Fast Response Enhanced Multi-queue packet Scheduler scheme for Wireless Sensor Network
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International Journal of Computer Trends and Technology (IJCTT) | 
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| © 2015 by IJCTT Journal | ||
| Volume-25 Number-3 |
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| Year of Publication : 2015 | ||
| Authors : Shital L. Bansod, Sonal Honale | ||
| DOI : 10.14445/22312803/IJCTT-V25P125 |
Shital L. Bansod, Sonal Honale "Fast Response Enhanced Multi-queue packet Scheduler scheme for Wireless Sensor Network". International Journal of Computer Trends and Technology (IJCTT) V25(3):127-133, July 2015. ISSN:2231-2803. www.ijcttjournal.org. Published by Seventh Sense Research Group.
Abstract -
Wireless Sensor Network (WSNs) interact with
critical physical environments, one of the critical issues of
WSNs are real time consideration. Existing WSNs suffers
from lack of real time task allocation In support of in
support of real time communication. In WSNs especially for
real time applications efforts to reduce energy
consumptions, end to end transmission delay must be
considered. Though various ways like data aggregation are
existing, packet scheduling is more important as it assures
the delivery of various types of packets depending upon the
priority. Many wireless sensor network (WSN) applications
heavily rely on information being transmitted in a timely
manner. In such sensor networks, packet scheduling plays a
vital role in reducing end-to-end data transmission delays. It
also helps in reducing sensors energy consumptions, thus
increasing the lifetime of the wireless sensor network. The
simplest packet scheduling scheme is FCFS (First Come
First Serve). Many more packet scheduling schemes have
been proposed for wireless sensor networks such as
EDF(Earliest Deadline First) and those based on priority
with single and multiple queues. In this paper we discuss
Fast Response Enhanced Multi-queue Packet Schedular
Scheme for Wireless sensor network. In Sensor Network
each node, except those at the last level of the virtual
hierarchy in the zone based topology of WSN, has three
levels of priority queues. Real-time packets are placed into
the highest-priority queue and can preempt data packets in
other queues. Non-real-time packets are placed into two
other queues based on a certain threshold of their estimated
processing time. Leaf nodes have two queues for real-time
and non-real-time data packets since they do not receive
data from other nodes and thus, reduce end-to-end delay.
Data packets sensed by nodes at different levels are
processed using a TDMA scheme.
References
[1]. Nidal Nasser, Lutful Karim & Tarik Talib, “Dynamic
Multilevel Priority Packet Scheduling Scheme for wireless sensor
network”, IEEE Trans on wireless communication, vol 12, NO. 4,
April 2013
[2]. G. Anastasi, M. Conti, and M. Di Francesco, “Extending the
lifetime of wireless sensor networks through adaptive sleep,” IEEE
Trans. Industrial Informatics, vol. 5, no. 3, pp. 351–365, 2009.
[3]. G. Bergmann, M. Molnar, L. Gonczy, and B. Cousin, “Optimal
period length for the CQS sensor network scheduling algorithm,” in
Proc. 2010 International Conf. Netw. Services, pp. 192–199.
[4]. E. Bulut and I. Korpeoglu, “DSSP: a dynamic sleep scheduling
protocol for prolonging the lifetime of wireless sensor networks,” in
Proc. 2007 International Conf. Advanced Inf. Networking Appl.,
vol. 2, pp. 725– 730.
[5]. S. Chachra and M. Marefat, “Distributed algorithms for sleep
scheduling in wireless sensor networks,” in Proc. 2006 IEEE
International Conf. Robot. Autom., pp. 3101–3107.
[6]. P. Guo, T. Jiang, Q. Zhang, and K. Zhang, “Sleep scheduling
for critical event monitoring in wireless sensor networks,” IEEE
Trans. Parallel Distrib. Syst., vol. 23, no. 2, pp. 345–352, Feb. 2012.
[7]. F. Liu, C. Tsui, and Y. J. Zhang, “Joint routing and sleep
scheduling for lifetime maximization of wireless sensor networks,”
IEEE Trans.Wireless Commun., vol. 9, no. 7, pp. 2258–2267, July
2010.
