Corona based clustering with mixed routing and data aggregation to avoid energy hole problem in wireless sensor network

Bhagyalakshmi, L.; Suman, Sanjay Kumar; Murugan, K.

doi:10.1109/icoac.2012.6416860

Cited by 13 publications

(7 citation statements)

References 15 publications

(17 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…If each sensor starts to transmit data, there may be chance of network congestion and hence it will lead to collision of data. Data collision drains the energy which is fixed in the form of battery [2].…”

Section: Clustering Techniquementioning

confidence: 99%

“…Thus, a sensor node, also known as a mote is capable of sensing and then collecting data, processing and storing data and communicating the processed data in the form of information. It can be noted that all motes are nodes but reverse is not always true [2]. It is also defined as application oriented networks, since depend on the specific applications, these networks might be equipped with GPS device for locating position, a power source and a mobility.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Enhancing the Performance of Wireless Sensor Networks thorugh Clustering and Joint Routing with Mobile Sink

2019

ijeat

View full text Add to dashboard Cite

In wireless sensor network, randomly deployed nodes are formed as a clusters of varying size for each area depending upon the numbers of users. This paper deals with the cluster based joint routing with mobile sink and with static sink in cognitive based wireless sensor network. The Joint Routing (JR) is designed to overcome the problems, due to data gatherings of the sensor nodes for any application. Channel resources usually may vary among the different routing methods based on the traffic characteristics and application they require, which poses a great challenge to guarantee time delivery services. These problems poses a great challenge for cognitive radio based WSN. The resource allocation technique overcomes the problems like spatial priority, time delay, transmission delay and energy loss and here the channel resources are allocated with the help of TDMA technique. The static sink in networks consumes more energy which results the early die out of the nodes. Hence throughput of the networks declines which badly affect the network life time. To overcome these issues, static sink is replaced by mobile sink, which consumes less energy, before each transmission in a sensor networks. The networks with mobile sink provide us optimal solution and performance as well, while comparing with network with static sink. It is shown that the proposed system achieves 15% of improved throughput, 20% of less packet loss and 35% of less delay when compare with the system having centralized sink.

show abstract

Section: Clustering Techniquementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Enhancing the Performance of Wireless Sensor Networks thorugh Clustering and Joint Routing with Mobile Sink

2019

ijeat

View full text Add to dashboard Cite

show abstract

“…for every point (x, y) of the network area S. Note that the point (x, y) is fixed for the integration of Equation (13). The integral is calculated over all possible hops departed from (x, y).…”

Section: Joint Probability Density Function For a Hopmentioning

confidence: 99%

“…In this case, the term load may be assigned to the energy consumption rate. On the other hand, in multi-hop wireless sensor networks, the nodes closer to the sink consume more energy because they have to transmit more packets than the distant ones [13,14]. In this case, the load can be defined as the number of packets transmitted by a node.…”

Section: Introductionmentioning

confidence: 99%

Average Load Definition in Random Wireless Sensor Networks: The Traffic Load Case

Demertzis

Οικονόμου

2018

Technologies

View full text Add to dashboard Cite

Load is a key magnitude for studying network performance for large-scale wireless sensor networks that are expected to support pervasive applications like personalized health-care, smart city and smart home, etc., in assistive environments (e.g., those supported by the Internet of Things). In these environments, nodes are usually spread at random, since deliberate positioning is not a practical approach. Due to this randomness it is necessary to use average values for almost all networks’ magnitudes, load being no exception. However, a consistent definition for the average load is not obvious, since both nodal load and position are random variables. Current literature circumvents randomness by computing the average value over nodes that happen to fall within small areas. This approach is insufficient, because the area’s average is still a random variable and also it does not permit us to deal with single points. This paper proposes a definition for the area’s average load, based on the statistical expected value, whereas a point’s average load is seen as the load of an area that has been reduced (or contracted) to that point. These new definitions are applied in the case of traffic load in multi-hop networks. An interesting result shows that traffic load increases in steps. The simplest form of this result is the constant step, which results in an analytical expression for the traffic load case. A comparison with some real-world networks shows that most of them are accurately described by the constant step model.

show abstract

“…The wireless sensor networks, a part of an ad hoc network, also consists of battery operated powered device, are used for sensing the environmental changes, data processing and communicating wirelessly [12]. The data processing in sensor networks consumes more power, therefore, transmission power control is equally important in wireless sensor networks too.…”

Section: Introductionmentioning

confidence: 99%

SINR Pricing in Non Cooperative Power Control Game for Wireless Ad Hoc Networks

2014

KSII TIIS

View full text Add to dashboard Cite

In wireless ad hoc networks the nodes focus on achieving the maximum SINR for efficient data transmission. In order to achieve maximum SINR the nodes culminate in exhausting the battery power for successful transmissions. This in turn affects the successful transmission of the other nodes as the maximum transmission power opted by each node serves as a source of interference for the other nodes in the network. This paper models the choice of power for each node as a non cooperative game where the throughput of the network with respect to the consumption of power is formulated as a utility function. We propose an adaptive pricing scheme that encourages the nodes to use minimum transmission power to achieve target SINR at the Nash equilibrium and improve their net utility in multiuser scenario.

show abstract

Corona based clustering with mixed routing and data aggregation to avoid energy hole problem in wireless sensor network

Cited by 13 publications

References 15 publications

Enhancing the Performance of Wireless Sensor Networks thorugh Clustering and Joint Routing with Mobile Sink

Enhancing the Performance of Wireless Sensor Networks thorugh Clustering and Joint Routing with Mobile Sink

Average Load Definition in Random Wireless Sensor Networks: The Traffic Load Case

SINR Pricing in Non Cooperative Power Control Game for Wireless Ad Hoc Networks

Contact Info

Product

Resources

About