Loading [MathJax]/extensions/MathZoom.js
An Efficient Tree-Based Power Saving Scheme for Wireless Sensor Networks With Mobile Sink | IEEE Journals & Magazine | IEEE Xplore

An Efficient Tree-Based Power Saving Scheme for Wireless Sensor Networks With Mobile Sink


Abstract:

Wireless sensor networks (WSNs) with mobile sink are expected to increase the flexibility for gathering information in large-scale sensing and detecting environments. Ene...Show More

Abstract:

Wireless sensor networks (WSNs) with mobile sink are expected to increase the flexibility for gathering information in large-scale sensing and detecting environments. Energy saving becomes one of the most important features of the sensor nodes to extend their lifetime in such networks. A novel tree-based power saving scheme is proposed in this paper to reduce the energy consumption in WSNs with mobile sink. We adopt a dynamic sorting algorithm to create a tree-cluster routing structure for the sensor nodes. The main goal of this scheme is to reduce the data transmission distances of the sensor nodes by employing the tree structure and multi-hop concepts. Based on the location of mobile sink, the distances between the sensor nodes, and the residual energy of each sensor node, the proposed scheme makes an efficient decision for creating the routing structure. The energy consumption is reduced and the lifetime is extended for the sensor nodes by balancing the network load. Simulation results demonstrate the superior performance of our proposed scheme and its ability to strike the appropriate performance in the energy consumption, network lifetime, throughput, and transmission overhead. In addition, suitable delay time and number of retransmission messages can be achieved for the WSNs with mobile sink.
Published in: IEEE Sensors Journal ( Volume: 16, Issue: 20, October 2016)
Page(s): 7545 - 7557
Date of Publication: 18 August 2016

ISSN Information:

Funding Agency:

References is not available for this document.

I. Introduction

Wireless sensor networks (WSNs) have been widely considered as supplementary technology in the wireless and mobile systems. Powerful, inexpensive, and low-power wireless micro-sensors are designed and used in the various monitoring environments [1]–[5]. A WSN consists of a large number of sensor nodes. Each sensor node has sensing, computing, and wireless communication capability. All of the sensor nodes play the role of an event detector and a data router. The sensor nodes are deployed in the sensing area to monitor specific targets and collect data. Then, the sensor nodes send the data to a sink or a base station (BS) by using the wireless transmission techniques. During the recent years, many energy efficient routing protocols have been proposed for WSNs. Energy efficient routing protocols can be classified into four main schemes: network structure, communication model, topology based, and reliable routing. An analytical survey on energy efficient routing protocols for WSNs is provided in [6]. An energy efficient routing protocol plays a vital role in data transmission and practical applications. To be efficient for WSNs, the most important feature of a routing protocol is the energy consumption and the extension of the network’s lifetime [6]–[8]. The sensor nodes need more transmission power to send data when a sink or a BS is fixed and located far from the sensor nodes. WSNs with mobile sink are expected to increase the flexibility for gathering information in large-scale sensing and detecting environments [8]–[10]. Because a sink can randomly move within the sensing area to collect the sensing data, the data transmission distances of the sensor nodes could be reduced. The sink mobility offers the convenience of data gathering and reduces the energy consumption for the sensor nodes. WSNs have been pervasive in various applications including health care systems, battlefield surveillance systems, environment monitoring systems, various underwater applications, and so on [5]–[12]. Fig. 1 shows the direct communication protocol in WSNs with mobile sink, where each sensor node directly transmits its sensing data to the sink. Energy saving is one of the most important features for the sensor nodes to extend their lifetime. In WSNs, the main power supply of a sensor node is battery and a sensor node consumes most of its energy in transmitting and receiving packets. However, in most application scenarios, users are usually difficult to reach the location of sensor nodes. Due to a large number of sensor nodes, the replacement of batteries might be impossible. Additionally, the battery energy is finite in a sensor node and a sensor node that has its battery drained could make the sensing area uncovered. The energy conservation becomes a critical concern in WSNs. In order to reduce the energy consumption and extend the network lifetime, new and efficient energy saving schemes must be developed. Hence, the performance parameters of interest in this paper are energy consumption and network lifetime.

