TOP 10 WIRELESS SENSOR NETWORKS PAPERS: RECOMMENDED READING – NETWORK RESEARCH

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Citation Count - 56
Wireless Sensor Networks Localization Algorithms: A
Comprehensive Survey
Asma Mesmoudi , Mohammed Feham , Nabila Labraoui
STIC Laboratory, Departemet of telecommunication,University of Tlemcen, Algeria
ABSTRACT
Wireless sensor networks (WSNs) have recently gained a lot of attention by scientific
community. Small and inexpensive devices with low energy consumption and limited
computing resources are increasingly being adopted in different application scenarios
including environmental monitoring, target tracking and biomedical health monitoring. In
many such applications, node localization is inherently one of the system parameters.
Localization process is necessary to report the origin of events, routing and to
answer questions on the network coverage ,assist group querying of sensors. In general,
localization schemes are classified into two broad categories: range-based and range-free.
However, it is difficult to classify hybrid solutions as range-based or range-free. In this
paper we make this classification easy, where range-based schemes and range-free
schemes are divided into two types: fully schemes and hybrid schemes. Moreover, we
compare the most relevant localization algorithms and discuss the future research
directions for wireless sensor networks localization schemes.
KEYWORDS
Localization, WSN, anchor node, range-based methods, range-free methods, hybrid-
based methods.
For More Details : http://airccse.org/journal/cnc/5613cnc03.pdf
Volume Link : http://airccse.org/journal/ijc2013.html

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Citation Count - 49
Towards Internet of Things (IOTS): Integration of
Wireless Sensor Network to Cloud Services for Data
Collection and Sharing
Rajeev Piyare and Seong Ro Lee
Department of Information Electronics Engineering, Mokpo National University,
534- 729, South Korea
ABSTRACT
Cloud computing provides great benefits for applications hosted on the Web that also
have special computational and storage requirements. This paper proposes an extensible
and flexible architecture for integrating Wireless Sensor Networks with the Cloud. We
have used REST based Web services as an interoperable application layer that can be
directly integrated into other application domains for remote monitoring such as e-health
care services, smart homes, or even vehicular area networks (VAN). For proof of
concept, we have implemented a REST based Web services on an IP based low power
WSN test bed, which enables data access from anywhere. The alert feature has also been
implemented to notify users via email or tweets for monitoring data when they exceed
values and events of interest.
KEYWORDS
Internet of Things, Cloud computing, REST, Wireless Sensor Network, XBee

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Citation Count - 21
A Reliable and Energy Efficient Transport Protocol for
Wireless Sensor Networks
Kamal Kumar Sharma1
, Ram Bahadur Patel2
, Harbhajan Singh3
1
Department of Electronics and Communication Engineering, RDJ Faculty of
Engineering Dist Mohali Punjab, INDIA
2
Department of Computer Engineering, MIT Deemed University, Laxamngarh
Rajasthan INDIA
3
Department of Electronics and Comm Engineering, SSIET, Derabassi, Punjab
INDIA
ABSTRACT
In wireless sensor networks (WSN), an ideal transport layer needs to support reliable
message delivery and provide congestion control in an efficient manner in order to extend
the lifetime of a WSN. The main use of transport protocol in WSN is to overcome the
congestion and the reliability with energy efficiency. In this paper, we develop a reliable
and energy efficient transport protocol (REETP), which mainly focuses on the reliability
and energy efficiency. Our proposed protocol consist of an Efficient Node Selection
Algorithm to determine a set of efficient nodes called E-Nodes which form a near
optimal coverage set with largest area and highest residual energy level. The key idea of
REETP is to transfer encoded packets using LT codes from the source to the sink block
by block and each block is forwarded to an E-node. After receiving encoded packets, the
E-node tries to reconstruct the original data packets and it encodes the original
data packets again and relays them to the next E-node until it reaches the sink. By
simulation results, we show that our proposed protocol has more packet delivery ratio
with reduced packet loss and energy consumption.
KEYWORDS
Wireless sensor networks, Congestion, Contention, Energy Efficient, Transmission rate,
Data flow
For More Details : http://airccse.org/journal/cnc/0910ijcnc06.pdf

REFERENCES
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4. Justin Jones and Mohammed Atiquzzaman, “Transport Protocols for Wireless Sensor
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International symposium on Mobile ad hoc networking & computing, 2003.

