SMT Versus Genetic and OpenOpt Algorithms: Concrete Planning in the PlanICS Framework

Niewiadomski, Artur; Skaruz, Jaroslaw; Penczek, Wojciech; Szreter, Maciej; Jarocki, Mariusz

doi:10.3233/fi-2014-1134

Cited by 6 publications

(5 citation statements)

References 9 publications

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“…SMT (Satisfiability Modulo Theories) is a formalized approach to constraint programming. Formalized as a form of the constraint satisfaction problem, (1) the algorithm of the solver always returns a solution, which guarantees that the deployment is feasible or the impossibility to deploy the application if no solution is found (addressing RQ2); and (2) a large number of constraints (required to solve the problem at hand) help SMT-solvers to reduce the search space and to find the optimal solution faster [41] [42]. However, the flexibility of our approach allows to use other mathematical models for optimization.…”

Section: Tasks Implementation Selectormentioning

confidence: 99%

Energy-Efficient Deployment of IoT Applications in Edge-Based Infrastructures: A Software Product Line Approach

Cañete

Amor

Fuentes

2021

IEEE Internet Things J.

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In order to lower latency and reduce energy consumption, Edge Computing proposes offloading some computation intensive tasks usually performed in the Cloud onto nearby devices in the frontier/Edge of the access networks. However, current task offloading approaches are often quite simple. They neither consider the high diversity of hardware and software technologies present in edge network devices, nor take into account that some tasks may require some specific software and hardware infrastructure to be executed. This paper proposes a task offloading process that leans on Software Product Line technologies, which are a very good option to model the variability of software and hardware present in edge environments. Firstly, our approach automates the separation of application tasks, considering the data and operation needs and restrictions among them, and identifying the hardware and software resources required by each task. Secondly, our approach models and manages separately the infrastructure available for task offloading, as a set of nodes that provide certain hardware and software resources. This separation allows to reason about alternative offloading of tasks with different hardware and software resource requirements, in heterogeneous nodes and minimizing energy consumption. In addition, the offloading process considers alternative implementations of tasks to choose the one that best fits the hardware and software characteristics of available edge network infrastructure. The experimental results shows that our approach reduces the energy consumption in the user node by approximately 41%-62%, and the energy consumption of the devices involved in a task offloading solution by 34%-48%.

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Section: Tasks Implementation Selectormentioning

confidence: 99%

Energy-Efficient Deployment of IoT Applications in Edge-Based Infrastructures: A Software Product Line Approach

Cañete

Amor

Fuentes

2021

IEEE Internet Things J.

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“…Concretely, these modules use Z3, a SMT (Satisfiability Modulo Theories) solver [13]. Thus, (1) the algorithm of the solver always returns a solution, which guarantees that the deployment is feasible or the impossibility to deploy the application if no solution is found; and (2) a large number of constraints (required to solve the problem at hand) help SMT-solvers to reduce the search space and to find the optimal solution faster [27].…”

Section: Our Approachmentioning

confidence: 99%

Supporting the evolution of applications deployed on edge-based infrastructures using multi-layer feature models

Cañete

Amor

Fuentes

2020

Proceedings of the 24th ACM International Systems and Software Product Line Conference - Volume B

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The proliferation of cyber-physical systems has encouraged the emergence of new technologies and paradigms to improve the performance of IoT-based applications. Edge Computing proposes using the nearby devices in the frontier/Edge of the access network for deploying application tasks. However, the functionality of cyberphysical systems, which is usually distributed in several devices and computers, imposes specific requirements on the infrastructure to run properly. The evolution of an application to meet new user requirements and the high diversity of hardware and software technologies in the edge can complicate the deployment of evolved applications. The aim of our approach is to apply Multi Layer Feature Models, which capture the variability of applications and the infrastructure, to support the deployment in edge-based environments of cyber-physical systems applications. This separation can support the evolution of application and infrastructure. Considering that IoT/Edge/Cloud infrastructures are usually shared by many applications, the SPL deployment process has to assure that there will be enough resources for all of them, informing developers about the alternatives of deployment. Prior to its deployment and leaning on the infrastructure feature models, the developer can calculate what is the configuration of minimal set of devices supporting application requirements of the evolved application. In addition, the developer can find which is the application configuration that can be hosted in the current evolved infrastructure. CCS CONCEPTS • Software and its engineering → Software product lines; • Computer systems organization → Distributed architectures; Embedded and cyber-physical systems.

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“…The offers are searched by a concrete planner in order to find the best solution satisfying all constraints and maximizing the quality function. Thus, the concrete planning problem can be formulated as a constrained optimization problem (see [13]). Its solution consists in selecting one offer from each offer set such that all constraints are satisfied and the value of the quality function is maximized.…”

Section: Collecting Offers and Planningmentioning

confidence: 99%

“…Automatic composition of Web services is a very active area of research which has provided a lot of important results [10,1,15,6] as well as many implemented approaches [11,12,2,3,13]. In this paper we present the system TripICS -a real-life application of our Web service composition system PlanICS [8,9,13] to planning trips and travels around the world. While there are systems offering some support for planning excursions and travels [4,5], our system uses advanced automated concrete planning methods [13,16,14].…”

Section: Introductionmentioning

confidence: 99%

“…In this paper we present the system TripICS -a real-life application of our Web service composition system PlanICS [8,9,13] to planning trips and travels around the world. While there are systems offering some support for planning excursions and travels [4,5], our system uses advanced automated concrete planning methods [13,16,14]. TripICS is a specialization of the concrete planning viewed as a constrained optimization problem to the ontology containing services provided by hotels, airlines, railways, museums etc.…”

Section: Introductionmentioning

confidence: 99%

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TripICS - a Web Service Composition System for Planning Trips and Travels

Niewiadomski

Switalski

Kowalczyk

et al. 2018

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SMT Versus Genetic and OpenOpt Algorithms: Concrete Planning in the PlanICS Framework

Cited by 6 publications

References 9 publications

Energy-Efficient Deployment of IoT Applications in Edge-Based Infrastructures: A Software Product Line Approach

Energy-Efficient Deployment of IoT Applications in Edge-Based Infrastructures: A Software Product Line Approach

Supporting the evolution of applications deployed on edge-based infrastructures using multi-layer feature models

TripICS - a Web Service Composition System for Planning Trips and Travels

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