Performance modelling and analysis of software defined networking

Software Defined Networking (SDN) is an emerging architecture for the next-generation Internet, providing unprecedented network programmability to handle the explosive growth of Big Data driven by the popularisation of smart mobile devices and the pervasiveness of content-rich multimedia applications. In order to quantitatively investigate the performance characteristics of SDN networks, several research efforts from both simulation experiments and analytical modelling have been reported in the current literature. Among those studies, analytical modelling has demonstrated its superiority in terms of cost-effectiveness in the evaluation of large-scale networks. However, for analytical tractability and simplification, existing analytical models are derived based on the unrealistic assumptions that the network traffic follows the Poisson process which is suitable to model non-bursty text data and the data plane of SDN is modelled by one simplified Single Server Single Queue (SSSQ) system. Recent measurement studies have shown that, due to the features of heavy volume and high velocity, the multimedia big data generated by real-world multimedia applications reveals the bursty and correlated nature in the network transmission. With the aim of the capturing such features of realistic traffic patterns and obtaining a comprehensive and deeper understanding of the performance behaviour of SDN networks, this paper presents a new analytical model to investigate the performance of SDN in the presence of the bursty and correlated arrivals modelled by Markov Modulated Poisson Process (MMPP). The Quality-of-Service performance metrics in terms of the average latency and average network throughput of the SDN networks are derived based on the developed analytical model. To consider realistic multi-queue system of forwarding elements, a Priority-Queue (PQ) system is adopted to model SDN data plane. To address the challenging problem of obtaining the key performance metrics, e.g., queue length distribution of PQ system with a given service capacity, a versatile methodology extending the Empty Buffer Approximation (EBA) method is proposed to facilitate the decomposition of such a PQ system to two SSSQ systems. The validity of the proposed model is demonstrated through extensive simulation experiments. To illustrate its application, the developed model is then utilised to study the strategy of the network configuration and resource allocation in SDN networksThis work is supported by the EU FP7 “QUICK” Project (Grant NO. PIRSES-GA-2013-612652) and the National Natural Science Foundation of China (Grant NO. 61303241)

Asymptotic analysis by the saddle point method of the Anick-Mitra-Sondhi model

We consider a fluid queue where the input process consists of N identical sources that turn on and off at exponential waiting times. The server works at the constant rate c and an on source generates fluid at unit rate. This model was first formulated and analyzed by Anick, Mitra and Sondhi. We obtain an alternate representation of the joint steady state distribution of the buffer content and the number of on sources. This is given as a contour integral that we then analyze for large N. We give detailed asymptotic results for the joint distribution, as well as the associated marginal and conditional distributions. In particular, simple conditional limits laws are obtained. These shows how the buffer content behaves conditioned on the number of active sources and vice versa. Numerical comparisons show that our asymptotic results are very accurate even for N=20

Fabric-on-a-Chip: Toward Consolidating Packet Switching Functions on Silicon

The switching capacity of an Internet router is often dictated by the memory bandwidth required to bu¤er arriving packets. With the demand for greater capacity and improved service provisioning, inherent memory bandwidth limitations are encountered rendering input queued (IQ) switches and combined input and output queued (CIOQ) architectures more practical. Output-queued (OQ) switches, on the other hand, offer several highly desirable performance characteristics, including minimal average packet delay, controllable Quality of Service (QoS) provisioning and work-conservation under any admissible traffic conditions. However, the memory bandwidth requirements of such systems is O(NR), where N denotes the number of ports and R the data rate of each port. Clearly, for high port densities and data rates, this constraint dramatically limits the scalability of the switch. In an effort to retain the desirable attributes of output-queued switches, while significantly reducing the memory bandwidth requirements, distributed shared memory architectures, such as the parallel shared memory (PSM) switch/router, have recently received much attention. The principle advantage of the PSM architecture is derived from the use of slow-running memory units operating in parallel to distribute the memory bandwidth requirement. At the core of the PSM architecture is a memory management algorithm that determines, for each arriving packet, the memory unit in which it will be placed. However, to date, the computational complexity of this algorithm is O(N), thereby limiting the scalability of PSM switches. In an effort to overcome the scalability limitations, it is the goal of this dissertation to extend existing shared-memory architecture results while introducing the notion of Fabric on a Chip (FoC). In taking advantage of recent advancements in integrated circuit technologies, FoC aims to facilitate the consolidation of as many packet switching functions as possible on a single chip. Accordingly, this dissertation introduces a novel pipelined memory management algorithm, which plays a key role in the context of on-chip output- queued switch emulation. We discuss in detail the fundamental properties of the proposed scheme, along with hardware-based implementation results that illustrate its scalability and performance attributes. To complement the main effort and further support the notion of FoC, we provide performance analysis of output queued cell switches with heterogeneous traffic. The result is a flexible tool for obtaining bounds on the memory requirements in output queued switches under a wide range of tra¢ c scenarios. Additionally, we present a reconfigurable high-speed hardware architecture for real-time generation of packets for the various traffic scenarios. The work presented in this thesis aims at providing pragmatic foundations for designing next-generation, high-performance Internet switches and routers

Performance Modelling and Resource Allocation of the Emerging Network Architectures for Future Internet

