Stochastic performance analysis of Network Function Virtualisation in future internet

This is the author accepted manuscript. The final version is available from the publisher via the DOI in this recordIEEE Network Function Virtualisation (NFV) has been considered as a promising technology for future Internet to increase network flexibility, accelerate service innovation and reduce the Capital Expenditures (CAPEX) and Operational Expenditures (OPEX) costs, through migrating network functions from dedicated network devices to commodity hardware. Recent studies reveal that although this migration of network function brings the network operation unprecedented flexibility and controllability, NFV-based architecture suffers from serious performance degradation compared with traditional service provisioning on dedicated devices. In order to achieve a comprehensive understanding of the service provisioning capability of NFV, this paper proposes a novel analytical model based on Stochastic Network Calculus (SNC) to quantitatively investigate the end-to-end performance bound of NFV networks. To capture the dynamic and on-demand NFV features, both the non-bursty traffic, e.g. Poisson process, and the bursty traffic, e.g. Markov Modulated Poisson Process (MMPP), are jointly considered in the developed model to characterise the arriving traffic. To address the challenges of resource competition and end-to-end NFV chaining, the property of convolution associativity and leftover service technologies of SNC are exploited to calculate the available resources of Virtual Network Function (VNF) nodes in the presence of multiple competing traffic, and transfer the complex NFV chain into an equivalent system for performance derivation and analysis. Both the numerical analysis and extensive simulation experiments are conducted to validate the accuracy of the proposed analytical model. Results demonstrate that the analytical performance metrics match well with those obtained from the simulation experiments and numerical analysis. In addition, the developed model is used as a practical and cost-effective tool to investigate the strategies of the service chain design and resource allocations in NFV networks.Engineering and Physical Sciences Research Council (EPSRC

Datacenter Traffic Control: Understanding Techniques and Trade-offs

Datacenters provide cost-effective and flexible access to scalable compute and storage resources necessary for today's cloud computing needs. A typical datacenter is made up of thousands of servers connected with a large network and usually managed by one operator. To provide quality access to the variety of applications and services hosted on datacenters and maximize performance, it deems necessary to use datacenter networks effectively and efficiently. Datacenter traffic is often a mix of several classes with different priorities and requirements. This includes user-generated interactive traffic, traffic with deadlines, and long-running traffic. To this end, custom transport protocols and traffic management techniques have been developed to improve datacenter network performance. In this tutorial paper, we review the general architecture of datacenter networks, various topologies proposed for them, their traffic properties, general traffic control challenges in datacenters and general traffic control objectives. The purpose of this paper is to bring out the important characteristics of traffic control in datacenters and not to survey all existing solutions (as it is virtually impossible due to massive body of existing research). We hope to provide readers with a wide range of options and factors while considering a variety of traffic control mechanisms. We discuss various characteristics of datacenter traffic control including management schemes, transmission control, traffic shaping, prioritization, load balancing, multipathing, and traffic scheduling. Next, we point to several open challenges as well as new and interesting networking paradigms. At the end of this paper, we briefly review inter-datacenter networks that connect geographically dispersed datacenters which have been receiving increasing attention recently and pose interesting and novel research problems.Comment: Accepted for Publication in IEEE Communications Surveys and Tutorial

Energy saving market for mobile operators

Ensuring seamless coverage accounts for the lion's share of the energy consumed in a mobile network. Overlapping coverage of three to five mobile network operators (MNOs) results in enormous amount of energy waste which is avoidable. The traffic demands of the mobile networks vary significantly throughout the day. As the offered load for all networks are not same at a given time and the differences in energy consumption at different loads are significant, multi-MNO capacity/coverage sharing can dramatically reduce energy consumption of mobile networks and provide the MNOs a cost effective means to cope with the exponential growth of traffic. In this paper, we propose an energy saving market for a multi-MNO network scenario. As the competing MNOs are not comfortable with information sharing, we propose a double auction clearinghouse market mechanism where MNOs sell and buy capacity in order to minimize energy consumption. In our setting, each MNO proposes its bids and asks simultaneously for buying and selling multi-unit capacities respectively to an independent auctioneer, i.e., clearinghouse and ends up either as a buyer or as a seller in each round. We show that the mechanism allows the MNOs to save significant percentage of energy cost throughout a wide range of network load. Different than other energy saving features such as cell sleep or antenna muting which can not be enabled at heavy traffic load, dynamic capacity sharing allows MNOs to handle traffic bursts with energy saving opportunity.Comment: 6 pages, 2 figures, to be published in ICC 2015 workshop on Next Generation Green IC

