Latency optimization through routing-aware time scheduling protocols for wireless sensor networks

Louail, Lemia; Felea, Violeta

doi:10.1016/j.compeleceng.2016.06.003

Cited by 10 publications

(5 citation statements)

References 6 publications

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“…Several techniques have been developed to reduce nodal delays, including the use of low latency approximation that increases compression performance at lower computational cost and latency [1]. Scheduling and rescheduling in wireless sensor network are controlled by temporal spatial decision of network layers [2] [3]. In extreme cases, nodal delays in packet transmission leads to general connection failures in wireless sensor networks [4].…”

Section: Introductionmentioning

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: Introductionmentioning

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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“…Nowadays, there are various attacks affecting the WSN, these attacks are carried out by invades on many nodes. Here, these attacks are noted that disrupting the secure routing process, that is, Sybil, spoofing, black hole, and denial of service (DoS) 6,7 . Various researchers have focused on establishing various secure routing protocols to secure the WSN.…”

Section: Introductionmentioning

confidence: 99%

“…Here, these attacks are noted that disrupting the secure routing process, that is, Sybil, spoofing, black hole, and denial of service (DoS). 6,7 Various researchers have focused on establishing various secure routing protocols to secure the WSN. The EC problem exists in WSN during the malicious activities involvement at the node, 8,9 because the energy in the sensor can be seen restricting the dangerous functions of the node.…”

Section: Introductionmentioning

confidence: 99%

Dolphin echolocation optimized sailfish algorithm for energy efficient and secured routing based on trust management in ZigBee wireless sensor network

Kumar

Babu

2022

Trans Emerging Tel Tech

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Security is the vital phenomenon of wireless sensor network (WSN) to preserve the energy. Traditional techniques does not concern the security of routing purpose, it has limitation like low energy resource, unsecure communication channel. In this article, a dolphin echolocation optimized sailfish (DESF) algorithm for energy efficient (EE) and secured routing based on trust management in ZigBee WSN is proposed. The proposed method is combination of enhanced shortcut tree routing based dolphin echolocation sailfish (EOSTR) and DESF, hence it is called EOSTR-DESF. Here, hybrid DESF with enhanced routing technique is used to select the optimal route. The proposed approach is implemented in NS2 and the performance of the proposed collaborative trust and tree routing based on DESF in ZigBee is compared with the existing approaches like particle swarm optimization-ant colony optimization, firefly algorithm-Hirschberg Sinclair, and whale optimization algorithm-simulated annealing algorithm. Moreover, the performance is analyzed with metrics like delay, packet delivery ratio, energy consumption, throughput, and residual energy. The simulation results demonstrate that the proposed method is more efficient with varying nodes of 33.25%, 20.17%, 8.04% for different data transfer rate of 31.36%, 15.62%, 9.10%.

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“…An adhoc network that is deployed consists of small weighted sensor nodes in a physical environment with a sensor base in which the sensor nodes send all data collected. Wireless sensor network communications are temporal controlled decisions through a network layers [5]. In wireless communication, latency is one of the major concerns that exist in provisioning data centers which are geographically distributed [6].…”

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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Latency optimization through routing-aware time scheduling protocols for wireless sensor networks

Cited by 10 publications

References 6 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

Dolphin echolocation optimized sailfish algorithm for energy efficient and secured routing based on trust management in ZigBee wireless sensor network

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

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