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Description, discovery, and recommendation of Cloud services: a survey

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Abstract

Cloud computing has become the most popular concept for on-demand delivery of Cloud computing services. Due to its high flexibility, many Cloud computing services are designed and implemented to meet the users’ needs and expectations. As a result, new challenges have emerged in the search for relevant Cloud services. In fact, the description, discovery, and recommendation of Cloud services are the main challenges of Cloud computing. It stems from the lack of standardization for the Cloud services description and publication, as well as the exponential growth in the number and functionality of Cloud services. Our objective in this paper is to present a comparative study of the different approaches that address the Cloud services description, discovery, and recommendation issues. This comparison study’s findings are separated into three parts. First, the approaches to Cloud service description have several flaws, such as the lack of a unified description that encompasses all types of Cloud services, the lack of a definition for several properties (such as Cloud characteristics, actors, and pricing model), and the failure to consider several critical SLA elements (for example, QoS guarantee, compensation, monitoring, notification, and termination). Second, we determined that web-based approaches, also known as crawling approaches, are the most likely to be adopted in the field of Cloud service discovery, in order to keep up with the ever-changing nature of Cloud computing. Hence, the crawling approach’s main purpose is to update the Cloud service registry with new services that are available on the internet. Existing crawling methods, on the other hand, have a set of shortcomings, including the types and categories of discovered Cloud services, the constant increase in web-published Cloud services, and the automatic updating of Cloud vocabulary. Finally, major Cloud service recommendation issues such as cold start, data sparsity, attack resistance, and diversity remain unaddressed.

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References

  1. Zorgati H, Ben Djemaa R, Amous Ben Amor I (2019) Service discovery techniques in Internet of Things: a survey. In: 2019 IEEE international conference on systems, man and cybernetics (SMC), pp 1720–1725

  2. Nabli H, Ben Djmeaa R, Amous Ben Amor I (2018) Efficient Cloud service discovery approach based on LDA topic modeling. J Syst Softw 146:233–248

    Article  Google Scholar 

  3. Nabli H, Ben Djmeaa R, Amous Ben Amor I (2021) Cloud services description ontology used for service selection. Serv Orien Comput Appl 16:1–14

    Google Scholar 

  4. Alshammari ST, Albeshri A, Alsubhi K (2021) Building a trust model system to avoid Cloud services reputation attacks. Egypt Inform J 22(4):493–503

    Article  Google Scholar 

  5. Heidari A, Navimipour NJ (2021) A new SLA-aware method for discovering the Cloud services using an improved nature-inspired optimization algorithm. PeerJ Comput Sci 7:e539

    Article  Google Scholar 

  6. Ramalingam C, Mohan P (2021) Addressing semantics standards for Cloud portability and interoperability in multi Cloud environment. Symmetry 13(2):317

    Article  Google Scholar 

  7. Nabli H, Cherif S, Ben Djmeaa R, Amous Ben Amor I (2018) SADICO: self-adaptive approach to the web service composition. In: International conference on intelligent interactive multimedia systems and services, pp 254–267

  8. Noor TH, Sheng QZ, Ngu AH, Dustdar S (2014) Analysis of web-scale Cloud services. IEEE Internet Comput 18(4):55–61

    Article  Google Scholar 

  9. Zhang M, Ranjan R, Haller A, Georgakopoulos D, Menzel M, Nepal S (2012) An ontology-based system for Cloud infrastructure services’ discovery. In: 8th international conference on collaborative computing: networking, applications and worksharing (CollaborateCom), pp 524–530

  10. Ghazouani S, Slimani Y (2017) A survey on Cloud service description. J Netw Comput Appl 91:61–74

    Article  Google Scholar 

  11. Kang J, Sim KM (2016) Ontology-enhanced agent-based Cloud service discovery. Int J Cloud Comput 5:144–171

    Article  Google Scholar 

  12. Parhi M, Pattanayak BK, Patra MR (2018) An ontology-based Cloud infrastructure service discovery and selection system. Int J Grid Util Comput 9(2):108–119

    Article  Google Scholar 

  13. Zhang Q, Haller A, Wang Q (2019) CoCoOn: cloud computing ontology for iaas price and performance comparison. In: International semantic web conference, pp 325–341

  14. Rekik M, Boukadi K, Ben-Abdallah H (2015) Cloud description ontology for service discovery and selection. In: 10th international joint conference on software technologies (ICSOFT), pp 1–11

  15. Modi KJ, Garg S (2019) A QoS-based approach for Cloud-service matchmaking, selection and composition using the Semantic Web. J Syst Inf Technol 21(1):63–89

