Interference-fault free transmission schedule in tree-structured WSN

Begum, Beneyaz A.; Nandury, Satyanarayana V.

doi:10.1109/icacci.2016.7732069

Cited by 5 publications

(10 citation statements)

References 12 publications

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“…This leads to propagation of corrupt signals across the network. To this end, Beneyaz et al [21][22][23] have developed algorithms to determine Interference-Fault Free Transmission (IFFT) schedules. The algorithms attempt to accomplish IFFT by (a) identifying nodes whose transmissions can potentially interfere with other ongoing transmissions of neighbouring nodes, and (b) mapping interference effect of each transmitting node on other on-going transmissions in the network.…”

Section: Background Literaturementioning

confidence: 99%

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Component Based Self-Healing Approach for Fault-Tolerant Data Aggregation in WSN

Begum

Nandury

2022

IEEE Access

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Node faults in WSNs are often attributed to battery energy drain outs. While data aggregation is widely acknowledged as an energy conservation tool; the aggregator nodes are susceptible to battery energy drain out faults. When an aggregator/ intermediary node in a data aggregation tree fails, the child nodes of the faulty node get detached from the aggregation tree and form disconnected nodes, termed as Affected Nodes (ANs) and/or subtrees. To tolerate such faults, we use the concepts of component-based graph theory and consider the subtrees as components that need to be connected back to the root-component tree. Based on this, we develop two component based self-healing fault-tolerant algorithms SCR and SCR-DTRA, that exploit the inherent redundancy in WSNs to determine alternate paths from the affected components to the root node. Unlike most other approaches, the hallmark of the component-based algorithms is that they preserve precedence relations in the data aggregation hierarchy. The results of our simulations show that the two algorithms succeed in the recovery of more than 90% of ANs and subtrees affected due to faults. In terms of longevity, the two algorithms, last more than twice the number of rounds compared to other algorithms used for comparison.

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Section: Background Literaturementioning

confidence: 99%

“…Therefore, we implement the algorithms on the initial BFS tree generated, instead of constructing a more efficient data aggregation tree. Under this premise we consider the initial BFS tree itself to be the data aggregation tree 𝒜 and proceed toward determining a data aggregation schedule for 𝒜 [21,22].…”

Section: A Construction Of Aggregation Treementioning

confidence: 99%

Component Based Self-Healing Approach for Fault-Tolerant Data Aggregation in WSN

Begum

Nandury

2022

IEEE Access

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“…Interference-Fault Free Transmission Tree (IFFTT) algorithm was proposed in [6] to achieve a damage free time slot-based communication for each connection in data collection hierarchy, and logically indicate the scheme was best and absolute. Experimental results detected an error occurred in packet transmission.…”

Section: Related Workmentioning

confidence: 99%

Improving The Performances of WSN Using Data Scheduler and Hierarchical Tree

Jayamma¹

2021

J Comput Sci Intell Technol

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Users of data-intensive implementation needs intelligent services and schedulers that will provide models and strategies to optimize their data transfer jobs. Normally sensor nodes are connected to consecutive sensor nodes depending on frequent transmission. To enhance end-to-end data flow parallelism for throughput optimization in high speed WSNs. The major objective is to maximize the WSNs throughput, minimizing the model overhead, avoiding disputation among users and using minimum number of end-system resources. Data packets are broadcasted from sender node to target node. Though, all nodes operate concurrently in various communications, the analysis shows that more packet latencies are occurred and priority-based transmission tasks are performed. Then the proposed Bearing parallelism-based Data Scheduler (BPDS) is used for data scheduling to enhance the end-to-end throughput input parameter. Sensor nodes are fast working node, it verifies each and every node before allocating packet transmission for that node. Busy resources are monitored to inform the nodes that are in processing, based on the schedule it allocates various paths to particular node and monitors the node capacity. Sampling algorithm supports for fixing threshold value, based on the values, they are further allocated to communicate between channels. It assigns the routing path with minimum resources and reduces end to end delay, to improve throughput, and network lifetime.

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“…Nevertheless, this frequency is shared with Wi-Fi/Bluetooth devices, microwave ovens, among others. Therefore, the nodes regularly suffer from interference generated by these devices, which leads to degrading the communication quality [174,175,176].…”

Section: Chapter 5 Interference Characterization and Identification F...mentioning

confidence: 99%

“…The presence of interference in the shared wireless medium degrades the communication quality [174,175,176]. Hence, in this Section, we present the behavior of an IEEE 802.15.4-compliant link under the influence of a source of interference.…”

Section: Link Quality Measurementsmentioning

confidence: 99%

A self-healing framework for WSNs : detection and recovery of faulty sensor nodes and unreliable wireless links

Salas¹

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Proponemos un marco conceptual para acoplar técnicas de auto-organización y técnicas de autocuración. A este marco se le llama de auto-curación y es capaz de hacer frente a enlaces inalámbricos inestables y nodos defectuosos. Dividimos el marco en dos componentes principales: la auto-organización y auto-curación. En el componente de auto-organización, nosotros construimos una topología de árbol que determine las rutas hacia el sumidero. En el componente de auto-curación, la topología del árbol se adapta a ambos tipos de fallas siguiendo tres pasos: recopilación de información, detección de fallas, y la recuperación de fallos. En el paso de recopilación de información, los nodos determinan el estado actual de la red mediante la recopilación de información de la capa MAC. En el paso de detección de fallas, los nodos analizan la información recopilada y detectan nodos/enlaces defectuosos. En el paso de recuperación de fallos, los nodos recuperan la topología del árbol mediante la sustitución de componentes defectuosos con redundantes (es decir, componentes de respaldo). Este marco permite una red con resiliencia que se recupera sin agotar los recursos de la red.

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Interference-fault free transmission schedule in tree-structured WSN

Cited by 5 publications

References 12 publications

Component Based Self-Healing Approach for Fault-Tolerant Data Aggregation in WSN

Component Based Self-Healing Approach for Fault-Tolerant Data Aggregation in WSN

Improving The Performances of WSN Using Data Scheduler and Hierarchical Tree

A self-healing framework for WSNs : detection and recovery of faulty sensor nodes and unreliable wireless links

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