A Non-Threshold-Based Cluster-Head Rotation Scheme for IEEE 802.15.4 Cluster-Tree Networks

The role of cluster-head in an IEEE 802.15.4 cluster-tree network is to aggregate data from various devices in the cluster and cumulatively transmit to the PANC. This is an energy efficient way of sending data compared to individual reporting of devices independently. Cluster-head coordinators expend more energy compared to other coordinators in the cluster as they have to remain active for longer duration and carry out tasks like aggregation and transmission. Therefore this role of a cluster-head has to be periodically rotated among different coordinators to prevent exhaustion of a particular coordinator's energy and to extend the overall network lifetime. Few of the works done in this direction consider the existence of single hop transmission link to the PANC. Majority of other works designed for wireless sensor networks (WSNs) base the cluster-head rotation decision on threshold of available residual-energy in a coordinator. In this paper, we present a non- threshold based cluster-head rotation scheme that makes a rotation decision based on network- lifetime. It considers the residual energy, transmission cost and aggregation cost from associated coordinators and end-devices in synchronized IEEE 802.15.4 cluster-tree networks. Through simulations, we show that the proposed mechanism extends the overall network lifetime, outperforming other approaches.

[1]  Jaime Lloret Mauri,et al.  Energy‐efficient multi‐level and distance‐aware clustering mechanism for WSNs , 2015, Int. J. Commun. Syst..

[2]  Rakesh Matam,et al.  Distributed beacon scheduling for IEEE 802.15.4 cluster-tree topology , 2016, 2016 IEEE Annual India Conference (INDICON).

[3]  Mahtab Seddigh,et al.  Dominating Sets and Neighbor Elimination-Based Broadcasting Algorithms in Wireless Networks , 2002, IEEE Trans. Parallel Distributed Syst..

[4]  Wendi Heinzelman,et al.  Energy-efficient communication protocol for wireless microsensor networks , 2000, Proceedings of the 33rd Annual Hawaii International Conference on System Sciences.

[5]  Ma Chaw Mon Thein,et al.  An Energy Efficient Cluster-Head Selection for Wireless Sensor Networks , 2010, 2010 International Conference on Intelligent Systems, Modelling and Simulation.

[6]  Majid Sarrafzadeh,et al.  Optimal Energy Aware Clustering in Sensor Networks , 2002 .

[7]  Majid Naderi,et al.  Energy-Efficient Cluster-Head Rotation in Beacon-Enabled IEEE 802.15.4 Networks , 2015, IEEE Transactions on Parallel and Distributed Systems.

[8]  Jaime Lloret Mauri,et al.  Improvement of the Wireless Sensor Network Lifetime Using LEACH with Vice-Cluster Head , 2015, Ad Hoc Sens. Wirel. Networks.

[9]  Lei Shu,et al.  Adaptive Duty Cycling in IEEE 802.15.4 Cluster Tree Networks Using MAC Parameters , 2017, MobiHoc.

[10]  Edward J. Coyle,et al.  An energy efficient hierarchical clustering algorithm for wireless sensor networks , 2003, IEEE INFOCOM 2003. Twenty-second Annual Joint Conference of the IEEE Computer and Communications Societies (IEEE Cat. No.03CH37428).

[11]  Miguel Garcia,et al.  A Cluster-Based Architecture to Structure the Topology of Parallel Wireless Sensor Networks , 2009, Sensors.

[12]  Pham Thanh Hiep.  Spatial Reuse Superframe for High Throughput Cluster-Based WBAN with CSMA/CA , 2016, Ad Hoc Sens. Wirel. Networks.

[13]  Lei Shu,et al.  Distributed Beacon Synchronization Mechanism for 802.15.4 Cluster-Tree Topology , 2016, WICON.

[14]  Ivan Stojmenovic,et al.  Handbook of Sensor Networks: Algorithms and Architectures , 2005, Handbook of Sensor Networks.

[15]  Clémentin Tayou Djamégni,et al.  ISCP: An Instantaneous and Secure Clustering Protocol for Wireless Sensor Networks , 2018, Netw. Protoc. Algorithms.