Quality of Service Enhancement of Mobile Adhoc Networks Using Priority Aware Mechanism in AODV Protocol

Jayabarathan, Jayson K.; Sivanantharaja, A.; Robinson, S.

doi:10.1007/s11277-017-4453-3

Cited by 8 publications

(4 citation statements)

References 13 publications

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“…A secure and temperature-aware routing protocol for WBSN, presented in [7], integrates the security primitive with thermal-aware routing to avoid hotspot nodes in the selected routes. Similarly, a priority-aware, distance vector routing protocol [15] uses hop-count with the transmission rate as a route selection metric. Most of the routing protocols consider the intra-BAN communication to broadcast data to the sink node by using single-hop and multi-hop communication in a star or mesh topology.…”

Section: Related Workmentioning

confidence: 99%

MIQoS-RP: Multi-Constraint Intra-BAN, QoS-Aware Routing Protocol for Wireless Body Sensor Networks

et al. 2020

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Wireless Body Sensor Networks (WBSNs) are becoming increasing popular in a number of healthcare applications. A particular requirement of WBSNs in a healthcare system is the transmission of time-sensitive and critical data, captured by heterogeneous biosensors, to a base station while considering the constraints of reliability, throughput, delay and link quality. However, the simultaneous communication among various biosensors also raises the possibility of congestion on nodes or transmission links. Consequently, the likelihood of a number of untoward situations increases, such as disruption (high delays), packet losses, retransmissions, bandwidth exhaustion, and insufficient buffer space. The significant level of interference in the network leads to a higher number of collisions and retransmissions. The selection of an optimized route to cope with these issues and satisfy the QoS requirements of a WBSN has not been well-studied in the relevant literature. In this regard, we propose a multi-constraint, Intra-BAN, QoS-Aware Routing Protocol (referred to as MIQoS-RP) which introduces an improved, multi-facet routing metric to optimize the route selection while satisfying the aforementioned constraints. The performance of the proposed protocol is evaluated in terms of average end-to-end delay, throughput and packet drop ratio. The comparison of MIQoS-RP with the existing routing protocols demonstrates its efficacy in terms of the selected criteria. The results show that the MIQoS-RP achieves improved throughput by 22%, average end-to-end delay by 29% and packet drop ratio performance by 41% as compares to existing schemes.

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Section: Related Workmentioning

confidence: 99%

MIQoS-RP: Multi-Constraint Intra-BAN, QoS-Aware Routing Protocol for Wireless Body Sensor Networks

et al. 2020

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“…The network layer based priority algorithms are presented in [11], [18], which distinguished the various traffic according to the type of the sensor nodes. Similarly, the Priority-Aware AODV (PA-AODV) protocol is presented in [19] and a Data Privacy based Pearson Correlation Coefficient (DP-PCC) is presented in [20]. Both of these schemes assign priorities according to the data rates.…”

Section: Related Workmentioning

confidence: 99%

LLTP-QoS: Low Latency Traffic Prioritization and QoS-Aware Routing in Wireless Body Sensor Networks

