In this paper we present the design and implementation of a generic GA-based optimization framework iMASKO ( iNL@ MATLAB Genetic Algorithm-based Sensor Networ K Optimizer) to optimize the performance metrics of wireless sensor networks. Due to the global search property of genetic algorithms, the framework is able to automatically and quickly fine tune hundreds of possible solutions for the given task to find the best suitable tradeoff. We test and evaluate the framework by using it to explore a SystemC-based simulation process to tune the configuration of the unslotted CSMA/CA algorithm of IEEE 802.15.4, aiming to discover the most available tradeoff solutions for the required performance metrics. In particular, in the test cases different sensor node platforms are under investigation. A weighted sum based cost function is used to measure the optimization effectiveness and capability of the framework. In the meantime, another experiment is performed to test the framework’s optimization characteristic in multi-scenario and multi-objectives conditions.
References
[1]
Zhu, N.H.; O’Connor, I. Performance Evaluations of Unslotted CSMA/CA Algorithm at High Data Rate WSNs Scenario. In Proceeding of the 9th IEEE International Wireless Communications and Mobile Computing Conference (IWCMC 2013), Cagliari, Italy, 1–5 July 2013; pp. 406–411.
[2]
Mackensen, E.; Lai, M.; Wendt, T.M. Bluetooth Low Energy (BLE) based wireless sensors. IEEE Sens. 2012, 1–4.
[3]
Zhang, J.Y.; Orlik, P.V.; Sahinoglu, Z.; Molisch, A.F.; Kinney, P. UWB systems for wireless sensor networks. Proc. IEEE 2009, 97, 313–331, doi:10.1109/JPROC.2008.2008786.
[4]
Buratti, C.; Conti, A.; Dardari, D.; Verdone, R. An overview on wireless sensor networks technology and evolution. Sensors 2009, 9, 6869–6896, doi:10.3390/s90906869.
[5]
Castagnetti, A.; Pegatoquet, A.; Belleudy, C.; Auguin, M. A framework for modeling and simulating energy harvesting WSN nodes with efficient power management policies. EURASIP J. Embed. Sys. 2012, 8, 1–20.
[6]
Sonavane, S.S.; Kumar, V.; Patil, B.P. MSP430 and nRF24L01 based wireless sensor network design with adaptive power control. ICGST CNIR J. 2009, 8, 11–15.
[7]
Pouwelse, J.; Langendoen, K.; Sips, H. Dynamic Voltage Scaling on a Low-Power Microprocessor. In Proceeding of the 7th Annual International Conference on Mobile Computing and Networking, Rome, Italy, 16–21 July 2001; pp. 251–259.
[8]
Benini, L.; Bogliolo, A.; de Micheli, G. A survey of design techniques for system-level dynamic power management. IEEE Trans. Large Scale Integr. Sys. 2000, 8, 299–316, doi:10.1109/92.845896.
[9]
Ye, W.; Heidemann, J.; Estrin, D. Medium access control with coordinated adaptive sleeping for wireless sensor networks. IEEE/ACM Trans. Netw. 2004, 12, 493–506, doi:10.1109/TNET.2004.828953.
[10]
van Dam, T.; Langendoen, K. An Adaptive Energy-Efficient MAC Protocol for Wireless Sensor Networks. In Proceeding of the First ACM SenSys conference, Los Angeles, CA, USA, 5–7 November 2003; pp. 171–180.
[11]
El-Hoiydi, A.; Decotignie, J.D.; Enz, C.; le Roux, E. WiseMAC: An Ultra Low Power MAC Protocol for the WiseNET Wireless Sensor Network. In Proceeding of the First ACM SenSys Conference (SenSys 2003), Los Angeles, CA, USA, 5–7 November 2003; pp. 302–303.
[12]
Polastre, J.; Hill, J.; Culler, D. Versatile Low Power Media Access for Wireless Sensor Networks. In Proceeding of the 2nd ACM SenSys conference (SenSys 2004), Baltimore, MD, USA, 3–5 November 2004; pp. 95–107.
[13]
Kimura, N.; Latifi, S. A Survey on Data Compression in Wireless Sensor Networks. In Proceeding of the International Conference on Information Technology: Coding and Computing (ITCC 2005), Las Vegas, NV, USA, 4–6 April 2005; pp. 8–13.
[14]
Xiang, L.; Luo, J.; Vasilakos, A.V. Compressed Data Aggregation for Energy Efficient Wireless Sensor Networks. Salt Lake City, UT, USA, 27–30 June 2011; pp. 46–54.