[8]. J. Liu, N. Gu, and S. He, “An energy-aware coverage based
node scheduling scheme for wireless sensor networks,” in Proc.
2008 International Conf. Young Comput. Scientists, pp. 462–468.
[9]. O. Khader, A. Willig, and A. Wolisz, “Distributed wakeup
scheduling scheme for supporting periodic traffic in wsns,” in Proc.
2009 European Wireless Conf., pp. 287–292.
[10]. B. Nazir and H. Hasbullah, “Dynamic sleep scheduling for
minimizing delay in wireless sensor network,” in Proc. 2011 Saudi
International Electron., Communications Photon. Conf., pp. 1–5.
[11]. D. Shuman and M. Liu, “Optimal sleep scheduling for a
wireless sensor network node,” in Proc. 2006 Asilomar Conf.
Signals, Syst. Comput., pp. 1337–1341.
[12]. S. Paul, S. Nandi, and I. Singh, “A dynamic balanced-energy
sleep scheduling scheme in heterogeneous wireless sensor
network,” in Proc.2008 IEEE International Conf. Netw., pp. 1–6,
2008.
[13]. A. R. Swain, R. C. Hansdah, and V. K. Chouhan, “An energy
aware routing protocol with sleep scheduling for wireless sensor
networks,” in Proc. 2010 IEEE International Conf. Adv. Inf. Netw.
Appl., pp. 933–940.
[14]. Y. H. Wang, Y. L. Wu, and K. F. Huang, “A power saving
sleep scheduling based on transmission power control for wireless
sensor networks,” in Proc. 2011 International Conf. Ubi-Media
Comput., pp. 19–24.
[15]. Y. Wang, D. Wang, W. Fu, and D. P. Agrawal, “Hops-based
sleep scheduling algorithm for enhancing lifetime of wireless sensor
networks,” in Proc. 2006 IEEE International Conf. Mobile Adhoc
Sensor Syst., pp. 709–714.
[16]. Y. Xiao, H. Chen, K. Wu, B. Sun, Y. Zhang, X. Sun, and C.
Liu, “Coverage and detection of a randomized scheduling algorithm
in wireless sensor networks,” IEEE Trans. Comput., vol. 59, no. 4,
pp. 507–521, Apr. 2010.
[17]. X. Xu, Y. H. Hu, J. Bi, and W. Liu, “Adaptive nodes
scheduling approach for clustered sensor networks,” in Proc. 2009
IEEE Symp. Comput.Commun., pp. 34–39.
[18]. Y. Zhao, J. Wu, F. Li, and S. Lu, “VBS: maximum lifetime
sleep scheduling for wireless sensor networks using virtual
backbones,” in Proc. 2010 IEEE INFOCOM, pp. 1–5.
[19]. B. Zeng, Y. Dong, and D. Lu, “Cooperation-based scheduling
algorithm in wireless multimedia sensor networks,” in Proc. 2011
International Conf. Wireless Commun., Netw. Mobile Comput., pp.
1–4.
[20]. N. Edalat, W. Xiao, C. Tham, E. Keikha, and L. Ong, “A
price-based adaptive task allocation for wireless sensor network,” in
Proc. 2009 IEEE International Conf. Mobile Adhoc Sensor Syst.,
pp. 888–893.
[21]. H. Momeni, M. Sharifi, and S. Sedighian, “A new approach to
task allocation in wireless sensor actor networks,” in Proc. 2009
International Conf. Computational Intelligence, Commun. Syst.
Netw., pp. 73–78.
[22]. F. Tirkawi and S. Fischer, “Adaptive tasks balancing in
wireless sensor networks,” in Proc. 2008 International Conf. Inf.
Commun. Technol.: From Theory Appl., pp. 1–6.
[23]. X. Yu, X. Xiaosong, and W. Wenyong, “Priority-based lowpower
task scheduling for wireless sensor network,” in Proc. 2009
International Symp. Autonomous Decentralized Syst., pp. 1–5.
Keywords
Data waiting time, wireless sensor network,
FCFS, packet scheduling, Non-preemptive priority
scheduling, Preemptive priority scheduling, Real-time
scheduling, Non- real time scheduling.