Fluid flow queue models for fixed-mobile network evaluation

A methodology for fast and accurate end-to-end KPI, like throughput and delay, estimation is proposed based on the service-centric traffic flow analysis and the fluid flow queuing model named CURSA-SQ. Mobile network features, like shared medium and mobility, are considered defining the models to be taken into account such as the propagation models and the fluid flow scheduling model. The developed methodology provides accurate computation of these KPIs, while performing orders of magnitude faster than discrete event simulators like ns-3. Finally, this methodology combined to its capacity for performance estimation in MPLS networks enables its application for near real-time converged fixed-mobile networks operation as it is proven in three use case scenarios

Performance Analysis and Optimisation of In-network Caching for Information-Centric Future Internet

The rapid development in wireless technologies and multimedia services has radically shifted the major function of the current Internet from host-centric communication to service-oriented content dissemination, resulting a mismatch between the protocol design and the current usage patterns. Motivated by this significant change, Information-Centric Networking (ICN), which has been attracting ever-increasing attention from the communication networks research community, has emerged as a new clean-slate networking paradigm for future Internet. Through identifying and routing data by unified names, ICN aims at providing natural support for efficient information retrieval over the Internet. As a crucial characteristic of ICN, in-network caching enables users to efficiently access popular contents from on-path routers equipped with ubiquitous caches, leading to the enhancement of the service quality and reduction of network loads. Performance analysis and optimisation has been and continues to be key research interests of ICN. This thesis focuses on the development of efficient and accurate analytical models for the performance evaluation of ICN caching and the design of optimal caching management schemes under practical network configurations. This research starts with the proposition of a new analytical model for caching performance under the bursty multimedia traffic. The bursty characteristic is captured and the closed formulas for cache hit ratio are derived. To investigate the impact of topology and heterogeneous caching parameters on the performance, a comprehensive analytical model is developed to gain valuable insight into the caching performance with heterogeneous cache sizes, service intensity and content distribution under arbitrary topology. The accuracy of the proposed models is validated by comparing the analytical results with those obtained from extensive simulation experiments. The analytical models are then used as cost-efficient tools to investigate the key network and content parameters on the performance of caching in ICN. Bursty traffic and heterogeneous caching features have significant influence on the performance of ICN. Therefore, in order to obtain optimal performance results, a caching resource allocation scheme, which leverages the proposed model and targets at minimising the total traffic within the network and improving hit probability at the nodes, is proposed. The performance results reveal that the caching allocation scheme can achieve better caching performance and network resource utilisation than the default homogeneous and random caching allocation strategy. To attain a thorough understanding of the trade-off between the economic aspect and service quality, a cost-aware Quality-of-Service (QoS) optimisation caching mechanism is further designed aiming for cost-efficiency and QoS guarantee in ICN. A cost model is proposed to take into account installation and operation cost of ICN under a realistic ISP network scenario, and a QoS model is presented to formulate the service delay and delay jitter in the presence of heterogeneous service requirements and general probabilistic caching strategy. Numerical results show the effectiveness of the proposed mechanism in achieving better service quality and lower network cost. In this thesis, the proposed analytical models are used to efficiently and accurately evaluate the performance of ICN and investigate the key performance metrics. Leveraging the insights discovered by the analytical models, the proposed caching management schemes are able to optimise and enhance the performance of ICN. To widen the outcomes achieved in the thesis, several interesting yet challenging research directions are pointed out