Heuristic Based Coverage Aware Load Balanced Clustering in WSNs and Enablement of IoT

Heuristic Based Coverage Aware Load Balanced Clustering in WSNs and Enablement of IoT

Surjit Singh, Rajeev Mohan Sharma
DOI: 10.4018/IJITWE.2018040101
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Abstract

Integration of heterogeneous communication systems is the major objective of Future Internet. Heterogeneous systems such as wired and wireless assert the concept of Internet of Things (IoT). Communication standard protocols based global network of identical addressable interconnected resources conferred to IoT. In this article, it is described how wireless sensor networks (WSN) are one of the keys enabling the IoT. Clustering in WSNs plays an important role since it allows altering the network topology and helps in balancing of traffic loads. Load balancing improves the lifespan and scalability of the WSNs. Here, a heuristic approach, coverage aware load balanced clustering, has been developed in order to increase the lifespan of the WSNs. Moreover, simulation results are demonstrated for a sample network and the results show that the network lifespan has increased and simultaneously energy consumption is reduced compared to the other existing techniques.
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1. Introduction

We are started experiencing towards global communication infrastructure such as with IoT (Internet of Things) and M2M (Machine to Machine) smart technologies. These may lead toward better economy, industrial and society enhancements, and supporting new services. IoT has major applications ranges from healthcare, construction, mining, manufacturing, water, green computing, logistics and aeronautics, and civilian to defence sectors. Theses make IoT popular among the research community and industries as well. However, to facilitate these applications IoT innovations provides new challenging issues to communication systems. Apart from that IoT also support numerous heterogeneous objects. IoT is currently a popular technology in the whole world. Industries have involved differently with different aspects of business with IoT. These are updating and transitioning their traditional infrastructure to support IoT. Advancement in technology makes it possible envision pervasive connectivity, computation and storage to support IoT enablement. The smart cities development is being gradually possible with the IoT based applications such as transportation, emergency notification, remote health monitoring etc. Further, high heterogeneity characterizing WSNs. There are different proprietary and non-proprietary solutions exists. The wide range of advancement in technology has delayed integration with traditional WSNs. The emerging standard 6LoWPAN/IPv6 enabling IP based WSNs (Mainetti, Patrono, & Vilei, 2011). It forces to move beyond proprietary and closed standards of communication system. This makes possibility of native connectivity between internet and sensor networks. And, help in enabling smart objects to collaborate to IoT. The different WSNs have already been deployed over the years. Therefore, it is difficult to build an all IP infrastructure. Mainetti et. al. (2011) presented a framework of allowing transitioning to an all IP infrastructure and new implementations at large scale. The authors presented state of the art able to harmonize legacy.

Integration of heterogeneous communication systems is the major objective of Future Internet (Atzori, Iera, & Morabito, 2010; Kortuem, Kawsar, Sundramoorthy, & Fitton, 2010). Heterogeneous systems such as wired and wireless assert the concept of Internet of Things (IoT). Communication standard protocols based global network of identical addressable interconnected resources conferred to IoT. Here, wireless sensor networks (WSNs) are one of the key enabling IoT.

To build virtual sensor network by integrating existing sensor networks the wide range of enhancements presently delaying a large-scale implementation of these technologies. The interoperability among different sensor networks along with abstraction between high and low layers are major challenging issues (Zorzi, Gluhak, Lange, & Bassi, 2010).

Software defined wireless sensor networks presented by authors (Bera, Misra, Roy, & Obaidat, 2016). A survey of network virtualization presented by authors (Chowdhury, & Boutaba, 2010; Fischer, et. al., 2013). Authors also presented optimal resource allocation in virtual sensor networks (Delgado et. al., 2016).

Recently, WSN has gained substantial attention of the researchers because of the challenges involved in deploying effective networks while setting the energy and bandwidth as the major constraints (Curry, & Smith, 2016). For information transformation, data collection and to analyze it requires energy from the battery powered sensors. In sensor placement environmental characteristics and accessibility, relocating forces of the sensors plays an important role.

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