Energy consumption model for density controlled divide-and-rule scheme for energy efficient routing in wireless sensor networks

Latif, Kamran; Javaid, Nadeem; Saqib, Malik Najmus; Khan, Zahoor Ali; Alrajeh, Nabil

doi:10.1504/ijahuc.2016.075192

Cited by 31 publications

(11 citation statements)

References 18 publications

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“…Latif, Kamran,et al, presented a clustering technique at routing layer for terrestrial wireless sensor networks called density controlled divide-and-rule (DDR) [11]. DDR have constant number of CHs in each round and it is based on static clustering.In DDR, the network field is divided into logical segments in order to reduce communication distance between sensor node to CH and between CH to sink(s).…”

Section: Related Workmentioning

confidence: 99%

“…The value of W is calculated from total width of the network field. Equation (11) calculates the value of W . In equation (12), we calculate the value of B from breadth of the network field.…”

Section: Seec:the Proposed Schemementioning

confidence: 99%

“…The phenomena of quick energy consumption of a sensor node due to unbalanced load of data forwarding is called energy hole. The energy hole problem causes death of a sensor node earlier than other nodes which creates a coverage hole due to which the area of this sensor node remains unobserved or un-sensed [11]. In addition, underwater sensor nodes are large in size so, sensor nodes are deployed with the help of ships, which is costly.…”

Section: Introductionmentioning

confidence: 99%

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SEEC: Sparsity-Aware Energy Efficient Clustering Protocol for Underwater Wireless Sensor Networks

Azam

Majid

Ahmad

et al. 2016

2016 IEEE 30th International Conference on Advanced Information Networking and Applications (AINA)

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Many routing protocols are proposed regarding energy efficiency in underwater wireless sensor networks (UWSNs). We propose sparsity-aware energy efficient clustering (SEEC) protocol for UWSNs. SEEC specially search sparse regions of the network. We divide the network region into subregions of equal size and search sparse and dense regions of the network field with the help of sparsity search algorithm (SSA) and density search algorithm (DSA). SEEC improves network lifetime through sink mobility in sparse regions and clustering in dense regions of the network. SEEC also achieves network stability with optimal number of clusters formation in dense regions of the network where each dense region logically represents a static cluster. The division of the network region into subregions control routing hole problem in the UWSNs. SEEC minimizes network energy consumption with balanced scheme operations. Effectiveness of our proposed protocol is verified by simulation results.

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Section: Related Workmentioning

confidence: 99%

Section: Seec:the Proposed Schemementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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SEEC: Sparsity-Aware Energy Efficient Clustering Protocol for Underwater Wireless Sensor Networks

Azam

Majid

Ahmad

et al. 2016

2016 IEEE 30th International Conference on Advanced Information Networking and Applications (AINA)

Self Cite

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“…There are several reasons to apply clustering techniques in WSNs such as increased scalability, less load, less energy consumption, latency reduction, collision avoidance, guarantee of connectivity, fault tolerance, load balancing, energy hole avoidance and increasing network lifetime [ 1 ]. In addition, dividing the network area into subareas helps control the coverage hole problem [ 2 ], which appears whenever some parts of the network areas are not covered by any sensor nodes.…”

Section: Introductionmentioning

confidence: 99%

An Energy-Efficient Mobile Sink-Based Unequal Clustering Mechanism for WSNs

Gharaei

Bakar

Hashim

et al. 2017

Sensors

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Network lifetime and energy efficiency are crucial performance metrics used to evaluate wireless sensor networks (WSNs). Decreasing and balancing the energy consumption of nodes can be employed to increase network lifetime. In cluster-based WSNs, one objective of applying clustering is to decrease the energy consumption of the network. In fact, the clustering technique will be considered effective if the energy consumed by sensor nodes decreases after applying clustering, however, this aim will not be achieved if the cluster size is not properly chosen. Therefore, in this paper, the energy consumption of nodes, before clustering, is considered to determine the optimal cluster size. A two-stage Genetic Algorithm (GA) is employed to determine the optimal interval of cluster size and derive the exact value from the interval. Furthermore, the energy hole is an inherent problem which leads to a remarkable decrease in the network’s lifespan. This problem stems from the asynchronous energy depletion of nodes located in different layers of the network. For this reason, we propose Circular Motion of Mobile-Sink with Varied Velocity Algorithm (CM2SV2) to balance the energy consumption ratio of cluster heads (CH). According to the results, these strategies could largely increase the network’s lifetime by decreasing the energy consumption of sensors and balancing the energy consumption among CHs.

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“…A group of sensor nodes is termed as a cluster and each cluster is having a cluster head (CH). A CH is chosen on the basis of many different parameters like its proximity to all the other nodes of the cluster, its residual energy, distance from the BS, and many more [3]. In a cluster, each and every node senses the data.…”

Section: Introductionmentioning

confidence: 99%

Comparative Analysis of Route Information Based Enhanced Divide and Rule Strategy in WSNs

Kumar¹,

Singh²,

Sharma³

2017

IJSC

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Energy consumption model for density controlled divide-and-rule scheme for energy efficient routing in wireless sensor networks

Cited by 31 publications

References 18 publications

SEEC: Sparsity-Aware Energy Efficient Clustering Protocol for Underwater Wireless Sensor Networks

SEEC: Sparsity-Aware Energy Efficient Clustering Protocol for Underwater Wireless Sensor Networks

An Energy-Efficient Mobile Sink-Based Unequal Clustering Mechanism for WSNs

Comparative Analysis of Route Information Based Enhanced Divide and Rule Strategy in WSNs

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