Analysis on Differential Router Buffer Size towards Network Congestion: A Simulation-based

Network resources are shared amongst a large number of users. Improper managing network traffic leads to congestion problem that degrades a network performance. It happens when the traffic exceeds the network capacity. In this research, we plan to observe the value of buffer size that contributes to network congestion. A simulation study by using OPNET Modeler 14.5 is conducted to achieve the purpose. A simple dumb-bell topology is used to observe several parameter such as number of packet dropped, retransmission count, end-to-end TCP delay, queuing delay and link utilization. The results show that the determination of buffer size based on Bandwidth-Delay Product (BDP) is still applicable for up to 500 users before network start to be congested. The symptom of near-congestion situation also being discussed corresponds to simulation results. Therefore, the buffer size needs to be determined to optimize the network performance based on our network topology. In future, the extension study will be carried out to investigate the effect of other buffer size models such as Stanford Model and Tiny Buffer Model. In addition, the buffer size has to be determined for wireless environment later on

Novel algorithms for fair bandwidth sharing on counter rotating rings

Rings are often preferred technology for networks as ring networks can virtually create fully connected mesh networks efficiently and they are also easy to manage. However, providing fair service to all the stations on the ring is not always easy to achieve. In order to capitalize on the advantages of ring networks, new buffer insertion techniques, such as Spatial Reuse Protocol (SRP), were introduced in early 2000s. As a result, a new standard known as IEEE 802.17 Resilient Packet Ring was defined in 2004 by the IEEE Resilient Packet Ring (RPR) Working Group. Since then two addenda have been introduced; namely, IEEE 802.17a and IEEE 802.17b in 2006 and 2010, respectively. During this standardization process, weighted fairness and queue management schemes were proposed to be used in the standard. As shown in this dissertation, these schemes can be applied to solve the fairness issues noted widely in the research community as radical changes are not practical to introduce within the context of a standard. In this dissertation, the weighted fairness aspects of IEEE 802.17 RPR (in the aggressive mode of operation) are studied; various properties are demonstrated and observed via network simulations, and additional improvements are suggested. These aspects have not been well studied until now, and can be used to alleviate some of the issues observed in the fairness algorithm under some scenarios. Also, this dissertation focuses on the RPR Medium Access Control (MAC) Client implementation of the IEEE 802.17 RPR MAC in the aggressive mode of operation and introduces a new active queue management scheme for ring networks that achieves higher overall utilization of the ring bandwidth with simpler and less expensive implementation than the generic implementation provided in the standard. The two schemes introduced in this dissertation provide performance comparable to the per destination queuing implementation, which yields the best achievable performance at the expense of the cost of implementation. In addition, till now the requirements for sizing secondary transit queue of IEEE 802.17 RPR stations (in the aggressive mode of operation) have not been properly investigated. The analysis and suggested improvements presented in this dissertation are then supported by performance evaluation results and theoretical calculations. Last, but not least, the impact of using different capacity links on the same ring has not been investigated before from the ring utilization and fairness points of view. This dissertation also investigates utilizing different capacity links in RPR and proposes a mechanism to support the same

Trading link utilization for queueing delays: an adaptive approach

Understanding the relationship between queueing delays and link utilization for general traffic conditions is an important open problem in networking research. Difficulties in understanding this relationship stem from the fact that it depends on the complex nature of arriving traffic and the problems associated with modelling such traffic. Existing AQM schemes achieve a "low delay" and "high utilization" by responding early to congestion without considering the exact relationship between delay and utilization. However, in the context of exploiting the delay/utilization tradeoff, the optimal choice of a queueing scheme's control parameter depends on the cost associated with the relative importance of queueing delay and utilization. The optimal choice of control parameter is the one that maximizes a benefit that can be defined as the difference between utilization and cost associated with queuing delay. We present two practical algorithms, Optimal Drop-Tail (ODT) and Optimal BLUE (OB), that are designed with a common performance goal: namely, maximizing this benefit. Their novelty lies in fact that they maximize the benefit in an online manner, without requiring knowledge of the traffic conditions, specific delay-utilization models, nor do they require complex parameter estimation. Packet level ns2 simulations are given to demonstrate the efficacy of the proposed algorithms and the framework in which they are designed

FavorQueue: A parameterless active queue management to improve TCP traffic performance

This paper presents and analyzes the implementation of a novel active queue management (AQM) named FavorQueue that aims to improve delay transfer of short lived TCP flows over best-effort networks. The idea is to dequeue packets that do not belong to a flow previously enqueued first. The rationale is to mitigate the delay induced by long-lived TCP flows over the pace of short TCP data requests and to prevent dropped packets at the beginning of a connection and during recovery period. Although the main target of this AQM is to accelerate short TCP traffic, we show that FavorQueue does not only improve the performance of short TCP traffic but also improves the performance of all TCP traffic in terms of drop ratio and latency whatever the flow size. In particular, we demonstrate that FavorQueue reduces the loss of a retransmitted packet, decreases the number of dropped packets recovered by RTO and improves the latency up to 30% compared to DropTail. Finally, we show that this scheme remains compliant with recent TCP updates such as the increase of the initial slow-start value

Model based analysis of some high speed network issues

The study of complex problems in science and engineering today typically involves large scale data, huge number of large-scale scientific breakthroughs critically depends on large multi-disciplinary and geographically-dispersed research teams, where the high speed network becomes the integral part. To serve the ongoing bandwidth requirement and scalability of these networks, there has been a continuous evolution of different TCPs for high speed networks. Testing these protocols on a real network would be expensive, time consuming and more over not easily available to the researchers worldwide. Network simulation is well accepted and widely used method for performance evaluation, it is well known that packet-based simulators like NS2 and Opnet are not adequate in high speed also in large scale networks because of its inherent bottlenecks in terms of message overhead and execution time. In that case model based approach with the help of a set of coupled differential equations is preferred for simulations. This dissertation is focused on the key challenges on research and development of TCPs on high-speed network. To address these issues/challenges this thesis has three objectives: design an analytical simulation methodology; model behaviors of high speed networks and other components including TCP flows and queue using the analytical simulation method; analyze them and explore impacts and interrelationship among them. To decrease the simulation time and speed up the process of testing and development of high speed TCP, we present a scalable simulation methodology for high speed network. We present the fluid model equations for various high-speed TCP variants. With the help of these fluid model equations, the behavior of high-speed TCP variants under various scenarios and its effect on queue size variations are presented. High speed network is not feasible unless we understand effect of bottleneck buffer size on performance of these high-speed TCP variants. A fluid model is introduced to accommodate the new observations of synchronization and de-synchronization phenomena of packet losses at bottleneck link and a microscopic analysis is presented on different buffer sizes at drop-tail queuing scheme. The proposed model based methods promotes principal understanding of the future heterogeneous networks and accelerates protocol developments

CloudJet4BigData: Streamlining Big Data via an Accelerated Socket Interface

Big data needs to feed users with fresh processing results and cloud platforms can be used to speed up big data applications. This paper describes a new data communication protocol (CloudJet) for long distance and large volume big data accessing operations to alleviate the large latencies encountered in sharing big data resources in the clouds. It encapsulates a dynamic multi-stream/multi-path engine at the socket level, which conforms to Portable Operating System Interface (POSIX) and thereby can accelerate any POSIX-compatible applications across IP based networks. It was demonstrated that CloudJet accelerates typical big data applications such as very large database (VLDB), data mining, media streaming and office applications by up to tenfold in real-world tests