Abstract
Configurable processes are increasingly being adopted by enterprises that seek experience sharing and best practice adoption. A configurable process is a customizable model that specifies how different enterprises perform similar processes. At the modeling level, a configurable process model provides for flexible business process reuse by (de)selecting the (ir)relevant parts to derive a particular process variant. At the exploitation level, it offers flexibility and agility to an enterprise looking to outsource its business process to different providers cooperating in a cloud federation. More specifically, an enterprise can use a configurable process model to derive particular process variants that it outsources depending on its objectives. In particular, it may opt for outsourcing the variant that results in the optimal deployment, e.g., having the minimal cost of allocated cloud services that fulfill the user Quality of Service (QoS) requirements. However, identifying the optimal deployment variants is a complex problem because of the heterogeneity of services within a cloud federation and the number of possible variants that can be derived from a configurable process model. In addition, the complexity of this problem increases for variable user QoS requirements. In this paper, we propose an approach to derive, from a configurable process model, the variant that has the optimal deployment in a cloud federation. We propose a linear programming approach that accounts for the variability of both the business process model and the user QoS requirements, and that ensures an optimal time-aware cloud service allocation. We experimentally show the effectiveness and flexibility of our approach on a generated testbed.
Original language | English |
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Journal | IEEE Transactions on Network and Service Management |
Volume | 15 |
Issue number | 4 |
DOIs | |
Publication status | Published - 8 Nov 2018 |
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Keywords
- Cloud computing
- cloud federation
- configurable business process
- Linear programming
- linear programming
- Logic gates
- optimal deployment.
- QoS requirement variability
- Quality of service
- Resource management
- Security
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Optimal deployment of configurable business processes in cloud federations. / Rekik, Molka; Boukadi, Khouloud; Assy, Nour; Gaaloul, Walid; Ben-Abdallah, Hanene.
In: IEEE Transactions on Network and Service Management, Vol. 15, No. 4, 08.11.2018.Research output: Contribution to journal › Article › Academic › peer-review
TY - JOUR
T1 - Optimal deployment of configurable business processes in cloud federations
AU - Rekik, Molka
AU - Boukadi, Khouloud
AU - Assy, Nour
AU - Gaaloul, Walid
AU - Ben-Abdallah, Hanene
PY - 2018/11/8
Y1 - 2018/11/8
N2 - Configurable processes are increasingly being adopted by enterprises that seek experience sharing and best practice adoption. A configurable process is a customizable model that specifies how different enterprises perform similar processes. At the modeling level, a configurable process model provides for flexible business process reuse by (de)selecting the (ir)relevant parts to derive a particular process variant. At the exploitation level, it offers flexibility and agility to an enterprise looking to outsource its business process to different providers cooperating in a cloud federation. More specifically, an enterprise can use a configurable process model to derive particular process variants that it outsources depending on its objectives. In particular, it may opt for outsourcing the variant that results in the optimal deployment, e.g., having the minimal cost of allocated cloud services that fulfill the user Quality of Service (QoS) requirements. However, identifying the optimal deployment variants is a complex problem because of the heterogeneity of services within a cloud federation and the number of possible variants that can be derived from a configurable process model. In addition, the complexity of this problem increases for variable user QoS requirements. In this paper, we propose an approach to derive, from a configurable process model, the variant that has the optimal deployment in a cloud federation. We propose a linear programming approach that accounts for the variability of both the business process model and the user QoS requirements, and that ensures an optimal time-aware cloud service allocation. We experimentally show the effectiveness and flexibility of our approach on a generated testbed.
AB - Configurable processes are increasingly being adopted by enterprises that seek experience sharing and best practice adoption. A configurable process is a customizable model that specifies how different enterprises perform similar processes. At the modeling level, a configurable process model provides for flexible business process reuse by (de)selecting the (ir)relevant parts to derive a particular process variant. At the exploitation level, it offers flexibility and agility to an enterprise looking to outsource its business process to different providers cooperating in a cloud federation. More specifically, an enterprise can use a configurable process model to derive particular process variants that it outsources depending on its objectives. In particular, it may opt for outsourcing the variant that results in the optimal deployment, e.g., having the minimal cost of allocated cloud services that fulfill the user Quality of Service (QoS) requirements. However, identifying the optimal deployment variants is a complex problem because of the heterogeneity of services within a cloud federation and the number of possible variants that can be derived from a configurable process model. In addition, the complexity of this problem increases for variable user QoS requirements. In this paper, we propose an approach to derive, from a configurable process model, the variant that has the optimal deployment in a cloud federation. We propose a linear programming approach that accounts for the variability of both the business process model and the user QoS requirements, and that ensures an optimal time-aware cloud service allocation. We experimentally show the effectiveness and flexibility of our approach on a generated testbed.
KW - Cloud computing
KW - cloud federation
KW - configurable business process
KW - Linear programming
KW - linear programming
KW - Logic gates
KW - optimal deployment.
KW - QoS requirement variability
KW - Quality of service
KW - Resource management
KW - Security
UR - http://www.scopus.com/inward/record.url?scp=85056334553&partnerID=8YFLogxK
U2 - 10.1109/TNSM.2018.2880195
DO - 10.1109/TNSM.2018.2880195
M3 - Article
AN - SCOPUS:85056334553
VL - 15
JO - IEEE Transactions on Network and Service Management
JF - IEEE Transactions on Network and Service Management
SN - 1932-4537
IS - 4
ER -