Deploying Real-Life WSN Applications: Challenges ... - IAM - CDS

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14 International Journal of Distributed Sensor Networks In the last simulation, we evaluate our design by comparing the sustain lifetimes of the WHSN when it is applied with different protocols explained in this paper. In this simulation, we set the WHSN with 10 plug-in nodes as shown in the simulation scenario and 90 battery-powered nodes randomly scattered in the house. In each time step, several nodes in the network are chosen to send packets to the gateway. For each packet transmission, if a battery-powered node is involved, it will consume some power for communication. If more battery-powered nodes are involved in packet transmissions, thenetworkwillbeoutofpowermorequickly.Wewillrecord in the simulation how long the battery-powered nodes can keep alive. e experiment results are briey shown in Figure 15, and in each graph, we use three different algorithms to be compared. Figure 15(a) shows the sustain lifetime of the network with D-HiPr, LEACH, and LEACH-Pi protocols. As we can see, the LEACH protocol which does not consider the strength of plug-in nodes discharges the battery-powered nodes very quickly and halts the network at about 1300 rounds. In contrast, the LEACH-Pi by taking the advantage of plug-in nodes can survive until more than 2000 rounds, while our D-HiPr protocol by integrating all the features of WHSN works well until more than 2300 rounds. In Figure 15(b), we use the protocols of D-HiPr, SPIN, and SPIN-Pi to test the network, while in Figure 15(c),weusethe D-HiPr, DD, and DD-Pi protocols. Similar to the conclusion drawn from Figure 15(a), becausetheSPINandDDdonot consider the plug-in nodes, they perform very poorly. SPIN- Pi and DD-Pi by considering the merit of plug-in nodes, they perform better. D-HiPr by taking the advantages of plug-in nodes as backbone and prime-numbered routing algorithm, itperformsbest,andasFigure 15(c) shows, its sustained lifetimecanbetripleasthatoftheDDprotocol. 6. Conclusion and Future Works In this paper, we have designed a hierarchical architecture for smart WHSN. By classifying sensor nodes into two categories, we can take the advantages of using xed plugin nodes as backbone nodes for data transportation while the mobile nodes as leaves to keep the exibility of the network. Based on our architecture design, we have made three major contributions: a novel prime-numbered hierarchical address allocation and routing protocol; an improvement of classic routing protocols for smart WHSN as well as improved network maintenance algorithms to model node mobility and backbone failure. Our simulation results manifest the efficiency and feasibility of our design. However, even if we are capable of dealing with some of the challenges of the domain, we leave many of the others for the future work. Firstly, our design should be integrated with the physical layer controlling protocol such as 802.15.4, but it is not tested. Second, our design should be veried in some real domains applications of WHSN, which will be an imperative work for the next step. irdly, connecting with Internet and matching our design with IPv6 network will be good issue le to the future work. Acknowledgments is research has been sponsored in part by the National Natural Science Foundation of China no. 60905042, National Key Technology R&D Program of China no. 2012BAI22B05, and Huawei Technology Foundation no. YBNW2010086. References [1] Z. S. Wu, “Convergence framework of internet and WSN,” Tech. Rep., 2011. [2] H. Dohler, “Routing requirements for urban low-power and lossy networks,” RFC 5488, 2009. [3] A. Azim and M. M. Islam, “Hybrid LEACH: a relay node based low energy adaptive clustering hierarchy for wireless sensor networks,” in Proceedings of the IEEE 9th Malaysia International Conference on Communications, December 2009. [4] W. B. Heinzelman, P. Anantha, and H. Balakrishnan, “An application-specic protocol architecture for wireless microsensor networks,” IEEE Transactions on Wireless Communications, vol. 1, no. 4, pp. 660–670, 2002. [5] V.D.ParkandM.S.Corson,“Ahighlyadaptivedistributed routing algorithm for mobile wireless networks,” in Proceedings of the 16th Annual Joint Conference of the IEEE Computer and Communications Societies (INFOCOM ’97), pp. 1405–1413, April 1997. [6] L. H. Zhang, L. P. Zhang, and R. H. Huang, “Energy efficient passive clustering based directed diffusion protocol,” in Proceedings of the International Conference on Advanced Measurement and Test, 2010. [7] N. M. White and J. E. Brignell, “Sensors in adaptronics,” in UNSPECIFIED Adaptronics and Smart Structures, Springer, Berlin, Germany, 2007. [8] J. Li, Y. Guo, and G. Poulton, “Critical damage reporting in intelligent sensor networks,” in Proceedings of the 17th Australian Joint Conference on Articial Intelligence, pp. 26–38, December 2004. [9] Y. X. Li and X. J. Huang, “e simulation of independent rayleigh faders,” IEEE Transactions on Communications, vol. 50, no. 9, pp. 1503–1514, 2002. [10] Z. Shelby, S. Chakravarti, and E. Nordmark, “Neighbor discoveryoptimization for low-power and lossy networks,” Tech. Rep., June 2010. [11] J. P. Vasseur and A. Dunkels, Interconnection Smart Objects with IP: e Next Internet, Elsevier, New York, NY, USA, 2010. [12] M. Esler, J. Hightower, T. Anderson, and G. Borriello, “Next century challenges: data-centric networking for invisible computing,” in Proceedings of the 5th Annual ACM/IEEE International Conference on Mobile Computing and Networking (MOBICOM ’97), e Protolano Project at the University of Washington, 2000. [13] G. K. Ee, C. K. Ng, N. K. Noordin, and B. M. Ali, “Path recovery mechanism in 6LoWPAN routing,” in Proceedings of the International Conference on Computer and Communication Engineering (ICCCE ’10), May 2010. [14] K. Akkaya and M. Younis, “A survey on routing protocols for wireless sensor networks,” Journal of Ad Hoc Networks, vol. 3, no. 3, pp. 325–349, 2005.
