ICTACT Journal on Communication Technology

Open Access Open Access  Restricted Access Subscription Access
Open Access Open Access Open Access  Restricted Access Restricted Access Subscription Access

Analysis on Performance Comparison of Virtual Grid-Base Dynamic Route Adjustment in Wireless Detector Networks


Affiliations
1 Department of Computer Science and Engineering, SriGuru Institute of Technology, India
2 Department of Computer Science and Engineering, Rathinam Technical campus, India
3 Department of Computer Science and Engineering, Cihan University - Duhok, Iraq
     

   Subscribe/Renew Journal


A virtual Grid-based dynamic routes adjustment scheme (virtual grid routing) for wireless sink-based wireless sensor networks is a recent introduction. Each mobile node in the network is capable of sensing, processing and communicating. In the present scenario, sensor networks are used in a variety of applications such as military, commercial, industrial, etc. which require constant monitoring and detection of specific event. The approach of efficient data delivery using communication of distance priority is used, avoiding the technique of previous schemes. Our method aims to reduce the routes reconstruction cost of sensor nodes while maintaining the most favorable routes to the mobile sink's recent location. It will improve the lifetime and reduce the cost consumption. This method highlights many routed schemes. A few such novel routing schemes are Virtual Grid based Dynamic Route Adjustment (VGDRA), Multiple Enhanced Specified-deployed Sub-sinks (MESS), Virtual Circle Combined Straight Routing (VCCSR), Hexagonal cell-based Data Dissemination (HexDD), Hierarchical Cluster-based Data Dissemination (HCDD), Backbone-based Virtual Infrastructure (BVI), Line-Based Data Dissemination (LBDD), Rail Road, Quadtree-based Data Dissemination (QDD), and Two-Tier Data Dissemination (TTDD). But, each scheme has its own advantages and disadvantages.

Keywords

VGDRA, MESS, VCCSR, HCDD, BVI, LBDD, QDD, TTDD, WDN, Grid Routing, Data Mining.
Subscription Login to verify subscription
User
Notifications
Font Size

  • J. Wang, J.Cao, S. Ji and J.H. Park, “Energy-Efficient Cluster-based Dynamic Routes Adjustment Approach for Wireless Sensor Networks with Mobile Sinks”, Journal of Supercomputing, Vol. 73, No. 7, pp. 3277-3290, 2017.

  • J.S. Pan, L. Kong, T.W. Sung, P.W. Tsai and V. Snasel, “A Clustering Scheme for Wireless Sensor Networks based on Genetic Algorithm and Dominating Set”, Journal of Internet Technology, Vol. 19, No. 4, pp. 1111-1118, 2018.

  • W. Qi, W. Liu, X. Liu, A. Liu, T. Wang, N.N. Xiong and Z. Cai, “Minimizing Delay and Transmission Times with Long Lifetime in Code Dissemination Scheme for High Loss Ratio and Low Duty Cycle Wireless Sensor Networks”, Sensors, Vol. 18, No. 10, pp. 3516-3523, 2018.

  • S. Chen, C. Zhao and M. Wu, “Compressive Network Coding for Wireless Sensor Networks: Spatio-Temporal Coding and Optimization Design”, Computer Networks, Vol. 108, No. 1, pp. 345-356, 2016.

  • X. Deng, Z. Tang, L.T. Yang, M. Lin and B. Wang, “Confident Information Coverage Hole Healing in Hybrid Industrial Wireless Sensor Networks”, IEEE Transactions on Industrial Informatics, Vol. 14, No. 5, pp. 2220-2229, 2017.

  • Y. Liu, K. Ota, K. Zhang, M. Ma and N. Xiong, “QTSAC: An Energy-Efficient MAC Protocol for Delay Minimization in Wireless Sensor Networks”, IEEE Access, Vol. 6, pp. 8273-8291, 2018.

  • T.L. Duc, D.T. Le, V.V. Zalyubovski and D.S. Kim, “Towards Broadcast Redundancy Minimization in Duty‐Cycled Wireless Sensor Networks”, International Journal of Communication Systems, Vol. 30, No. 6, pp. 3108-3117, 2017.

  • J. Tan, W. Liu, T. Wang, S. Zhang, A. Liu, M. Xie and M. Zhao, “An Efficient Information Maximization based Adaptive Congestion Control Scheme in Wireless Sensor Network”, IEEE Access, Vol. 7, pp. 64878-64896, 2019.

