Peningkatan Utilisasi Jaringan Distributed Storage System Menggunakan Kombinasi Server dan Link Load Balancing

Distributed Storage System (DSS) memiliki sejumlah perangkat server penyimpanan yang terhubung dengan banyak perangkat switch untuk meningkatkan utilisasi jaringan. DSS harus memperhatikan keseimbangan beban pada sisi server penyimpanan dan trafik data pada semua jalur yang terhubung. Jika beban pada sisi server penyimpanan dan trafik data tidak seimbang, maka dapat menyebabkan bottleneck network yang menurunkan utilisasi jaringan. Kombinasi server dan link load balancing adalah solusi yang tepat untuk menyeimbangkan beban pada sisi server penyimpanan dan trafik data. Penelitian ini mengusulkan metode kombinasi algoritme least connection sebagai metode server-load balancing dan algoritme global first fit sebagai metode link load balancing. Algoritme global first fit merupakan salah satu dari algoritme load balancing hedera yang bertujuan untuk menyeimbangkan trafik data berukuran besar (10% dari bandwidth), sehingga terhindar dari permasalahan bottleneck network. Algoritme least connection merupakan salah satu algoritme server load balancing yang menggunakan jumlah total koneksi dari server untuk menentukan prioritas server. Hasil evaluasi kombinasi metode tersebut didapatkan peningkatan pada rata-rata throughput sebesar 77,9% dibanding hasil metode Equal Cost Multi Path (ECMP) dan Round robin (RR). Peningkatan pada rata-rata penggunaan bandwidth sebesar 65,2% dibanding hasil metode ECMP dan RR. Hasil Penggunaan CPU dan memory pada server di metode kombinasi ini juga terjadi penurunan beban CPU sebesar 34,29% dan penurunan beban penggunaan memory sebesar 9,8% dibanding metode ECMP dan RR. Dari hasil evaluasi, penerapan metode kombinasi metode server dan link load balancing berhasil meningkatkan utilisasi jaringan dan juga mengurangi beban server. AbstractDistributed Storage System (DSS) has a number of storage server devices that are connected to multiple switch devices to increase network utilization. DSS must pay attention to the balance of the load on the storage server side and data traffic on all connected lines. If the load on the storage server side and data traffic is not balanced, it can cause a network bottleneck that reduces network utilization. The combination of server and link-load balancing is the right solution to balance the load on the server side of storage and data traffic. This study proposes a combination of the least connection algorithm as a server-load balancing method and the global first fit algorithm as a link-load balancing method. The global first fit algorithm is one of Hedera's load balancing algorithms which aims to balance large data traffic (10% of bandwidth), so as to avoid network bottleneck problems. Least connection algorithm is one of the server balancing algorithms that uses the total number of connections from the server to determine server priority. The results of the evaluation of the combination of these methods showed an increase in the average throughput of 77.9% compared to the results of the Equal Cost Multi Path (ECMP) and Round robin (RR) methods. The increase in the average bandwidth usage is 65.2% compared to the results of the ECMP and RR methods. The results of CPU and memory usage on the server in this combination method also decreased CPU load by 34.29% and a decrease in memory usage load by 9.8% compared to the ECMP and RR methods. From the evaluation results, the application of a combination of the server method and the link load balancing method has succeeded in increasing network utilization and also reducing server load

A Survey on Data Plane Programming with P4: Fundamentals, Advances, and Applied Research

With traditional networking, users can configure control plane protocols to match the specific network configuration, but without the ability to fundamentally change the underlying algorithms. With SDN, the users may provide their own control plane, that can control network devices through their data plane APIs. Programmable data planes allow users to define their own data plane algorithms for network devices including appropriate data plane APIs which may be leveraged by user-defined SDN control. Thus, programmable data planes and SDN offer great flexibility for network customization, be it for specialized, commercial appliances, e.g., in 5G or data center networks, or for rapid prototyping in industrial and academic research. Programming protocol-independent packet processors (P4) has emerged as the currently most widespread abstraction, programming language, and concept for data plane programming. It is developed and standardized by an open community and it is supported by various software and hardware platforms. In this paper, we survey the literature from 2015 to 2020 on data plane programming with P4. Our survey covers 497 references of which 367 are scientific publications. We organize our work into two parts. In the first part, we give an overview of data plane programming models, the programming language, architectures, compilers, targets, and data plane APIs. We also consider research efforts to advance P4 technology. In the second part, we analyze a large body of literature considering P4-based applied research. We categorize 241 research papers into different application domains, summarize their contributions, and extract prototypes, target platforms, and source code availability.Comment: Submitted to IEEE Communications Surveys and Tutorials (COMS) on 2021-01-2