Browsing by Subject "Deployment"

Now showing 1 - 3 of 3

Open Access
Domain specific language for deployment of parallel applications on parallel computing platforms
(Association for Computing Machinery, 2014-08) Arkın, E.; Tekinerdoğan, Bedir
To increase the computing performance the current trend is towards applying parallel computing in which parallel tasks are executed on multiple nodes. The deployment of tasks on the computing platform usually impacts the overall performance and as such needs to be modelled carefully. In the architecture design community the deployment viewpoint is an important viewpoint to support this mapping process. In general the derived deployment views are visual notations that are not amenable for run-time processing, and do not scale well for deployment of large scale parallel applications. In this paper we propose a domain specific language (DSL) for modeling the deployment of parallel applications and for providing automated support for the deployment process. The DSL is based on a metamodel that is derived after a domain analysis on parallel computing. We illustrate the application of the DSL for a traffic simulation system and provide a set of important scenarios for using the DSL. © 2014 ACM.
Open Access
Optimization of transportation requirements in the deployment of military units
(Elsevier, 2007) Akgün, İ.; Tansel, B. Ç.
We study the deployment planning problem (DPP) that may roughly be defined as the problem of the planning of the physical movement of military units, stationed at geographically dispersed locations, from their home bases to their designated destinations while obeying constraints on scheduling and routing issues as well as on the availability and use of various types of transportation assets that operate on a multimodal transportation network. The DPP is a large-scale real-world problem for which analytical models do not exist. We propose a model for solving the problem and develop a solution methodology which involves an effective use of relaxation and restriction that significantly speeds up a CPLEX-based branch-and-bound. The solution times for intermediate-sized problems are around 1 h at maximum, whereas it takes about a week in the Turkish Armed Forces to produce a suboptimal feasible solution based on trial-and-error methods. The proposed model can be used to evaluate and assess investment decisions in transportation infrastructure and transportation assets as well as to plan and execute cost-effective deployment operations at different levels of planning.
Open Access
Optimization of transportation requirements in the deployment of military units
(2005) Akgün, İbrahim
We study the deployment planning problem (DPP) that may roughly be defined as the problem of the planning of the physical movement of military units, stationed at geographically dispersed locations, from their home bases to their designated destinations while obeying constraints on scheduling and routing issues as well as on the availability and use of various types of transportation assets that operate on a multimodal transportation network. The DPP is a large-scale real-world problem for which no analytical models are existent. In this study, we define the problem in detail and analyze it with respect to the academic literature. We propose three mixed integer programming models with the objectives of cost, lateness (the difference between the arrival time of a unit and its earliest allowable arrival time at its destination), and tardiness (the difference between the arrival time of a unit and its latest arrival time at its destination) minimization to solve the problem. The cost-minimization model minimizes total transportation cost of a deployment and is of use for investment decisions in transportation resources during peacetime and for deployment planning in cases where the operation is not imminent and there is enough time to do deliberate planning that takes costs into account. The lateness and tardiness minimization models are of min-max type and are of use when quick deployment is of utmost concern. The lateness minimization model is for cases when the given fleet of transportation assets is sufficient to deploy units within their allowable time windows and the tardiness minimization model is for cases when the given fleet is not sufficient. We propose a solution methodology for solving all three models. The solution methodology involves an effective use of relaxation and restriction that significantly speeds up a CPLEX-based branchand-bound. The solution times for intermediate sized problems are around one hour at maximum for cost and lateness minimization models and around two hours for the tardiness minimization model. Producing a suboptimal feasible solution based on trial and error methods for a problem of the same size takes about a week in the current practice in the Turkish Armed Forces. We also propose a heuristic that is essentially based on solving the models incrementally rather than at one step. Computational results show that the heuristic can be used to find good feasible solutions for the models. We conclude the study with comments on how to use the models in the realworld.