    Article  Google Scholar 

  16. Di Martino B, Cretella G, Esposito A (2014) Towards a unified OWL ontology of Cloud vendors’ appliances and services at paas and saas level. In: Eighth international conference on complex, intelligent and software intensive systems, pp 570–575

  17. Fang D, Liu X, Romdhani I, Jamshidi P, Pahl C (2016) An agility-oriented and fuzziness-embedded semantic model for collaborative Cloud service search, retrieval and recommendation. Fut Gener Comput Syst 56:11–26

    Article  Google Scholar 

  18. Zhenglan X, Hankun Y (2018) Selection of optimal Cloud services based on quality of service ontology. Ingenierie des Systemes d’Information 23(6):127–141

    Google Scholar 

  19. Ghazouani S, Slimani Y (2017) Towards a standardized Cloud service description based on USDL. J Syst Softw 132:1–20

    Article  Google Scholar 

  20. Sun L, Ma J, Wang H, Zhang Y, Yong J (2015) Cloud service description model: an extension of USDL for Cloud services. IEEE Trans Serv Comput 11(2):354–368

    Article  Google Scholar 

  21. Shetty J, D’Mello D A (2015) An XML based data representation model to discover infrastructure services. In: International conference on smart technologies and management for computing, communication, controls, energy and materials (ICSTM), pp 119–125

  22. Benfenatki H, Da Silva CF, Benharkat A, Ghodous P, Maamar Z (2017) Linked USDL extension for describing business services and users’ requirements in a cloud context. Int J Syst Serv-Orien Eng (IJSSOE) 7(3):15–31

    Article  Google Scholar 

  23. Saouli H, Kazar O, Benharkat AN (2015) SaaS-DCS: software-as-a-service discovery and composition system-based existence degree. Int J Commun Netw Distrib Syst 14(4):339–378

    Google Scholar 

  24. Oberle D, Barros A, Kylau U, Heinzl S (2013) A unified description language for human to automated services. Inf Syst 38(1):155–181

    Article  Google Scholar 

  25. Quinton C, Romero D, Duchien L (2016) SALOON: a platform for selecting and configuring Cloud environments. Softw Pract Exp 46(1):55–78

    Article  Google Scholar 

  26. Mastelic T, Brandic I, García A G (2014) Towards uniform management of Cloud services by applying model-driven development. In: IEEE 38th annual computer software and applications conference, pp 129–138

  27. Gudenkauf S, Josefiok M, Göring A, Norkus O (2013) A reference architecture for Cloud service offers. In: 17th IEEE international enterprise distributed object computing conference, pp 227–236

  28. Al-Sayed MM, Hassan HA, Omara FA (2020) An intelligent Cloud service discovery framework. Fut Gener Comput Syst 106:438–466

    Article  Google Scholar 

  29. Hepp M (2008) Goodrelations: An ontology for describing products and services offers on the web. In: International conference on knowledge engineering and knowledge management, pp 329–346

  30. Gruber TR (1995) Toward principles for the design of ontologies used for knowledge sharing? Int J Hum-Comput Stud 43:907–928

    Article  Google Scholar 

  31. Cardoso J, Barros A, May N, Kylau U (2010) Towards a unified service description language for the internet of services: requirements and first developments. In: IEEE international conference on services computing, pp 602–609

  32. Pedrinaci C, Cardoso J, Leidig T (2014) Linked USDL: a vocabulary for web-scale service trading. In: European semantic web conference, pp 68–82

  33. Cardoso J, Pedrinaci C (2015) Evolution and overview of linked USDL. In: International conference on exploring services science, pp 50–64

  34. Höfer CN, Karagiannis G (2011) Cloud computing services: taxonomy and comparison. J Internet Serv Appl 2(2):81–94

    Article  Google Scholar 

  35. Parhi M, Pattanayak BK, Patra MR (2018) A multi-agent-based framework for Cloud service discovery and selection using ontology. Serv Orien Comput Appl 12(2):137–154

    Article  Google Scholar 

  36. Nagarajan R, Thirunavukarasu R, Shanmugam S (2018) A Cloud broker framework for infrastructure service discovery using semantic network. Int J Intell Eng Syst 11(3):11–19

    Google Scholar 

  37. Al-Sayed MM, Hassan HA, Omara FA (2019) An intelligent Cloud service discovery framework. Future Gener Comput Syst 106:438–466

