420
R. Khennaoui and N. Belala
The scenario illustrated in Fig. 1 is highly context dependent, especially in
the following way:
If the system detects a problem on the switch in datacenter location, he sends
a request to the closest helpdesk. This one has to move to the location of the
switch and send the current state by email to the management system:
State 1 fine, indicate that there is no critical problem.
State 2 not fine, in case of critical one which need to be fixed.
The corresponding CPSw to the scenario is illustrated in Fig. 2. It is built
from the initial Ag-LOTOS description:
move(l1); check;
(x!(fine); exit [] x!(not_fine); fix_it(l1); exit
4 Conclusion
Workflow systems are currently used by many organizations including health
care, automation and finance. Context awareness is the ability for workflows to
react to the changing situations. In this paper, we introduced a context-aware
workflow model, the CPSw, that presents all the possible evolutions of workflow’s activities constrained by the contextual information. CPSw is constructed
formally based on Ag-LOTOS description giving the set of activities.
We learned that using Ag-LOTOS to describe workflow activities is a promising approach. Mainly, because it allows a formal description of the current context in each state as pre- and post -conditions, and dynamically adjusts the modifications. Furthermore, it allows the verification and validation of the model.
The proposed model can be used in the verification process to verify certain
contextual properties. For future works, we aim to consider different types of
context information such as the time.
References
1. Remagnino, P., Foresti, G.: Ambient intelligence: a new multidisciplinary
paradigm. IEEE Trans. Syst. Man Cybern. - Part A: Syst. Hum. 35(1), 1–6 (2004)
2. Ramos, C.: Ambient intelligence a state of the art from artificial intelligence perspective. In: Neves, J., Santos, M.F., Machado, J.M. (eds.) EPIA 2007. LNCS,
vol. 4874, pp. 285–295. Springer, Heidelberg (2007). https://doi.org/10.1007/9783-540-77002-2 24
3. Abowd, D., Dey, A.K., Orr, R., et al.: Context-awareness in wearable and ubiquitous computing. Virtual Reality 3(3), 200–211 (1998)
4. Smanchat, S., Ling, S., Indrawan, M.: A survey on context-aware workflow adaptations. In: Proceedings of the 6th International Conference on Advances in Mobile
Computing and Multimedia, pp. 414–417 (2008)
5. Wieland, M., Kopp, O., Nicklas, D., Leymann, F.: Towards context-aware workflows. In: CAiSE07 Proceedings of the Workshops and Doctoral Consortium, vol.
2, no. S25, p. 15 (2007)
R. Khennaoui and N. Belala
The scenario illustrated in Fig. 1 is highly context dependent, especially in
the following way:
If the system detects a problem on the switch in datacenter location, he sends
a request to the closest helpdesk. This one has to move to the location of the
switch and send the current state by email to the management system:
State 1 fine, indicate that there is no critical problem.
State 2 not fine, in case of critical one which need to be fixed.
The corresponding CPSw to the scenario is illustrated in Fig. 2. It is built
from the initial Ag-LOTOS description:
move(l1); check;
(x!(fine); exit [] x!(not_fine); fix_it(l1); exit
4 Conclusion
Workflow systems are currently used by many organizations including health
care, automation and finance. Context awareness is the ability for workflows to
react to the changing situations. In this paper, we introduced a context-aware
workflow model, the CPSw, that presents all the possible evolutions of workflow’s activities constrained by the contextual information. CPSw is constructed
formally based on Ag-LOTOS description giving the set of activities.
We learned that using Ag-LOTOS to describe workflow activities is a promising approach. Mainly, because it allows a formal description of the current context in each state as pre- and post -conditions, and dynamically adjusts the modifications. Furthermore, it allows the verification and validation of the model.
The proposed model can be used in the verification process to verify certain
contextual properties. For future works, we aim to consider different types of
context information such as the time.
References
1. Remagnino, P., Foresti, G.: Ambient intelligence: a new multidisciplinary
paradigm. IEEE Trans. Syst. Man Cybern. - Part A: Syst. Hum. 35(1), 1–6 (2004)
2. Ramos, C.: Ambient intelligence a state of the art from artificial intelligence perspective. In: Neves, J., Santos, M.F., Machado, J.M. (eds.) EPIA 2007. LNCS,
vol. 4874, pp. 285–295. Springer, Heidelberg (2007). https://doi.org/10.1007/9783-540-77002-2 24
3. Abowd, D., Dey, A.K., Orr, R., et al.: Context-awareness in wearable and ubiquitous computing. Virtual Reality 3(3), 200–211 (1998)
4. Smanchat, S., Ling, S., Indrawan, M.: A survey on context-aware workflow adaptations. In: Proceedings of the 6th International Conference on Advances in Mobile
Computing and Multimedia, pp. 414–417 (2008)
5. Wieland, M., Kopp, O., Nicklas, D., Leymann, F.: Towards context-aware workflows. In: CAiSE07 Proceedings of the Workshops and Doctoral Consortium, vol.
2, no. S25, p. 15 (2007)