=Paper=
{{Paper
|id=Vol-2339/paper4
|storemode=property
|title=Towards Dynamic Resource Management in Business Processes
|pdfUrl=https://ceur-ws.org/Vol-2339/paper4.pdf
|volume=Vol-2339
|authors=Sven Ihde,Luise Pufahl,Asvin Goel,Mathias Weske
|dblpUrl=https://dblp.org/rec/conf/zeus/IhdePGW19
}}
==Towards Dynamic Resource Management in Business Processes==
https://ceur-ws.org/Vol-2339/paper4.pdf
Towards Dynamic Resource Management in
Business Processes?
Sven Ihde1 , Luise Pufahl1 , Asvin Goel2 , and Mathias Weske1
1
Hasso Plattner Institute, University of Potsdam, 14482 Potsdam, Germany
{sven.ihde,luise.pufahl,mathias.weske}@hpi.de
2
Kühne Logistics University, Hamburg, Germany
asvin.goel@the-klu.org
Abstract. Resource management is an important part of modern busi-
ness processes. Although some extensions for handling resource allocation
within the modeling standard Business Process Model and Notation have
been proposed before, we argue that these are limited for the dynamic
management of resources in business processes, where an efficient alloca-
tion of resources to tasks is of crucial importance for achieving overall
efficiency. In this paper we show challenges of resource management based
on a real-world example, and why current approaches are not able to
fully handle them. We propose to extend existing business process man-
agement systems by a so-called Resource Manager with which powerful
optimization algorithms for resource allocations can be used and discuss
its main functionality and remaining challenges.
Keywords: Resource Allocation · Resource Optimization · Business
Process Modeling · Business Process Architecture.
1 Introduction
Business processes are indispensable for organizations to achieve certain goals,
such as selling products or hiring employees. Especially for a business, its processes
increase in amount and complexity alongside with its growth [5]. This raises
the need for concepts, methods, and techniques to represent business processes
in such a way, that the process experts can analyze, comprehend, and improve
existing business processes [15]. The main artifact is thereby a process model
representing visually a certain business process. The de facto standard Business
Process Model and Notation (BPMN) [10] is commonly used as process modeling
notation. The resulting model can also be used to automatically execute a process
with business process management systems (BPMSs) [5, 15].
For enacting business processes, resources (e.g. employees, organizations,
hardware, software, etc.) are indispensable [15]. Given that many resources are
cost-intensive and limited, a main challenge for efficient process execution is to
?
The research leading to these results has been partly funded by the BMWi under
grant agreement 01MD18012C, Project SMile. http://smile-project.de
S. Kolb, C. Sturm (Eds.): 11th ZEUS Workshop, ZEUS 2019, Bayreuth, Germany, 14-15
February 2019, published at http://ceur-ws.org/Vol-2339
18 Sven Ihde et al.
find a perfect balance between having enough resources available at all times in
order to execute processes without delays, and not having too many resources
available which are under-utilized [1]. For the case of human resources, there
exist so called resource allocation patterns [12], with are used to pre-define at
design time to allocate resources at runtime.
Schedule Deliver parcel
parcel delivery
Parcel delivery Scheduled time Parcel delivered
requested occured
Fig. 1. Simplified model of a parcel delivery process
Rule-based allocations of resources to tasks cannot leverage the full potential
of an efficient resource management. The example in Fig. 1 shows a very simple
process model of a parcel delivery process where each parcel has its own process
instance. For each parcel, the delivery is scheduled and when the scheduled
time is reached, the parcel is delivered to the customer. Clearly, resources, i.e.,
delivery vehicles, are needed in order to actually conduct the delivery. In order to
efficiently utilize these vehicles, the scheduling of the individual parcels must be
conducted in such a way that cost-efficient routes for the vehicles can be found,
allowing to deliver all parcels at their scheduled times. Thus, the scheduling
represented as a simple user task (cf. Fig. 1) is a complex task, where all suitable
vehicles and all other delivery requests should be considered. In our example, we
assume that this task is done manually by a dispatcher, who has knowledge about
all resources available and all delivery requests. However, the task could also
be executed by an optimization engine using algorithms for solving a so-called
vehicle routing problem [14], a combinatorial optimization problem known to be
N P-hard, and thus, being extremely difficult to solve.
Similar combinatorial optimization problems, in which rule-based allocations
of tasks to resources can lead to significant efficiency problems, can also be
found in many other business processes. Therefore, an innovative approach that
enables current business processes to be extended by the means to dynamically
manage resources is needed. We propose an extension of existing Business Process
Enactment Systems by introducing a new component, which is responsible
for resource allocations – the Resource Manager. The Resource Manager is
supposed to accumulate and congregate the knowledge of the different resources,
as well as having access to currently running processes, resulting in a highly
adaptive resource allocation.
In the next section 2, existing approaches concerning resource allocation are
discussed. In section 3 we introduce the Resource Manager and what require-
ments it has to fulfill. On top of that, we will explain how our approach can fill
the shortcoming of the current approaches in accordance to the given example.
