CHSEO: An Energy Optimization Approach for Communication in the Internet of Things

The Internet of Things (IoT) is an emerging platform which bridges the real world and cyber world though communication. Any object or thing in the real world are connected and communicated with the user through the IoT. The major research issue involved in the IoT is energy consumption. Many wireless sensor network algorithms are proposed to optimize energy and those are not suitable for the IoT. The architecture of IoT is different from the traditional WSNs. To achieve the energy efficient mechanism, this paper proposed a hierarchical framework for IoT communications. An energy model is developed for each node and associated roles are assigned based on the services. Cluster head selection for energy optimization (CHSEO) algorithm was proposed for electing the optimal cluster head with in the available nodes to reduce the overall network energy. The efficiency of the CHSEO algorithm is tested with different conditions and it is proved that the CHSEO algorithm performs well when compared to the traditions WSN mechanism.

[1]  Metin Koç,et al.  Controlled Sink Mobility Algorithms for Wireless Sensor Networks , 2014, Int. J. Distributed Sens. Networks.

[2]  Francine Krief,et al.  Power Control and Clustering in Wireless Sensor Networks , 2005, Med-Hoc-Net.

[3]  Guangjie Han,et al.  A Comparative Study of Routing Protocols of Heterogeneous Wireless Sensor Networks , 2014, TheScientificWorldJournal.

[4]  Shideh Sadat Shirazi.  ENERGY EFFICIENT HIERARCHICAL CLUSTER -BASED ROUTING FOR WIRELESS SENSOR NETWORKS , 2015 .

[5]  Yu Zhou,et al.  Deployment of a Reinforcement Backbone Network with Constraints of Connection and Resources , 2010, 2010 IEEE 30th International Conference on Distributed Computing Systems.

[6]  Hossam S. Hassanein,et al.  A Priced Public Sensing Framework for Heterogeneous IoT Architectures , 2013, IEEE Transactions on Emerging Topics in Computing.

[7]  Deborah Estrin,et al.  An energy-efficient MAC protocol for wireless sensor networks , 2002, Proceedings.Twenty-First Annual Joint Conference of the IEEE Computer and Communications Societies.

[8]  Feng Li,et al.  Autonomous Deployment for Load Balancing $k$-Surface Coverage in Sensor Networks , 2015, IEEE Transactions on Wireless Communications.

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

[10]  Jin-Shyan Lee,et al.  Fuzzy-Logic-Based Clustering Approach for Wireless Sensor Networks Using Energy Predication , 2012, IEEE Sensors Journal.

[11]  Henry Leung,et al.  A Joint Fusion, Power Allocation and Delay Optimization Approach for Wireless Sensor Networks , 2011, IEEE Sensors Journal.

[12]  Steve Hodges,et al.  Prototyping Connected Devices for the Internet of Things , 2013, Computer.

[13]  Jyoteesh Malhotra,et al.  EEICCP—Energy Efficient Protocol for Wireless Sensor Networks , 2013 .

[14]  Zhangbing Zhou,et al.  An energy efficient hierarchical clustering index tree for facilitating time-correlated region queries in the Internet of Things , 2014, J. Netw. Comput. Appl..

[15]  Young-Ju Han,et al.  The Concentric Clustering Scheme for Efficient Energy Consumption in the PEGASIS , 2007, The 9th International Conference on Advanced Communication Technology.

[16]  Mojtaba Alizadeh,et al.  Energy Efficient Routing in Wireless Sensor Networks Based on Fuzzy Ant Colony Optimization , 2014, Int. J. Distributed Sens. Networks.

[17]  Mohamed F. Younis,et al.  EQAR: Effective QoS-Aware Relay Node Placement Algorithm for Connecting Disjoint Wireless Sensor Subnetworks , 2011, IEEE Transactions on Computers.

[18]  Edward J. Coyle,et al.  Quantization, channel compensation, and optimal energy allocation for estimation in sensor networks , 2012, TOSN.

[19]  R. B. Patel,et al.  Multi-Hop Data Communication Algorithm for Clustered Wireless Sensor Networks , 2011, Int. J. Distributed Sens. Networks.

[20]  Bechir Hamdaoui,et al.  A Survey on Energy-Efficient Routing Techniques with QoS Assurances for Wireless Multimedia Sensor Networks , 2012, IEEE Communications Surveys & Tutorials.

[21]  M. Madheswaran,et al.  A Hybrid Optimized Weighted Minimum Spanning Tree for the Shortest Intrapath Selection in Wireless Sensor Network , 2014 .

[22]  L. Benini,et al.  Context-Adaptive Multimodal Wireless Sensor Network for Energy-Efficient Gas Monitoring , 2013, IEEE Sensors Journal.

[23]  Bin Hu,et al.  A Hybrid Node Scheduling Approach Based on Energy Efficient Chain Routing for WSN , 2014 .

[24]  Guohong Cao,et al.  Distributed critical location coverage in wireless sensor networks with lifetime constraint , 2012, 2012 Proceedings IEEE INFOCOM.

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

[26]  Yu Meng,et al.  A Novel Deployment Scheme for Green Internet of Things , 2014, IEEE Internet of Things Journal.