DBSR: Dynamic Base Station Repositioning Using Genetic Algorithm in Wireless Sensor Network

Wireless sensor networks (WSNs) are commonly used in various ubiquitous and pervasive applications. Due to limited power resources, the optimal dynamic base station (BS) replacement could be Prolong the sensor network lifetime. In this paper we’ll present a dynamic optimum method for base station replacement so that can save energy in sensors and increases network lifetime. Because positioning problem is a NP-hard problem [1], therefore we’ll use genetic algorithm to solve positioning problem. We’ve considered energy and distance parameters for finding BS optimized position. In our represented algorithm base station position is fixed just during each round and its positioning is done at the start of next round then it’ll be placed in optimized position. Evaluating our proposed algorithm, we’ll execute DBSR algorithm on LEACH & HEED Protocols.

[1]  Xingqun Zhan,et al.  A Modified Kalman Filtering via Fuzzy Logic System for ARVs Location , 2007, 2007 International Conference on Mechatronics and Automation.

[2]  Liang Xue,et al.  Fuzzy Adaptive Extended Kalman Filter for miniature Attitude and Heading Reference System , 2009, 2009 4th IEEE International Conference on Nano/Micro Engineered and Molecular Systems.

[3]  Martin J. Shepperd,et al.  Search Heuristics, Case-based Reasoning And Software Project Effort Prediction , 2002, GECCO.

[4]  T. Siegmund,et al.  Modeling of the transient responses of the vocal fold lamina propria. , 2009, Journal of the mechanical behavior of biomedical materials.

[5]  Sauro Longhi,et al.  Localization of a wheeled mobile robot by sensor data fusion based on a fuzzy logic adapted Kalman filter , 1998 .

[6]  Stergios I. Roumeliotis,et al.  Extended Kalman filter for frequent local and infrequent global sensor data fusion , 1997, Other Conferences.

[7]  Sungshin Kim,et al.  An accurate localization for mobile robot using extended Kalman filter and sensor fusion , 2008, 2008 IEEE International Joint Conference on Neural Networks (IEEE World Congress on Computational Intelligence).

[8]  John H. Holland,et al.  Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence , 1992 .

[9]  Rik Van de Walle,et al.  The MPEG-21 Book , 2006 .

[10]  Coarticulation • Suprasegmentals,et al.  Acoustic Phonetics , 2019, The SAGE Encyclopedia of Human Communication Sciences and Disorders.

[11]  Berj L. Bardakjian,et al.  On a Population of Labile Synthesized Relaxation Oscillators , 1983, IEEE Transactions on Biomedical Engineering.

[12]  Stephen G. MacDonell,et al.  A Comparison of Modeling Techniques for Software Development Effort Prediction , 1997, ICONIP.

[13]  Q. Wang,et al.  Fuzzy adaptive Kalman filtering for INS/GPS data fusion , 1999 .

[14]  N. F. Toda,et al.  Divergence in the Kalman Filter , 1967 .

[15]  Manfred Glesner,et al.  Advanced hardware/software co-design on reconfigurable network-on-chip based hyper-platforms , 2007, Comput. Electr. Eng..

[16]  Gang Zhang,et al.  Mobile Robot Localization Based on Extended Kalman Filter , 2006, 2006 6th World Congress on Intelligent Control and Automation.

[17]  Sangdeok Park,et al.  An Effective Kalman Filter Localization Method for Mobile Robots , 2006, 2006 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[18]  Moataz A. Ahmed,et al.  Adaptive fuzzy logic-based framework for software development effort prediction , 2005, Inf. Softw. Technol..

[19]  Mohinder S. Grewal,et al.  Kalman Filtering: Theory and Practice , 1993 .

[20]  Frank Vahid,et al.  SpecSyn: an environment supporting the specify-explore-refine paradigm for hardware/software system design , 1998, IEEE Trans. Very Large Scale Integr. Syst..

[21]  Rahul Sarpeshkar,et al.  A Low-Power Wide-Linear-Range Transconductance Amplifier , 1997 .

[22]  Ian F. Akyildiz,et al.  Wireless sensor networks: a survey , 2002, Comput. Networks.

[23]  Damien Lyonnard,et al.  Object-based hardware/software component interconnection model for interface design in system-on-a-chip circuits , 2004, J. Syst. Softw..

[24]  Bart De Decker,et al.  Towards a software architecture for DRM , 2005, DRM '05.

[25]  Nadia Nedjah,et al.  Efficient and secure cryptographic systems based on addition chains: Hardware design vs. software/hardware co-design , 2007, Integr..

[26]  Khaled El Emam,et al.  Software Cost Estimation with Incomplete Data , 2001, IEEE Trans. Software Eng..

[27]  A. E. Abdalla,et al.  Fuzzy adaptive Kalman filter for multi-sensor system , 2009, 2009 International Conference on Networking and Media Convergence.

[28]  Robert Sutton,et al.  Adaptive tuning of a Kalman filter via fuzzy logic for an intelligent AUV navigation system , 2004 .

[29]  Stephen G. MacDonell Software source code sizing using fuzzy logic modeling , 2003, Inf. Softw. Technol..

[30]  Sauro Longhi,et al.  Development and experimental validation of an adaptive extended Kalman filter for the localization of mobile robots , 1999, IEEE Trans. Robotics Autom..

[31]  P. W. Garratt,et al.  A Neurofuzzy cost estimator , 1999 .

[32]  K. Nay,et al.  A voltage-controlled resistance with wide dynamic range and low distortion , 1983 .

