Network tomography application in mobile ad-hoc network using stitching algorithm

Khan, Mohammad S.; Kumar, Anup; Xie, Bin; Sahoo, Prasanna K.

doi:10.1016/j.jnca.2015.07.003

Cited by 7 publications

(5 citation statements)

References 25 publications

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“…Controls and management in facility application surveillance, intrusion detection, industrial processes controls, and machine health monitoring and so many to mention, were among many applications used in wireless sensor network. [9] Mobile Network and WSN-Wireless sensor network technology are continuously derived in local network behavior performances [20]. However, most of the techniques previously used were not schedule systematically using data-mule.…”

Section: Related Workmentioning

confidence: 99%

A Distance-Based Data-Mule Scheduling Technique for Lesser Nodal Delay in Wireless Sensor Network

Alba

Festijo

Medina

2022

Int. j. commun. netw. inf. secur.

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Nodal delay in wireless sensor network is an indisputable factor in the medium of communication. Factor such as changeability of communication devices, network topologies, packet-sizes, and transmission rate demands to develop data-mule queue scheduling technique. Our proposed data-mule scheduling technique accomplish this through simulations using standard software written in C# by controlling data-mule schedules that collects data from all the nodes connected to the hop. The scheme identifies the hierarchical positions of static source nodes and the distance of mobile source nodes from the hop with rescheduling based on the newly acquired distances. Source nodes applied with data-mule scheduling technique resulted to lower nodal delay. Transmission of packet-data is efficiently and effectively improved.

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Section: Related Workmentioning

confidence: 99%

A Distance-Based Data-Mule Scheduling Technique for Lesser Nodal Delay in Wireless Sensor Network

Alba

Festijo

Medina

2022

Int. j. commun. netw. inf. secur.

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“…We are going to adopt a minimum-risk point estimation procedure to estimate the mean vector P λ. Having recorded Y (1) , Y (2) , ..., Y (n) , with,…”

Section: An Adaptive Proceduresmentioning

confidence: 99%

“…T from the two observed vectors of data y (1) and y (2) . Note that W and γ are known to begin with.…”

Section: An Adaptive Proceduresmentioning

confidence: 99%

“…Hence estimating such a vector of parameters is of great importance. This idea of Network Tomography [1] has received lots of attention recently in understanding the link performance in ad-hoc networks to VANET [2,3,4,5,6], and other related areas. Most recently, evaluation of software open-source IMS network under the load of SIP messages was addressed by [7] and identifying and correcting the network weaknesses by incorporating bandwidth measurements was discussed by [8].…”

Section: Introductionmentioning

confidence: 99%

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An Adaptive Technique for Estimating Traffic Intensities for a Network in Random Markovian Routing

Bhattacharjee

Zhuang

2020

Wseas Transactions on Mathematics

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We propose an efficient method for estimating a vector of parameters that characterize the node-tonode traffic intensities in a network. The estimation procedure is free from any initial estimate which is often difficult to choose for iterative procedures that occur in maximum likelihood estimation or method of moments. The procedure discussed here updates the information from a continuous chain of data until a stopping variable decides the final sample size and the estimate. More importantly, it considers the cost of logistics in sampling. We discuss important desirable properties of the estimation-procedure under the assumption of Poisson distribution. Data analyses reveal a highly accurate estimation and demonstrate a fast convergence

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“…Facility application surveillance, intrusion detection, industrial processes controls and machine health monitoring were among many applications used in wireless sensor network. [10] Wireless sensor network and mobile network technology are continuously derived in local network behavior performances [11].…”

Section: Introductionmentioning

confidence: 99%

A Case Study of Wireless Sensor Network Latency in the Philippines for Enhancement of Packet-data Transmission

2018

Proceedings of 2018 the 8th International Workshop on Computer Science and Engineering

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Wireless sensor network is the engine of communication in the digital world. Communication rules the entire industry including business, medicine agriculture and many more. In this research paper, researchers discuss delay of packet data transmission of wireless sensor network communication in the Philippines. The research was conducted in a route based configuration wireless sensor network designed in a laboratory setting. Packet data congestion in network was identified by the researchers to be addressed. Openstat population-data of Philippine Statistic Authority were used during the simulation (http://openstat.psa.gov.ph/). Transmission delay of packet data from one route to another route was measured through response duration and return time-lapse. Researchers present an experimental evaluation of Dynamic Resource Routing (DRS), Self Selective Routing (SSR) and Ad-hoc Distance Vector Routing (ADVR). Experiments were evaluated to determine the lowest latency value of the returning node from a route going to next route. Authors compare different parameters such as number of nodes, source nodes, time interval, distance (meters 2), stop-time, packet size and average number of wireless sensor users. Improvements to lessen the delay of transmission of packet data from devices passing through a multiple network route were listed. This research identifies the comparison of number of routes required to the number of users and the size of the packet data in a particular area in average. We proved that the number of source nodes (users) should have average number of route that correspond the lowering of network latency.

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Network tomography application in mobile ad-hoc network using stitching algorithm

Cited by 7 publications

References 25 publications

A Distance-Based Data-Mule Scheduling Technique for Lesser Nodal Delay in Wireless Sensor Network

A Distance-Based Data-Mule Scheduling Technique for Lesser Nodal Delay in Wireless Sensor Network

An Adaptive Technique for Estimating Traffic Intensities for a Network in Random Markovian Routing

A Case Study of Wireless Sensor Network Latency in the Philippines for Enhancement of Packet-data Transmission

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