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Mechanism for Wireless Sensor Networks”, International Journal of Sensor Networks,
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Citation Count – 21
Concepts and Evolution of Research in the Field Of
Wireless Sensor Networks
Ado Adamou ABBA ARI 1, 3
*, Abdelhak GUEROUI 1
, Nabila LABRAOUI 2
and Blaise Omer YENKE 3
1
PRISM, University of Versailles St-Quentin-en-Yvelines, France
2
STIC, University of Tlemcen, Algeria
3
LASE, University of Ngaoundere, Cameroon
ABSTRACT
The field of Wireless Sensor Networks (WSNs) is experiencing a resurgence of interest
and a continuous evolution in the scientific and industrial community. The use of this
particular type of ad hoc network is becoming increasingly important in many contexts,
regardless of geographical position and so, according to a set of possible application.
WSNs offer interesting low cost and easily deployable solutions to perform a remote real
time monitoring, target tracking and recognition of physical phenomenon. The uses of
these sensors organized into a network continue to reveal a set of research questions
according to particularities target applications. Despite difficulties introduced by sensor
resources constraints, research contributions in this field are growing day by day. In this
paper, we present a comprehensive review of most recent literature of WSNs and outline
open research issues in this field.
KEYWORDS
WSNs, protocols, sensor, applications, routing, services, survey, bio-inspired.

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Citation Count - 20
H-MAC : A Hybrid MAC Protocol for Wireless Sensor Networks
S. Mehta and K.S. Kwak
UWB Wireless Communications Research Center, Inha University
Incheon, 402-751, Korea
ABSTRACT
In this paper, we propose a hybrid medium access control protocol (H-MAC) for wireless
sensor networks. It is based on the IEEE 802.11’s power saving mechanism (PSM) and
slotted aloha, and utilizes multiple slots dynamically to improve performance. Existing
MAC protocols for sensor networks reduce energy consumptions by introducing
variation in an active/sleep mechanism. But they may not provide energy efficiency in
varying traffic conditions as well as they did not address Quality of Service (QoS) issues.
H-MAC, the propose MAC protocol maintains energy efficiency as well as QoS issues
like latency, throughput, and channel utilization. Our numerical results show that H-
MAC has significant improvements in QoS parameters than the existing MAC protocols
for sensor networks while consuming comparable amount of energy.
KEYWORDS
Sensor networks, MAC protocol, energy efficiency.
For More Details : http://airccse.org/journal/cnc/10108.pdf

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Citation Count – 19
AOM : An Efficient Approach to Restore Actor-Actor Connectivity in
Wireless Sensor and Actor Networks
Azadeh Zamanifar, Omid Kashefi and Mohsen Sharifi
Computer Engineering Department, Iran University of Science and Technology,
Tehran, Iran
ABSTRACT
Wireless sensor and actor networks (WSANs) consist of powerful actors and resource
constraint sensors that are linked together in wireless networks. They mostly rely on
actors to make proper decisions and perform desired coordination to achieve the goals of
the entire network. They are usually deployed in critical applications and actor-actor
network connectivity is thus vital to their effective utilization. Since WSAN applications
are mostly deployed in harsh environments, actor nodes may fail and so partition their
network. We propose a comparatively more efficient distributed approach, nicknamed
AOM, to restore actor-actor connectivity upon the failure of any actor. We identify
critical actors by combining the result of determining critical actors using the
Stojmenovich’s method with the connectivity dominating set (CDS) of the network. This
hybrid method of detecting critical actors helps in detecting critical nodes and candidate
replacement actors more precisely while minimizing the total number of required
messages for network restoration. The failure handling of actors is done in a proactive
manner. Our proposed method minimizes both the restoration time of network and the
total number of actor movements. When a failed actor is a critical node, actors in its
neighborhood are relocated in a coordinated way to reconnect the actor network. The
superiority of our approach compared to other works is shown by simulative experiments
measuring two important parameters to WSANS, namely, the total number of
transmitted messages and the total number of actor movements during actor-actor
network reconnection process.
KEYWORDS
Wireless Sensor and Actor Network; Network Restoration; Actor Connectivity; Cut
Vertex; Connectivity Dominating Set (CDS)
Volume Link : http://airccse.org/journal/j2current.html

