A Hybrid Unequal Clustering Based on Density with Energy Conservation in Wireless Nodes

The Internet of things (IoT) provides the possibility of communication between smart devices and any object at any time. In this context, wireless nodes play an important role in reducing costs and simple use. Since these nodes are often used in less accessible locations, recharging their battery is hardly feasible and in some cases is practically impossible. Hence, energy conservation within each node is a challenging discussion. Clustering is an efficient solution to increase the lifetime of the network and reduce the energy consumption of the nodes. In this paper, a novel hybrid unequal multi-hop clustering based on density (HCD) is proposed to increase the network lifetime. In the proposed protocol, the cluster head (CH) selection is performed only by comparing the status of each node to its neighboring nodes. In this new technique, the parameters involving energy of nodes, the number of neighboring nodes, the distance to the base station (BS), and the layer where the node is placed in are considered in CH selection. So, in this new and simple technique considers energy consumption of the network and load balancing. Clustering is performed unequally so that cluster heads (CHs) close to BS have more energy for data relay. Also, a hybrid dynamic–static clustering was performed to decrease overhead. In the current protocol, a distributed clustering and multi-hop routing approach was applied between cluster members (CMs), to CHs, and CHs to BS. HCD is applied as a novel assistance to cluster heads (ACHs) mechanism, in a way that a CH accepts to use member nodes with suitable state to share traffic load. Furthermore, we performed simulation for two different scenarios. Simulation results showed the reliability of the proposed method as it was resulted in a significant increase in network stability and energy balance as well as network lifetime and efficiency.

[1]  MengChu Zhou,et al.  Recent Advances in Energy-Efficient Routing Protocols for Wireless Sensor Networks: A Review , 2016, IEEE Access.

[2]  Guangjie Han,et al.  An Energy-Efficient Ring Cross-Layer Optimization Algorithm for Wireless Sensor Networks , 2018, IEEE Access.

[3]  Seyed Mostafa Bozorgi,et al.  A new clustering protocol for energy harvesting-wireless sensor networks , 2017, Comput. Electr. Eng..

[4]  R. Santhiya,et al.  Energy Aware Multi - Hop Routing Protocol for WSNs , 2019 .

[5]  Srinivasulu Tadisetty,et al.  SEES: a scalable and energy-efficient scheme for green IoT-based heterogeneous wireless nodes , 2018, Journal of Ambient Intelligence and Humanized Computing.

[6]  Ossama Younis,et al.  An energy-aware distributed clustering protocol in wireless sensor networks using fuzzy logic , 2012, Ad Hoc Networks.

[7]  Seyed Mostafa Bozorgi,et al.  A novel dynamic multi-hop clustering protocol based on renewable energy for energy harvesting wireless sensor networks , 2015, 2015 2nd International Conference on Knowledge-Based Engineering and Innovation (KBEI).

[8]  Anantha P. Chandrakasan,et al.  An application-specific protocol architecture for wireless microsensor networks , 2002, IEEE Trans. Wirel. Commun..

[9]  Nathalie Mitton,et al.  Energy-based clustering for wireless sensor network lifetime optimization , 2013, 2013 IEEE Wireless Communications and Networking Conference (WCNC).

[10]  Shuang Wu,et al.  A grid-based reliable routing protocol for wireless sensor networks with randomly distributed clusters , 2016, Ad Hoc Networks.

[11]  Mohammad Patwary,et al.  Universal and Dynamic Clustering Scheme for Energy Constrained Cooperative Wireless Sensor Networks , 2017, IEEE Access.

[12]  Miguel Soriano,et al.  Securing cognitive radio networks , 2010 .

[13]  Narottam Chand,et al.  Energy Efficient Clustering and Cluster Head Rotation Scheme for Wireless Sensor Networks , 2012 .

[14]  L. Malathi,et al.  Energy efficient data collection through hybrid unequal clustering for wireless sensor networks , 2015, Comput. Electr. Eng..

[15]  Rajoo Pandey,et al.  An improved energy aware distributed unequal clustering protocol for heterogeneous wireless sensor networks , 2016 .

[16]  Da-Ren Chen,et al.  An energy-efficient QoS routing for wireless sensor networks using self-stabilizing algorithm , 2016, Ad Hoc Networks.

[17]  Shigenobu Sasaki,et al.  An Unequal Multi-hop Balanced Immune Clustering protocol for wireless sensor networks , 2016, Appl. Soft Comput..

[18]  Zhetao Li,et al.  Noise-Tolerant Wireless Sensor Networks Localization via Multinorms Regularized Matrix Completion , 2018, IEEE Transactions on Vehicular Technology.

[19]  Miltiadis D. Lytras,et al.  Innovative services and applications of wireless sensor networks: Research challenges and opportunities , 2018, Int. J. Distributed Sens. Networks.

[20]  Bin Li,et al.  An Energy Efficient Distance-Aware Routing Algorithm with Multiple Mobile Sinks for Wireless Sensor Networks , 2014, Sensors.

[21]  Ossama Younis,et al.  HEED: a hybrid, energy-efficient, distributed clustering approach for ad hoc sensor networks , 2004, IEEE Transactions on Mobile Computing.

[22]  Yongtae Shin,et al.  A Density and Distance based Cluster Head Selection algorithm in Sensor Networks , 2010, 2010 The 12th International Conference on Advanced Communication Technology (ICACT).

[23]  Arun Kumar Sangaiah,et al.  Survey on clustering in heterogeneous and homogeneous wireless sensor networks , 2017, The Journal of Supercomputing.

[24]  Xueying Zhang,et al.  Polar Coordinate-Based Energy-Efficient-Chain Routing in Wireless Sensor Networks Using Random Projection , 2018, IEEE Access.

[25]  Olga León Abarca,et al.  Securing cognitive radio networks , 2010 .

[26]  Robert Simon Sherratt,et al.  Energy-aware distributed routing algorithm to tolerate network failure in wireless sensor networks , 2017, Ad Hoc Networks.

[27]  Sipra Das Bit,et al.  An Enhanced Energy-Efficient Protocol with Static Clustering for WSN , 2011, The International Conference on Information Networking 2011 (ICOIN2011).

[28]  A. S. Rostami,et al.  A novel and optimized Algorithm to select monitoring sensors by GSA , 2011, The 2nd International Conference on Control, Instrumentation and Automation.

[29]  Bin Li,et al.  Bio-inspired ant colony optimization based clustering algorithm with mobile sinks for applications in consumer home automation networks , 2015, IEEE Transactions on Consumer Electronics.

[30]  Eduardo Cerqueira,et al.  A Routing Protocol Based on Energy and Link Quality for Internet of Things Applications , 2013, Sensors.

[31]  Jiguo Yu,et al.  ECDC: An energy and coverage-aware distributed clustering protocol for wireless sensor networks , 2014, Comput. Electr. Eng..

[32]  Hadi Larijani,et al.  A Survey on Centralised and Distributed Clustering Routing Algorithms for WSNs , 2015, 2015 IEEE 81st Vehicular Technology Conference (VTC Spring).