An energy-balancing clustering approach for gradient-based routing in wireless sensor networks

Liu, Tao; Li, Qingrui; Liang, Ping

doi:10.1016/j.comcom.2012.06.013

Cited by 130 publications

(76 citation statements)

References 24 publications

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“…With varying network topology, such as cluster based [2], tree based [3], chain based [4], various data aggregation schemes have been proposed [4], [5], [6], [7], [8], [9]. Data aggregation mainly exploits the redundancy in the spatially and temporally corelated data sensed by the nodes [10].…”

Section: Related Workmentioning

confidence: 99%

Hierarchical Compressed Sensing for Cluster Based Wireless Sensor Networks

Singh¹,

Kumar²

2016

ijacsa

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Abstract-Data transmission consumes significant amount of energy in large scale wireless sensor networks (WSNs). In such an environment, reducing the in-network communication and distributing the load evenly over the network can reduce the overall energy consumption and maximize the network lifetime significantly. In this work, the aforementioned problem of network lifetime and uneven energy consumption in large scale wireless sensor networks is addressed. This work proposes a hierarchical compressed sensing (HCS) scheme to reduce the innetwork communication during the data gathering process. Corelated sensor readings are collected via a hierarchical clustering scheme. A compressed sensing (CS) based data processing scheme is devised to transmit the data from the source to the sink. The proposed HCS is able to identify the optimal position for the application of CS to achieve reduced and similar number of transmissions on all the nodes in the network. An activity map is generated to validate the reduced and uniformly distributed communication load of the WSN. Based on the number of transmissions per data gathering round, the bit-hop metric model is used to analyse the overall energy consumption. Simulation results validate the efficiency of the proposed method over the existing CS based approaches.

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Section: Related Workmentioning

confidence: 99%

Hierarchical Compressed Sensing for Cluster Based Wireless Sensor Networks

Singh¹,

Kumar²

2016

ijacsa

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“…Low-energy adaptive clustering hierarchy (LEACH) [20] is one of the most classical distributed cluster-based routing protocols in WSNs [15]. It adopts an approach to evenly distribute the energy loads by randomly rotating the role of cluster heads (CHs).…”

Section: Related Workmentioning

confidence: 99%

“…Among them the protocols based on clustering are promising methods owing to their support for data fusion and other good properties such as good scalability and arrangement, as shown in [6,10,[14][15][16][17].…”

Section: Introductionmentioning

confidence: 99%

An Energy-Efficient Clustering Routing Protocol Based on Evolutionary Game Theory in Wireless Sensor Networks

Lin

Wang

Lin

et al. 2015

International Journal of Distributed Sensor Networks

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The features that sensor nodes are powered by battery and have severe energy constraint make the design of energy-efficient protocol a key task for wireless sensor networks (WSNs). Clustering protocols significantly cut down the energy expenditure of each sensor node. However, hot spots problem occurs in locations close to the sink. Besides, it makes things worse if the nodes with less energy are selected as cluster heads (CHs), because they are often loaded heavier traffic than cluster members (CMs) due to their duty. The issues which exist in WSNs are proposed and the primary reason why cluster head election is hard to control is then presented. A mathematical model aiming to ease the hot spots problem via optimizing the cluster size is proposed and an optimal cluster size (OCS) algorithm is given firstly. Subsequently, an evolutionary game model for the sensor nodes to terminate the anarchism during the process of cluster head selection is presented, and a novel routing protocol named Energy Efficient Routing protocol based on Evolutionary Game (EEREG) theory is proposed. Finally, extensive simulation experiments and performance comparisons with the well-known hierarchical routing protocols are conducted. The experiment results show that a significant improvement in energy efficiency as well as lifetime extension is achieved.

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“…A number of issues need to be addressed while using UWSNs. Different from terrestrial sensor networks, the underwater scenario poses some challenges, like high transmission delay, nodes' irregular movement, varying network topology and frequent loss of connectivity due to underwater currents [1,2,4,10,14,18]. Therefore, conventional routing protocols are not appropriate for UWSNs.…”

Section: Introductionmentioning

confidence: 99%

Mobile-MultiSink Routing Protocol for Underwater Wireless Sensor Networks

Wang¹

2017

IJPE

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Underwater Wireless Sensor Networks (UWSNs) are increasingly applied to explore underwater environments and resources. Some characteristics of mobile UWSNs, such as energy restriction, low transmission rate, node mobility and multiplicity, affect networks' performance significantly. In this paper, a Mobile-MultiSink (MMS) routing protocol is proposed for UWSNs with multiple mobile sink nodes. In the proposed MMS routing protocol, sensor nodes report events to multiple sink nodes using dynamic routing. There are two phases in this protocol, the layering phase and the construction phase. In the layering phase, each sink node establishes a layered structure, which needs to be refreshed periodically. Taking into consideration that the packet delivery rate (PDR) will reduce because of the mobility of nodes, we stipulate that every sink node should refresh its layered structure every time the PDR comes below a critical value. In the communication phase, the intermediate relay nodes are selected to forward data to the target sink node. This phase contains the selection of target sink node and the selection of relay nodes. We evaluate the performance of MMS using NS-3. Our findings demonstrate that the proposed protocol has better packet delivery rate and lower energy consumption in UWSNs with multiple mobile sink nodes.

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An energy-balancing clustering approach for gradient-based routing in wireless sensor networks

Cited by 130 publications

References 24 publications

Hierarchical Compressed Sensing for Cluster Based Wireless Sensor Networks

Hierarchical Compressed Sensing for Cluster Based Wireless Sensor Networks

An Energy-Efficient Clustering Routing Protocol Based on Evolutionary Game Theory in Wireless Sensor Networks

Mobile-MultiSink Routing Protocol for Underwater Wireless Sensor Networks

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