Estimation of hop count in multi-hop wireless sensor networks with arbitrary node density

Jerew, Oday D.; Blackmore, Kim

doi:10.1504/ijwmc.2014.062014

Cited by 10 publications

(5 citation statements)

References 25 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The results show that the optimal node density distribution is 4:2.5:1, and the closer it is to the base station, the greater the sensor node density. In [ 27 ], it mainly studies the relationship between node density and the number of hops. Experimental results show that when the node density is 5, it is most beneficial to network data transmission.…”

Section: Evaluation and Discussionmentioning

confidence: 99%

A New Data Fusion Algorithm for Wireless Sensor Networks Inspired by Hesitant Fuzzy Entropy

Wang

Tawose

Jiang

et al. 2019

Sensors

View full text Add to dashboard Cite

The wireless sensor network (WSN) is mainly composed of a large number of sensor nodes that are equipped with limited energy and resources. Therefore, energy consumption in wireless sensor networks is one of the most challenging problems in practice. On the other hand, data fusion can effectively decrease data redundancy, reduce the amount of data transmission and energy consumption in the network, extend the network life cycle, improve the utilization of bandwidth, and thus overcome the bottleneck on energy and bandwidth consumption. This paper proposes a new data fusion algorithm based on Hesitant Fuzzy Entropy (DFHFE). The new algorithm aims to reduce the collection of repeated data on sensor nodes from the source, and strives to utilize the information provided by redundant data to improve the data reliability. Hesitant fuzzy entropy is exploited to fuse the original data from sensor nodes in the cluster at the sink node to obtain higher quality data and make local decisions on the events of interest. The sink nodes periodically send local decisions to the base station that aggregates the local decisions and makes the final judgment, in which process the burden for the base station to process all the data is significantly released. According to our experiments, the proposed data fusion algorithm greatly improves the robustness, accuracy, and real-time performance of the entire network. The simulation results demonstrate that the new algorithm is more efficient than the state-of-the-art in terms of both energy consumption and real-time performance.

show abstract

Section: Evaluation and Discussionmentioning

confidence: 99%

A New Data Fusion Algorithm for Wireless Sensor Networks Inspired by Hesitant Fuzzy Entropy

Wang

Tawose

Jiang

et al. 2019

Sensors

View full text Add to dashboard Cite

show abstract

“…First Corona Sensors collected data packets are transferred by the cluster heads to the base station when the same comes in close to the cluster heads. The authors of [10] implemented a new technique for finding the hop count. He shortest path between the source and the destination is used when these nodes are positioned in equal manner.…”

Section: Third Corona Sensors Second Corona Sensorsmentioning

confidence: 99%

Linear optimization model for mobile cluster heads to improve the lifetime of sensor network

Rakesh

Kumar

2022

ijhs

View full text Add to dashboard Cite

Mobile elements are used in wireless sensor network to increase the longevity of network by minimizing the overloading of one hop sensors. Mobility has proven very useful in reducing the formation of energy holes by balancing the load among all the sensor nodes. The paper proposes exploiting mobile cluster heads to move along a predetermined trajectory to collect data. As autonomous moving strategies impose heavy overhead and data latency issues, predetermined trajectories have proven successful in improvising the lifespan of network. The contributions of the paper are twofold. First we have proposed a predetermined trajectory model along with a cluster formation procedure for the cluster heads to involve in data collection. The cluster heads stop for a fixed time duration “t” at each rendezvous point for data collection. Second, we have proposed a mathematical formulation to optimize the sojourn time duration of thecluster head based on the one hop residual energy of the sensornodes.

show abstract

“…The experimental outcomes show the basic presentation of the proposed conspire and its capacity to accomplish ideal execution in power utilization, lifetime organization, working limit, and information move.The work in [17] shows that the impact of hub clog is significant, and this element has not been satisfactorily tended to in many researches Subsequently, a couple of hop count plans mean a nearby course, regardless of whether they expect to think about course more limited courses. In this manner, the creators of [Jerew et al, 2014] have proposed a clever method for working out bounce counts. They consider the quantity of jump where the organization hubs are designed similarly and the more limited way among source and area is chosen.…”

Section: Figure 1 Sensor Network Architecturementioning

confidence: 99%

Deploying mobile cluster heads in wireless sensor network using heuristic protocol

Krishna¹,

Kumar²

2022

ijhs

View full text Add to dashboard Cite

Exploiting mobile base stations in wireless sensor network increases longevity as it is very effective in dealing with the power hole problem. Mobile sinks are elements used to collect data from network sensors nodes. The movement of the sink eventually changes the sensors of a single hop which will prevent the formation of the hotspot thereby improving the life of the network to a critical level. In this paper we propose the Greedy Heuristic Protocol for Data Collection called GHPDC which selfishly selects energy-rich sites for a mobile channel. Apart from this the paper also proposes the formation of Linear Programming which enhances the station duration which will have a direct impact on prolonging the life of the network. The design of the system line takes into account the residual power of the sensor nodes to determine the amount of time for the base station to halt.

show abstract

Estimation of hop count in multi-hop wireless sensor networks with arbitrary node density

Cited by 10 publications

References 25 publications

A New Data Fusion Algorithm for Wireless Sensor Networks Inspired by Hesitant Fuzzy Entropy

A New Data Fusion Algorithm for Wireless Sensor Networks Inspired by Hesitant Fuzzy Entropy

Linear optimization model for mobile cluster heads to improve the lifetime of sensor network

Deploying mobile cluster heads in wireless sensor network using heuristic protocol

Contact Info

Product

Resources

About