Service-aware LSP selection with fuzzy based packet scheduling scheme for non-real time traffics

An essential solution is available in Multi-protocol label switching (MPLS), which solve the problems faced by present-day networks: speed, scalability, quality-of-service (QoS) management, and traffic engineering. This paper is an extension of work on Fuzzy based Packet Scheduling Algorithm (FPSA) combined with Packets Processing Algorithm (PPA) in an Internet Protocol/Multi-Protocol Label Switching (IP/MPLS) networks. This will make provision for an intelligent service to the Label Switched Path (LSP) in MPLS networks. Several research work have been proposed on the MPLS Traffic Engineering. However, it is still imperative to further research on the effect of bandwidth increment on the core network using different mechanisms such as the analytical model of MPLS, expert-based packet scheduling algorithm for MPLS QoS support. Since MPLS is not able to provide intelligent routing, it is necessary to propose an intelligent expert system of FPSA combined with PPA. And analytical model of packet forwarding in the MPLS network would be given to provide suitable solution to traffic congestion and reliable services. Furthermore, the network model created using Network Simulator (NS 2), which carries non-real time application such as File Transfer Protocol (FTP) with bandwidth variations. The results obtained from trace files are interpreted by AWK script and used for the further analysis.

An Adaptive Throughput-First Packet Scheduling Algorithm for DPDK-Based Packet Processing Systems

The continuous increase in network traffic has sharply increased the demand for high-performance packet processing systems. For a high-performance packet processing system based on multi-core processors, the packet scheduling algorithm is critical because of the significant role it plays in load distribution, which is related to system throughput, attracting intensive research attention. However, it is not an easy task since the canonical flow-level packet scheduling algorithm is vulnerable to traffic locality, while the packet-level packet scheduling algorithm fails to maintain cache affinity. In this paper, we propose an adaptive throughput-first packet scheduling algorithm for DPDK-based packet processing systems. Combined with the feature of DPDK burst-oriented packet receiving and transmitting, we propose using Subflow as the scheduling unit and the adjustment unit making the proposed algorithm not only maintain the advantages of flow-level packet scheduling algorithms when the adjustment does not happen but also avoid packet loss as much as possible when the target core may be overloaded Experimental results show that the proposed method outperforms Round-Robin, HRW (High Random Weight), and CRC32 on system throughput and packet loss rate.

AN ENHANCED PACKET SCHEDULING ALGORITHM FOR THE DOWNLINK COGNITIVE LONG TERM EVOLUTION-ADVANCED

A packet scheduling algorithm known as Enhanced Maximum-Largest Weighted Delay First (EM-LWDF) is proposed in this paper. It aims to maximize the number of Real Time (RT) and Non Real Time (NRT) users that meet their desired Quality of Service (QoS) in the cognitive Long Term Evolution-Advanced (LTE-A). This cognitive LTE-A allows its Component Carriers (CCs) to be combined with licensed CCs from another system. This enables the LTE-A to further expand the available bandwidth for packet transmission. The EM-LWDF algorithm decides the priority of each user on the basis of the desired QoS of each packet, the urgency of each packet, channel quality and the average throughput. The potential of this algorithm is validated via computer simulation where it is able to simultaneously maximize more users that meet their desired QoS in realistic RT and NRT multimedia of the downlink cognitive LTE-A. ABSTRAK: Algoritma penjadualan paket yang dikenali sebagai Enhanced Maximum-Largest Weighted Delay First (EM-LWDF) dicadangkan dalam kertas ini. Ia bertujuan untuk memaksimumkan bilangan pengguna Real Time (RT) dan Non Real Time (NRT) yang memenuhi Kualiti Perkhidmatan yang dikehendaki (QoS) dalam system kognitif Long Term Evolution-Advanced (LTE-A). Kognitif LTE-A ini membolehkan Carrier Component (CC) untuk digabungkan dengan CC berlesen dari sistem lain. Ini membolehkan LTE-A untuk memperluaskan jalur lebar yang tersedia bagi penghantaran paket. Algoritma EM-LWDF menentukan keutamaan setiap pengguna berdasarkan QoS yang dikehendaki dari setiap paket, kecemasan setiap paket, kualiti saluran dan purata penghantaran. Potensi algoritma ini disahkan melalui simulasi komputer di mana ia dapat memaksimumkan lebih banyak pengguna yang memenuhi QoS yang dikehendaki mereka dalam realistik RT dan NRT multimedia dari downlink sistem kognitif LTE-A.