Survivable Path Routing in WSN for IoT applications

Elappila, Manu; Chinara, Suchismita; Parhi, Dayal R.

doi:10.1016/j.pmcj.2017.11.004

Cited by 93 publications

(43 citation statements)

References 19 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…It analyzed two main points namely the selection of the route using the routing time algorithm (LRTA) and the transfer of data using the grouping procedure. The authors [23] discussed a fault-tolerant routing protocol approach for the forest fire detection that investigates network lifetime and network response time to an event.…”

Section: Related Workmentioning

confidence: 99%

Multi-Level Multi-Constraint Multi-Priority Fuzzy Sensor Routing (M3L-C-PFSR)

Agarkhed¹,

Kadrolli²,

Patil³

2019

IJITEE

View full text Add to dashboard Cite

In the field of Wireless Sensor Network (WSN), real time applications, the interesting research emerged in the field of QoS routing. Networks must address resource constraints although providing an accurate guarantee of quality of service (PDR, throughput, energy, End-to-End delay).This document presents the routing protocol compatible with QoS, namely [M3 L-C-PFSR] Multilevel, Multi constraint Multi Priority Fuzzy Sensor Routing Protocol which gives priority for important packets of important applications and also ensures the PDR, delay and throughput. Applying a scheme of multi level fuzzy based efficient buffer management to limit packet loss due to overflow. It supports lower throughput for packets which are lower in priority and higher throughput will be given for real-time prioritized packets which are assigned privileged higher priority, thus reducing end-to-end delay. The proposed work performance will be appraised [M3 L-C-PFSR] in NS2. The results of the simulation depicts that the proposed protocol [M3 L-C-PFSR] effectively minimizes the losses of critical packet, with different traffic conditions, ensuring the reliability and required delivery of data.

show abstract

Section: Related Workmentioning

confidence: 99%

Multi-Level Multi-Constraint Multi-Priority Fuzzy Sensor Routing (M3L-C-PFSR)

Agarkhed¹,

Kadrolli²,

Patil³

2019

IJITEE

View full text Add to dashboard Cite

show abstract

“…Some of the issues have been observed in the existing works of Sensors Routing in IoT. In paper [21] proposed an energy efficient technique for IoT applications which is based on three variables to find the best next hop in routing process. Provides the platform [22] to improve the energy efficiency of various smart gadgets and also introduces the genetic algorithm for clustering.…”

Section: Related Workmentioning

confidence: 99%

Energy Efficient Decision based Routing Technique using Fog Computing Paradigm

2019

IJITEE

View full text Add to dashboard Cite

In the era of new technologies, Fog computing becomes very popular in today’s scenario. Fog computing paradigm brings a concept that extends cloud computing to the edge and close proximity to the Internet of Things (IoT) network. The fundamental components of fog computing are fog nodes. Additionally, fog nodes are energy efficient nodes. Numerous fog nodes are deployed in the associated fields that will handle the Internet of Things (IoT) sensors computation. Meanwhile, the Internet of Things (IoT) faces challenges, among which energy efficiency is one of the most prominent or critical challenges in the current scenario. However, sensor devices are an energy constraintthatcreateshotspotduringtheroutingprocess.Forthis reason,tohandlesuchconstraints,thispaperpresentsaneffective hotspot mechanism using fog nodes that demonstrate the routing process and directed the sensors to choose the routing path as selected by the fog node. Moreover, fog node will act as a decision maker node and maintain the energy efficiency of sensors during the routing as fog nodes are energy efficient nodes. As it moves towards the emergency situation, the most appropriate and effective routing approach has been designed who maintain the energy level of sensors will be high during the routing process. The proposed routing technique could be better performance for the sake of efficient routing in terms of energy consumption and prolonging networklifetime.

show abstract

“…The particular area, where a certain number of sensors become faulted and cannot collect the interested data anymore, is called as a sensing hole [7]. In order to prevent a sensing hole occurred, various studies such as schemes of minimizing energy consumption by adjusting the active/idle states and energy efficient routing protocols have been conducted [8][9][10]. Although the energy limit of the sensor node can be reduced by various applications, it is impossible to solve the sensor node failure problem completely.…”

Section: Introductionmentioning

confidence: 99%

Energy-Efficient Wireless Hopping Sensor Relocation Based on Prediction of Terrain Conditions

2019

View full text Add to dashboard Cite

It is inevitable for data collection that IoT sensors are distributed to interested areas. However, not only the proper placement of sensors, but also the replacement of sensors that have run out of energy is very difficult. As a remedy, wireless charging systems for IoT sensors have been researched recently, but it is apparent that the availability of charging system is limited especially for IoT sensors scattered in rugged terrain. Thus, it is important that the sensor relocation models to recover sensing holes employ energy-efficient scheme. While there are various methods in the mobile model of wireless sensors, well-known wheel-based movements in rough areas are hard to achieve. Thus, research is ongoing in various areas of the hopping mobile model in which wireless sensors jump. Many past studies about hopping sensor relocation assume that all sensor nodes are aware of entire network information throughout the network. These assumptions do not fit well to the actual environment, and they are nothing but classical theoretical research. In addition, the physical environment (sand, mud, etc.) of the area in which the sensor is deployed can change from time to time. In this paper, we overcome the theoretical-based problems of the past researches and propose a new realistic hopping sensor relocation protocol considering terrain conditions. Since the status of obstacles around the sensing hole is unknown, the success rate of the hopping sensor relocation is used to predict the condition of the surrounding environment. Also, we are confident that our team is uniquely implementing OMNeT++ (Objective Modular Network Testbed in C++) simulation in the hopping sensor relocation protocol to reflect the actual communication environment. Simulations have been performed on various obstacles for performance evaluation and analysis, and we are confident that better energy efficiency with later appearance of sensing holes can be achieved compared to well-known relocation protocols.

show abstract

Survivable Path Routing in WSN for IoT applications

Cited by 93 publications

References 19 publications

Multi-Level Multi-Constraint Multi-Priority Fuzzy Sensor Routing (M3L-C-PFSR)

Multi-Level Multi-Constraint Multi-Priority Fuzzy Sensor Routing (M3L-C-PFSR)

Energy Efficient Decision based Routing Technique using Fog Computing Paradigm

Energy-Efficient Wireless Hopping Sensor Relocation Based on Prediction of Terrain Conditions

Contact Info

Product

Resources

About