Implementasi Load Balancing Web Server dengan Algoritma Dynamic Load Balancing berbasis Server pada Software Defined Network
Kata Kunci:
software defined network, dynamic load balancing, SDN, Load balancing, Random, Round-robbinAbstrak
Dibandingkan dengan jaringan secara tradisional cloud-computing menawarkan berbagai macam keuntungan seperti fleksibilitas dalam virtualisasi jaringan, mampu mengalokasikan kebutuhan berdasarkan kepentingan pengguna dan mengatasi masalah high usage. Salah satu perkembangan cloud-computing untuk membantu mengatasi alokasi kebutuhan pada jaringan yaitu menggunakan Load Balancing. Beberapa penelitian sebelumnya sudah menggunakan berbagai jenis algoritma dalam arsitektur jaringan SDN(software defined network) yaitu round robbin, shortest delay, random dan algoritma berbasis penggunaan CPU dengan hasil yang berbeda-beda. Untuk mengetahui beban yang diterima oleh server maka digunakan parameter nilai penggunaan CPU dan memori pada masing-masing server. Sistem ini bekerja menggunakan algoritma dynamic load balancing dengan memilih server mana yang memiliki nilai penggunaan memori dan cpu terendah dari setiap server guna untuk menentukan server mana yang akan menangani request dari client. Hasil dari penggunaan algoritma dynamic load balancing akan dibandingkan dengan hasil penggunaan dari algoritma random dan round-robbin dengan parameter nilai response time dan nilai troughput serta akan menggunakan skenario uji yang sama. Pada algoritma dynamic load balancing, server 3 memiliki penggunaan cpu dan memori lebih rendah yaitu 16,15% dibandingkan dengan penggunaan algoritma random dan round-robbin yaitu 19,77% dan 19,37%. Dan pada server 2 penggunaan cpu dan memori saat menggunakan algoritma dynamic load balancing bernilai lebih tinggi yaitu 7,45% jika dibandingkan dengan penggunaan algoritma random dan round-robbin yaitu dengan nilai 6,37% dan 6,41%. Pada algoritma dynamic load balancing, server 1 memiliki penggunaan cpu dan memori lebih tinggi yaitu 9,59% dibandingkan dengan penggunaan algoritma random dan round-robbin yaitu 9,52% dan 9,28%.
Referensi
Abdelaziz, A.A., Ahmed, E., Fong, A.T., Gani, A. and Imran, M., 2018. SDN-Based load balancing service for cloud servers. IEEE Communications Magazine, 56(8), pp.106–111. https://doi.org/10.1109/MCOM.2018.1701016.
Ahmed, H.G. and Ramalakshmi, R., 2018. Performance Analysis of Centralized and Distributed SDN Controllers for Load Balancing Application. Proceedings of the 2nd International Conference on Trends in Electronics and Informatics, ICOEI 2018, (Icoei), pp.758–764. https://doi.org/10.1109/ICOEI.2018.8553946.
Akella, A. V. and Xiong, K., 2014. Quality of service (QoS)-guaranteed network resource allocation via software defined networking (SDN). Proceedings - 2014 World Ubiquitous Science Congress: 2014 IEEE 12th International Conference on Dependable, Autonomic and Secure Computing, DASC 2014, pp.7–13. https://doi.org/10.1109/DASC.2014.11.
Alsaeedi, M., Mohamad, M.M. and Al-Roubaiey, A.A., 2019. Toward Adaptive and Scalable OpenFlow-SDN Flow Control: A Survey. IEEE Access, 7, pp.107346–107379. https://doi.org/10.1109/ACCESS.2019.2932422.
Aslam, F.A., Mohammed, H.N., Musab, J. and Munir, M., 2015. International Journal of Advanced Research in Computer Science Available Online at www.ijarcs.info Efficient Way Of Web Development Using Python And Flask. 6(2), pp.54–57.
Chindalia, U., Skanda, C., Chandrashekar, S. and Sharma, O., 2019. Real Time Application and CPU Utilisation Monitoring Tool. Proceedings of the 3rd International Conference on Electronics and Communication and Aerospace Technology, ICECA 2019, pp.1136–1140. https://doi.org/10.1109/ICECA.2019.8822069.
Fani, L., Ardy, I., Bhawiyuga, A. and Yahya, W., 2018. Implementasi Load Balancer Berdasarkan Server Status pada Arsitektur Software Defined Network ( SDN ). Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer (J-PTIIK), 2(5), pp.2135–2143.
Li, W. and Shi, H., 2009. Dynamic load balancing algorithm based on FCFS. 2009 4th International Conference on Innovative Computing, Information and Control, ICICIC 2009, pp.1528–1531. https://doi.org/10.1109/ICICIC.2009.182.
Lin, L. and Xu, Q., 2017. Load Balancing in SDN: A Survey. IEEE International Conference on Electronics Information and Emergency Communication (ICEIEC), pp.403–408.
Mosberger, D. and Jin, T., 1998. httperf - A tool for measuring web server performance. Performance Evaluation Review, 26(3), pp.31–37. https://doi.org/10.1145/306225.306235.
Prakash, S.W. and Deepalakshmi, P., 2017. Server-based Dynamic Load Balancing. 2017 International Conference on Networks and Advances in Computational Technologies, NetACT 2017, (July), pp.25–28. https://doi.org/10.1109/NETACT.2017.8076736.
Ronny, L., Negara, C., Yahya, W. and Primananda, R., 2018. Analisis Dan Implementasi Load Balancing Pada Web server Dengan Algoritme Shortest Delay Pada Software Defined Network. Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer (J-PTIIK) Universitas Brawijaya, 2(9), pp.2791–2797.