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Citation Count - 10
Empirical Examination of Mobile Ad Hoc Routing Protocols on Wireless
Sensor Networks
Zhongwei Zhang1
and Hong Zhou2
1
Department of Mathematics and Computing, University of Southern Queensland,
Toowoomba, QLD 4350
2
Department of Electronic Engineering, University of Southern Queensland,
Toowoomba, QLD 4350
ABSTRACT
Wireless sensor networks (WSNs) have great potential of being deployed in many places
where traditional wired or wireless networks are not feasible. But they have also many
new challenges more than other wireless networks. These challenges include the design
of embedded intelligent sensors and wireless networking technology, ie. routing
protocols and network security. WSNs also have some constraints such as sensor nodes
failure which render WSN unavailable. The routing protocol in the sensor networks plays
a critical role. They influence the performance of the WSNs and have significant impact
on the security and the availability of WSNs. Wireless sensor networks (WSNs) have
been regarded as an incarnation of Ad Hoc Networks for a specific application. Since a
WSN consists of potentially hundreds of low cost, small size and battery powered sensor
nodes, it has more potentials than a MANET to be deployed in many emerging areas.
However, they also raised many new challenges, and these challenges include the design
of embedded sensors and wireless networking technology, ie. routing protocols and
network security. Many ad hoc routing protocols such as AODV, DSR, DSDR, TORA
and OLSR, which have been developed particularly for the mobile wireless ad hoc
networks (MANETs), performed satisfactorily on MANETs. Research has shown that
these ad-hoc routing protocols work well for MANETs with different characteristics and
requirements. In this paper, we investigate how well these ad-hoc routing protocols work
on wireless sensor networks (WSNs). We focus on their performances in terms of
average end-to end delay, packet delivery ratio and routing overheads.
KEYWORDS
Wireless technology, Sensor nodes, Dynamic routing, Throughput, Wireless Network,
End-to-End delay
Volume Link : http://airccse.org/journal/j2current.html

REFERENCES
[1] Ian F. Akyildiz, Weilian Su, Yogesh Sankarasubramaniam, and E. Cayirci (2002). A
survey on sensor networks. IEEE Communications Magazine, Aug 2002. pp 102-114.
[2] H. Chan and A. Perrig, (2003) Security and privacy in sensor networks. IEEE
Computer, Oct 2003. pp 103-105.
[3] Carla Fabiana Chiasserini and Michele Garetto, (2004) Modeling the performance of
wireless sensor networks. IEEE INFOCOM, Hong Kong, March 7-11, 2004.
[4] Marco Conti and Silvia Giordano, (2007) Multihop Ad Hoc Networking: The Reality,
IEEE Communication Magazine, April 2007. pp 88-95.
[5] Ian Downard, (2004) Simulating sensor network in ns-2. NRL Formal Report 5522.
[6] Deborah Estrin, David Cullar, Kris Pister and Gaurav Sukhatme, (2002) Connecting
the Physical World with Pervasive Networks, Pervasive Computing, Jan 2002. pp 59-69.
[7] Qiangfeng Jiang and D. Manivannan, (2004) Routing Protocols for Sensor Networks,
Consumer Communications and Networking Conference, First IEEE Volume Issue, Jan
2004. pp 93-98.
[8] Anthony D. Wood and John A. Stankovic (2002) Denial of Service in Sensor
Networks, IEEE Computer, Oct 2002. pp54-62.
[9] Yunjiao Xue, Ho Sung Lee, Ming Yang, Priantha Kumarawadu, Hamada H.
Ghenniwa and Weiming Shen (2007) Performance Evaluation of NS2 Simulator for
Wireless Sensor Networks, IEEE, 2007. pp 1372-1375.
[10] H. Zhou, J. Lu, Z. Zhang, H. Ali, and C. Won (2007) Application and performance
of extended TTDD’s in large-scale wireless sensor networks. MSN 2007, LNVC 4864,
Dec. 2007. pp 135- 142.