Direct communication protocol in WSNs with mobile sink.

Select All
1.
P. Corke, T. Wark, R. Jurdak, W. Hu, P. Valencia and D. Moore, "Environmental wireless sensor networks", Proc. IEEE, vol. 98, no. 11, pp. 1903-1917, Nov. 2010.
2.
L. Atzori, A. Iera and G. Morabito, "The Internet of things: A survey", Comput. Netw., vol. 54, no. 15, pp. 2787-2805, Oct. 2010.
3.
M. Tubaishat and S. Madria, "Sensor networks: An overview", IEEE Potentials, vol. 22, no. 2, pp. 20-23, Apr./May 2003.
4.
J. N. Al-Karaki and A. E. Kamal, "Routing techniques in wireless sensor networks: A survey", IEEE Wireless Commun., vol. 11, no. 6, pp. 6-28, Dec. 2004.
5.
A. Chamam and S. Pierre, "On the planning of wireless sensor networks: Energy-efficient clustering under the joint routing and coverage constraint", IEEE Trans. Mobile Comput., vol. 8, no. 8, pp. 1078-1086, Aug. 2009.
6.
N. A. Pantazis, S. A. Nikolidakis and D. D. Vergados, "Energy-efficient routing protocols in wireless sensor networks: A survey", IEEE Commun. Surveys Tuts., vol. 15, no. 2, pp. 551-591, 2nd Quart. 2013.
7.
G. Han, J. Jiang, N. Bao, L. Wan and M. Guizani, "Routing protocols for underwater wireless sensor networks", IEEE Commun. Mag., vol. 53, no. 11, pp. 72-78, Nov. 2015.
8.
C. Tunca, S. Isik, M. Y. Donmez and C. Ersoy, "Ring routing: An energy-efficient routing protocol for wireless sensor networks with a mobile sink", IEEE Trans. Mobile Comput., vol. 14, no. 9, pp. 1947-1960, Sep. 2015.
9.
C.-F. Wang, J.-D. Shih, B.-H. Pan and T.-Y. Wu, "A network lifetime enhancement method for sink relocation and its analysis in wireless sensor networks", IEEE Sensors J., vol. 14, no. 6, pp. 1932-1943, Jun. 2014.
10.
H. Salarian, K.-W. Chin and F. Naghdy, "An energy-efficient mobile-sink path selection strategy for wireless sensor networks", IEEE Trans. Veh. Technol., vol. 63, no. 5, pp. 2407-2419, Jun. 2014.
11.
P. Chanak, I. Banerjee, W. Jin and R. S. Sherratt, "Obstacle avoidance routing scheme through optimal sink movement for home monitoring and mobile robotic consumer devices", IEEE Trans. Consum. Electron., vol. 60, no. 4, pp. 596-604, Nov. 2014.
12.
M. Abo-Zahhad, S. M. Ahmed, N. Sabor and S. Sasaki, "Mobile sink-based adaptive immune energy-efficient clustering protocol for improving the lifetime and stability period of wireless sensor networks", IEEE Sensors J., vol. 15, no. 8, pp. 4576-4586, Aug. 2015.
13.
W. R. Heinzelman, A. Chandrakasan and H. Balakrishnan, "Energy-efficient communication protocol for wireless microsensor networks", Proc. 33rd Annu. Hawaii Int. Conf. Syst. Sci., pp. 1-10, Jan. 2000.
14.
W. B. Heinzelman, A. P. Chandrakasan and H. Balakrishnan, "An application-specific protocol architecture for wireless microsensor networks", IEEE Trans. Wireless Commun., vol. 1, no. 4, pp. 660-670, Oct. 2002.
15.
M. J. Handy, M. Haase and D. Timmermann, "Low energy adaptive clustering hierarchy with deterministic cluster-head selection", Proc. 4th IEEE Conf. Mobile Wireless Commun. Netw., pp. 368-372, 2002.
16.
