Router CPU Research Articles

Quality optimization of OSPFV3 and EIGRP for IPV4 in hierarchical network environment using GNS3 tool

In network world, due to shortage of IP addresses in version 4, a new version of IP address, namely IPv6, has come into play, but due to non-exchange ability between IPv4 and IPv6, different routing protocol is come to play for IPv6 that is RIPng, OSPFv3 and EIGRP for IPv6 in the place of RIP, OSPFv2 and EIGRP in IPv4 environment. Transmission of data is based on the routing protocol which selects the best routes in network world. Two types of interior routing protocol which selects the best routes in network world that is distance vector and link state. In this research we compare two types of routing protocol are chosen as the simulation base that is OSPFv3 (Link state) and EIGRP IPv6 (Distance Vector) in terms of convergence and router CPU usage. These routing protocols are mostly used in network as well as internet. In this project, we are going to use GNS3 to simulate and compare OSPF and EIGRPv6 with authentication and without authentication in large hierarchical network using ipv4 and ipv6 environment. On top of everything, as a second step GNS3 simulator installed. Familiarity with GNS3 is essential to achieve this research study. As a second step, a certain hierarchical routing scheme scenarios will be created. Secondly, OSPFv3 and EIGRP IPv6 without authentication implemented and configured to get the required results in terms of CPU processing power and convergence time. Later, OSPFv3 and EIGRP IPv6 with authentication implemented and configured to get results for a comparison in terms of resources usage and convergence. As a final stage overall results of the research study compared to analyze the research parameters which are with and without authentication on both routing protocols. At the end of this research study, the result is drawn and presented in the thesis and a final comparative analysis presented in tabular format. In this Research study compare two parameters, CPU utilization and Processing power with and without authentication. We found that OSPFv3 uses less power as compared to EIGRP for IPv6 without authentication in hierarchal environment, but it takes more time to converge and with authentication it is also found that it ospfv3 uses less power as compared to EIGRP for IPv6 while EIGPR for IPv6 is faster than OSPFv3.

What do parrots and BGP routers have in common?

The Border Gateway Protocol propagates routing information accross the Internet in an incremental manner. It only advertises to its peers changes in routing. However, as early as 1998, observations have been made of BGP announcing the same route multiple times, causing router CPU load, memory usage and convergence time higher than expected. In this paper, by performing controlled experiments, we pinpoint multiple causes of duplicates, ranging from the lack of full RIB-Outs to the discrete processing of update messages. To mitigate these duplicates, we insert a cache at the output of the routers. We test it on public BGP traces and discuss the relation of the cache performance with the existence of bursts of updates in the trace.

Router CPU Time Management in Cellular IP Networks using GA

Providing good QoS in Cellular IP networks is one of the important issues in order to improve the performance of the Cellular IP network. Resource reservation is one of the methods used in achieving this goal and is proven to be effective. Resources of Cellular IP network that can be reserved are bandwidth, buffer and CPU cycles. Router CPU cycle is the time taken to process a packet before forwarding it to the next router (hop). This paper is proposing a model for CPU cycle optimization of routers for real-time flows in Cellular IP network. The model applies Genetic Algorithm as a soft computing tool to optimize the CPU cycles and reduces the flow processing time at each router in the route taken by a flow. Simulation experiments show the efficacy of the model.

Router CPU Time Management using Particle Swarm Optimization in Cellular IP Networks

Providing QoS is one of the important issues in order to improve the performance of Cellular IP network. Resource reservation is often used in achieving this goal and it is proven to be an effective mechanism so far. Resources of Cellular IP network that can be reserved are bandwidth, buffer and CPU cycles. This paper is proposing a model for router CPU cycle reservation for real-time flows in Cellular IP network. The model applies Particle Swarm Optimization, as a soft computing tool, to reserve the CPU cycles and reduce the flow processing time at each router in the route taken by a flow. Simulation experiments reveal the efficacy of the model.

A novel resource scheduling algorithm for QoS-aware services on the Internet

The popularity and availability of Internet connection has opened up the opportunity for network-centric collaborative work that was impossible a few years ago. Contending traffic flows in this collaborative scenario share different kinds of resources such as network links, buffers, and router CPU. The goal should hence be overall fairness in the allocation of multiple resources rather than a specific resource. In this paper, firstly, we present a novel QoS-aware resource scheduling algorithm called Weighted Composite Bandwidth and CPU Scheduler (WCBCS), which jointly allocates the fair share of the link bandwidth as well as processing resource to all competing flows. WCBCS also uses a simple and adaptive online prediction scheme for reliably estimating the processing times of the incoming data packets. Secondly, we present some analytical results, extensive NS-2 simulation work, and experimental results from our implementation on Intel IXP2400 network processor. The simulation and implementation results show that our low complexity scheduling algorithm can efficiently maximise the CPU and bandwidth utilisation while maintaining guaranteed Quality of Service (QoS) for each individual flow.

Design, Analysis and Implementation of a Novel Multiple Resource Scheduler

Over the past decade, the problem of achieving fair bandwidth allocation on a link shared by multiple traffic flows has been extensively researched. However, as these flows traverse a computer network, they share many different kinds of resources, such as links, buffers, and router CPU. The ultimate goal should hence be overall fairness in the allocation of multiple resources rather than a single specific resource such as link bandwidth. In this paper, we present a novel scheduler, called prediction-based composite fair queuing (PCFQ), which jointly allocates the fair share of the link bandwidth and processing resources to all competing flows. We derive the worst-case delay bound, the work complexity, and the relative fairness bound for the PCFQ scheduler and show that it outperforms a system consisting of separate bandwidth and CPU schedulers. We further present simulation results which illustrate the improved performance characteristics achieved by PCFQ. We also demonstrate that our composite scheduler can be easily implemented on an off-the-shelf network processor such as the Intel IXP 2400. Experimental results from the IXP 2400 implementation highlight the effectiveness and high performance of this algorithm in a real-world system.

Design, Analysis, and Implementation of a Novel Low Complexity Scheduler for Joint Resource Allocation

Over the past decade, the problem of fair bandwidth allocation among contending traffic flows on a link has been extensively researched. However, as these flows traverse a computer network, they share different kinds of resources (e.g., links, buffers, router CPU). The ultimate goal should hence be overall fairness in the allocation of multiple resources rather than a specific resource. Moreover, conventional resource scheduling algorithms depend strongly upon the assumption of prior knowledge of network parameters and cannot handle variations or lack of information about these parameters. In this paper, we present a novel scheduler called the composite bandwidth and CPU scheduler (CBCS), which jointly allocates the fair share of the link bandwidth as well as processing resource to all competing flows. CBCS also uses a simple and adaptive online prediction scheme for reliably estimating the processing times of the incoming data packets. Analytically, we prove that CBCS is efficient, with a per-packet work complexity of O(1). Finally, we present simulation results and experimental outcomes from a real-world implementation of CBCS on an Intel IXP 2400 network processor. Our results highlight the improved performance achieved by CBCS and demonstrate the ease with which it can be implemented on off-the-shelf hardware

Scheduling computations on a software-based router

Recent efforts to add new services to the Internet have increased the interest in software-based routers that are easy to extend and evolve. This paper describes our experiences implementing a software-based router, with a particular focus on the main difficulty we encountered: how to schedule the router's CPU cycles. The scheduling decision is complicated by the desire to differentiate the level of service for different packet flows, which leads to two fundamental conflicts: (1) assigning processor shares in a way that keeps the processes along the forwarding path in balance while meeting QoS promises, and (2) adjusting the level of batching in a way that minimizes overhead while meeting QoS promises.