Transcript of ECMFA 2015 - Energy Consumption Analysis and Design with Foundational UML
- 1. Energy Consumption Analysis and Design of Energy-Aware WSN
Agents in fUML Luca Berardinelli, Antinisca Di Marco, Stefano Pace,
Luigi Pomante and Walter Tiberti 11th European Conference on
Modelling Foundations and Applications 2015 LAquila, Italy, July 20
24, 2015 Part of the conferences at STAF 2015
- 2. Outline Introduction: Wireless Sensor Network, Agilla
Middleware Problem: No Energy Aware Agilla Middleware Contribution:
Energy Measurements and Energy-Aware Agilla Problem: No MDE for
Agilla Contribution: Agilla Modeling Framework (AMF) o Foundational
UML for AMF as Simulation Infrastructure o Energy Analysis
Extension of AMF Conclusions 2
- 3. Introduction: WSN and Agilla Wireless Sensor Network (WSN) o
Spatially distributed, autonomous sensor that cooperate to
accomplish a task. o Sensor nodes are small, low-cost, wireless,
and battery powered. o Application domain: domotics, disaster
relief, security, health Agilla Middleware (MW) o A Mobile Agent
Middleware for Wireless Sensor Networks
http://mobilab.wustl.edu/projects/agilla/ o Assembly like: Agent,
Task, Instruction levels. o Agents can migrate with their execution
state. o Implemented on top of TinyOS, open source OS, for
resource- constrained nodes written in nesC, a C dialect. 3 VISION
is a project funded by an ERC Starting Independent Grant
- 4. Problem: No Energy-aware Agilla Lack of energy consumption
monitoring capability. Lack of energy consumption measurements of
Agilla MW, and hardware platforms for WSNs. Base Station PC Temp C
Reader (R) R R R RR 4
- 5. Contribution: Extension of Agilla MW Energy-aware Agilla MW
New battery instruction added to the Agilla MW ISA
http://mobilab.wustl.edu/projects/agilla/isa.html battery provides
voltage information with a precision of 100 mV. Technically, the
new instruction reads data from the ADC and puts it on the top of
the agent stack after some processing (e.g., a value 33 represents
3.3V). New Battery-Aware Reader Agent. Battery-Aware Reader (baR)
baR 5
- 6. Contribution: Extension of Agilla MW Measurements on real
target platform: IRIS Memsic node. Execution Time (in milliseconds)
of each instruction of the Agilla ISA (in EPEW2013). Energy
Consumption (in Milliamp Hours, mAh) of each instruction of the
Agilla ISA. ET/EC = constant Working with Warning Good condition
Serious Warning time Volt Ideal condition3 2.8 2.4 1/8 sec 1 sec
sensing every Energy Consumption = , =1 6 Battery-Aware Reader
(baR)
- 7. Problem: No MDE 4 Agilla Traditionally, WSN applications
have been developed with a code-and-fix approach. Lack of
(model-based) software engineering approaches. Risk of missing
non-functional requirements. No tailored approaches for WSN in
general, Agilla in particular. Base Station PC Temp C Reader (R) R
R R RR 7
- 8. Contribution: AMF Agilla Modeling Framework (AMF), a
model-based simulation framework based on Foundational UML (ongoing
work) Extension of Agilla MW and AMF framework to support Energy
Analysis Luca Berardinelli, Antinisca Di Marco, Stefano Pace:
fUML-Driven Design and Performance Analysis of Software Agents for
Wireless Sensor Network. ECSA 2014: 324-339 Luca Berardinelli,
Antinisca Di Marco, Stefano Pace, Stefano Marchesani, Luigi
Pomante: Modeling and Timing Simulation of Agilla Agents for WSN
Applications in Executable UML. EPEW 2013: 300-311 Jrmie Tatibouet,
Arnaud Cuccuru, Sbastien Grard, Franois Terrier: Principles for the
realization of an open simulation framework based on fUML (WIP).
