Energy Consumption Analysis and Design of Energy-Aware WSN Agents in fUML

Berardinelli, Luca; Marco, Antinisca Di; Pace, Stefano; Pomante, Luigi; Tiberti, Walter

doi:10.1007/978-3-319-21151-0_1

Cited by 13 publications

(8 citation statements)

References 14 publications

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“…This estimates (5) An immediate feedback is given to the developer about the energy that would be consumed on the final platforms. It can hence help her doing the best design choices for energy efficiency (6).…”

Section: The Energy-estimation Modeling Processmentioning

confidence: 99%

Annotating executable DSLs with energy estimation formulas

Fosse

Tisi

Mottu

et al. 2020

Proceedings of the 13th ACM SIGPLAN International Conference on Software Language Engineering

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Reducing the energy consumption of a complex, especially cyber-physical, system is a cross-cutting concern through the system layers, and typically requires long feedback loops between experts in several engineering disciplines. Having an immediate automatic estimation of the global system consumption at design-time would significantly accelerate this process, but cross-layer tools are missing in several domains.Executable domain-specific modeling languages (xDSLs) can be used to design several layers of the system under development in an integrated view. By including the behavioral specification for software and physical components of the system, they are an effective source artifact for cross-layer energy estimation.In this paper we propose EEL, a language for annotating xDSL primitives with energy-related properties, i.e. how their execution would contribute to the energy consumption on a specific runtime platform. Given an xDSL, energy specialists create EEL models of that xDSL for each considered runtime platform. The models are used at design time, to predict the energy consumption of the real systems. This avoids the need of energetic analysis by deployment and measurement on all runtime platforms, that is slow and expensive.We augment an existing language workbench for xDSLs with an editor for EEL models and a component that computes energy-consumption estimations during model editing. The evaluation shows that EEL can be used to represent

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Section: The Energy-estimation Modeling Processmentioning

confidence: 99%

Annotating executable DSLs with energy estimation formulas

Fosse

Tisi

Mottu

et al. 2020

Proceedings of the 13th ACM SIGPLAN International Conference on Software Language Engineering

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“…Luca Berardinelli et. al., propose an extension of the Agilla Modeling Language (AML) with an instruction triggering energy measurements of nodes in Wireless Sensors Network (WSN) [2]. The energy measured is then used for predicting and optimizing the design of the WSN, towards a better energy-awareness.…”

Section: Related Workmentioning

confidence: 99%

“…An implementation is available on GitHub 2 . Figure 1 proposes an overview of the approach and its three actors implied in it: the DSL Engineer, who knows the meta-programming approach and can design an executable meta-model with its operational semantic, the end-user who knows the executable meta-model (or a DSL), creates executable models conforming to it and runs them using the execution engine, and finally the Energy Estimation (EE) Specialist, who knows the EE meta-model, 2 https://github.com/atlanmod/energy-estimation-language the operational semantics of the execution meta-model, and the platform on which the models are executed. Whereas the DSL engineer and end-user actors are rather common in the realm of xDSMLs [5], the (EE) specialist is a novelty.…”

Section: Approachmentioning

confidence: 99%

Towards Platform Specific Energy Estimation for Executable Domain-Specific Modeling Languages

Fosse

Tisi

Bousse

et al. 2019

2019 ACM/IEEE 22nd International Conference on Model Driven Engineering Languages and Systems Companion (MODELS-C)

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Energy consumption is becoming a major subject when designing, developing and running programs. Most developers code and run their applications in an energy oblivious manner, mostly because of a lack of energy-related knowledge about their system. This problem also exists in the realm of executable domain-specific modeling languages, where end-users create models conforming to a given meta-model and execute them with little knowledge about their operational semantic and related energy consumption. In this work, we propose a domainspecific language for decorating meta-models of executable languages with platform-specific energy estimation formulas. We also extend the GEMOC execution engine to dynamically perform energy estimations on any executable model conforming to the decorated meta-model. The energy estimation model defined can then be easily adapted to other models and platforms, without requiring any measurement tooling or knowledge from the enduser.

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“…In the following, we list further approaches to the graph-based and model-based construction of TC algorithms. In [108], an extension to Agilla [44], a model-driven middleware for developing WSN applications, is proposed that introduces an instruction set for reading the current remaining energy of sensor nodes. In [45], a model-driven development process is proposed that allows to design TC algorithms based on meta-models and state charts and then to generate platform-specific code from this representation.…”

Section: Rq4-generalizabilitymentioning

confidence: 99%

A systematic approach to constructing incremental topology control algorithms using graph transformation

Kluge

Stein²,

Varr

et al. 2017

Journal of Visual Languages & Computing

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This document corresponds to the accepted manuscript of the article Kluge, R., Stein, M., Varró, G., Schürr, A., Hollick, M., Mühlhäuser, M.: "A Systematic Approach to Constructing Incremental Topology Control Algorithms using Graph Transformation," in: JVLC 2016. The URL of the formal version is https://dx.Communication networks form the backbone of our society. Topology control algorithms optimize the topology of such communication networks. Due to the importance of communication networks, a topology control algorithm should guarantee certain required consistency properties (e.g., connectivity of the topology), while achieving desired optimization properties (e.g., a bounded number of neighbors). Real-world topologies are dynamic (e.g., because nodes join, leave, or move within the network), which requires topology control algorithms to operate in an incremental way, i.e., based on the recently introduced modifications of a topology. Visual programming and specification languages are a proven means for specifying the structure as well as consistency and optimization properties of topologies. In this paper, we present a novel methodology, based on a visual graph transformation and graph constraint language, for developing incremental topology control algorithms that are guaranteed to fulfill a set of specified consistency and optimization constraints. More specifically, we model the possible modifications of a topology control algorithm and the environment using graph transformation rules, and we describe consistency and optimization properties using graph constraints. On this basis, we apply and extend a well-known constructive approach to derive refined graph transformation rules that preserve these graph constraints. We apply our methodology to re-engineer an established topology control algorithm, kTC, and evaluate it in a network simulation study to show the practical applicability of our approach. Meta-modeling [Sec. 2] WSN meta-model Topology control (TC) Graph constraints [Sec. 3] Structural constraints TC constraints Connectivity Consistency Graph transformation [Sec. 4] TC rules TC algorithm Context event rules Rule refinement [Sec. 5] Rule refinement algorithm Restoring rule applicability Enforcing termination Proving preservation of connectivity Evaluation [Sec. 6] RQ1: Correctness RQ2: Incrementality RQ3: Generalizability RQ4: Performance Figure 1: Overview of the proposed constructive methodology and structure of this paper (i) We characterize the required and desired properties of output topologies of a TC algorithm using graph constraints (as described in [42]).(ii) We use GT rules to describe TC operations, which specify the possible modifications during an execution of a TC algorithm, and context events, which specify the possible modifications by the environment.(iii) We apply and enhance the constructive refinement approach for GT rules presented in [42,43] to TC. Our approach is able to cope with temporarily constraint-violating rules, which contrary to [42,43] may not be restricted.(iv) We ...

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Energy Consumption Analysis and Design of Energy-Aware WSN Agents in fUML

Cited by 13 publications

References 14 publications

Annotating executable DSLs with energy estimation formulas

Annotating executable DSLs with energy estimation formulas

Towards Platform Specific Energy Estimation for Executable Domain-Specific Modeling Languages

A systematic approach to constructing incremental topology control algorithms using graph transformation

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