O. Younis and S. Fahmy, "HEED: A hybrid energy-efficient distributed clustering approach for ad hoc sensor networks", IEEE Trans. Mobile Comput., vol. 3, no. 4, pp. 366-379, Oct./Dec. 2004.
17.
S. Babaie, A. K. Zadeh and M. G. Amiri, "The new clustering algorithm with cluster members bounds for energy dissipation avoidance in wireless sensor network", Proc. Int. Conf. Comput. Design Appl. (ICCDA), pp. 613-617, Jun. 2010.
18.
M. H. Khodashahi, F. Tashtarian, M. H. Y. Mohammad and M. T. Honary, "Optimal location for mobile sink in wireless sensor networks", Proc. IEEE Wireless Commun. Netw. Conf. (WCNC), pp. 1-6, Apr. 2010.
19.
F. Zhao, C. Zhao, Y. Wang, X. Sun and T. Jiang, "An energy-saving cluster routing algorithm for wireless sensor networks with mobile sink", Proc. Int. Conf. Adv. Intell. Awarenss Internet (AIAI), pp. 113-117, Oct. 2010.
20.
T. Ying and O. Yang, "A novel chain-cluster based routing protocol for mobile wireless sensor networks", Proc. 6th Int. Conf. Wireless Commun. Netw. Mobile Comput. (WiCOM), pp. 1-4, Sep. 2010.
21.
L. T. Nguyen, X. Defago, R. Beuran and Y. Shinoda, "An energy efficient routing scheme for mobile wireless sensor networks", Proc. IEEE Int. Symp. Wireless Commun. Syst. (ISWCS), pp. 568-572, Oct. 2008.
22.
S. A. B. Awwad, C. K. Ng, N. K. Noordin and M. F. A. Rasid, "Cluster based routing protocol for mobile nodes in wireless sensor network", Proc. Int. Symp. Collaborative Technol. Syst. (CTS), pp. 233-241, May 2009.
23.
S. Deng, J. Li and L. L. Shen, "Mobility-based clustering protocol for wireless sensor networks with mobile nodes", IET Wireless Sensor Syst., vol. 1, no. 1, pp. 39-47, Mar. 2011.
24.
J.-Y. Chang and P.-H. Ju, "An efficient cluster-based power saving scheme for wireless sensor networks", EURASIP J. Wireless Commun. Netw., vol. 2012, no. 1, pp. 1-10, May 2012.
25.
S. Lindsey and C. S. Raghavendra, "PEGASIS: Power-efficient gathering in sensor information systems", Proc. IEEE Aerosp. Conf., vol. 3, pp. 1125-1130, Mar. 2002.
26.
S. Lindsey, C. Raghavendra and K. M. Sivalingam, "Data gathering algorithms in sensor networks using energy metrics", IEEE Trans. Parallel Distrib. Syst., vol. 13, no. 9, pp. 924-935, Sep. 2002.
27.
Y.-C. Lin and J.-H. Zhong, "Hilbert-chain topology for energy conservation in large-scale wireless sensor networks", Proc. 9th Int. Conf. Auton. Trusted Comput. Ubiquitous Intell. Comput. (UIC/ATC), pp. 225-232, Sep. 2012.
28.
A. W. Khan, A. H. Abdullah, M. A. Razzaque and J. I. Bangash, "VGDRA: A virtual grid-based dynamic routes adjustment scheme for mobile sink-based wireless sensor networks", IEEE Sensors J., vol. 15, no. 1, pp. 526-534, Jan. 2015.
29.
S. Laki and R. N. Shukla, "Deployment in wireless sensor networks", Int. J. Adv. Res. Electron. Commun. Eng., vol. 2, no. 2, pp. 1-4, Feb. 2013.
30.
D. Niculescu and B. Nath, "Ad hoc positioning system (APS) using AOA", Proc. 2nd Annu. Joint Conf. IEEE Comput. Commun., vol. 3, pp. 1734-1743, Mar./Apr. 2003.

Contact IEEE to Subscribe

References

References is not available for this document.