et al. 2019

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Wireless Body Sensor Network (WBSN) is deployed in delay-sensitive application scenarios where providing Quality-of-Service (QoS) is utmost important. The QoS-aware routing protocol not only discovers a route from source to destination but also satisfies QoS requirements in heavily loaded wireless networks. Emergency / critical data packets must reach the intended destination without incurring significant delays and fulfill multiconstrained demands (reliability, delay, Packet Delivery Ratio (PDR)) of heterogeneous applications. Congestion occurs in heavy traffic situation when the incoming traffic load exceeds the capacity of transmission link, buffer overflows, packet collision, channel contention. Consequently, it impacts QoS in terms of packet loss, end-to-end delay and PDR. Moreover, the selection of poor links/routes may have detrimental impacts of the performance of WBSN and there can be significant variations in throughput, delay, network lifetime, route stability performance. Majority of the existing priority-aware routing protocols proposed for Medium Access Control (MAC) layer to solve the slot allocation problem by which data packets are classified into different categories. However, less attention has been given to traffic prioritization at network layer for data categorization. Furthermore, optimized traffic prioritization has been overlooked, thereby increases the data redundancy, queue/link delay, data loss and decreases the reliability of the network, and it does not satisfy the QoS requirements of WBSN and affects the critical data to be delivered in a less privileged manner. This work proposes the Low Latency Traffic Prioritization scheme for QoS-aware routing (LLTP-QoS). The LLTP-QoS is designed to enhance the transmission of critical data in a privileged manner (reliability) and avoids the end-to-end delay. The performance of proposed scheme is evaluated in terms of throughput, average end-to-end delay, PDR, normalized routing load, network lifetime through extensive simulations using Network Simulator-2 (NS2). The simulation results verified improved performance of proposed LLTP-QoS scheme as compared to existing routing protocols. INDEX TERMS Wireless body sensor networks, physiological data, QoS, data traffic, priority queue, packet delivery ratio, latency.

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“…The routing approach is categorized based on three types, that is, proactive routing protocols, reactive routing (on-demand) protocols, and hybrid routing protocols. [14][15][16] DSDV was a proactive protocol, in which the nodes in this protocol follows the table-based pre-established routes. 17,18 For route construction and maintenance, the overhead caused will possibly worsen the performance, reduce the scalability, and a lot of memory will be consumed by the routing table when the size of the network grows.…”

Section: Introductionmentioning

confidence: 99%

“…Routing protocols that are based on topology rely on the network's current topology, which is called table‐based routing. The routing approach is categorized based on three types, that is, proactive routing protocols, reactive routing (on‐demand) protocols, and hybrid routing protocols 14–16 . DSDV was a proactive protocol, in which the nodes in this protocol follows the table‐based pre‐established routes 17,18 .…”

Section: Introductionmentioning

confidence: 99%

Geographic routing with hybrid firefly algorithm and galactic swarm optimization for efficient ‘void’ handling in mobile ad hoc networks

Kaliyamurthi

Anandhakumar

2020

Int J Communication

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Summary Geographic routing in mobile ad hoc network (MANET) has gained much attention even though it fails to find a route when a node meets a void zone (hole). Therefore, an efficient approach is required to avoid the void issues and to effectively transfer the data packets if a path is available between the source and destination nodes. For such, a hybrid evolutionary algorithm is introduced with geographical routing protocol (GRP) for avoiding the void, which selects the shortest route for routing from the source to the destination by combining firefly (FF) algorithm and galactic swarm optimization (HFFGSO). This proposed algorithm exploits the strengths of both the FF algorithm and galactic swarm mechanisms. In this paper, the cross‐layer design approach is implemented, which contains data link and network layer. The proposed hybrid FFGSO‐GRP algorithm improves the routing process within these layers. The implementation process for this proposed technique is carried out in NS2 simulator. From the simulation results, it is observed that our hybrid protocol when compared with the existing approaches proves its significance in terms of packet delivery ratio (PDR), delay, throughput, energy efficiency, power consumption, routing overhead and hop count.

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Quality of Service Enhancement of Mobile Adhoc Networks Using Priority Aware Mechanism in AODV Protocol

Cited by 8 publications

References 13 publications

MIQoS-RP: Multi-Constraint Intra-BAN, QoS-Aware Routing Protocol for Wireless Body Sensor Networks

MIQoS-RP: Multi-Constraint Intra-BAN, QoS-Aware Routing Protocol for Wireless Body Sensor Networks

LLTP-QoS: Low Latency Traffic Prioritization and QoS-Aware Routing in Wireless Body Sensor Networks

Geographic routing with hybrid firefly algorithm and galactic swarm optimization for efficient ‘void’ handling in mobile ad hoc networks

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