TY - GEN
T1 - Efficient topology discovery and routing in thick wireless Linear Sensor Networks
AU - Jawhar, Imad
AU - Zhang, Sheng
AU - Wu, Jie
AU - Mohamed, Nader
AU - Masud, Mohammad M.
N1 - Funding Information:
This work was supported in part by UAEU - UPAR Grant No.: 31T059- UPAR (1) 2014 under Grant Code G00001655.
Publisher Copyright:
© 2017 IEEE.
PY - 2017/11/20
Y1 - 2017/11/20
N2 - Wireless devices such as sensors have increasingly more processing, storage, and networking capabilities, making wireless sensor networks (WSNs) get lots of attentions in recent years. In addition, the cost of sensors is constantly decreasing making it possible to use large quantities of these sensors in a wide variety of important applications in environmental, military, commercial, health care, and other fields. In order to monitor certain types of infrastructures, many of these applications involve lining up the sensors in a linear form, making a special class of these networks which are defined as Linear Sensor Networks (LSNs). In this paper, we take advantage of the linearity of the network to design two graph-search-based topology discovery algorithms for LSNs, namely, LNBN and L2BN. LNBN focuses on minimizing the number of messages used to construct the backbone, while L2BN targets to minimizing the average number of communication hops. The proposed algorithms have several good properties. First, they allow for significant improvement in the scalability of the communication process. Second, the linearity of the structure and the discovered backbone can enhance the routing reliability by jumping over failed nodes by increasing the range. Lastly, they do not require sensor nodes to have location detection capabilities such as GPS, which would otherwise lead to higher costs of sensor nodes.
AB - Wireless devices such as sensors have increasingly more processing, storage, and networking capabilities, making wireless sensor networks (WSNs) get lots of attentions in recent years. In addition, the cost of sensors is constantly decreasing making it possible to use large quantities of these sensors in a wide variety of important applications in environmental, military, commercial, health care, and other fields. In order to monitor certain types of infrastructures, many of these applications involve lining up the sensors in a linear form, making a special class of these networks which are defined as Linear Sensor Networks (LSNs). In this paper, we take advantage of the linearity of the network to design two graph-search-based topology discovery algorithms for LSNs, namely, LNBN and L2BN. LNBN focuses on minimizing the number of messages used to construct the backbone, while L2BN targets to minimizing the average number of communication hops. The proposed algorithms have several good properties. First, they allow for significant improvement in the scalability of the communication process. Second, the linearity of the structure and the discovered backbone can enhance the routing reliability by jumping over failed nodes by increasing the range. Lastly, they do not require sensor nodes to have location detection capabilities such as GPS, which would otherwise lead to higher costs of sensor nodes.
KW - Backbone discovery
KW - Routing
KW - Wireless linear sensor networks
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U2 - 10.1109/INFCOMW.2017.8116358
DO - 10.1109/INFCOMW.2017.8116358
M3 - Conference contribution
AN - SCOPUS:85041311405
T3 - 2017 IEEE Conference on Computer Communications Workshops, INFOCOM WKSHPS 2017
SP - 91
EP - 96
BT - 2017 IEEE Conference on Computer Communications Workshops, INFOCOM WKSHPS 2017
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2017 IEEE Conference on Computer Communications Workshops, INFOCOM WKSHPS 2017
Y2 - 1 May 2017 through 4 May 2017
ER -