An energy aware Genetic Algorithm Multipath Distance Vector Protocol for efficient routing

Seetaram, J; Kumar, Priyatam

doi:10.1109/wispnet.2016.7566488

Cited by 12 publications

(7 citation statements)

References 8 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Network Life by improving the consumption of energy Networks life has been increased. This protocol delays the lower average end by increasing the network life by consuming less energy.Seetaram, J [10], has designed the EA-AOMDV (Energy AWDV) protocol, which modifies AOMDV. Route has been selected based on node residual energy in the modified protocol.…”

Section: Literature Surveymentioning

confidence: 99%

“…Remove routes with more energy-driven reliable routes and zone technology. In the fig 6 (c) packet distribution ratio, in different simulation times (10,15,20, 25 and 30 seconds), the routing protocol is displayed by ZBLE, AODV and AOMDV. The ZBLE protocol lowers high energy, strong and zone-based routing packet traffic, increasing data traffic.…”

Section: Packet Delivery Ratiomentioning

confidence: 99%

See 1 more Smart Citation

ZBLE: Zone Based Leader Selection Protocol

Sahu¹,

Sharma²,

Rizvi³

2019

IJWMT

View full text Add to dashboard Cite

Various wireless mobile nodes are simultaneously a network that does not depend on any central administration system. This kind of network is called Mobile Ad Hoc Network (MANET). Due to the nodes dependent on the battery in MANET, energy consumption has become a major problem. Because of the mobility of the nodes in the network, the nodes rapidly change their positions, causing the battery to end very quickly, thereby reducing the life of such a network. The main objective of this paper is to reduce energy consumption and increase the life of the network by modifying the AOMDV protocol using zone-based technology. Keeping this objective in mind, a zone-based protocol was developed which has been addressed in the name of Zone Based Leader Selection Protocol (ZBLE). This proposed protocol uses zone-based technology to select the path based on high energy and high power. For the data forward, selecting the Leader node in each zone, the best path is chosen based on the energy level of the node and the strength of the probe. The proposed protocol has been evaluated using Network Simulator version 2.35. Comparison of ZBLE, protocols the most popular protocols are from AODV and AOMDV. With the help of simulation results, we have used service parameters such as packet distribution ratio, energy consumption, network lifetime and throughput to tell the quality of the proposed protocol.

show abstract

Section: Literature Surveymentioning

confidence: 99%

Section: Packet Delivery Ratiomentioning

confidence: 99%

ZBLE: Zone Based Leader Selection Protocol

Sahu¹,

Sharma²,

Rizvi³

2019

IJWMT

View full text Add to dashboard Cite

show abstract

“…Salah satu tipe di dalam evolutionary algorithm menggunakan pedoman seleksi alam untuk menemukan suatu solusi optimal yang biasa dikenal dengan Algoritma Genetika (Seetaram and Kumar, 2016). Algoritma Genetika menggunakan proses perubahan setiap individu sehingga mendapatkan hasil yang mendekati optimal (Chen et al, 2016a).…”

Section: Algoritma Genetikaunclassified

Optimasi Derajat Keanggotaan Fuzzy Tsukamoto Menggunakan Algoritma Genetika Untuk Diagnosis Penyakit Sapi Potong

Kurnianingtyas

Mahmudy

Widodo

2017

JTIIK

View full text Add to dashboard Cite

AbstrakSistem inferensi fuzzy bisa digunakan untuk diagnosis penyakit pada sapi potong. Untuk mendapatkan akurasi yang tinggi maka batasan fungsi keanggotaan fuzzy perlu ditentukan secara tepat. Penggunaan metode logika fuzzy untuk memperoleh hasil diagnosis penyakit pada sapi potong sesuai pakar berdasarkan batasan gejala penyakit dan aturan-aturan yang diperoleh dari pakar. Batasan tersebut bisa diperbaiki menggunakan Algoritma Genetika untuk mendapatkan akurasi yang lebih baik. Pengujian yang dilakukan pada 51 data dari beberapa gejala penyakit menghasilkan akurasi sebesar 98,04% dengan menggunakan parameter genetika terbaik antara lain ukuran populasi sebesar 80, ukuran generasi sebesar 15, nilai Crossover rate (Cr) sebesar 0,9, dan nilai Mutation rate (Mr) sebesar 0,06. Akurasi tersebut mengalami peningkatan sebesar 3,54% sesudah dilakukannya optimasi pada metode logika fuzzy.

show abstract

“…Pada tabel Average End to End Delay in second, metode GA menurun sebesar 11,86%, 20,16%, 33,87%, dan 15,71% jika dibandingkan dengan metode AOMDV dengan 25, 50, 75, dan 100 jumlah node. Selanjutnya, metode GA berkurang pada tabel Average Number of hops to sink sebesar 10,09%, 0,86%, 10,72%, dan 14,62% jika dibandingkan dengan metode AOMDV dengan 25, 50, 75, dan 100 jumlah node [9].…”

Section: Kata Kunci-metropolitan Mesh Network (Mmn) Optimasiunclassified

Optimasi Routing pada Metropolitan Mesh Network Menggunakan Adaptive Mutation Genetic Algorithm

Lestandy¹,

Pramono²,

Aswin³

2017

Jurnal Nasional Teknik Elektro dan Teknologi Informasi (JNTETI)

View full text Add to dashboard Cite

Abstract-In dynamic and wide networks, such as Metropolitan Mesh Network (MMN), routing becomes very complex because a packet can be blocked before it reaches its destination. In addition, users can also log in or log out from network topology. Therefore, a good routing algorithm, which is able to reduce time in network update process or when there is an error in the network, are required. Routing problems can be represented as the shortest path problem to facilitate completion. In this paper, a routing algorithm optimization using Adaptive Mutation Genetic Algorithm (AMGA) on MMN is presented by determining a probability of 0.000005782 at the beginning, with crossover probability of 0.000847, to reduce or avoid premature convergence.Intisari-Pada jaringan dinamis dan sangat besar seperti Metropolitan Mesh Network (MMN), routing menjadi sangat kompleks karena banyak potensi terhalangnya suatu paket di tengah jalan, sebelum mencapai tujuannya. Selain itu, pengguna pun dapat masuk dan keluar dari topologi jaringan. Oleh karena itu, dibutuhkan algoritme routing yang baik dan mampu menekan waktu dalam update jaringan atau jika terjadi kesalahan dalam jaringan. Permasalahan routing dapat direpresentasikan sebagai masalah jalur terpendek untuk memudahkan penyelesaiannya. Pada makalah ini dihasilkan bahwa Adaptive Mutation Genetic Algorithm (AMGA) mampu mengoptimalkan routing pada MMN dengan menentukan probabilitas mutasi di awal sebesar 0,000005782 dan probabiltas crossover sebesar 0,000847, sehingga mampu mengurangi atau menghindari adanya premature convergence.

show abstract

An energy aware Genetic Algorithm Multipath Distance Vector Protocol for efficient routing

Cited by 12 publications

References 8 publications

ZBLE: Zone Based Leader Selection Protocol

ZBLE: Zone Based Leader Selection Protocol

Optimasi Derajat Keanggotaan Fuzzy Tsukamoto Menggunakan Algoritma Genetika Untuk Diagnosis Penyakit Sapi Potong

Optimasi Routing pada Metropolitan Mesh Network Menggunakan Adaptive Mutation Genetic Algorithm

Contact Info

Product

Resources

About