Hindawi Publishing Corporation International Journal of Distributed Sensor Networks Volume 2012, Article ID 937462, 12 pages doi:10.1155/2012/937462 Research Article Node Classification Based on Functionality in Energy-Efficient and Reliable Wireless Sensor Networks Ning Sun, 1 Youngbuk Cho, 2 and Sangho Lee 2 1 Department of Computer Science, Chungbuk National University, 52 Naesudong-ro, Cheongju 361-763, Republic of Korea 2 Department of Software Engineering, Chungbuk National University, 52 Naesudong-ro, Cheongju 361-763, Republic of Korea Correspondence should be addressed to Sangho Lee, shlee@cbnu.ac.kr Received 27 May 2012; Revised 24 September 2012; Accepted 30 November 2012 Academic Editor: Regina B. Araujo Copyright © 2012 Ning Sun et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Energy efficiency and reliability are two important factors when we design a wireless sensor network (WSN). In this paper, we proposed an energy-efficient and reliable hierarchical mechanism for WSNs. We utilized clustering structure to decrease energy consumption. Because cluster head plays an important role in WSN, we designed a substitute of cluster head (SCH) in order to guarantee the data propagation reliability. Based on different functionalities of sensor nodes we creatively classify sensor nodes into five categories: branch node (BN), cluster head (CH), substitute of cluster head (SCH), intermedium node (IN), and normal node. By adopting different MAC and network strategies for different node categories, energy consumption can be greatly reduced and data reliability can be significantly increased in the proposed WSN mechanism. The simulation results showed that this proposed mechanism realized the objective in aspects of energy efficiency and reliability. 1. Introduction Wireless sensor networks consist of hundreds to thousands of sensor nodes. These sensor nodes are usually homogenous and one or more resource-rich base stations exist in WSNs which is the medium between WSNs and the outside information systems. The sensor nodes collect interest data through sensing the environment parameters such as temperature, wind speed, and humidity, then propagate the sensed data to the base station for furthering processing. Nowadays, WSN technology has been considered mature enough for real-life application such as control and automation, environment monitoring, healthcare, security and surveillance, smart home and building, vehicle tracking and detection, and precision agriculture. Due to the small size and low price, most sensor nodes have constrains in processors, memory size, communications, and energy capability. Among these limitations, energy saving is always a remarkable issue and has got much attention for designing the WSN protocol. Amounts of protocols in MAC and network layers have been proposed with the purpose of saving energy [1, 2]. Meanwhile, strict energy constraints restrict long and reliable performance of sensor nodes. Hardware often cannot work regularly due to energy depletion. At the same time, sensor networks are often deployed in harsh and hazardous environments, which affect normal operation of sensor nodes. The wireless radios of sensor nodes are severely affected by these environment factors. Communication faults often occur in WSNs due to the interferences. Therefore, reliability is another highlighted challenge for the real-life applications in WSNs. It is necessary for the WSN system to maintain high fault tolerant capability. Many literatures [2–5] have shown that hierarchical structure is an efficient means to save energy in WSNs. Hierarchical structure can greatly reduce the amount of direct communications between sensor nodes and base station. It is concluded [3] that the energy consumption of cluster head is much higher than normal nodes due to the extra works. By electing cluster heads in rotation the energy consumption can be balanced among nodes and the total energy consumption can be significantly reduced such that network lifetime is prolonged. In this paper we utilized the clustering hierarchical structure. Besides the hierarchical structure, energy-efficient MAC protocols [1] also achieve energy savings by controlling the radio wake/sleep and arranging reasonable access schedule
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