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A Smart and Balanced Energy-Efficient Multihop Clustering Algorithm (Smart-BEEM) for MIMO IoT Systems in Future Networks.

ABSTRACT: Wireless Sensor Networks (WSNs) are typically composed of thousands of sensors powered by limited energy resources. Clustering techniques were introduced to prolong network longevity offering the promise of green computing. However, most existing work fails to consider the network coverage when evaluating the lifetime of a network. We believe that balancing the energy consumption in per unit area rather than on each single sensor can provide better-balanced power usage throughout the network. Our former work-Balanced Energy-Efficiency (BEE) and its Multihop version BEEM can not only extend the network longevity, but also maintain the network coverage. Following WSNs, Internet of Things (IoT) technology has been proposed with higher degree of diversities in terms of communication abilities and user scenarios, supporting a large range of real world applications. The IoT devices are embedded with multiple communication interfaces, normally referred as Multiple-In and Multiple-Out (MIMO) in 5G networks. The applications running on those devices can generate various types of data. Every interface has its own characteristics, which may be preferred and beneficial in some specific user scenarios. With MIMO becoming more available on the IoT devices, an advanced clustering solution for highly dynamic IoT systems is missing and also pressingly demanded in order to cater for differing user applications. In this paper, we present a smart clustering algorithm (Smart-BEEM) based on our former work BEE(M) to accomplish energy efficient and Quality of user Experience (QoE) supported communication in cluster based IoT networks. It is a user behaviour and context aware approach, aiming to facilitate IoT devices to choose beneficial communication interfaces and cluster headers for data transmission. Experimental results have proved that Smart-BEEM can further improve the performance of BEE and BEEM for coverage sensitive longevity.

SUBMITTER: Xu L

PROVIDER: S-EPMC5539611 | biostudies-other | 2017 Jul

REPOSITORIES: biostudies-other

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Project description:Wireless sensor networks (WSNs) form an important part of industrial application. There has been growing interest in the potential use of WSNs in applications such as environment monitoring, disaster management, health care monitoring, intelligence surveillance and defence reconnaissance. In these applications, the sensor nodes (SNs) are envisaged to be deployed in sizeable numbers in an outlying area, and it is quite difficult to replace these SNs after complete deployment in many scenarios. Therefore, as SNs are predominantly battery powered devices, the energy consumption of the nodes must be properly managed in order to prolong the network lifetime and functionality to a rational time. Different energy-efficient and energy-balanced routing protocols have been proposed in literature over the years. The energy-efficient routing protocols strive to increase the network lifetime by minimizing the energy consumption in each SN. On the other hand, the energy-balanced routing protocols protract the network lifetime by uniformly balancing the energy consumption among the nodes in the network. There have been various survey papers put forward by researchers to review the performance and classify the different energy-efficient routing protocols for WSNs. However, there seems to be no clear survey emphasizing the importance, concepts, and principles of load-balanced energy routing protocols for WSNs. In this paper, we provide a clear picture of both the energy-efficient and energy-balanced routing protocols for WSNs. More importantly, this paper presents an extensive survey of the different state-of-the-art energy-efficient and energy-balanced routing protocols. A taxonomy is introduced in this paper to classify the surveyed energy-efficient and energy-balanced routing protocols based on their proposed mode of communication towards the base station (BS). In addition, we classified these routing protocols based on the solution types or algorithms, and the input decision variables defined in the routing algorithm. The strengths and weaknesses of the choice of the decision variables used in the design of these energy-efficient and energy-balanced routing protocols are emphasised. Finally, we suggest possible research directions in order to optimize the energy consumption in sensor networks.

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A Smart and Balanced Energy-Efficient Multihop Clustering Algorithm (Smart-BEEM) for MIMO IoT Systems in Future Networks.

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