Citation Count - 10
A Cross-Layer Approach for Minimizing Interference and Latency of
Medium Access in Wireless Sensor Networks
Behnam Dezfouli1
, Marjan Radi2
, Shukor Abd Razak3
Faculty of Computer Science and Information Systems, Universiti Teknologi
Malaysia (UTM), Malaysia
ABSTRACT
In low power wireless sensor networks, MAC protocols usually employ periodic
sleep/wake schedule to reduce idle listening time. Even though this mechanism is simple
and efficient, it results in high end-to end latency and low throughput. On the other hand,
the previously proposed CSMA/CA based MAC protocols have tried to reduce inter-node
interference at the cost of increased latency and lower network capacity. In this paper we
propose IAMAC, a CSMA/CA sleep/wake MAC protocol that minimizes internode
interference, while also reduces per-hop delay through cross-layer interactions with the
network layer. Furthermore, we show that IAMAC can be integrated into the SP
architecture to perform its interlayer interactions. Through simulation, we have
extensively evaluated the performance of IAMAC in terms of different performance
metrics. Simulation results confirm that IAMAC reduces energy consumption per node
and leads to higher network lifetime compared to S-MAC and Adaptive S-MAC, while it
also provides lower latency than S-MAC. Throughout our evaluations we have
considered IAMAC in conjunction with two error recovery methods, i.e., ARQ and Seda.
It is shown that using Seda as the error recovery mechanism of IAMAC results in higher
throughput and lifetime compared to ARQ.
KEYWORDS
Wireless Sensor Networks, MAC, IAMAC, Tree-Based Routing, Cross-Layer
Optimization, Interference.
For More Details : http://airccse.org/journal/cnc/0710ijcnc11.pdf
Volume Link: http://airccse.org/journal/ijc2010.html

REFERENCES
[1] M. Z. Zamalloa and B. Krishnamachari, "An analysis of unreliability and asymmetry
in low-power wireless links," ACM Trans. Sen. Netw., vol. 3, 2007, p. 7.
[2] A. Woo, T. Tong, and D. Culler, "Taming the underlying challenges of reliable
multihop routing in sensor networks," Proceedings of the 1st international conference on
Embedded networked sensor systems, Los Angeles, California, USA: ACM, 2003, pp.
14-27.
[3] Q. Cao, T. He, L. Fang, T. Abdelzaher, J. Stankovic, and S. Son, "Efficiency centric
communication model for wireless sensor networks," Proceedings IEEE INFOCOM
2006. 25TH IEEE International Conference on Computer Communications, IEEE, 2006,
pp. 1-12.
[4] A. Cerpa, J. Wong, L. Kuang, M. Potkonjak, and D. Estrin, "Statistical model of lossy
links in wireless sensor networks," Proceedings of the 4th international symposium on
information processing in sensor networks, IEEE Press, 2005, p. 11.
[5] D. S. Couto, D. Aguayo, J. Bicket, and R. Morris, "A high-throughput path metric for
multi-hop wireless routing," Wirel. Netw., vol. 11, 2005, pp. 419-434.
[6] J. Heidemann and D. Estrin, "An energy-efficient MAC protocol for wireless sensor
networks," IEEE INFOCOM, New York, USA: 2002, pp. 1567-1576.
[7] T. van Dam and K. Langendoen, "An adaptive energy-efficient MAC protocol for
wireless sensor networks," Proceedings of the first international conference on Embedded
networked sensor systems - SenSys '03, New York, New York, USA: ACM Press, 2003,
p. 171.
[8] W. Ye, J. Heidemann, and D. Estrin, "Medium access control with coordinated
adaptive sleeping for wireless sensor networks," IEEE/ACM Trans. Netw., vol. 12, 2004,
pp. 493-506.
[9] J. Polastre, J. Hill, and D. Culler, "Versatile low power media access for wireless
sensor networks," Proceedings of the 2nd international conference on Embedded
networked sensor systems - SenSys '04, New York, New York, USA: ACM Press, 2004,
p. 95.
[10] M. Sichitiu, "Cross-layer scheduling for power efficiency in wireless sensor
networks," IEEE INFOCOM 2004, IEEE, 2004, pp. 1740-1750.
[11] V. Kawadia and P. R. Kumar, "A cautionary perspective on cross-layer design,"
Wireless Communications, IEEE, vol. 12, 2005, pp. 3-11.
[12] V. Srivastava and M. Motani, "Cross-layer design: A survey and the road ahead,"
Communications Magazine, IEEE, vol. 43, 2005, p. 112,119.