[33]  Gary D. Boetticher,et al.  An Assessment of Metric Contribution in the Construction of a Neural Network-Based Effort Estimator , 2022 .

[34]  Moshood Omolade Saliu,et al.  Soft Computing Based Effort Prediction Systems — A Survey , 2004 .

[35]  Z. Fei,et al.  f-COCOMO: fuzzy constructive cost model in software engineering , 1992, [1992 Proceedings] IEEE International Conference on Fuzzy Systems.

[36]  Rahul Sarpeshkar,et al.  An Electronically Tunable Linear or Nonlinear MOS Resistor , 2008, IEEE Transactions on Circuits and Systems I: Regular Papers.

[37]  Zouhair Guennoun,et al.  Improvement of MPEG-21 right expression language , 2009, 2009 IEEE/ACS International Conference on Computer Systems and Applications.

[38]  R. Mehra On the identification of variances and adaptive Kalman filtering , 1970 .

[39]  Alain Abran,et al.  COCOMO cost model using fuzzy logic , 2000 .

[40]  J. Liljencrants,et al.  Dept. for Speech, Music and Hearing Quarterly Progress and Status Report a Four-parameter Model of Glottal Flow , 2022 .

[41]  Mohamed F. Younis,et al.  Safe base-station repositioning in wireless sensor networks , 2006, 2006 IEEE International Performance Computing and Communications Conference.

[42]  Jerry M. Mendel,et al.  Generating fuzzy rules by learning from examples , 1992, IEEE Trans. Syst. Man Cybern..

[43]  G. Reina,et al.  Adaptive Kalman Filtering for GPS-based Mobile Robot Localization , 2007, 2007 IEEE International Workshop on Safety, Security and Rescue Robotics.

[44]  J. Ryder,et al.  Fuzzy modeling of software effort prediction , 1998, 1998 IEEE Information Technology Conference, Information Environment for the Future (Cat. No.98EX228).

[45]  Chris J. Harris,et al.  An adaptive neurofuzzy Kalman filter , 1996, Proceedings of IEEE 5th International Fuzzy Systems.

[46]  Tran Huu Cong,et al.  Hybrid Extended Kalman Filter-based localization with a highly accurate odometry model of a mobile robot , 2008, 2008 International Conference on Control, Automation and Systems.

[47]  Cosmin Popa Linearized CMOS active resistor independent on the bulk effect , 2007, GLSVLSI '07.

[48]  Fumitoshi Matsuno,et al.  A Neuro-Fuzzy Assisted Extended Kalman Filter-Based Approach for Simultaneous Localization and Mapping (SLAM) Problems , 2007, IEEE Transactions on Fuzzy Systems.

[49]  Rahul Sarpeshkar,et al.  An Analog Integrated-Circuit Vocal Tract , 2008, IEEE Transactions on Biomedical Circuits and Systems.

[50]  Dan Boneh,et al.  On genetic algorithms , 1995, COLT '95.

[51]  Satish Kumar,et al.  Next century challenges: scalable coordination in sensor networks , 1999, MobiCom.

[52]  W. Pedrycz,et al.  A fuzzy set approach to cost estimation of software projects , 1999, Engineering Solutions for the Next Millennium. 1999 IEEE Canadian Conference on Electrical and Computer Engineering (Cat. No.99TH8411).

[53]  Thiagalingam Kirubarajan,et al.  Estimation with Applications to Tracking and Navigation , 2001 .

[54]  Martin J. Shepperd,et al.  Making inferences with small numbers of training sets , 2002, IEE Proc. Softw..

[55]  Douglas Fisher,et al.  Machine Learning Approaches to Estimating Software Development Effort , 1995, IEEE Trans. Software Eng..

[56]  Witold Pedrycz,et al.  Software cost estimation with fuzzy models , 2000, SIAP.

[57]  Barry W. Boehm,et al.  Software development cost estimation approaches — A survey , 2000, Ann. Softw. Eng..

[58]  Yiwei Thomas Hou,et al.  Algorithm design for a class of base station location problems in sensor networks , 2009, Wirel. Networks.

[59]  Barry W. Boehm,et al.  Software Engineering Economics , 1993, IEEE Transactions on Software Engineering.

[60]  Jan M. Rabaey,et al.  PicoRadio Supports Ad Hoc Ultra-Low Power Wireless Networking , 2000, Computer.

[61]  Moti Yung,et al.  Proceedings of the First international conference on Digital Rights Management: technologies, Issues, Challenges and Systems , 2005 .

[62]  Martin J. Shepperd,et al.  Comparing Software Prediction Techniques Using Simulation , 2001, IEEE Trans. Software Eng..

[63]  Mohamed Abid,et al.  A unified model for co-simulation and co-synthesis of mixed hardware/software systems , 1995, Proceedings the European Design and Test Conference. ED&TC 1995.

[64]  Cristina Silvano,et al.  Power estimation of embedded systems: a hardware/software codesign approach , 1998, IEEE Trans. Very Large Scale Integr. Syst..

[65]  Gavin R. Finnie,et al.  Estimating software development effort with connectionist models , 1997, Inf. Softw. Technol..

[66]  Margrit Betke,et al.  Mobile robot localization using landmarks , 1997, IEEE Trans. Robotics Autom..

[67]  Jaime Ramirez-Angulo,et al.  Linearisation of MOS resistors using capacitive gate voltage averaging , 2005 .

[68]  Wouter Joosen,et al.  A Software Architecture to Facilitate the Creation of DRM Systems , 2007, 2007 4th IEEE Consumer Communications and Networking Conference.