FFBAT: A security and cost‐aware workflow scheduling approach combining firefly and bat algorithms

Arunarani, A. R.; Manjula, D.; Sugumaran, Vijayan

doi:10.1002/cpe.4295

Cited by 30 publications

(6 citation statements)

References 21 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Arunarani et al combined FA and bat algorithm (BA) to solve the workflow scheduling. 31 To accurately forecast the software cost, Kaushik et al designed a new method by coupling FA and artificial neural network. 32 To deal with the superior solution set search problem, a novel FA was designed based on the quantitative demand level of users.…”

Section: A Review Of Famentioning

confidence: 99%

See 1 more Smart Citation

A modified firefly algorithm based on neighborhood search

2020

Concurrency and Computation

View full text Add to dashboard Cite

Firefly algorithm (FA) is a new member of intelligent optimization algorithms. Several studies demonstrated that FA could successfully deal with several engineering and theoretical optimization problems. Nevertheless, there are some weak points in FA, such as parameter dependence and high computational complexity. To overcome the above issues, this paper proposes a modified FA based on neighborhood search (MFANS). In MFANS, there are three modifications. First, a modified attraction strategy is employed to reduce the complexity. Then, a neighborhood search method is used to search around the best neighborhood solutions. Third, the step parameter is dynamically adjusted. Performance of MFANS is compared with two improved FAs. Results show the effectiveness of MFANS.

show abstract

Section: A Review Of Famentioning

confidence: 99%

“…There are several scheduling problems in cloud computing. Arunarani et al combined FA and bat algorithm (BA) to solve the workflow scheduling 31 . To accurately forecast the software cost, Kaushik et al designed a new method by coupling FA and artificial neural network 32 .…”

Section: A Review Of Famentioning

confidence: 99%

A modified firefly algorithm based on neighborhood search

2020

Concurrency and Computation

View full text Add to dashboard Cite

show abstract

“…Li et al [8] and Arunarani et al [11] presented algorithms to find schedules that combines different levels of authentication, integrity verification, and encryption services, and a VM instance for each task for minimizing the execution cost, while meeting the minimum security requirement and deadline. However, these algorithms do not guarantee that all tasks that handle sensitive data (critical tasks) will be secured, due the codification of the optimization.…”

Section: Introductionmentioning

confidence: 99%

“…Consider solutions s 1 which applies security services for tasks A-B-C, and leaves D with no security and s 2 where A-C-D are secured, while B is not. The algorithms in [8] and [11] do not take into consideration the semantics of each workflow task. In their work, both solutions s 1 and s 2 have secured three tasks and, therefore, present the same security level.…”

Section: Introductionmentioning

confidence: 99%

(WIP) Tasks Selection Policies for Securing Sensitive Data on Workflow Scheduling in Clouds

Shishido

Estrella

Toledo

et al. 2018

2018 IEEE International Conference on Services Computing (SCC)

View full text Add to dashboard Cite

Scheduling is an important topic to support data security for workflow execution in clouds. Some workflow scheduling algorithms use security services such as authentication, integrity verification, and encryption for all workflow tasks. However, applying security services to no sensitive data does not make sense as no benefit is gained, yet it increases the makespan and monetary costs. In this paper, we introduce five policies for selection of tasks that handle sensitive data. We also propose a workflow scheduling algorithm based on a multipopulational genetic algorithm for minimizing cost while meeting a deadline. Experiments using four workflow applications show that our proposal can minimize both the makespan and cost while maintaining the security of sensitive data compared to another approach in the literature.

show abstract

“…Arunarani et al propose a security and cost aware scheduling algorithm for heterogeneous tasks in scientific workflow executed in a cloud. A core semantics extraction model (CSEM) is proposed by Liu et al to improve the novel and rich semantics of multi‐document summary.…”

mentioning

confidence: 99%

Special issue on selected technologies and applications in smart city computing

Yen

Sugumaran

2017

Concurrency and Computation

Self Cite

View full text Add to dashboard Cite

Special issue on selected technologies and applications in smart city computingDeveloping smart city is the key to the next generation urbanization process for improving the efficiency, reliability, and security of a traditional city. The concept of smart city includes various aspects such as environmental sustainability, social sustainability, regional competitiveness, natural resources management, cybersecurity, and quality of life improvement. With the massive deployment of networked smart devices/sensors, unprecedentedly large amount of sensory data can be collected and processed by advanced computing paradigms which are the enabling techniques for smart city. For example, given historical environmental, population and economic information, salient modeling, and analytics are needed to simulate the impact of potential city planning strategies, which will be critical for intelligent decision making. Analytics are also indispensable for discovering the underlying structure from retrieved data in order to design the optimal policies for real-time automatic control in the cyberphysical smart city system. Furthermore, uncertainties and security concerns in the data collected from heterogeneous resources aggravate the problem, which makes smart city planning, operation, monitoring, and control highly challenging.The submitted manuscripts were reviewed by experts from both academia and industry. After two rounds of reviewing, the highest quality manuscripts were accepted for this special issue. Totally, 14 papers are accepted. This special issue will be published by CCPE as special issues. ACKNOWLEDGMENTSThe guest editors would like to thank Prof Geoffrey C. Fox who is the editor in chief of CCPE. His help and trust is the most important thing for the success of this SI. The guest editors would like to thank the reviewers for their high-quality reviews, which provided insightful and constructive feedback to the authors of the papers. ORCIDZheng Xu

show abstract

FFBAT: A security and cost‐aware workflow scheduling approach combining firefly and bat algorithms

Cited by 30 publications

References 21 publications

A modified firefly algorithm based on neighborhood search

A modified firefly algorithm based on neighborhood search

(WIP) Tasks Selection Policies for Securing Sensitive Data on Workflow Scheduling in Clouds

Special issue on selected technologies and applications in smart city computing

Contact Info

Product

Resources

About