[15]
Krishnamachari, B.; Estrin, D.; Wicker, S. The Impact of Data Aggregation in Wireless Sensor Networks. In Proceeding of 22nd International Conference on Distributed Computing Systems Workshops, Vienna, Austria, 2–5 July 2002; pp. 575–578.
[16]
Chilamkurti, N.; Zeadally, S.; Vasilakos, A.; Sharma, V. Cross-layer support for energy efficient routing in wireless sensor networks. J. Sens. 2009.
[17]
IEEE 802 Working Group. Part 15.4: Wireless Medium Access Control (MAC) and Physical Layer (PHY) Specifications for Low-Rate Wireless Personal Area Networks (LR-WPANs); IEEE Std 802.15.4-2006; 2006.
[18]
He, Y.; Sun, J.; Ma, X.; Vasilakos, A.V.; Yuan, R.; Gong, W. Semi-random backoff: towards resource reservation for channel access in wireless LANS. IEEE/ACM Trans. Netw. 2003, 21, 204–217.
[19]
The MathWorks Inc. Genetic Algorithm-Find Global Minima for Highly Nonlinear Problems. Available online: http://www.mathworks.cn/discovery/genetic-algorithm.html (accessed on 6 May 2013).
[20]
Sivanandam, S.N.; Deepa, S.N. Genetic Algorithms. In Introduction to Genetic Algorithms; Springer: Berlin, Germany, 2007. Chapter 2; pp. 15–36.
[21]
Sivanandam, S.N.; Deepa, S.N. Applications of Genetic Algorithm. In Introduction to Genetic Algorithms; Springer: Berlin, Germany, 2007. Chapter 10; pp. 317–402.
[22]
Frantz, F.; Labrak, L.; O’Connor, I. 3D IC floorplanning: Automating optimization settings and exploring new thermal-aware management techniques. Microelectron. J. 2012, 43, 423–432, doi:10.1016/j.mejo.2012.03.005.
[23]
Chipperfield, A.; Fleming, P.; Pohlheim, H.; Fonseca, C. Genetic algorithm toolbox user’s guide. Available online: http://crystalgate.shef.ac.uk/code/manual.pdf (accessed on 10 May 2013).
[24]
Hussain, S.; Matin, A.W.; Islam, O. Genetic algorithm for hierarchical wireless sensor networks. J. Netw. 2007, 2, 87–97.
[25]
Sudha, N.; Valarmathi, M.L.; Neyandar, T.C. Optimizing Energy in WSN Using Evolutionary Algorithm. In Proceeding of IJCA on International Conference on VLSICommunications and Instrumentation (ICVCI 2011), Kerala, India, 7–9 April 2011; pp. 26–29.
Yen, Y.S.; Chao, H.C.; Chang, R.S.; Vasilakos, A. Flooding-limited and multi-constrained QoS multicast routing based on the genetic algorithm for MANETs. Math. Comput. Model. 2011, 53, 2238–2250, doi:10.1016/j.mcm.2010.10.008.
[28]
Ferentinos, K.P.; Tsiligiridis, T.A. Adaptive design optimization of wireless sensor networks using genetic algorithms. Comput. Netw. 2007, 51, 1031–1051, doi:10.1016/j.comnet.2006.06.013.
[29]
Sengupta, S.; Das, S.; Nasir, M.D.; Panigrahi, B.K. Multi-objective node deployment in WSNs: In search of an optimal trade-off among coverage, lifetime, energy consumption, and connectivity. Eng. Appl. Arti. Intell. 2013, 26, 405–416, doi:10.1016/j.engappai.2012.05.018.
Sengupta, S.; Das, S.; Nasir, M.; Vasilakos, A.V.; Pedrycz, W. An evolutionary multiobjective sleep-scheduling scheme for differentiated coverage in wireless sensor networks. IEEE Trans. Sys. Man Cybern. Part C Appl. Rev. 2012, 42, 1093–1102, doi:10.1109/TSMCC.2012.2196996.
[32]
Zhu, N.; Mieyeville, F.; Navarro, D.; Du, W.; O’Connor, I. Research on High Data Rate Wireless Sensor Networks. In Proceedings of 14ème Journées Nationales du Réseau Doctoral de Micro et Nanoélectronique (JNRDM 2011), Paris, France, 23–25 May 2011.
[33]
Zhu, N.; O’Connor, I. Energy Performance of High Data Rate and Low Power Transceiver based Wireless Body Area Networks. In Proceeding of 2nd International Conference on Sensor Networks (SENSORNETS 2013), Barcelona, Spain, 19–21 Feburary 2013; pp. 141–144.
