana,et al.  Providing IaaS resources automatically through prediction and monitoring approaches , 2014, 2014 IEEE Symposium on Computers and Communications (ISCC).

[46]  Massimo Pezzini,et al.  Magic Quadrant for Enterprise Integration Platform as a Service , 2014 .

[47]  Arnaud Le Hors,et al.  The linked data platform (LDP) , 2013, WWW '13 Companion.

[48]  Theo Lynn,et al.  Quantifying the Financial Value of Cloud Investments: A Systematic Literature Review , 2017, 2017 IEEE International Conference on Cloud Computing Technology and Science (CloudCom).

[49]  Shahenda Sarhan,et al.  A novel hybrid of Shortest job first and round Robin with dynamic variable quantum time task scheduling technique , 2017, Journal of Cloud Computing.

[50]  Norman May,et al.  Benchmarking integration pattern implementations , 2016, DEBS.

[51]  Norman May,et al.  Patterns for emerging application integration scenarios: A survey , 2017, Inf. Syst..

[52]  Jyh-Horng Chou,et al.  Optimized task scheduling and resource allocation on cloud computing environment using improved differential evolution algorithm , 2013, Comput. Oper. Res..

[53]  Zaki Brahmi,et al.  Temporal Reconfiguration-Based Orchestration Engine in the Cloud Computing , 2014, BIS.

[54]  Rajkumar Buyya,et al.  Task granularity policies for deploying bag-of-task applications on global grids , 2013, Future Gener. Comput. Syst..

[55]  Yves Caseau,et al.  Self-adaptive middleware: Supporting business process priorities and service level agreements , 2005, Adv. Eng. Informatics.

[56]  Nico Ebert,et al.  Integration Platform as a Service , 2017, Bus. Inf. Syst. Eng..

[57]  Fabricia Roos-Frantz,et al.  Mathematical Model for Simulating an Application Integration Solution in the Academic Context of Unijuí University , 2016 .

[58]  Rafael Corchuelo,et al.  On the design of a maintainable software development kit to implement integration solutions , 2016, J. Syst. Softw..

[59]  Antonio F. Gómez-Skarmeta,et al.  Evaluating Open Source Enterprise Service Bus , 2010, 2010 IEEE 7th International Conference on E-Business Engineering.

[60]  Daniel Cordes,et al.  Automatic Extraction of Pipeline Parallelism for Embedded Software Using Linear Programming , 2011, 2011 IEEE 17th International Conference on Parallel and Distributed Systems.

[61]  Vahid Garousi,et al.  Guidelines for including the grey literature and conducting multivocal literature reviews in software engineering , 2017, Inf. Softw. Technol..

[62]  Gregor Hohpe,et al.  Enterprise Integration Patterns: Designing, Building, and Deploying Messaging Solutions , 2003 .

[63]  Max Jacobson,et al.  A Pattern Language: Towns, Buildings, Construction , 1981 .

[64]  Radu Prodan,et al.  A workflow runtime environment for manycore parallel architectures , 2015, WORKS@SC.

[65]  David G. Messerschmitt,et al.  Software Ecosystem: Understanding an Indispensable Technology and Industry , 2003 .

[66]  Fabricia Roos-Frantz,et al.  On the Formalisation of an Application Integration Language Using Z Notation , 2014, ICEIS.

[67]  Nadine Gottschalk,et al.  Camel In Action , 2016 .

[68]  Sören Balko,et al.  In-Memory Business Process Management , 2015, 2015 IEEE 19th International Enterprise Distributed Object Computing Conference.

[69]  Rafael Corchuelo,et al.  A proposal to detect errors in Enterprise Application Integration solutions , 2012, J. Syst. Softw..

[70]  Christine Legner,et al.  Why Do Companies Migrate Towards Cloud Enterprise Systems? A Post-Implementation Perspective , 2014, 2014 IEEE 16th Conference on Business Informatics.

[71]  Mark Harman,et al.  Cloud engineering is Search Based Software Engineering too , 2013, J. Syst. Softw..