Towards Dynamic Resource Management in Business Processes 19
Lastly, in section 4 we will give an outlook on how we will work to realize our
proposal as well as validate its functionality.
2 Related Work
Next to the control-flow and data-flow perspective, the resource-perspective is
essential for business processes describing how to allocate required resources to
a process task for its successful execution [15]. So called Resource Allocation
Patterns [12] have been introduced to manage (mostly) human resources. Further
it was shown (see [2, 6, 16]) that these resource allocation patterns could be used
during process modeling by adapting the existing modeling notation BPMN [10].
These resource-aware Process Models (see [7, 13]), where then analyzed by Ca-
banillas et al. [3, 4]. They stated that these models tend to be too complex for a
process modeler to use or only offer a limited flexibility of resource allocation
rules. When looking at non-human resources, there exist multiple approaches
(see [9, 11]) that try to efficiently combine process instances for certain activities
(i.e., batching) in order to optimize the resource utilization. However, these
approaches only support a fixed set of allocation algorithms or only resources of
one type, which, especially with upcoming trends like Internet of Things (see [8])
and digitization, is not enough. Given that the problem of allocating resources
to tasks is a complex problem that can be tackled in many different ways (e.g.
manually or by use of optimization algorithms), we can observe that there is
a need to explicitly model an entity for making resource allocation decisions,
allowing a process designer to focus on the process model, whereas the resource
allocation decisions can be optimized by a dedicated engine having access to all
relevant information about resources and requests for these resources.
3 Resource Manager
In this section, we introduce a new approach that extends the current business
process management system by adding one further component (see Fig. 2).
Traditionally, a BPMS consists of two main components: the Process Modeling
and the Process Engine component. With the Modeling component, process
models can be created by a process designer and stored into a Process Model
Repository. The current versions of the models in the Repository are then
accessed by the Engine to execute them. If the process contains service tasks, the
Engine calls other applications – in the case of a user task, the Engine provides
the tasks to the process participants over an user interface via the Environment.
The new component is an additional service for business processes, which
allows an optimized resource allocation. It is independent from the individual
process execution, but has on the other hand knowledge on the existing resources,
their characteristics (static data), their availability (dynamic data), and on the
other hand, access to the currently executing process cases (i.e. process instances).
Our extension is built up similarly to the traditional BPMS and consists of three
parts: Resource Modeling, Resources, and Resource Manager.
20 Sven Ihde et al.
Process Designer Process Participant Resource Designer
Process Environment Resource
Modeling Modeling static
Resources
Process Process Resource dynamic
Model Engine Manager
Repository
Applications
Traditional BPES Extension
Fig. 2. FMC model of our proposal for the extended Business Process Management
System
Resource Modeling. Similar to the Process Modeling, this component is used
by the Resource Designer to model the static part of resources according to
a notation, that can be translated and executed by the Resource Manager.
The Resource Modeling is responsible for defining the static data required to
determine whether a resource may be allocated to a request or not, as well as
the data required to assess and evaluate resource allocations. For example, the
data may include the type of the resource, the hourly costs, capacity, etc.
Resources. The Resources contain the full information on the static information
of resources that are supposed to be modeled. During runtime the Resources
additionally contain dynamic data, which is updated by the Resource Manager
only. In this way the Resources part contains the exact representation of the
existing resources. This means if a resource can not be found in the Resources it
does not exist and if we find two resources of the same type, we have exactly two
resources. Additionally we propose to give read-only access to the Resources to
the Process Designer during Process Modelling in order to make sure if the
process is going to use resources, it is done correctly. Thanks to that, in contrast
to traditional process designing, the Process Designer does not need to specify
the concrete resource for an activity but can instead ask the Resource Manager
to allocate the needed resource at run-time. This means that there is the need of
a change in the Process Modeling, whenever a resource is a part of the process
(see Fig. 3).
Towards Dynamic Resource Management in Business Processes 21
Resource Manager. The Resource Manager is a component maintaining informa-
tion about the current state (dynamic data) of all resources. Whenever a resource
is requested by a process instance, it collects all relevant data concerning the
resource request so that allocation decisions can be made. The actual allocation
decisions can then either be performed via an appropriate user interface by a
human decision maker or via a suitable interface by an optimization engine.
Whenever a resource is allocated to one or multiple requests, the state of the
resource is updated and the respective process instances are informed about the
allocation. Whenever a requested resource is no longer needed, the Resource
Manager is informed by the process instance so that the state of the resource can
be updated accordingly.
Resource Manager
Process Engine
Deliver
parcel
Parcel delivery Request Vehicle Release Parcel
requested vehicle allocated allocation delivered
Fig. 3. Parcel delivery process with resource manager
Fig. 3 shows an adaptation of the parcel deliver process in which the com-
munication between the process model and the Resource Manager is explicitly
modelled. In comparison to the process shown in Fig. 1, the scheduling task is
no longer executed within the process instance itself. Thus, instead of having the
planning tasks distributed over all individual process instances, the scheduling
task, which should consider information about all delivery requests and vehicles,
can be executed where all of this information is available. As the Resource
Manager has to be called from inside the Engine that executes the business
process, there has to be a close connection between these two components. An-
other idea would be to fully incorporate the Resource Manager into the Engine.
