Multi-Objective Optimum Solutions for IoT-Based Feature Models of Software Product Line

Abbas, Asad; Siddiqui, Isma Farah; Lee, Scott Uk-Jin; Ejaz, Waleed; Qureshi, Nawab Muhammad Faseeh

doi:10.1109/access.2018.2806944

Cited by 20 publications

(8 citation statements)

References 27 publications

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“…Constraint (13) ensures that for each XOR feature set, exactly one feature in P is selected if p is selected.…”

Section: Multi-objective Optimisation Modelmentioning

confidence: 99%

“…Currently, there are many applications of IoT such as home automation, healthcare, smart greenhouse, education, entertainment, social life, energy conservation, among others. These multi‐domain IoT applications are interesting for an MPL implementation since this paradigm arises for the development of large and complex systems through several independent SPLs that are developed by several organisations [13, 14] with different hardware and software technologies for different geographical areas and in any context.…”

Section: Introductionmentioning

confidence: 99%

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Multiple software product lines to configure applications of internet of things

et al. 2020

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Software product lines (SPL) emulate the industrial production lines that are capable of generating large volumes of products through reuse schemes and mass production. A multi product line (MPL) aims to reuse of several SPL. Feature models are often used to manage the existing resources of SPLs and define valid products through notations and relationships such as mandatory, optional, and alternative features. The main contribution of this study is a method to manage the variability of multiple SPL and generate a new portfolio of products for Internet of Things (IoT). For this, the problem of developing a universal feature model (FM) for an MPL from merging the FMs of the individual SPLs with a Search-Based Software Engineering (SBSE) technique is addressed. In addition, the authors propose a multi-objective optimisation model to maximise the reusability and compatibility between features and minimise the development cost. The model facilitates the design of an MPL-feature model. Authors' empirical results show that the proposed model solved by genetic algorithms allows to configure a variety of software products and to determine the scope of the MPL.

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“…Constraint (13) ensures that for each XOR feature set, exactly one feature in P is selected if p is selected.…”

Section: Multi-objective Optimisation Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Multiple software product lines to configure applications of internet of things

et al. 2020

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“…Therefore, it is crucial to efficiently manage the charging demands of EVs and infrastructure while considering the heterogeneous charging requirements of EVs. In this context, Internet of vehicles (IoV) is an emerging paradigm that can enable EVs and mobile charging infrastructure to use sensing and communication technologies for sustainable and budget-friendly intelligent transportation system as well as effectively manage consumer resources and reduce operating cost [2]- [4]. The main components of an IoVbased charging management system include sensing devices, actuators, communications technologies, and servers for data processing.…”

Section: Introductionmentioning

confidence: 99%

IoV-Based Deployment and Scheduling of Charging Infrastructure in Intelligent Transportation Systems

et al. 2021

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Internet of vehicles (IoV) is an emerging paradigm to exchange and analyze information collected from sensors using wireless technologies between vehicles and people, vehicles and infrastructure, and vehicles-to-vehicles. With the recent increase in the number of electric vehicles (EVs), the seamless integration of IoV in EVs and charging infrastructure can offer environmentally sustainable and budget-friendly transportation. In this paper, we propose an IoV-based framework that consists of deployment and scheduling of a mobile charging infrastructure. For the deployment, we formulate an optimization problem to minimize the total cost of mobile charging infrastructure placement while considering constraints on the number of EVs that can be charged simultaneously. The formulated problem is mixedinteger programming and solved by using the branch and bound algorithm. We then propose an IoV-based scheduling scheme for EVs charging to minimize travel distance and charging costs while satisfying the constraints of charging time requirement of EVs and resources of a charging station. We consider passive road sensors and traffic sensors in the proposed IoV-based scheduling scheme to enable EV users for finding a charging station that can fulfill their requirements, as well as to enable service providers to know about the demand in the area. Simulation results illustrate the significant impact of the optimal deployment of charging infrastructure and scheduling optimization on the efficiency of EVs charging.

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“…for specific market segments or domains [1] [2]. SPL is used for reusability of resources in family of products [3] [4]. In the competitive market, the most challenging task in SPL is designing the architecture.…”

Section: Introductionmentioning

confidence: 99%

Investigation of Tools, Techniques and Languages for Model Driven Software Product Lines (SPL): A Systematic Literature Review

Yousaf¹,

Akram²,

Bhatti³

et al. 2019

JSEA

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Software development is a complex and difficult task that requires the investment of sufficient resources and carries major risk of failure. Model Driven Engineering (MDE) focuses on creating software models and automating code generation from the models. Model Driven Software Development (MDSD) offers significantly more effective approaches. These approaches improve the way of building software. Model driven approaches partially increase developer productivity, decrease the cost of software construction, improve software reusability, and make software more maintainable. This paper investigates the methods where Model Driven Software Development is integrated with Software Product Line (SPL). This SLR has been conducted to identify 71 research works published since 2014. We have collected 18 tools, 14 techniques and 17 languages used for MDSD for SPL. We analyze which technique is suitable for SPL. We compare the techniques on the basis of features provided by these tools to understand the better-quality results.

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Multi-Objective Optimum Solutions for IoT-Based Feature Models of Software Product Line

Cited by 20 publications

References 27 publications

Multiple software product lines to configure applications of internet of things

Multiple software product lines to configure applications of internet of things

IoV-Based Deployment and Scheduling of Charging Infrastructure in Intelligent Transportation Systems

Investigation of Tools, Techniques and Languages for Model Driven Software Product Lines (SPL): A Systematic Literature Review

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