Interference charecterisation, location and bandwidth estimation in emerging WiFi networks

Wireless LAN technology based on the IEEE 802.11 standard, commonly referred to as WiFi, has been hugely successful not only for the last hop access to the Internet in home, office and hotspot scenarios but also for realising wireless backhaul in mesh networks and for point -to -point long- distance wireless communication. This success can be mainly attributed to two reasons: low cost of 802.11 hardware from reaching economies of scale, and operation in the unlicensed bands of wireless spectrum.The popularity of WiFi, in particular for indoor wireless access at homes and offices, has led to significant amount of research effort looking at the performance issues arising from various factors, including interference, CSMA/CA based MAC protocol used by 802.11 devices, the impact of link and physical layer overheads on application performance, and spatio-temporal channel variations. These factors affect the performance of applications and services that run over WiFi networks. In this thesis, we experimentally investigate the effects of some of the above mentioned factors in the context of emerging WiFi network scenarios such as multi- interface indoor mesh networks, 802.11n -based WiFi networks and WiFi networks with virtual access points (VAPs). More specifically, this thesis comprises of four experimental characterisation studies: (i) measure prevalence and severity of co- channel interference in urban WiFi deployments; (ii) characterise interference in multi- interface indoor mesh networks; (iii) study the effect of spatio-temporal channel variations, VAPs and multi -band operation on WiFi fingerprinting based location estimation; and (iv) study the effects of newly introduced features in 802.11n like frame aggregation (FA) on available bandwidth estimation.With growing density of WiFi deployments especially in urban areas, co- channel interference becomes a major factor that adversely affects network performance. To characterise the nature of this phenomena at a city scale, we propose using a new measurement methodology called mobile crowdsensing. The idea is to leverage commodity smartphones and the natural mobility of people to characterise urban WiFi co- channel interference. Specifically, we report measurement results obtained for Edinburgh, a representative European city, on detecting the presence of deployed WiFi APs via the mobile crowdsensing approach. These show that few channels in 2.4GHz are heavily used and there is hardly any activity in the 5GHz band even though relatively it has a greater number of available channels. Spatial analysis of spectrum usage reveals that co- channel interference among nearby APs operating in the same channel can be a serious problem with around 10 APs contending with each other in many locations. We find that the characteristics of WiFi deployments at city -scale are similar to those of WiFi deployments in public spaces of different indoor environments. We validate our approach in comparison with wardriving, and also show that our findings generally match with previous studies based on other measurement approaches. As an application of the mobile crowdsensing based urban WiFi monitoring, we outline a cloud based WiFi router configuration service for better interference management with global awareness in urban areas.For mesh networks, the use of multiple radio interfaces is widely seen as a practical way to achieve high end -to -end network performance and better utilisation of available spectrum. However this gives rise to another type of interference (referred to as coexistence interference) due to co- location of multiple radio interfaces. We show that such interference can be so severe that it prevents concurrent successful operation of collocated interfaces even when they use channels from widely different frequency bands. We propose the use of antenna polarisation to mitigate such interference and experimentally study its benefits in both multi -band and single -band configurations. In particular, we show that using differently polarised antennas on a multi -radio platform can be a helpful counteracting mechanism for alleviating receiver blocking and adjacent channel interference phenomena that underlie multi -radio coexistence interference. We also validate observations about adjacent channel interference from previous studies via direct and microscopic observation of MAC behaviour.Location is an indispensable information for navigation and sensing applications. The rapidly growing adoption of smartphones has resulted in a plethora of mobile applications that rely on position information (e.g., shopping apps that use user position information to recommend products to users and help them to find what they want in the store). WiFi fingerprinting is a popular and well studied approach for indoor location estimation that leverages the existing WiFi infrastructure and works based on the difference in strengths of the received AP signals at different locations. However, understanding the impact of WiFi network deployment aspects such as multi -band APs and VAPs has not received much attention in the literature. We first examine the impact of various aspects underlying a WiFi fingerprinting system. Specifically, we investigate different definitions for fingerprinting and location estimation algorithms across different indoor environments ranging from a multi- storey office building to shopping centres of different sizes. Our results show that the fingerprint definition is as important as the choice of location estimation algorithm and there is no single combination of these two that works across all environments or even all floors of a given environment. We then consider the effect of WiFi frequency bands (e.g., 2.4GHz and 5GHz) and the presence of virtual access points (VAPs) on location accuracy with WiFi fingerprinting. Our results demonstrate that lower co- channel interference in the 5GHz band yields more accurate location estimation. We show that the inclusion of VAPs has a significant impact on the location accuracy of WiFi fingerprinting systems; we analyse the potential reasons to explain the findings.End -to -end available bandwidth estimation (ABE) has a wide range of uses, from adaptive application content delivery, transport-level transmission rate adaptation and admission control to traffic engineering and peer node selection in peer -to- peer /overlay networks [ 1, 2]. Given its importance, it has been received much research attention in both wired data networks and legacy WiFi networks (based on 802.11 a/b /g standards), resulting in different ABE techniques and tools proposed to optimise different criteria and suit different scenarios. However, effects of new MAC/PHY layer enhancements in new and next generation WiFi networks (based on 802.11n and 802.11ac standards) have not been studied yet. We experimentally find that among different new features like frame aggregation, channel bonding and MIMO modes (spacial division multiplexing), frame aggregation has the most harmful effect as it has direct effect on ABE by distorting the measurement probing traffic pattern commonly used to estimate available bandwidth. Frame aggregation is also specified in both 802.11n and 802.1 lac standards as a mandatory feature to be supported. We study the effect of enabling frame aggregation, for the first time, on the performance of the ABE using an indoor 802.11n wireless testbed. The analysis of results obtained using three tools - representing two main Probe Rate Model (PRM) and Probe Gap Model (PGM) based approaches for ABE - led us to come up with the two key principles of jumbo probes and having longer measurement probe train sizes to counter the effects of aggregating frames on the performance of ABE tools. Then, we develop a new tool, WBest+ that is aware of the underlying frame aggregation by incorporating these principles. The experimental evaluation of WBest+ shows more accurate ABE in the presence of frame aggregation.Overall, the contributions of this thesis fall in three categories - experimental characterisation, measurement techniques and mitigation/solution approaches for performance problems in emerging WiFi network scenarios. The influence of various factors mentioned above are all studied via experimental evaluation in a testbed or real - world setting. Specifically, co- existence interference characterisation and evaluation of available bandwidth techniques are done using indoor testbeds, whereas characterisation of urban WiFi networks and WiFi fingerprinting based location estimation are carried out in real environments. New measurement approaches are also introduced to aid better experimental evaluation or proposed as new measurement tools. These include mobile crowdsensing based WiFi monitoring; MAC/PHY layer monitoring of co- existence interference; and WBest+ tool for available bandwidth estimation. Finally, new mitigation approaches are proposed to address challenges and problems identified throughout the characterisation studies. These include: a proposal for crowd - based interference management in large scale uncoordinated WiFi networks; exploiting antenna polarisation diversity to remedy the effects of co- existence interference in multi -interface platforms; taking advantage of VAPs and multi -band operation for better location estimation; and introducing the jumbo frame concept and longer probe train sizes to improve performance of ABE tools in next generation WiFi networks