SpringSim (TMS-DEVS) 2013 8
- 9. Contribution: AMF Agilla Modeling Framework (AMF), a
model-based simulation framework based on Foundational UML (ongoing
work) Extension of Agilla MW and AMF framework to support Energy
Analysis 1. Everything is a (UML) Model: the Case Study, AMF,
Analysis Results 2. Timing, Performance and Energy consumption
analyses enabled on top of fUML 3. No need of model transformations
to external notations 4. Tool supported (UML Modeling Tools, fUML
Virtual Machine, AMF) 9
- 10. Contribution: AMF (fUML background) COMPONENTS COMPOSITE
STRUCTURES DEPLOYMENTS INTERACTIONS STATE MACHINES USE CASES
CLASSES ACTIONS ACTIVITIES PROFILES lightweight extensions by
Foundational UML (fUML) - OMG Standard v.1.1 (2013) - dynamic
semantics for UML Classes and Activities - Virtual Machine (Java)
10
- 11. Contribution: AMF (fUML background) Foundational UML (fUML)
- OMG Standard v.1.1 (2013) - dynamic semantics for UML Classes and
Activities - Virtual Machine (Java) 11
- 12. Contribution: AMF- App.Design Classes and hierarchical set
of UML Activities (flow of Task actions, flow of Instructions)
Agent structure and Task actions are user-defined Instruction
actions represent the predefined Agilla ISA, i.e., they are
re-usable model elements AMF Model Library 12 Where is it? @
simulation time
- 13. Contribution: AMF- Library&Simulation AMF tailored for
Agilla programmers: Modeling as coding, 1:1 mapping, no abstraction
Activities are modeled as sequences of actions: no need to
explicitly model the control flow reader_obj:AgentComp
start_obj:TaskComp pushc_obj:Pushc setvar_obj:Setvar fUML Instance
Model @simulation time after parsing own_tasks own_instr
rjump_obj:Setvar if cc=1 if cc=0 Parsing support by AML Library: it
builds a hierarchical graph of TaskComp and InstrComp Semantics
support by AML Library: behavior() of InstrComp accesses linked
InstrComp and Agilla data structures (e.g., stack, condition code)
modeled in fUML 13
- 14. Contribution: AMF- Simulation
https://code.google.com/a/eclipselabs.org/p/agilla-modeling-framework/
(Old Version, Timing Analysis, No Parsing Only Sequential Flows,
Only Constant Time Values) 14
- 15. Contribution: AMF- Energy Analysis Energy Consumption = =1
, #1 #4 #5 15 #2 #3
- 16. Contribution: AMF- Energy Analysis R = Reader baR = Battery
Aware Reader Sc1, Sc2, Sc3: The three different simulation
scenarios differ from the agents sleep time between two consecutive
sense and dispatch (rout) of temperature to the base station (BS)
As expected, the baReader agent saves energy (from 38,37% in Sc1 up
to 43,22% in Sc3); Energy consumption is invariant w.r.t. the
sensing frequency (sleep busy wait) Lower delta max-min in R than
in baR (more complex control flow in baR, too few runs) max min max
min 16
- 17. Conclusion PROs o Everything is a model, including your
analysis tool o No model transformations to external notations
Agilla Middleware supports software agents for WSN Problem: No
Energy-aware Agilla Contribution: Extension of Agilla MW and Energy
Measurements Problem: No MDE 4 Agilla Contribution: Extension of
the Agilla Modeling Framework based on fUML 17
- 18. Conclusion CONs o high modeling effort for fUML library
provider (not user!) o scalability issue: fUML VM is not optimized
Agilla Middleware supports software agents for WSN Problem: No
Energy-aware Agilla Contribution: Extension of Agilla MW and Energy
Measurements Problem: No MDE 4 Agilla Contribution: Extension of
the Agilla Modeling Framework based on fUML 18