Dissertation title: A study of wireless sensor network
Chapter 1: Introduction
Chapter 2: The applications of wireless sensor network
Chapter 3: The factors of wireless sensor network design
Chapter 4: Communication protocols of wireless sensor network Chapter 5: A design concept of wireless sensor network
Chapter 6: Conclusion
In recent years, with the development of Micro-Electro-Mechanical (MEMS) technology, wireless communications and digital electronics, wireless sensor networks have gained world attention. A wireless sensor network (WSN) is composed of a large number of low cost, low power and small sized sensor nodes. These sensor nodes are able to sense, measure and gather information from the surrounding environment. This sensed data can be transmitted to the end users based on some wireless communication schemes. A WSN consist of various number of sensor nodes, these sensor nodes generally have two types of deployments, structured and unstructured. In a structured WSN, all the sensor nodes are pre-determined to be deployed at a fixed position. The advantage of this type of deployment is perfect monitor coverage in sensing field, not a small space being left. However, the precise deployment consumes large amounts of time and energy. For this reason, this structured network is only suitable for small sensing field. For unstructured WSN, the locations of sensor notes are not pre-determined, which means the sensor network protocols must have self-organizing capabilities. Sensor nodes in unstructured network will be randomly deployed into sensing field. By means of a processing unit which fixed in each sensor node, these sensor nodes can perform some simple computations and send the required and partially processed data to each other. WSNs have great potential for a wild range of applications, such as military, health and environment. In military applications, WSN can help to monitor some critical area conditions, like battlefield or inaccessible terrain. For health applications, doctors can remotely monitor the physiological data of patients with the help of WSN. It conveniently helps the doctor to better understand the current conditions of their patients. Unlike traditional networks, WSNs have some own design constrains. One of the most important constrains on WSN is the limited power for sensor nodes. Due to the inaccessible of the sensor nodes in many applications, the power consumption directly determines the lifetime of WSN. For traditional network, achieving high quality of service (QoS) is the first goal on design. However, most of WSNs have to make a trade-off between QoS and working lifetime. In some special conditions， sensor network will even increase the transmission delay to extend the sensor nodes working time. Multihop communication in WSN is also an effective scheme to solve limited power problem. Since the deployment of sensor nodes are densely, the neighbor sensor nodes could be very close to each other, therefore, multihop communication can validly shorten the communication distance and consequently decrease the power consumption. To solve the problems which are brought by these constrains, many protocols and technologies have been developed. In this dissertation, the status of WSN development will be researched, in addition, by means of the research, a design concept of WSN on container transport will be proposed at the end of this dissertation. From the design concept, both of the function and the positive effects of WSN will be displayed.
2. The applications of wireless sensor network
As sensor network can be set up with different kinds of sensors, such as visual, thermal, seismic, radar and so on. Many different academic and industrial applications have been developed based on wireless sensor networks. These applications cover many aspects ranging from military to civilians applications. The idea beyond most of these applications is for the unique...
References:  Yan Ming ,RenJiawen , Zhang Zhanhai. The Progress of glaciological studies in Svalbard and Chinese construction of glacier monitoring system close to Yellow River Station. Chinese Journal of Polar Research, 2006, 18(2): 137-147.
 Martinez K, Riddoch A, Hart J. Intelligent Spaces [M]. New York: Springer, 2006: 137-138
4. Shih, E. et al. 2001. Proceedings of ACM MobiCom’o1: Physical layer driven protocol and algorithm design for energy-efficient wireless sensor networks. 272－286.
5. Rabaey, M.J. et al. 2000. PicoRadio supports ad hoc ultra-low power wireless networking, IEEE Computer Magazine, 42-48.
6. Li, L. and Halpern, J.Y. 2001. Minimum-energy mobile wireless networks revisited, IEEE International Conference on Communications ICC’01. Helsinki.
7. Kahn, J.M., Katz, R.H. and Pister, K.S.J. 1999. Next century challenges: mobile networking for smart dust, Proceedings of the ACM MobiCom’99. Washington: 271-278.
8. Pottie, G.J. and Kaiser, W.J. 2000. Wireless integrated network sensors, Communications of the ACM, 43 (5): 551-558.
9. Meguerdichian, S. et al. 2001. Exposure in wireless ad-hoc sensor networks, Proceedings of ACM MobiCom’o1. Rome: 139-150.
10. Melly, T. et al. 1999. IEEE International Symposium on Low Power Electronics and Design Conference, A 1.2 V, 430 MHz, 4dBm power amplifier and a 250 uW Frontend, using a standard digital CMOS process. San Diego: 233-237.
11. Warneke, B., Leibowitz, B. and Pister, K.S.J. 2001. Smart dust: communicating with a cubic-millimeter computer, IEEE Computer. 2-9.
12. Hoblos, G., Staroswiecki, M. and Aitouche, A. 2000.
Please join StudyMode to read the full document