A Clustering Protocol with Mode Selection for Wireless Sensor Network

Kusdaryono, Aries; Lee, Kyung Oh

doi:10.3745/jips.2011.7.1.029

Cited by 13 publications

(6 citation statements)

References 14 publications

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“…For each cluster, a single node among all members, called cell head node (CH), acts as the receiver of the information sensed by the other CH members. We indicate that the number of techniques to elect one node as CH of the group is rather large [22]; but due to space limitations they are not discussed in this paper. Hence, as a first approach used in our study we have assumed that the CH is approximately located at the center of the hexagon.…”

Section: Cells Sensors and Cell Head Selectionmentioning

confidence: 99%

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End to End Delay and Energy Consumption in a Two Tier Cluster Hierarchical Wireless Sensor Networks

et al. 2019

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In this work it is considered a circular Wireless Sensor Networks (WSN) in a planar structure with uniform distribution of the sensors and with a two-level hierarchical topology. At the lower level, a cluster configuration is adopted in which the sensed information is transferred from sensor nodes to a cluster head (CH) using a random access protocol (RAP). At CH level, CHs transfer information, hop-by-hop, ring-by-ring, towards to the sink located at the center of the sensed area using TDMA as MAC protocol. A Markovian model to evaluate the end-to-end (E2E) transfer delay is formulated. In addition to other results such as the well know energy hole problem, the model reveals that for a given radial distance between the CH and the sink, the transfer delay depends on the angular orientation between them. For instance, when two rings of CHs are deployed in the WSN area, the E2E delay of data packets generated at ring 2 and at the “west” side of the sink, is 20% higher than the corresponding E2E delay of data packets generated at ring 2 and at the “east” side of the sink. This asymmetry can be alleviated by rotating from time to time the allocation of temporary slots to CHs in the TDMA communication. Also, the energy consumption is evaluated and the numerical results show that for a WSN with a small coverage area, say a radio of 100 m, the energy saving is more significant when a small number of rings are deployed, perhaps none (a single cluster in which the sink acts as a CH). Conversely, topologies with a large number of rings, say 4 or 5, offer a better energy performance when the service WSN covers a large area, say radial distances greater than 400 m.

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Section: Cells Sensors and Cell Head Selectionmentioning

confidence: 99%

“…Next we take into account the third term of Equation (24), RW 4,3 h , whose expression is given in Equation (26). Since our tagged data packet travels alone the WSN, according to Equation (22) and to Equation (23), r E 4,3 p = W r 4,3 h = 0. Finally, with regard to the term TT 4,3 h , 3,2 h in Equation 26…”

Section: Model Validationmentioning

confidence: 99%

End to End Delay and Energy Consumption in a Two Tier Cluster Hierarchical Wireless Sensor Networks

et al. 2019

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“…BIDRP does not provide an alternative solution in situations where these higher energy CH nodes die. Clustering Protocol with Mode Selection (CPMS) is proposed in [11]. This protocol is based on [8] for CH selection and on [10] for levels formation.…”

Section: Related Workmentioning

confidence: 99%

Energy Evaluation Model for an Improved Centralized Clustering Hierarchical Algorithm in WSN

Jan

Nanda

2013

Lecture Notes in Computer Science

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Wireless Sensor Networks (WSN) consists of battery-powered sensor nodes which collect data and route the data to the Base Station. Centralized Cluster-based routing protocols efficiently utilize limited energy of the nodes by selecting Cluster Heads (CHs) in each round. Selection of CHs and Cluster formation is performed by the Base Station. In each round, nodes transmit their location information and their residual energy to the Base Station. This operation is a considerable burden on these resource hungry sensor nodes. In this paper we propose a scheme whereby a small number of High-Energy nodes gather location information and residual energy status of the sensing nodes and transmit to the Base Station. This scheme eliminates CH advertisement phase in order to conserve energy. Based on the energy consumption by various types of nodes, we have derived an energy model for our algorithm which depicts the total energy consumption in the network.

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“…There are many solutions to medium access control (MAC) for traditional sensor and ad hoc networks. Some of those are centralized protocols [4][5][6][7][8] and some are decentralized [9]. But none of those protocols are directly applicable to a CRN because of different spectrum etiquette.…”

Section: Introductionmentioning

confidence: 99%

A Fully Distributed Resource Allocation Mechanism for CRNs without Using a Common Control Channel

Mahmud¹,

Lee²,

Koo

2015

Mathematical Problems in Engineering

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Spatial and temporal variations in the available spectrum for cognitive devices add additional complexity in designing a medium access strategy for cognitive radio (CR) networks. To ease this complication, a common control channel (CCC) is often used as a common platform to exchange control messages, so the CR users can make decisions concerning resource allocation. Much of the literature in this area opts for forming groups and negotiating a CCC from the available channels rather than considering a dedicated common control channel. However, if a primary user appears on the CCC, all the CR users have to vacate that channel and negotiate another CCC, and thus overhead continues to grow with an agile primary network. We propose a medium access control protocol that can work in the absence of a CCC and reduce the possible overhead to a greater extent. In our proposed protocol, CR users take advantage of similar spectrum availability in their neighborhood for resource utilization. We also propose a contention-based spectrum allocation mechanism that works in a distributed manner over different available channels. Simulation results show that this approach can reduce broadcast overhead significantly while maintaining connectivity success similar to its counterparts.

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A Clustering Protocol with Mode Selection for Wireless Sensor Network

Cited by 13 publications

References 14 publications

End to End Delay and Energy Consumption in a Two Tier Cluster Hierarchical Wireless Sensor Networks

End to End Delay and Energy Consumption in a Two Tier Cluster Hierarchical Wireless Sensor Networks

Energy Evaluation Model for an Improved Centralized Clustering Hierarchical Algorithm in WSN

A Fully Distributed Resource Allocation Mechanism for CRNs without Using a Common Control Channel

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