[13] J. Polastre, J. Hui, P. Levis, J. Zhao, D. Culler, S. Shenker, and I. Stoica, "A
unifying link abstraction for wireless sensor networks," Proceedings of the 3rd
international conference on Embedded networked sensor systems - SenSys '05, New
York, USA: ACM Press, 2005, p. 76.
[14] N. Ramanathan, M. Yarvis, J. Chhabra, N. Kushalnagar, L. Krishnamurthy, and D.
Estrin, "A stream-oriented power management protocol for low duty cycle sensor
network applications," Proceedings of the 2nd IEEE workshop on Embedded Networked
Sensors, IEEE Computer Society, 2005, pp. 53-61.
[15] J. van Greunen and J. Rabaey, "Lightweight time synchronization for sensor
networks," Proceedings of the 2nd ACM international conference on wireless sensor
networks and applications - WSNA '03, New York, USA: ACM Press, 2003, p. 11.
[16] J. Elson, L. Girod, and D. Estrin, "Fine-grained network time synchronization using
reference broadcasts," ACM SIGOPS Operating Systems Review, vol. 36, 2002, p. 147.
[17] Y. Zhao, M. Ma, C. Miao, and T. Nguyen, "An energy-efficient and low-latency
MAC protocol with Adaptive Scheduling for multi-hop wireless sensor networks,"
Computer Communications, In Press, 2010.
[18] R. K. Ganti, P. Jayachandran, H. Luo, and T.F. Abdelzaher, "Datalink streaming in
wireless sensor networks," Proceedings of the 4th international conference on Embedded
networked sensor systems - SenSys '06, New York, USA: ACM Press, 2006, p. 209.
[19] T. Melodia, M. C. Vuran, and D. Pompili, "The state of the art in cross-layer design
for wireless sensor networks," Proceedings of EuroNGI Workshops on Wireless and
Mobility, Springer Lecture Notes on Computer Science, LNCS 388, Como, Italy: 2005.

Citation Count - 08
Performance Analysis of an Improved Graded Precision Localization
Algorithm for Wireless Sensor Networks
Sanat Sarangi and Subrat Kar
Bharti School of Telecommunication Technology and Management, IIT Delhi,
Hauz Khas, New Delhi, India – 110 016
ABSTRACT
In this paper an improved version of the graded precision localization algorithm
GRADELOC, called IGRADELOC is proposed. The performance of GRADELOC is
dependent on the regions formed by the overlapping radio ranges of the nodes of the
underlying sensor network. A different region pattern could significantly alter the nature
and precision of localization. In IGRADELOC, two improvements are suggested. Firstly,
modifications are proposed in the radio range of the fixed-grid nodes, keeping in
mind the actual radio range of commonly available nodes, to allow for routing through
them. Routing is not addressed by GRADELOC, but is of prime importance to the
deployment of any adhoc network, especially sensor networks. A theoretical model
expressing the radio range in terms of the cell dimensions of the grid infrastructure is
proposed, to help in carrying out a deployment plan which achieves the desirable
precision of coarse-grained localization. Secondly, in GRADELOC it is observed that
fine-grained localization does not achieve significant performance benefits over coarse-
grained localization. In IGRADELOC, this factor is addressed with the introduction of a
parameter that could be used to improve and fine-tune the precision of fine-grained
localization.
KEYWORDS
Wireless sensor networks, Localization, Centroid, TDOA, Fixed-grid
For More Details: http://airccse.org/journal/cnc/0710ijcnc13.pdf

REFERENCES
[1] J. W. Kim, H. J. Jang, D. Hwang, and C. Park, A step, stride and heading
determination for the pedestrian navigation system, Journal of Global Positioning
Systems 3 (2004), no. 1-2, 273–279.
[2] L. Klingbeil and T. Wark, A wireless sensor network for real-time indoor localization
and motion monitoring, Proc. of 7th Intl Conf. on Inf. Proc. in Sensor Networks, 2008,
pp. 39–50.
[3] D. Ping, Yongjun, X., and L. Xiaowei, A robust location algorithm with biased
extended kalman filtering of tdoa data for wireless sensor networks, Proc. of Intl Conf. on
Wireless Comm., Networking & Mobile Computing (WCNM’05) (Wuhan, China), vol.
2, 2005, pp. 883–886.
[4] S. Sarangi and S. Kar, A novel algorithm for graded precision localization in wireless
sensor networks, Proc. of 1st Intl. Conf. on Networks and Comm. (NETCOM'09)
(Chennai, India), pp. 18–22, 2009.

