Efficiency Parameters for Node Indexing to Get Energy Efficient and Bandwidth Aware Path

Author:

Sharma Anupama1,Bansal Abhay1,Rishiwal Vinay2

Affiliation:

1. School of Communication, Amity University, Noida, Uttar Pradesh, India

2. Department Of Computer Science and Information Technology, MJP Rohilkhand University, Bareilly, Uttar Pradesh, India

Abstract

Background: MANET is a constrained environment having limited energy, restricted bandwidth, and unstable wireless connectivity, etc. It creates a high demand to design an efficient QoS routing protocol having a multi-criteria metric to make efficient routing decisions. Aims: This work is to enhance end-to-end network throughput. To achieve our aim we optimized MBQA-OLSR, which is an enhancement of MP-OLSR. MP-OLSR is enhancement of OLSR, which is a prominent proactive routing protocol. Main advantageous concept in OLSR is selection of MPR nodes that minimize excessive transmission of control packets. Selected MPR nodes should carry enough battery to increase network life time. Packet loss is another issue on wirelesThe main aim of QoS based routing protocol EB-OLSR (Energy efficient and Bandwidth aware Optimized Link State Routing) is to achieve enhanced aggregate network throughput. Which is acquired by selecting QoS qualified efficient nodes to transmit data packets. EB-OLSR set out analogous efficient mobile nodes for routing by applying newly defined multi-criteria metric EPNI (Efficiency Parameters for Node Indexing) which estimates the node’s efficiency index on the basis of four QoS parameters that are unconsumed power, slothful period, queue length and residual bandwidth.s links, it is due to poor quality unstable links; hence link quality is another work of this paper. Method: We obtained a single node index for each mobile node through EPNI metric based on residual battery, node idle time, packet queue length and residual bandwidth. Result: EB-OLSR produced aggregate network throughput enhancement of 574 bits per second in comparison of MP-OLSR and 390.66 bits per second in comparison to MBQA-OLSR. Average End-to-End Delay for EB-OLSR is 0.41, 0.16 times less and Packet Delivery Ratio enhances 30.74%, 9.5% respectively. Conclusion: This paper evaluated network performance parameters of proposeExperimental results proved that the EB-OLSR is an energy-efficient and bandwidth aware optimized link-state routing protocol, which successfully meets the main aim of this study i.e. throughput enhancement of mobile ad-hoc network. The EPNI metric is the major strength of the work which is used to get a single-valued weighted sum of multiple criteria.d routing protocol EB-OLSR that are packet delivery ratio average end to end delay and throughput. It has been observed from simulation experiments that EB-OLSR outer perform other compared similar kind of routing protocols at different network sizes. In proposed work, EPNI metric is defined to get weighted sum of multiple criteria and it is considered to make decision for routing data packets. Single valued multiple criteria evaluation helps to simplify relationship and priority between multiple criteria and combined them in a single node index. Hence along with optimized throughput control overheads are also minimized. EB-OLSR is energy efficient and bandwidth aware optimized link state routing protocol, which successfully meet the main aim of this study i.e. throughput enhancement of mobile ad-hoc network. Aggregate throughput enhances 574 bits per second in comparison of MP-OLSR and 390.66 bits per second in comparison of MBQA-OLSR. Average End-to-End Delay for EB-OLSR is 0.41, 0.16 times less in comparison of MP-OLSR, MBQA-OLSR respectively. Packet delivery ratio enhances 30.74% in comparison of MP-OLSR and 9.5% in comparison of MBQA-OLSR. Performance analyzes at varying traffic load shows only slighter improvement. In this study, we put fixed weights to every considered metric according to general priority. In future, we will study the priorities of metrics in different network scenarios like at varying node speeds, at different mobility patterns, etc to see whether priorities of metrics changes in different scenario or not.

Publisher

Bentham Science Publishers Ltd.

Subject

Electrical and Electronic Engineering,Control and Optimization,Computer Networks and Communications,Computer Science Applications

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