  • L. Kong, J.S. Pan and V. Snasel, “An Energy-Aware Routing Protocol for Wireless Sensor Network based on Genetic Algorithm”, Telecommunication Systems, Vol. 67, No. 3, pp. 451-463, 2018.

  • E.P.K. Gilbert, B. Kaliaperumal, E.B. Rajsingh and M. Lydia, “Trust based Data Prediction, Aggregation and Reconstruction using Compressed Sensing for Clustered Wireless Sensor Networks”, Computers and Electrical Engineering, Vol. 72, pp. 894-909, 2018.

  • F. Ma, X. Liu, A. Liu, M. Zhao, C. Huang and T. Wang, “A Time and Location Correlation Incentive Scheme for Deep Data Gathering in Crowdsourcing Networks”, Wireless Communications and Mobile Computing, Vol. 32, No. 2, pp. 1-16, 2018.

  • K. Muthukumaran, K. Chitra and C. Selvakumar, “An Energy Efficient Clustering Scheme using Multilevel Routing for Wireless Sensor Network”, Computers and Electrical Engineering, Vol. 69, pp. 642-652, 2018.

  • A. Agrawal, V. Singh, S. Jain and R.K. Gupta, “GCRP: Grid-Cycle Routing Protocol for Wireless Sensor Network with Mobile Sink”, AEU-International Journal of Electronics and Communications, Vol. 94, No. 2, pp. 1-11, 2018.

  • W. Chen and I.J. Wassell, “Cost-Aware Activity Scheduling for Compressive Sleeping Wireless Sensor Networks”, IEEE Transactions on Signal Processing, Vol. 64, No. 9, pp. 2314-2323, 2016.

  • J.S. Pan, L. Kong and P.W. Tsail, “α-Fraction First Strategy for Hierarchical Model in Wireless Sensor Networks”, Journal of Internet Technology, Vol. 19, No. 6, pp. 1717-1726, 2018.

  • S.M. Amini, A. Karimi and M. Esnaashari, “Energy-Efficient Data Dissemination Algorithm based on Virtual Hexagonal Cell-Based Infrastructure and Multi-Mobile Sink for Wireless Sensor Networks”, Journal of Supercomputing, Vol. 76, No. 1, pp. 150-173, 2020.


Abstract Views: 224

PDF Views: 0




  • Analysis on Performance Comparison of Virtual Grid-Base Dynamic Route Adjustment in Wireless Detector Networks

Abstract Views: 224  |  PDF Views: 0

Authors

D. Vikneshkumar
Department of Computer Science and Engineering, SriGuru Institute of Technology, India
D. Kaleeswaran
Department of Computer Science and Engineering, Rathinam Technical campus, India
D. Yuvaraj
Department of Computer Science and Engineering, Cihan University - Duhok, Iraq

Abstract


A virtual Grid-based dynamic routes adjustment scheme (virtual grid routing) for wireless sink-based wireless sensor networks is a recent introduction. Each mobile node in the network is capable of sensing, processing and communicating. In the present scenario, sensor networks are used in a variety of applications such as military, commercial, industrial, etc. which require constant monitoring and detection of specific event. The approach of efficient data delivery using communication of distance priority is used, avoiding the technique of previous schemes. Our method aims to reduce the routes reconstruction cost of sensor nodes while maintaining the most favorable routes to the mobile sink's recent location. It will improve the lifetime and reduce the cost consumption. This method highlights many routed schemes. A few such novel routing schemes are Virtual Grid based Dynamic Route Adjustment (VGDRA), Multiple Enhanced Specified-deployed Sub-sinks (MESS), Virtual Circle Combined Straight Routing (VCCSR), Hexagonal cell-based Data Dissemination (HexDD), Hierarchical Cluster-based Data Dissemination (HCDD), Backbone-based Virtual Infrastructure (BVI), Line-Based Data Dissemination (LBDD), Rail Road, Quadtree-based Data Dissemination (QDD), and Two-Tier Data Dissemination (TTDD). But, each scheme has its own advantages and disadvantages.

Keywords


VGDRA, MESS, VCCSR, HCDD, BVI, LBDD, QDD, TTDD, WDN, Grid Routing, Data Mining.

References