Priority Workflow Nets

Ţiplea, Ferucio Laurenţiu; Bocǎnealǎ, Corina

doi:10.1109/tsmca.2012.2198465

Cited by 9 publications

(25 citation statements)

References 40 publications

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“…In what follows we adopt the type L behavior of timed Petri nets [10] together with the standard behavior of priority Petri nets [24] Example 3: We add to the Petri net in Fig. 1 the time duration function δ given by δ(t F ) = 1, δ(t 1 C ) = δ(t 2 C ) = 2, and δ(t 1 P ) = δ(t 2 P ) = δ(t 3 P ) = 5.…”

Section: Timed Priority Resource-constrainedmentioning

confidence: 99%

“…Remark 1: The (k, R)-closure of a timed priority mlRCWF net γ = ( r , ρ, δ) is simply obtained as in Definition 3. The characterization in Proposition 1(1) cannot be extended to timed priority mlRCWF nets because it does not work for priority RCWF nets (see [24], Remark 3.1) which form a subclass of the class of timed priority mlRCWF nets.…”

Section: Timed Priority Resource-constrainedmentioning

confidence: 99%

“…Traditionally, workflow modeling has only focused on the control flow aspect in the specification. More recently, workflow models have been proposed, which take into consideration time constraints [5]- [13], resource constraints [9], [12], [14]- [19], [20]- [23], and priorities between tasks [24].…”

Section: Introductionmentioning

confidence: 99%

“…One such most important criteria is soundness [2], which means that proper termination of a workflow execution is ensured and no anomaly has occurred, such as deadlock or livelock. Soundness was originally formulated for unconstrained WF nets, and then extended to WF nets with time constraints [10], [11], [13], to WF nets with resource constraints [14], [16], [23], and to WF nets with priorities [24]. a) Paper Contribution: The complex workflows arising from practical applications usually combine time, resource, and task priority constraints.…”

Section: Introductionmentioning

confidence: 99%

“…The approach we use is to show that the time constraints we have imposed can be removed and the study of soundness of the time priority mlRCWF net model can be reduced to the study of soundness of the untimed priority resource constraint WF net model. This is an important result because the complexity of the reduction is linear in the size of the original model, and some techniques to study soundness of priority resource constraint WF nets already exist [24].…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Resource Relocation in Workflow Nets With Time, Resource, and Task Priority Constraints

Ţiplea

Bocǎnealǎ

2014

IEEE Trans. Syst. Man Cybern, Syst.

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Complex workflows arising from practical applications usually combine time, resource, and task priority constraints. The goal of this paper is to formulate a suitable WF net model with all these three types of constraints, and to investigate the soundness property of the resulting model. Thus, the concept of a multilevel resource constrained workflow net (mlRCWF net) as being a place composition of resource constrained workflow (RCWF) nets is introduced, and its soundness property is investigated. This model is then enriched with time and task priority constraints. It is shown that the soundness property of timed priority mlRCWF nets can be reduced in linear time to the soundness property of (untimed) priority RCWF nets. A resource relocation policy is a policy by which resources already allocated to some task are then relocated to urgent tasks, the current task being thus delayed. When the current tasks support an indefinite delay, the soundness of timed priority mlRCWF nets with resource relocation can be reduced in quadratic time to the soundness property of (untimed) priority RCWF nets.

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Section: Timed Priority Resource-constrainedmentioning

confidence: 99%

Section: Timed Priority Resource-constrainedmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Resource Relocation in Workflow Nets With Time, Resource, and Task Priority Constraints

Ţiplea

Bocǎnealǎ

2014

IEEE Trans. Syst. Man Cybern, Syst.

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A collaborative mobile edge computing and user solution for service composition in 5G systems

Ridhawi

Aloqaily

Kotb

et al. 2018

Trans Emerging Tel Tech

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Mobile edge computing (MEC) is an emergent technology that has revolutionized traditional cloud service solutions. Mobile edge computing extends cloud computing by providing processing, storage, and networking capabilities at the edge of the mobile network. Delay‐sensitive and context‐aware applications are able to execute within close proximity of mobile users. Additionally, today's cloud services are not tailored to user specifications, but rather diversified toward a group of users. To guarantee delivery of user‐specific services in 5G networks, service composition techniques should be incorporated. This article envisions a real‐time, context‐aware, service‐composition collaborative framework that lies at the edge of the network, comprising MEC and user devices for fast composite service delivery. The proposed solution decomposes cloud data into a set of files and services, which are then replicated to MEC nodes. Frequently requested files and services are further cached onto user mobile devices for faster access. Both MEC nodes and mobile users advertise their services onto the collaborative edge/user space, where services are delivered either composite or unrendered according to users' requests. Service composition is achieved through a learning‐based workflow‐net approach that relies on previous composition results to build service composition models to be used for new compositions. The presented solution provides guaranteed and fast delivery of the requested cloud composite services to end users while sustaining QoS requirements and load balancing among edge and mobile nodes.

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