    Article  Google Scholar 

  38. Dhanasekaran S, Vasudevan V (2019) A Cognizant agent system for optimizing Cloud service searching strategy. Cluster Comput 22(6):13381–13386

    Article  Google Scholar 

  39. Vasudevan M, Haleema PK, Iyengar NCS (2014) Semantic discovery of Cloud service catalog published over resource description framework. Int J Grid Distrib Comput 7(6):211–220

    Article  Google Scholar 

  40. Maheswari JU, Karpagam GR (2014) Ontology based comprehensive architecture for service discovery in emergency Cloud. Int J Eng Technol (IJET) 6(1):242–251

    Google Scholar 

  41. Alkalbani A, Shenoy A, Hussain F K, Hussain O K, Xiang Y (2015) Design and implementation of the hadoop-based crawler for saas service discovery. In: IEEE 29th international conference on advanced information networking and applications, pp 785–790

  42. Boukadi K, Rekik M, Rekik M, Ben-Abdallah H (2018) FC4CD: a new SOA-based Focused Crawler for Cloud service Discovery. Computing 100(10):1081–1107

    Article  Google Scholar 

  43. Alfazi A, Sheng Q Z, Qin Y, Noor T H (2015) Ontology-based automatic Cloud service categorization for enhancing Cloud service discovery. In: IEEE 19th international enterprise distributed object computing conference, pp 151–158

  44. Wheal J, Yang Y (2015) CSRecommender: a Cloud service searching and recommendation system. J Comput Commun 3(6):65–73

    Article  Google Scholar 

  45. Viji Rajendran V, Swamynathan S (2014) Multi Threaded priority based semantic crawler for Cloud services. In: International conference on Intelligent Information Technologies (ICIIT), pp 122–130

  46. Saravanan K, Radhakrishnan A (2018) Dynamic search engine platform for Cloud service level agreements using semantic annotation. Int J Seman Web Inf Syst (IJSWIS) 14(3):70–98

    Article  Google Scholar 

  47. Frey S, Reich C, Lüthje C (2013) Key performance indicators for Cloud computing SLAs. In: The fifth international conference on emerging network intelligence, EMERGING, pp 60–64

  48. Rodrigues R B, da Silva C M, Ferreira W O, MM, G (2013) A Cloud-based recommendation system. In: International conference on WWW/Internet, pp 384–386

  49. Soltani S, Elgazzar K, Martin P (2016) QuARAM service recommender: a platform for IaaS service selection. In: IEEE/ACM 9th international conference on utility and cloud computing (UCC), pp 422–425

  50. Balaji S, Rajkumar K (2018) A personalized Cloud service recommendation system using collaborative filtering. Int J Pure Appl Math 119(12):14173–14180

    Google Scholar 

  51. Mezni H, Abdeljaoued T (2018) A Cloud services recommendation system based on Fuzzy Formal Concept Analysis. Data Knowl Eng 116:100–123

    Article  Google Scholar 

  52. Zheng X, Da X, Chai SL (2017) Qos recommendation in Cloud services. IEEE Access 5:5171–5177

    Article  Google Scholar 

  53. Ma H, Hu Z, Li K, Zhu H (2019) Variation-aware Cloud service selection via collaborative QoS prediction. IEEE Trans Serv Comput:1–14

  54. Tang M, Zhang T, Liu J, Chen J (2015) Cloud service QoS prediction via exploiting collaborative filtering and location-based data smoothing. Concurr Comput Pract Exp 27(18):5826–5839

    Article  Google Scholar 

  55. Wang F F, Chen F Z, Li M Q (2019) A collaborative filtering method for Cloud service recommendation via exploring usage history. In: Proceeding of the 24th international conference on industrial engineering and engineering management, pp 716–725

  56. Ding S, Wang Z, Wu D, Olson DL (2017) Utilizing customer satisfaction in ranking prediction for personalized Cloud service selection. Decis Supp Syst 93:1–10

    Article  Google Scholar 

  57. Afify YM, Moawad IF, Badr NL, Tolba MF (2017) A personalized recommender system for SaaS services. Concurr Comput Pract Exp 29(4):e3877

    Article  Google Scholar 

  58. Djiroun R, Guessoum M A, Boukhalfa K, Benkhelifa E (2017) A novel Cloud services recommendation system based on automatic learning techniques. In: International conference on new trends in computing sciences (ICTCS), pp 42–49

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Nabli, H., Ben Djemaa, R. & Amous Ben Amor, I. Description, discovery, and recommendation of Cloud services: a survey. SOCA 16, 147–166 (2022). https://doi.org/10.1007/s11761-022-00343-7

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