High availability IEEE 1588 nodes over IEEE 802.1aq Shortest Path Bridging networks

IEEE 1588 applied in the environment of high availability LANs

2007 IEEE International Symposium on Precision Clock Synchronization for Measurement, Control and Communication ◽

10.1109/ispcs.2007.4383781 ◽

2007 ◽

Cited By ~ 8

Author(s):

Sven Meier ◽

Hans Weibel

Keyword(s):

High Availability ◽

Ieee 1588

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HALR: A TCP Enhancement Scheme Using Local Caching in High-Availability Cluster

IEICE Transactions on Communications ◽

10.1587/transcom.e92.b.26 ◽

2009 ◽

Vol E92-B (1) ◽

pp. 26-33

Author(s):

Yi-Hsuan FENG ◽

Nen-Fu HUANG ◽

Yen-Min WU

Keyword(s):

High Availability

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The Expected Distance of Shortest Path-Based In-Trees along Spanning Root Mobility on Grid Graph

IEICE Transactions on Fundamentals of Electronics Communications and Computer Sciences ◽

10.1587/transfun.2019kep0003 ◽

2020 ◽

Vol E103.A (9) ◽

pp. 1071-1077

Author(s):

Yoshihiro KANEKO

Keyword(s):

Shortest Path ◽

Grid Graph

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The Map-Based Shortest Route Selection by Using Ant Colony Optimization Algorithm

Indonesian Journal of Artificial Intelligence and Data Mining ◽

10.24014/ijaidm.v1i1.4600 ◽

2018 ◽

Vol 1 (1) ◽

pp. 15

Author(s):

Achmad Fanany Onnilita Gaffar ◽

Agusma Wajiansyah ◽

Supriadi Supriadi

Keyword(s):

Ant Colony Optimization ◽

Shortest Path ◽

Optimization Algorithm ◽

Optimization Problems ◽

Google Earth ◽

Ant Colony ◽

Food Sources ◽

Shortest Route ◽

Study Results ◽

Destination Point

The shortest path problem is one of the optimization problems where the optimization value is a distance. In general, solving the problem of the shortest route search can be done using two methods, namely conventional methods and heuristic methods. The Ant Colony Optimization (ACO) is the one of the optimization algorithm based on heuristic method. ACO is adopted from the behavior of ant colonies which naturally able to find the shortest route on the way from the nest to the food sources. In this study, ACO is used to determine the shortest route from Bumi Senyiur Hotel (origin point) to East Kalimantan Governor's Office (destination point). The selection of the origin and destination points is based on a large number of possible major roads connecting the two points. The data source used is the base map of Samarinda City which is cropped on certain coordinates by using Google Earth app which covers the origin and destination points selected. The data pre-processing is performed on the base map image of the acquisition results to obtain its numerical data. ACO is implemented on the data to obtain the shortest path from the origin and destination point that has been determined. From the study results obtained that the number of ants that have been used has an effect on the increase of possible solutions to optimal. The number of tours effect on the number of pheromones that are left on each edge passed ant. With the global pheromone update on each tour then there is a possibility that the path that has passed the ant will run out of pheromone at the end of the tour. This causes the possibility of inconsistent results when using the number of ants smaller than the number of tours.

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One dynamic shortest path algorithm in a traffic network based on a genetic algorithm

Advances in Civil, Transportation and Environmental Engineering ◽

10.2495/ctee120281 ◽

2013 ◽

Author(s):

Shuijian Zhang

Keyword(s):

Genetic Algorithm ◽

Shortest Path ◽

Traffic Network ◽

Shortest Path Algorithm

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Finding Shortest Path Basing on Dijkstra's Algorithm For Baghdad Universities by using Geographic Information System Applications

10.25212/icoit17.030 ◽

2017 ◽

Author(s):

Roaa Ebada Saeed ◽

Amer Saleem Elameer ◽

Rafah Shahab Alhamdani

Keyword(s):

Information System ◽

Geographic Information System ◽

Shortest Path ◽

Geographic Information ◽

Dijkstra’S Algorithm ◽

Dijkstra's Algorithm

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Clustering Server Pada Cloud Computing Berbasis Proxmox VE Menggunakan Metode High Availability

JOINTECS (Journal of Information Technology and Computer Science) ◽

10.31328/jointecs.v3i1.498 ◽

2018 ◽

Vol 3 (1) ◽

Author(s):

Linda Apriliana ◽

Ucuk Darusala Darusalam ◽

Novi Dian Nathasia

Keyword(s):

Cloud Computing ◽

File System ◽

High Availability ◽

Client Server ◽

Network File System

Layanan dan data teknologi Cloud Computing tersimpan pada server, hal ini menjadikan faktor pentingnya server sebagai pendukung ketersediaan layanan. Semakin banyak pengguna yang mengakses layanan tersebut akan mengakibatkan beban kinerja mesin server menjadi lebih berat dan kurang optimal, karena layanan harus bekerja menyediakan data terus-menerus yang dapat diakses kapanpun oleh penggunanya melalui jaringan terkoneksi. Perangkat keras server memiliki masa performa kinerja. Hal serupa dengan perangkat lunak yang dapat mengalami crash. Dengan fungsi server yang memberikan layanan kepada client, server dituntut untuk memiliki tingkat availability yang tinggi. Hal tersebut memungkinkan mesin server mengalami down. Server juga harus dimatikan untuk keperluan pemeliharaan. Penelitian bertujuan ini membangun Clustering Server yang dapat bekerja bersama yang seolah merupakan sistem tunggal diatas lingkungan virtual. Hal ini merupakan solusi untuk mengatasi permasalahan tersebut. Pada penelitian ini penulis menggunakan server virtualisasi proxmox, FreeNAS sebagai server NAS dan DRBD untuk pendukung ketersediaan layanan tinggi dalam lingkup HA, sinkronisasi data dalam High Availability (HA) yang dapat melakukan mirroring sistem kemesin lain. Dengan diterapkannya metode HA dan sinkronasi DRBD serta penggunaan NFS (Network File System) pada sistem cluster didapatkan hasil rata-rata waktu migrasi sebesar 9.7(s) pada node1 menuju node2, 3.7(s) node2 menuju node3, dan 3(s) pada node3 menuju node1. Didaptkan juga waktu downtime yang lebih sedikit yaitu sebesar 0.58 ms pada node1, 0.02 ms pada node2, dan 0.02 ms pada node3.

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