ReasoNet:Inferring Network Policies Using Ontologies

Modern SDN control stacks consist of multiple abstraction and virtualization layers to enable flexibility in the development of new control features. Rich data modeling frameworks are essential when sharing information across control layers. Unfortunately, existing NOS data modeling capabilities are limited to simple type-checking and code templating. We present an exploration of a more extreme point on SDN data modeling: ReasoNet. Developers can use semantic web technologies to enrich their data models with reasoning rules and integrity/consistency constraints and automate state inference across layers. We demonstrate the ability of ReasoNet to automate state verification and cross-layer debugging, through the implementation of two popular control applications, a learning switch and a QoS policy engine

On the Impact of 802.11n Frame Aggregation on End-to-End Available Bandwidth Estimation

Abstract-We consider for the first time available bandwidth estimation (ABE) in the context of 802.11n, which is fast replacing the legacy 802.11a/b/g networks. We experimentally show that the frame aggregation (FA) feature of 802.11n is the dominant one among 802.11n features affecting the ABE. Using an indoor 802.11n wireless testbed, we compare three ABE tools (WBest, DietTopp and pathChirp) in various cross-traffic scenarios. We find that FA significantly hurts the accuracy of all ABE tools; DietTopp and pathChirp are relatively more robust than WBest. Because faster available bandwidth estimation and less intrusiveness are desirable properties of any ABE tool and WBest satisfies them relatively better than the other two tools, we conduct an in-depth investigation into the harmful effect of FA on ABE using WBest. This in turn led us to come up with two key design principles to counter FA effects: (1) treating aggregated probes as one jumbo probe; and (2) generating a larger number of probes. We then develop an enhanced version of WBest termed WBest+ that incorporates these principles. Our evaluation shows that the new version is effective in achieving accurate ABE in the presence of FA

The Extended Cloud:Review and Analysis of Mobile Edge Computing and Fog from a Security and Resilience Perspective

