Bcwsn- a Dynamic Load Balancing Algorithm for Decrease Congestion Cost in Wireless Sensor Network
-
3107
Downloads
-
5006
Views
Authors
Arash Rahbari
- Department of Computer, Payame Noor University, PO BOX 19395-3697, Tehran, Iran.
Arash Ghorbannia Delavar
- Department of Computer, Payame Noor University, PO BOX 19395-3697, Tehran, Iran.
Abstract
Lifetime network is one of the important needs in wireless sensor networks. Case studies show that
network increased lifetime possible by spending costs. The cost of congestion is one of those cases.
The cost of back pressuring and blocking the rout with timer is obtained in the difference literature.
We will be given a dynamic balancing algorithm by BCWSN to reduce congestion. By integration
of certain parameters in this the proposed method we have achieved the objective function. To
achieve a dynamic balance in the network, with the help of this function and provides the detection
threshold and assign the proper id, we have proposed strategies to choose the receiver and sender
nodes. Finally, we could with reducing the processing time in the BCWSN proposed method increase
network lifetime as compared to the previous.
Share and Cite
ISRP Style
Arash Rahbari, Arash Ghorbannia Delavar, Bcwsn- a Dynamic Load Balancing Algorithm for Decrease Congestion Cost in Wireless Sensor Network, Journal of Mathematics and Computer Science, 16 (2016), no. 1, 18-25
AMA Style
Rahbari Arash, Delavar Arash Ghorbannia, Bcwsn- a Dynamic Load Balancing Algorithm for Decrease Congestion Cost in Wireless Sensor Network. J Math Comput SCI-JM. (2016); 16(1):18-25
Chicago/Turabian Style
Rahbari, Arash, Delavar, Arash Ghorbannia. "Bcwsn- a Dynamic Load Balancing Algorithm for Decrease Congestion Cost in Wireless Sensor Network." Journal of Mathematics and Computer Science, 16, no. 1 (2016): 18-25
Keywords
- Wireless Sensor network
- BCWSN algorithm
- load balancing
- congestion cost.
References
-
[1]
M. I. Akbas, D. Turgut, Lightweight routing with dynamic interests in wireless sensor and actor networks, Ad Hoc Networks, 11 (2013), 2313-2328.
-
[2]
K. Akkaya, M. Younis, Energy and QoS aware routing for wireless sensor networks , Cluster Comput., 8 (2005), 179-188.
-
[3]
J. N. Al-Karaki, A. E. Kamal, Routing techniques in wireless sensor networks: a survey, IEEE Wireless Commun., 11 (2004), 6-28.
-
[4]
M. Amadeo, A. Molinaro, G. Ruggeri, E-CHANET: Routing,forwarding and transport in Information- Centric multihop wireless networks, Comput. Commun., 36 (2013), 792-803.
-
[5]
O. Banimelhem, S. Khasawneh, GMCAR: Grid-based multipath with congestion avoidance routing protocolin wireless sensor networks, Ad Hoc Networks, 10 (2012), 1346-1361.
-
[6]
F. Castano, A. Rossi, M. Sevaux, N. Velasco, On the use of multiple sinks to extend the lifetime in connected wireless sensor networks , Electron. Notes Discrete Math., 41 (2013), 77-84.
-
[7]
G. H. Ekbatanifard, R. Monsefi, M. H. Yaghmaee, S. A. Hosseini, Queen-MAC: A quorum-based energy- efficient medium access control protocol for wireless sensor networks, Comput. Networks, 56 (2012), 2221-2236.
-
[8]
M. Eslami, J. Vahidi, M. Askarzadeh, Designing and Implementing a Distributed Genetic Algorithm for Optimizing Work Modes in Wireless Sensor Network, J. math. comput. sci., 11 (2014), 291-299.
-
[9]
B. Fateh, M. Govindarasu, Energy minimization by exploiting data redundancy in real-time wireless sensor networks, Ad Hoc Networks, 11 (2013), 1715-1731.
-
[10]
S. Hedayati, A. Ghorbannia Delavar, The method of GBR optimization by special parameters to decrease energy consumption in WSNs , J. math. comput. sci., 8 (2014), 387-397.
-
[11]
W. R. Heinzelman, A. Chandrakasan, H. Balakrishnam, Energy-efficient communication protocol for wireless sensor networks, IEEE System Sci., 2 (2000), 10 pages.
-
[12]
R. Kacimi, R. Dhaou, A. L. Beylot, Load balancing techniques for lifetime maximizing in wireless sensor networks, Ad Hoc Networks, 11-8 (2013), 2172-2186.
-
[13]
J. Kang, Y. Zhang, B. Nath, TARA: Topology-Aware Resource Adaptation to Alleviate Congestion in Sensor Networks, , 18 (2007), 919-931.
-
[14]
K. S. Lee, S. Oh, C. Kim, A dynamic ID management protocol for CSMA/IC in ad hoc networks , Ad Hoc Networks, 11 (2013), 991-1005.
-
[15]
C. Y. Lee, L. C. Shiu, F. T. Lin, C. S. Yang, Distributed topology control algorithm on broadcasting in wireless sensor network, J. Network Comput. Appl., 36 (2013), 1186-1195.
-
[16]
I. A. Modupe, O. O. Olugbara, A. Modupe, Minimizing Energy Consumption in Wireless Ad hoc Networks with Meta heuristics, Procedia Comput. Sci., 19 (2013), 106-115.
-
[17]
I. H. Peng, Y. W. Chen, Energy consumption bounds analysis and its applications for grid based wireless sensor networks, J. network Comput. Appl., 36 (2013), 444-451.
-
[18]
A. A. Rezaee, M. H. Yaghmaee, A. M. Rahmani, A. H. Mohajerzadeh, HOCA: Healthcare Aware Optimized Congestion Avoidance and control protocol for wireless sensor networks, J. Network Comput. Appl., 37 (2014), 216-228.
-
[19]
F. Rouhi, A. Ghorbannia Delavar, S. Hedayati, ETDWSN: A method for energy efficiency increase by combining the index parameters in wireless sensor networks, J. math. comput. sci., 11 (2014), 166-176.
-
[20]
C. Sergiou, V. Vassiliou, A. Paphitis, Hierarchical Tree Alternative Path (HTAP) algorithm for congestion control in wireless sensor networks, Ad Hoc Networks, 11 (2013), 257-272.
-
[21]
X. Wang, H. Qian, Research on all-IP communication between wireless sensor networks and IPv6 networks , Comput. Standards & Interfaces, 35 (2013), 403-414.
-
[22]
F. Yan, A. K. H. Yeung, G. Chen, A numerical study of energy consumption and time efficiency of sensor networks with difrerent structural topologies and routing methods , Commun. Nonlinear Science Numer. Simul., 18-9 (2013), 2515-2526.