IETF-based Finite Automaton for Service Composition in Service Function Chaining

Khosravian, Pouya; Emadi, Sima; Mirjalily, Ghasem; Zamani, Behzad

doi:10.1007/s11277-020-07417-9

Cited by 4 publications

(5 citation statements)

References 24 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Additionally, grammar can reduce the number of service compositions and search space by removing invalid SFCs. 28,29 Given the optimization nature of this problem, the GGA with the grammar F is used to create a service chain instance. A chromosome in the proposed GGA is equivalent to a service chain instance consistent.…”

Section: The Proposed Methodsmentioning

confidence: 99%

“…Since the chaining rules depend on the substrate physical platform, the proposed FA is based on the data center, mobile, and security scenarios introduced by the IETF. 28 This FA created a grammar and evaluated it by the Cocke-Younger-Kasami algorithm. 29 The benefit of this method is using the standard to the reduction in service compositions.…”

Section: Literature Reviewmentioning

confidence: 99%

See 1 more Smart Citation

Service function chain composition and placement using grammar‐based genetic algorithm

Khosravian

Emadi

Mirjalily

et al. 2021

Concurrency and Computation

Self Cite

View full text Add to dashboard Cite

Service function chaining (SFC) creates a requested orchestration for composition and placement of several service functions. One of the most critical issues for the service function providers is achieving the highest quality of service. We consider the problem of optimal Service Function composition and placement in an SFC-enabled network with the aim of achieving maximum Quality of Service (QoS). To this end, a method of merging the composition, routing, and placement phases is introduced. A genetic algorithm is designed to find the service chain instance with the maximum QoS using grammar-based Genetic Algorithm (GA) operators. This grammar is provided to filter invalid service compositions based on the data center, security, and mobile scenarios defined by Internet engineering task force. A chromosome in the proposed genetic algorithm corresponds to a service chain instance that matches the proposed grammar.For routing, strongly connected components (SCCs) are extracted to reduce search time in the network. Consequently, the search space is reduced for requests whose start and end nodes are placed in a SCC. Besides, the Floyd Warshall algorithm is used for routing between consecutive services. According to the results, the proposed method outperformed other methods in terms of the number of responded requests, runtime, and cost.

show abstract

Section: The Proposed Methodsmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

Service function chain composition and placement using grammar‐based genetic algorithm

Khosravian

Emadi

Mirjalily

et al. 2021

Concurrency and Computation

Self Cite

View full text Add to dashboard Cite

show abstract

“…Since the chaining rules depend on the substrate physical platform, their model acts based on the data center, mobile, and security use cases introduced by IETF. The finite automaton matcher showed that the model was a suitable tool for validating the composed service chain correctness (Khosravian et al, 2020). Mehraghdam & Karl (2016) proposed an innovative solution to select a set of compounds from different services based on the required resources.…”

Section: Related Workmentioning

confidence: 99%

“…Since this is an optimization problem, the GA can be employed to solve it. Also, the grammar can reduce the number of service compositions and search space by removing the invalid SFCs (Khosravian et al, 2019;Khosravian et al, 2020). Therefore, the GA is used along with the CFG to create service chain instances.…”

Section: The Proposed Algorithmmentioning

confidence: 99%

See 1 more Smart Citation

QoS-aware service composition based on context-free grammar and skyline in service function chaining using genetic algorithm

Khosravian

Emadi

Mirjalily

et al. 2021

PeerJ Computer Science

Self Cite

View full text Add to dashboard Cite

Service function chaining (SFC) is a mechanism that allows service providers to combine various service functions and exploit the available virtual infrastructure. The best selection of virtual services in the network is essential for meeting user requirements and constraints. This paper proposes a novel approach to generate the optimal composition of the service functions. To this end, a genetic algorithm based on context-free grammar (CFG) that adheres to the Internet Engineering Task Force (IETF) standard and Skyline was developed to use in SFC. The IETF uses cases of the data center, security, and mobile network filtered out the invalid service chains, which resulted in reduced search space. The proposed genetic algorithm found the Skyline service chain instance with the highest quality. The genetic operations were defined to ensure that the service function chains generated in the algorithm process were standard. The experimental results showed that the proposed service composition method outperformed the other methods regarding the quality of service (QoS), running time, and time complexity metrics. Ultimately, the proposed CFG could be generalized to other SFC use cases.

show abstract

Next Generation Mobile Core Resource Orchestration: Comprehensive Survey, Challenges and Perspectives

Al-Surmi

Raddwan

Al-Baltah

2021

Wireless Pers Commun

View full text Add to dashboard Cite

IETF-based Finite Automaton for Service Composition in Service Function Chaining

Cited by 4 publications

References 24 publications

Service function chain composition and placement using grammar‐based genetic algorithm

Service function chain composition and placement using grammar‐based genetic algorithm

QoS-aware service composition based on context-free grammar and skyline in service function chaining using genetic algorithm

Next Generation Mobile Core Resource Orchestration: Comprehensive Survey, Challenges and Perspectives

Contact Info

Product

Resources

About