Quantifying and evaluating the technical debt on mobile cloud-based service level

Georgios Skourletopoulos, Constandinos X. Mavromoustakis, Jordi Mongay Batalla, George Mastorakis, Evangelos Pallis, Georgios Kormentzas

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

As network bandwidth and coverage continue to increase, the adoption rates of mobile devices are growing over time and the mobile technology is becoming increasingly industrialized. In mobile cloud marketplaces, the cloud-supported mobile services can be leased off. However, the mobile service selection may introduce technical debt (TD), which is essential to be predicted and quantified. In this context, this paper examines the incurrence of technical debt in the future when leasing cloud-based mobile services by proposing a novel quantitative model, which adopts a linear and symmetric approach as a linear growth in the number of users is predicted. The formulation of the problem is based on a cost-benefit analysis, elaborating on the potential profit that could be obtained if the number of users would be equal to the maximum value. The probability of overutilization of the selected service in the long run is also researched. Finally, a quantification tool has been developed as a proof of concept (PoC), which initiates the technical debt analysis and optimization on mobile cloud-based service level and aims to provide insights into the overutilization or underutilization of a web service when a linear increase in the number of users occurs.

Original languageEnglish
Title of host publication2016 IEEE International Conference on Communications, ICC 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781479966646
DOIs
Publication statusPublished - 12 Jul 2016
Event2016 IEEE International Conference on Communications, ICC 2016 - Kuala Lumpur, Malaysia
Duration: 22 May 201627 May 2016

Other

Other2016 IEEE International Conference on Communications, ICC 2016
Country/TerritoryMalaysia
CityKuala Lumpur
Period22/05/1627/05/16

Keywords

  • decision making
  • linearity
  • quantitative model
  • service level selection
  • technical debt evaluation
  • technical debt quantification

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