Shang, Z., Chen, W., Ma, Q. and Wu, B., 2013. Design and implementation of server cluster dynamic load balancing based on OpenFlow. 2013 International Joint Conference on Awareness Science and Technology and Ubi-Media Computing: Can We Realize Awareness via Ubi-Media?, iCAST 2013 and UMEDIA 2013, pp.691–696. https://doi.org/10.1109/ICAwST.2013.6765526.
Zakia, U. and Ben Yedder, H., 2017. Dynamic load balancing in SDN-based data center networks. 2017 8th IEEE Annual Information Technology, Electronics and Mobile Communication Conference, IEMCON 2017, pp.242–247. https://doi.org/10.1109/IEMCON.2017.8117206.
Zhong, H., Fang, Y. and Cui, J., 2018. Reprint of ‘LBBSRT: An efficient SDN load balancing scheme based on server response time’. Future Generation Computer Systems, [online] 80. https://doi.org/10.1016/j.future.2017.11.012.
Zhong, H., Lin, Q., Cui, J., Shi, R. and Liu, L., 2015. An Efficient SDN Load Balancing Scheme Based on Variance Analysis for Massive Mobile Users. Mobile Information Systems, 2015. https://doi.org/10.1155/2015/241732.
Abdelaziz, A.A., Ahmed, E., Fong, A.T., Gani, A. and Imran, M., 2018. SDN-Based load balancing service for cloud servers. IEEE Communications Magazine, 56(8), pp.106–111. https://doi.org/10.1109/MCOM.2018.1701016.
Ahmed, H.G. and Ramalakshmi, R., 2018. Performance Analysis of Centralized and Distributed SDN Controllers for Load Balancing Application. Proceedings of the 2nd International Conference on Trends in Electronics and Informatics, ICOEI 2018, (Icoei), pp.758–764. https://doi.org/10.1109/ICOEI.2018.8553946.
Akella, A. V. and Xiong, K., 2014. Quality of service (QoS)-guaranteed network resource allocation via software defined networking (SDN). Proceedings - 2014 World Ubiquitous Science Congress: 2014 IEEE 12th International Conference on Dependable, Autonomic and Secure Computing, DASC 2014, pp.7–13. https://doi.org/10.1109/DASC.2014.11.
Alsaeedi, M., Mohamad, M.M. and Al-Roubaiey, A.A., 2019. Toward Adaptive and Scalable OpenFlow-SDN Flow Control: A Survey. IEEE Access, 7, pp.107346–107379. https://doi.org/10.1109/ACCESS.2019.2932422.
Aslam, F.A., Mohammed, H.N., Musab, J. and Munir, M., 2015. International Journal of Advanced Research in Computer Science Available Online at www.ijarcs.info Efficient Way Of Web Development Using Python And Flask. 6(2), pp.54–57.
Chindalia, U., Skanda, C., Chandrashekar, S. and Sharma, O., 2019. Real Time Application and CPU Utilisation Monitoring Tool. Proceedings of the 3rd International Conference on Electronics and Communication and Aerospace Technology, ICECA 2019, pp.1136–1140. https://doi.org/10.1109/ICECA.2019.8822069.
Fani, L., Ardy, I., Bhawiyuga, A. and Yahya, W., 2018. Implementasi Load Balancer Berdasarkan Server Status pada Arsitektur Software Defined Network ( SDN ). Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer (J-PTIIK), 2(5), pp.2135–2143.
Li, W. and Shi, H., 2009. Dynamic load balancing algorithm based on FCFS. 2009 4th International Conference on Innovative Computing, Information and Control, ICICIC 2009, pp.1528–1531. https://doi.org/10.1109/ICICIC.2009.182.
Lin, L. and Xu, Q., 2017. Load Balancing in SDN: A Survey. IEEE International Conference on Electronics Information and Emergency Communication (ICEIEC), pp.403–408.
Mosberger, D. and Jin, T., 1998. httperf - A tool for measuring web server performance. Performance Evaluation Review, 26(3), pp.31–37. https://doi.org/10.1145/306225.306235.
Prakash, S.W. and Deepalakshmi, P., 2017. Server-based Dynamic Load Balancing. 2017 International Conference on Networks and Advances in Computational Technologies, NetACT 2017, (July), pp.25–28. https://doi.org/10.1109/NETACT.2017.8076736.
Ronny, L., Negara, C., Yahya, W. and Primananda, R., 2018. Analisis Dan Implementasi Load Balancing Pada Web server Dengan Algoritme Shortest Delay Pada Software Defined Network. Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer (J-PTIIK) Universitas Brawijaya, 2(9), pp.2791–2797.
Shang, Z., Chen, W., Ma, Q. and Wu, B., 2013. Design and implementation of server cluster dynamic load balancing based on OpenFlow. 2013 International Joint Conference on Awareness Science and Technology and Ubi-Media Computing: Can We Realize Awareness via Ubi-Media?, iCAST 2013 and UMEDIA 2013, pp.691–696. https://doi.org/10.1109/ICAwST.2013.6765526.
Zakia, U. and Ben Yedder, H., 2017. Dynamic load balancing in SDN-based data center networks. 2017 8th IEEE Annual Information Technology, Electronics and Mobile Communication Conference, IEMCON 2017, pp.242–247. https://doi.org/10.1109/IEMCON.2017.8117206.
Zhong, H., Fang, Y. and Cui, J., 2018. Reprint of ‘LBBSRT: An efficient SDN load balancing scheme based on server response time’. Future Generation Computer Systems, [online] 80. https://doi.org/10.1016/j.future.2017.11.012.
Zhong, H., Lin, Q., Cui, J., Shi, R. and Liu, L., 2015. An Efficient SDN Load Balancing Scheme Based on Variance Analysis for Massive Mobile Users. Mobile Information Systems, 2015. https://doi.org/10.1155/2015/241732.
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