Mobile Edge Computing (MEC) and Fog are emerging computing models that extend the cloud and its services to the edge of the network. The emergence of both MEC and fog introduce new requirements, which mean their supported deployment models must be investigated. In this paper, we point out the influence and strong impact of the extended cloud (i.e., the MEC and fog) on existing communication and networking service models of the cloud. Although the relation between them is fairly evident, there are important properties, notably those of security and resilience, that we study in relation to the newly posed requirements from the MEC and fog. Although security and resilience have been already investigated in the context of the cloud - to a certain extent - existing solutions may not be applicable in the context of the extended cloud. Our approach includes the examination of models and architectures that underpin the extended cloud, and we provide a contemporary discussion on the most evident characteristics associated with them. We examine the technologies that implement these models and architectures, and analyse them with respect to security and resilience requirements. Furthermore, approaches to security and resilience-related mechanisms are examined in the cloud (specifically, anomaly detection and policy based resilience management), and we argue that these can also be applied in order to improve security and achieve resilience in the extended cloud environment

DataPlane Broker:Open WAN control for multi-site service orchestration

NFV-MANO has become the de-facto standard for network service orchestration in future programmable network infrastructures. Relevant standards define an architecture and a data model that allows an orchestration entity to deploy, dynamically configure and monitor virtual and physical network functions across virtualized datacenters. Although the model offers extensive details for network function management and host-level network configuration, end-to-end connectivity management beyond the datacenter remains limited. The responsibility for cross-site connectivity is delegated to a control abstraction, the WAN Infrastructure Manager (WIM), which is partially defined in relevant standards. The reference implementation of the NFV-MANO standards, Open Source MANO (OSM), has recently released a reference WIM driver model, but no open-source WIM implementation is currently available, thus restricting the ability of researchers to experiment with multi-site service deployments. In this paper, we present the DataPlane Broker (DPB), the first open-source WIM implementation for software-defined networks. Using an extensive data model, DPB seamlessly translates NFV-MANO requirements into SDN configuration, supporting point-to-point and multipoint connectivity with strong bandwidth guarantees. DPB is integrated with OSM FIVE via a WIM plugin. Initial experiments highlight that path computation can scale to large network topologies and a large number of services, with negligible computational overheads, while DPB increases by less than 10% the overall deployment delay of an OSM service

Baguette:towards end-to-end service orchestration in heterogeneous networks

Network services are the key mechanism for operators to introduce intelligence and generate profit from their infrastructures. The growth of the number of network users and the stricter application network requirements have highlighted a number of challenges in orchestrating services using existing production management and configuration protocols and mechanisms. Recent networking paradigms like Software Defined Networking (SDN) and Network Function Virtualization (NFV), provide a set of novel control and management interfaces that enable unprecedented automation, flexibility and openness capabilities in operator infrastructure management. This paper presents Baguette, a novel and open service orchestration framework for operators. Baguette supports a wide range of network technologies, namely optical and wired Ethernet technologies, and allows service providers to automate the deployment and dynamic re-optimization of network services. We present the design of the orchestrator and elaborate on the integration of Baguette with existing low-level network and cloud management frameworks

Network service orchestration standardization:a technology survey

Network services underpin operator revenues, and value-added services provide income beyond core (voice and data) infrastructure capability. Today, operators face multiple challenges: a need to innovate and offer a wider choice of value-added services, whilst increasing network scale, bandwidth and flexibility. They must also reduce operational costs, and deploy services far faster - in minutes rather than days or weeks. In the recent years, the network community, motivated by the aforementioned challenges, has developed production network architectures and seeded technologies, like Software Defined Networking, Application-based Network Operations and Network Function Virtualization. These technologies enhance the highly desired properties for elasticity, agility and cost-effectiveness in the operator environment. A key requirement to fully exploit the benefits of these new architectures and technologies is a fundamental shift in management and control of resources, and the ability to orchestrate the network infrastructure: coordinate the instantiation of high-level network services across different technological domains and automate service deployment and re-optimization. This paper surveys existing standardization efforts for the orchestration - automation, coordination, and management - of complex set of network and function resources (both physical and virtual), and highlights the various enabling technologies, strengths and weaknesses, adoption challenges for operators, and areas where further research is required

Leveraging SDN to provide an in-network QoE measurement framework

Online video streaming using HTTP Adaptive Streaming (HAS) is becoming the most popular content delivery mechanism for media services. Network and content providers would like to ensure a high degree of video Quality of Experience (QoE) for their end-users. However, traditional network-level metrics do not necessarily reflect the end-users’ true perception of delivered content.We introduce an in-network QoE measurement framework (IQMF) that provides QoE monitoring for HAS streams as a service. The framework leverages Software Defined Networking for its control plane functionality to streamline non-intrusive quality monitoring and to offer a closed control loop for QoE-aware service management. IQMF adopts two specifically designed QoE metrics to capture the user experience of HAS streams with respect to video fidelity and switching impact. Finally, we used a pan-European SDN testbed to demonstrate how IQMF can be used as a foundation for in-network QoE measurement and service optimisation