With the rapid development of information and communications technologies, the traditional network architecture has approached to its performance limit, and thus is unable to meet the requirements of various resource-hungry applications. Significant infrastructure improvements to the network domain are urgently needed to guarantee the continuous network evolution and innovation. To address this important challenge, tremendous research efforts have been made to foster the evolution to Future Internet. Long-term Evolution Advanced (LTE-A), Software Defined Networking (SDN) and Network Function Virtualisation (NFV) have been proposed as the key promising network architectures for Future Internet and attract significant attentions in the network and telecom community. This research mainly focuses on the performance modelling and resource allocations of these three architectures. The major contributions are three-fold: 1) LTE-A has been proposed by the 3rd Generation Partnership Project (3GPP) as a promising candidate for the evolution of LTE wireless communication. One of the major features of LTE-A is the concept of Carrier Aggregation (CA). CA enables the network operators to exploit the fragmented spectrum and increase the peak transmission data rate, however, this technical innovation introduces serious unbalanced loads among in the radio resource allocation of LTE-A. To alleviate this problem, a novel QoS-aware resource allocation scheme, termed as Cross-CC User Migration (CUM) scheme, is proposed in this research to support real-time services, taking into consideration the system throughput, user fairness and QoS constraints. 2) SDN is an emerging technology towards next-generation Internet. In order to improve the performance of the SDN network, a preemption-based packet-scheduling scheme is firstly proposed in this research to improve the global fairness and reduce the packet loss rate in SDN data plane. Furthermore, in order to achieve a comprehensive and deeper understanding of the performance behaviour of SDN network, this work develops two analytical models to investigate the performance of SDN in the presence of Poisson Process and Markov Modulated Poisson Process (MMPP) respectively. 3) NFV is regarded as a disruptive technology for telecommunication service providers to reduce the Capital Expenditure (CAPEX) and Operational Expenditure (OPEX) through decoupling individual network functions from the underlying hardware devices. While NFV faces a significant challenging problem of Service-Level-Agreement (SLA) guarantee during service provisioning. In order to bridge this gap, a novel comprehensive analytical model based on stochastic network calculus is proposed in this research to investigate end-to-end performance of NFV network. The resource allocation strategies proposed in this study significantly improve the network performance in terms of packet loss probability, global allocation fairness and throughput per user in LTE-A and SDN networks; the analytical models designed in this study can accurately predict the network performances of SDN and NFV networks. Both theoretical analysis and simulation experiments are conducted to demonstrate the effectiveness of the proposed algorithms and the accuracy of the designed models. In addition, the models are used as practical and cost-effective tools to pinpoint the performance bottlenecks of SDN and NFV networks under various network conditions

a simulative model of a 5g telco operator network

Abstract In the near future, an important milestone for the evolution of wireless technologies will be the deployment of 5G network, having the target of supporting very huge data rate generated by a very high number of devices. One of the main technological enablers in this evolution is the joint SDN/NFV paradigm, defined in the last years to support the softwarization process of the Telco Operator networks. Given the very hard quality of experience (QoE) and quality of service (QoS) requirements in some application scenarios, mainly in terms of end-to-end delay, a challenging activity is to realize tools that can support network architects in performance evaluation and network design. With this in mind, this paper proposes a simulative tool for 5G networks, which is able to capture delay statistics due to both CPU load and transmission link congestions in NFVI-PoP nodes. The model is then applied to a case study to demonstrate how it can be applied for performance evaluation

Application of learning algorithms to traffic management in integrated services networks.

SIGLEAvailable from British Library Document Supply Centre-DSC:DXN027131 / BLDSC - British Library Document Supply CentreGBUnited Kingdo

Performance analysis of an ATM network with multimedia traffic: a simulation study

Traffic and congestion control are important in enabling ATM networks to maintain the Quality of Service (QoS) required by end users. A Call Admission Control (CAC) strategy ensures that the network has sufficient resources available at the start of each call, but this does not prevent a traffic source from violating the negotiated contract. A policing strategy (User Parameter Control (UPC)) is also required to enforce the negotiated rates for a particular connection and to protect conforming users from network overload. The aim of this work is to investigate traffic policing and bandwidth management at the User to Network Interface (UNI). A policing function is proposed which is based on the leaky bucket (LB) which offers improved performance for both real time (RT) traffic such as speech and video and non-real time (non-RT) traffic, mainly data by taking into account the QoS requirements. A video cell in violation of the negotiated bit rate causes the remainder of the slice to be discarded. This 'tail clipping' provides protection for the decoder from damaged video slices. Speech cells are coded using a frequency domain coder, which places the most significant bits of a double speech sample into a high priority cell and the least significant bits into a high priority cell. In the case of congestion, the low priority cell can be discarded with little impact on the intelligibility of the received speech. However, data cells require loss-free delivery and are buffered rather than being discarded or tagged for subsequent deletion. This triple strategy is termed the super leaky bucket (SLB). Separate queues for RT and non-RT traffic, are also proposed at the multiplexer, with non pre-emptive priority service for RT traffic if the queue exceeds a predetermined threshold. If the RT queue continues to grow beyond a second threshold, then all low priority cells (mainly speech) are discarded. This scheme protects non-RT traffic from being tagged and subsequently discarded, by queueing the cells and also by throttling back non-RT sources during periods of congestion. It also prevents the RT cells from being delayed excessively in the multiplexer queue. A simulation model has been designed and implemented to test the proposal. Realistic sources have been incorporated into the model to simulate the types of traffic which could be expected on an ATM network. The results show that the S-LB outperforms the standard LB for video cells. The number of cells discarded and the resulting number of damaged video slices are significantly reduced. Dual queues with cyclic service at the multiplexer also reduce the delays experienced by RT cells. The QoS for all categories of traffic is preserved