LOGIN TO YOUR ACCOUNT

Username
Password
Remember Me
Or use your Academic/Social account:

CREATE AN ACCOUNT

Or use your Academic/Social account:

Congratulations!

You have just completed your registration at OpenAire.

Before you can login to the site, you will need to activate your account. An e-mail will be sent to you with the proper instructions.

Important!

Please note that this site is currently undergoing Beta testing.
Any new content you create is not guaranteed to be present to the final version of the site upon release.

Thank you for your patience,
OpenAire Dev Team.

Close This Message

CREATE AN ACCOUNT

Name:
Username:
Password:
Verify Password:
E-mail:
Verify E-mail:
*All Fields Are Required.
Please Verify You Are Human:
fbtwitterlinkedinvimeoflicker grey 14rssslideshare1
Iqbal, Qasim
Languages: English
Types: Doctoral thesis
Subjects:

Classified by OpenAIRE into

ACM Ref: ComputerSystemsOrganization_COMPUTER-COMMUNICATIONNETWORKS
arxiv: Computer Science::Networking and Internet Architecture
Ad hoc wireless sensor networks (WSNs) are formed from self-organising configurations of distributed, energy constrained, autonomous sensor nodes. The service lifetime of such sensor nodes depends on the power supply and the energy consumption, which is typically dominated by the communication subsystem. One of the key challenges in unlocking the potential of such data gathering sensor networks is conserving energy so as to maximize their post deployment active lifetime. This thesis described the research carried on the continual development of the novel energy efficient Optimised grids algorithm that increases the WSNs lifetime and improves on the QoS parameters yielding higher throughput, lower latency and jitter for next generation of WSNs. Based on the range and traffic relationship the novel Optimised grids algorithm provides a robust traffic dependent energy efficient grid size that minimises the cluster head energy consumption in each grid and balances the energy use throughout the network. Efficient spatial reusability allows the novel Optimised grids algorithm improves on network QoS parameters. The most important advantage of this model is that it can be applied to all one and two dimensional traffic scenarios where the traffic load may fluctuate due to sensor activities. During traffic fluctuations the novel Optimised grids algorithm can be used to re-optimise the wireless sensor network to bring further benefits in energy reduction and improvement in QoS parameters. As the idle energy becomes dominant at lower traffic loads, the new Sleep Optimised grids model incorporates the sleep energy and idle energy duty cycles that can be implemented to achieve further network lifetime gains in all wireless sensor network models. Another key advantage of the novel Optimised grids algorithm is that it can be implemented with existing energy saving protocols like GAF, LEACH, SMAC and TMAC to further enhance the network lifetimes and improve on QoS parameters. The novel Optimised grids algorithm does not interfere with these protocols, but creates an overlay to optimise the grids sizes and hence transmission range of wireless sensor nodes.
  • The results below are discovered through our pilot algorithms. Let us know how we are doing!

    • Chapter 1 ........................................................................................................ 19 1.1 Statement of the Problems and Direction of the Research...................................20 1.2 Principal Aims......................................................................................................22 1.3 Significant Contributions .....................................................................................22 1.4 Thesis Layout .......................................................................................................23
    • Chapter 3 ........................................................................................................ 48 3.1 Modelling WSNs using Simulation Tools ...........................................................48 3.1.1 Components of a Wireless Ad hoc Sensor network......................................51
    • Chapter 7 ...................................................................................................... 223 7.1 Summary of Research ........................................................................................223 7.2 Significant Contributions to the Fields Wireless Sensor Networks ...................224 7.3 Future Research Directions ................................................................................228
    • Andel, T. R. and A. Yasinsac (2006). "On the Credibility of Manet Simulations." COMPUTER: 48-54.
    • Bagrodia, R., R. Meyer, et al. (1998). "Parsec: A Parallel Simulation Environment for Complex Systems." COMPUTER: 77-85.
    • Bajaj, L., M. Takai, et al. (1999). "GloMoSim: A Scalable Network Simulation Environment." UCLA Computer Science Department Technical Report 990027.
    • Bajaj, S., L. Breslau, et al. (1998). "Virtual InterNetwork Testbed: Status and research agenda." University of Southern California, Tech Report: 98-678.
    • Banerjee, S. and A. Misra (2002). "Minimum energy paths for reliable communication in multi-hop wireless networks." Proceedings of the 3rd ACM international symposium on Mobile ad hoc networking & computing: 146-156.
    • Banks, J. (1998). Handbook of Simulation: Principles, Methodology, Advances, Applications, and Practice, Wiley-Interscience.
    • Banks, J. (1999). Introduction to simulation, ACM New York, NY, USA.
    • Broch, J., D. A. Maltz, et al. (1998). A performance comparison of multi-hop wireless ad hoc network routing protocols, ACM Press New York, NY, USA.
    • Broderson, R. W. and A. P. Chandrakasan (1995). Low power digital CMOS design, Kluwer Academic Publishers, Massachusetts.
    • Cavin, D., Y. Sasson, et al. (2002). On the accuracy of MANET simulators, ACM Press New York, NY, USA.
    • Cerpa, A. and D. Estrin (2004). "ASCENT: Adaptive Self-Configuring sEnsor Networks Topologies." IEEE TRANSACTIONS ON MOBILE COMPUTING: 272-285.
    • Chang, J. H. and L. Tassiulas (2004). "Maximum lifetime routing in wireless sensor networks." IEEE/ACM Transactions on Networking (TON) 12(4): 609-619.
    • Chen, B., K. Jamieson, et al. (2002). "Span: An Energy-Efficient Coordination Algorithm for Topology Maintenance in Ad Hoc Wireless Networks." Wireless Networks 8(5): 481-494.
    • Chen, D. and P. K. Varshney "QoS Support in Wireless Sensor Networks: A Survey." Proc. Int'l Conf. Wireless Networks: 227-233.
    • Chipcon, C. "Power RF Transceiver. 2002: http://www. chipcon. com/files." CC1000_Data_Sheet_2_1. pdf.
    • Conner, W. S., J. Chhabra, et al. (2003). "Experimental evaluation of synchronization and topology control for in-building sensor network applications." Proceedings of the 2nd ACM international conference on Wireless sensor networks and applications: 38-49.
    • Deng, J., Y. S. Han, et al. (2004). "Optimum transmission range for wireless ad hoc networks." Wireless Communications and Networking Conference, 2004. WCNC. 2004 IEEE 2.
  • No related research data.
  • No similar publications.

Share - Bookmark

Cite this article