[34]
Du, W.; Mieyeville, F.; Navarro, D.; O’Connor, I. IDEA1: A validated SystemC-based system-level design and simulation environment for wireless sensor networks. EURASIP J. Wirel. Commun. Netw. 2011, 143.
[35]
Chen, Z.; Hu, C.; Liao, J.; Liu, S. Protocol Architecture for Wireless Body Area Network based on nRF24L01. In Proceeding of IEEE International Conference on Automation and Logistics (ICAL 2008), Qingdao, China, 1–3 September 2008; pp. 3050–3054.
[36]
Weder, A. An Energy Model of the Ultra-Low-Power Transceiver nRF24L01 for Wireless Body Sensor Networks. In Proceeding of 2010 Second International Conference on Computational IntelligenceCommunication Systems and Networks (CICSyN 2010), Liverpool, UK, 28–30 July 2010; pp. 118–123.
[37]
Wang, X.; Vasilakos, A.V.; Chen, M.; Liu, Y.; Kwon, T.T. A survey of green mobile networks: opportunities and challenges. Mob. Netw. Appl. 2012, 17, 4–20, doi:10.1007/s11036-011-0316-4.
[38]
Bhatti, M.S.; Kapoor, D.; Kalia, R.K.; Reddy, A.S.; Thukral, A.K. RSM and ANN modeling for electrocoagulation of copper from simulated wastewater: Multi objective optimization using genetic algorithm approach. Desalination 2011, 274, 74–80, doi:10.1016/j.desal.2011.01.083.
[39]
Ferreira, F.F. Architectural Exploration Methods and Tools for Heterogeneous 3D-IC. Ph.D. Thesis, Ecole Centrale de Lyon, Lyon, France, 26 October 2012.
[40]
Zhu, N.; O’Connor, I. Energy Measurements and Evaluations on High Data Rate and Ultra Low Power WSN Node. In Proceeding of IEEE International Conference on NetworkingSensing and Control (ICNSC 2013), Paris, France, 10–12 April 2013; pp. 232–236.
[41]
Polastre, J.; Szewczyk, R.; Culler, D. Telos: Enabling Ultra-Low Power Wireless Research. In Proceeding of Fourth International Symposium on Information Processing in Sensor Networks (IPSN 2005), Los Angeles, CA, USA, 25–27 April 2005; pp. 364–369.
[42]
Varga, A.; Hornig, R. An Overview of the OMNeT++ Simulation Environment. In Proceeding of the 1st International Conference on Simulation Tools and Techniques for Communications, Networks and Systems & Workshops (Simutools 2008), Marseille, France, 3–7 March 2008.
[43]
Simon, G.; V？lgyesi, P.; Maróti, M.; Lédeczi, A. Simulation-Based Optimization of Communication Protocols for Large-Scale Wireless Sensor Networks. In Proceeding of IEEE Aerospace Conference, Big Sky, MT, USA, 8–15 March 2003; pp. 3_1339–3_1346.
[44]
Latré, B.; Braem, B.; Moerman, I.; Blondia, C.; Demeester, P. A Survey on wireless body area networks. Wireless Netw. 2011, 17, 1–18, doi:10.1007/s11276-010-0252-4.
[45]
Chen, M.; Gonzalez, S.; Vasilakos, A.; Cao, H.; Leung, V.C.M. Body area networks: A survey. Mobile Netw. Appl. 2011, 16, 171–193, doi:10.1007/s11036-010-0260-8.
[46]
Microchip Technology Inc. PIC16F87/88 Data Sheet. Available online: http://ww1.microchip.com/downloads/en/devicedoc/30487c.pdf (accessed on 8 Feburary 2013).
[47]
Nordic Semiconductor Inc. nRF24L01+ Product Specification. Available online: http://www.nordicsemi.com/eng/content/download/2726/34069/file/nRF24L01P_Product_Specification_1_0.pdf (accessed on 2 April 2013).
[48]
Microchip Technology Inc. Microchip MiWi？ Wireless Networking Protocol Stack. Available online: http://ww1.microchip.com/downloads/en/AppNotes/AN1066%20-%20MiWi%20App%20Note.pdf (accessed on 18 Feburary 2013).
[49]
Xiao, Y.; Peng, M.; Gibson, J.; Xie, G.G.; Du, D.Z.; Vasilakos, A.V. Tight performance bounds of multihop fair access for mac protocols in wireless sensor networks and underwater sensor networks. IEEE Trans. Mob. Comput. 2012, 11, 1538–1554, doi:10.1109/TMC.2011.190.