Citation Count - 08
Determination of Optimal Number of Clusters in Wireless Sensor
Networks
Ravi Tandon
Department of Computer Science and Engineering, Indian Institute of Technology
Guwahati, India.
ABSTRACT
Prolonged network lifetime, scalability and efficient load balancing are essential for
optimal performance of a wireless sensor network. Clustering provides an effective way
of extending the lifetime of a sensor network. Clustering is the process that divides sensor
networks into smaller localized group (called clusters) of members with a cluster head.
Clustering protocols need to elect optimal number of clusters in hierarchically structured
wireless sensor networks. Any clustering scheme that elects clusters uniformly
(irrespective of the distance from Base Station) incurs excessive energy usage on
clusters proximal and distant to Base Station. In single hop networks a gradual increment
in the energy depletion rate is observed as the distance from the cluster head
increases[17]. This work focuses on the analysis of wasteful energy consumption within a
uniform cluster head election model (EPEM) and provides an analytical solution to
reduce the overall consumption of energy usage amongst the clusters elected in a wireless
sensor network. A circular model of sensor network is considered, where the sensor
nodes are deployed around a centrally located Base Station. The sensor network is
divided into several concentric rings centred at the Base Station. A model, Unequal
Probability Election Model (UEPEM), which elects cluster heads non-uniformly is
proposed. The probability of cluster head election depends on the distance from the Base
Station. UEPEM reduces the overall energy usage by about 21% over EPEM.
The performance of UEPEM improves as the number of rings is increased.
KEYWORDS
Wireless sensor networks, Ad-hoc networks, clustering.

REFERENCES
1. Chatterjee, M., Das, S., & Turgut, D. (2002). WCA: A weighted clustering algorithm
for mobile ad hoc networks. Cluster Computing , 5 (2), 193-204.
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3. Dietrich, I., & Dressler, F. (Feburary 2009). On the Lifetime of Wireless Sensor
Networks. ACM Transactions Sensor Networks, 5, pp. 5:1--5:39. International Journal
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specific protocol architecture for wireless microsensor networks. IEEE Transactions on
Wireless Communications , 1 (4), 660-670.
6. Hill, J., Szewczyk, R., Woo, A., Hollar, S., Culler, D., & Pister, K. (2000). System
architecture directions for networked sensors. ACM Sigplan Notices , 35 (11), 93-104.
7. Lee, S., Yoo, J., & Chung, T. (2004). Distance-based energy efficient clustering for
wireless sensor networks. 29th Annual IEEE International Conference on Local
Computer Networks, 2004. , (pp. 567-568).
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mechanism for wireless sensor networks. IEEE International Conference on Mobile
Adhoc and Sensor Systems Conference. IEEE press.
9. Mhatre, V., & Rosenberg, C. (2004). Design guidelines for wireless sensor networks:
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10. Mhatre, V., & Rosenberg, C. (2004). Homogeneous vs heterogeneous clustered
sensor networks: a comparative study. IEEE International Conference on
Communications, 2004. 6, pp. 3646- 651. IEEE press.
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ACM SIGCOMM Computer Communication Review. 26, pp. 219-230. ACM.
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Protocol for clustered heterogeneous wireless sensor networks. Second International
Workshop on Sensor and Actor Network Protocols and Applications (SANPA 2004).

14. Soro, S., & Heinzelman, W. (2005). Prolonging the lifetime of wireless sensor
networks via unequal clustering. In Parallel and Distributed Processing Symposium,
2005. Proceedings. 19th IEEE International. IEEE press.
15. Wang, W., Wang, B., Liu, Z., Guo, L., & Xiong, W. (2011). A cluster-based and tree-
based power efficient data collection and aggregation protocol for wireless sensor
networks. Information Technology Journal , 10, 557-564.
16. Wu, M. Y., Li, C., Chen, G., & Jie. (2005). An energy efficient clustering scheme in
wireless sensor networks. In Proceedings of the IEEE International Performance
Computing and Communications Conference (pp. 535-540). IEEE Press.
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distribution in wireless sensor networks. IEEE International Conference on Mobile
Adhoc and Sensor Systems (MASS), 2006 (pp. 180-187). IEEE press.
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