Modeling and Timing Simulation of Agilla Agents for WSN Applications in Executable UML

Abstract

Abstract. Wireless Sensor Networks are becoming one of the most successful choices for the development and deployment of a wide range of applications, from intelligent homes to environment monitoring. In response to the growing demand for fast development of WSN applications, we extend an existing UML-based approach for the design and code generation of Agilla applications with functional simulation and timing analysis capabilities through executable UML models. The proposed approach makes use of both a UML profile and an executable model library for Agilla. Execution times, annotated on Agilla instructions and patterns in the library, are given as additional input parameters during the model execution to carry out a timing analysis of the simulated Agilla applications. Modeling and simulation activities rely on MagicDraw© and Cameo Simulation Toolkit©. A running case study is provided to show the approach and the supporting tools at work.

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

“…To re-use the timing and performance analysis defined in [1,2] also for Agilla2.0/TOS2.x, we performed once again the measurement of the execution time of each single Agilla2.0 instruction. The techniques used in [1] were partially adapted by exploiting a free-running HW counter to timestamp start and end times of each instruction. Such timestamps have been then collected and used to evaluate offline (in order to be as less as possible intrusive in the code behavior) the average execution time for each instruction and other statistical information.…”

“…In this paper we reuse and extend the Wildfire Tracking Application (WTA), an existing case study originally described in [3] and already adopted in our previous work [1,2]. The WTA software is deployed on a WSN distributed into a region that is prone to fires.…”

“…The other AMF capabilities (parsing, instruction semantics simulation, trace generation, timing and performance analyses) are described in our previous works [1,2].…”

“…In [1] we modeled and implemented 8 the timing analysis algorithm which collects and sums slot values corresponding to measured instruction execution times (e.g., the et default value of pushc in Figure 7c). In [2] we further enhanced AMF with a First Come First Served (FCFS) scheduling policy required by the Performance Analysis capability to generate additional timed properties like waiting (wt), and completion times (ct).…”

“…For this aim i) we extend the Agilla Instruction Set with the new battery instruction able to sense at run-time the battery of a WSN node; ii) we measure the energy that the execution of each Agilla instruction consumes on a target platform; and iii) we extend the Agilla Modeling Framework (AMF) [1,2] with a new analysis that, leveraging on the conducted energy consumption measurements, predicts the energy required by the Agilla agents running on the WSN. AMF is an executable model library we implemented to model and analyze Agilla based applications running on WSN.…”