However, this will lead to problems as the Resource Manager is supposed to
manage the resources for multiple processes (instances) as those different execu-
tion might not necessarily be on the same Engine. That is why we need to have
the Resource Manager as a stand-alone component. Furthermore, the Resource
Manager is expected to be the expert concerning all resources it is in charge of.
This means it further encapsulates the resource specific knowledge as not all
processes need the complete information or on different detail levels.
22 Sven Ihde et al.
4 Future Work
In this work we introduced a concept to extend the architecture of BPMS in
such a way that an effective linking between tasks and resources is possible to
cope with challenges from multiple and even freshly emerging fields (e.g. IoT,
parcel delivery, cloud etc.). However, so far we only theoretically showed the
shortcomings of existing approaches and how a component managing resources as
a service could bridge these gaps. In order to evaluate our approach, we are going
to implement a proof of concept. We have identified three main challenges we
need to accomplish. Firstly, as mentioned during the explanation of the Resource
Modeling, the challenge is to define a standard notation for resource models.
After we have resources defined in such a way processes can use them, we can
create resource-aware business processes. For this we need to adapt the Process
Modeling part, so that a process now can access resources when needed. This
means we will have to introduce new modeling concepts concerning resources.
Lastly we are going to implement a Resource Manager that at runtime uses its
expertise to enable dynamic resource allocation. As the Resource Manager is
supposed to be the expert for many different allocation problems, we need to
define the communication between the Engine and Resource Manager. For this
we are going to define an interface for each allocation problem the Resource
Manager can solve, where the Engine will send its constraints and expectation
on the result, which are used to come up with an efficient allocation. We are
going to evaluate the implementation on a real-world example in the context of a
logistics project (SMile Project). Depending on these results we can then further
refine our approach.
References
1. Armbrust, M., Fox, A., Griffith, R., Joseph, A.D., Katz, R., Konwinski, A., Lee,
G., Patterson, D., Rabkin, A., Stoica, I., Zaharia, M.: A view of cloud computing.
Commun. ACM 53(4), 50–58 (Apr 2010). https://doi.org/10.1145/1721654.1721672
2. Awad, A., Grosskopf, A., Meyer, A., Weske, M.: Enabling resource assignment
constraints in BPMN. Tech. rep., BPT Technical Report 04, Hasso Plattner Institute,
Potsdam (2009)
3. Cabanillas, C., Knuplesch, D., Resinas, M., Reichert, M., Mendling, J., Ruiz-Cortés,
A.: Ralph: a graphical notation for resource assignments in business processes. In:
CAiSE. pp. 53–68. Springer (2015)
4. Cabanillas, C., Resinas, M., Ruiz-Cortés, A.: Ral: A high-level user-oriented resource
assignment language for business processes. In: CAiSE. pp. 50–61. Springer (2011)
5. Dumas, M., Rosa, M.L., Mendling, J., Reijers, H.A.: Fundamentals of Business
Process Management, Second Edition. Springer (2018). https://doi.org/10.1007/978-
3-662-56509-4
6. Großkopf, A.: An extended resource information layer for BPMN. Master’s thesis,
Hasso-Plattner-Institute for IT Systems Engineering, University of Potsdam (2007)
7. Künzle, V., Weber, B., Reichert, M.: Object-aware business processes: Fundamental
requirements and their support in existing approaches. International Journal of
Information System Modeling and Design (IJISMD) 2(2), 19–46 (2011)
Towards Dynamic Resource Management in Business Processes 23
8. Meyer, S., Ruppen, A., Magerkurth, C.: Internet of things-aware process modeling:
integrating IoT devices as business process resources. In: CAiSE. pp. 84–98. Springer
(2013)
9. Natschläger, C., Bögl, A., Geist, V.: Optimizing resource utilization by combining
running business process instances. In: Service-Oriented Computing-ICSOC 2014
Workshops. pp. 120–126. Springer (2015)
10. OMG: Notation BPMN version 2.0. OMG Specification, Object Management Group
(2011)
11. Pufahl, L., Weske, M.: Batch activities in process modeling and execution. In:
International Conference on Service-Oriented Computing. pp. 283–297. Springer
(2013)
12. Russell, N., van der Aalst, W.M.P., ter Hofstede, A.H., Edmond, D.: Workflow
resource patterns: Identification, representation and tool support. In: CAiSE. pp.
216–232. Springer (2005)
13. Saidani, O., Nurcan, S.: Towards context aware business process modelling. In:
BPMDS’07, CAiSE. vol. 7, p. 1 (2007)
14. Toth, P., Vigo, D.: Vehicle Routing: Problems, Methods, and Applications. No. 18
in MOS-SIAM Series on Optimization, SIAM (2014)
15. Weske, M.: Business Process Management - Concepts, Languages, Architectures,
2nd Edition. Springer (2012). https://doi.org/10.1007/978-3-642-28616-2
16. Wolter, C., Schaad, A.: Modeling of task-based authorization constraints in BPMN.
In: CAiSE. pp. 64–79. Springer (2007)