Treatment-Based Classi?cation in Residential Wireless Access Points

IEEE 802.11 wireless access points (APs) act as the central communication hub inside homes, connecting all networked devices to the Internet. Home users run a variety of network applications with diverse Quality-of-Service requirements (QoS) through their APs. However, wireless APs are often the bottleneck in residential networks as broadband connection speeds keep increasing. Because of the lack of QoS support and complicated configuration procedures in most off-the-shelf APs, users can experience QoS degradation with their wireless networks, especially when multiple applications are running concurrently. This dissertation presents CATNAP, Classification And Treatment iN an AP , to provide better QoS support for various applications over residential wireless networks, especially timely delivery for real-time applications and high throughput for download-based applications. CATNAP consists of three major components: supporting functions, classifiers, and treatment modules. The supporting functions collect necessary flow level statistics and feed it into the CATNAP classifiers. Then, the CATNAP classifiers categorize flows along three-dimensions: response-based/non-response-based, interactive/non-interactive, and greedy/non-greedy. Each CATNAP traffic category can be directly mapped to one of the following treatments: push/delay, limited advertised window size/drop, and reserve bandwidth. Based on the classification results, the CATNAP treatment module automatically applies the treatment policy to provide better QoS support. CATNAP is implemented with the NS network simulator, and evaluated against DropTail and Strict Priority Queue (SPQ) under various network and traffic conditions. In most simulation cases, CATNAP provides better QoS supports than DropTail: it lowers queuing delay for multimedia applications such as VoIP, games and video, fairly treats FTP flows with various round trip times, and is even functional when misbehaving UDP traffic is present. Unlike current QoS methods, CATNAP is a plug-and-play solution, automatically classifying and treating flows without any user configuration, or any modification to end hosts or applications

Adaptive split transmission for video streams in wireless mesh networks

Wireless mesh networks hold great promise in the wireless transmission of video flows, particularly if the problem of providing sufficient network capacity can be addressed. For this reason, schemes which help to address this difficulty in capacity-limited wireless networks are of great interest. This paper presents a novel and simple algorithm, adaptive split transmission algorithm, for achieving real-time, and quality-guaranteed video transmission in wireless mesh networks. The algorithm utilizes the unused capacities of multiple channels rather than trying to transmit the flow over just one overloaded channel. The flow is efficiently split into several sub-flows in a capacity-aware manner, each sub-flow then being transmitted through different channels in parallel. The adaptive split transmission algorithm controls flows dynamically in response to changes in the states of the available channels, thereby avoiding the overloading of any one channel. We evaluate the algorithm through simulations. The results show that the adaptive split transmission algorithm achieves synchronized, quality-guaranteed, and real-time wireless video transmission. The proposed algorithm can be used for interactive real-time wireless video applications without changing current wireless hardware, MAC protocols and upper-layer protocols

Slicing with guaranteed quality of service in wifi networks

Network slicing has recently been proposed as one of the main enablers for 5G networks. The slicing concept consists of the partition of a physical network into several self-contained logical networks (slices) that can be tailored to offer different functional or performance requirements. In the context of 5G networks, we argue that existing ubiquitous WiFi technology can be exploited to cope with new requirements. Therefore, in this paper, we propose a novel mechanism to implement network slicing in WiFi Access Points. We formulate the resource allocation problem to the different slices as a stochastic optimization problem, where each slice can have bit rate, delay, and capacity requirements. We devise a solution to the problem above using the Lyapunov drift optimization theory, and we develop a novel queuing and scheduling algorithm. We have used MATLAB and Simulink to build a prototype of the proposed solution, whose performance has been evaluated in a typical slicing scenario.This work has been supported in part by the European Commission and the Spanish Government (Fondo Europeo de Desarrollo Regional, FEDER) by means of the EU H2020 NECOS (777067) and ADVICE (TEC2015-71329) projects, respectivel

An Efficient Framework of Congestion Control for Next-Generation Networks

The success of the Internet can partly be attributed to the congestion control algorithm in the Transmission Control Protocol (TCP). However, with the tremendous increase in the diversity of networked systems and applications, TCP performance limitations are becoming increasingly problematic and the need for new transport protocol designs has become increasingly important.Prior research has focused on the design of either end-to-end protocols (e.g., CUBIC) that rely on implicit congestion signals such as loss and/or delay or network-based protocols (e.g., XCP) that use precise per-flow feedback from the network. While the former category of schemes haveperformance limitations, the latter are hard to deploy, can introduce high per-packet overhead, and open up new security challenges. This dissertation explores the middle ground between these designs and makes four contributions. First, we study the interplay between performance and feedback in congestion control protocols. We argue that congestion feedback in the form of aggregate load can provide the richness needed to meet the challenges of next-generation networks and applications. Second, we present the design, analysis, and evaluation of an efficient framework for congestion control called Binary Marking Congestion Control (BMCC). BMCC uses aggregate load feedback to achieve efficient and fair bandwidth allocations on high bandwidth-delaynetworks while minimizing packet loss rates and average queue length. BMCC reduces flow completiontimes by up to 4x over TCP and uses only the existing Explicit Congestion Notification bits.Next, we consider the incremental deployment of BMCC. We study the bandwidth sharing properties of BMCC and TCP over different partial deployment scenarios. We then present algorithms for ensuring safe co-existence of BMCC and TCP on the Internet. Finally, we consider the performance of BMCC over Wireless LANs. We show that the time-varying nature of the capacity of a WLAN can lead to significant performance issues for protocols that require capacity estimates for feedback computation. Using a simple model we characterize the capacity of a WLAN and propose the usage of the average service rate experienced by network layer packets as an estimate for capacity. Through extensive evaluation, we show that the resulting estimates provide good performance

Smartphone-based crowdsourcing for estimating the bottleneck capacity in wireless networks

Crowdsourcing enables the fine-grained characterization and performance evaluation of today׳s large-scale networks using the power of the masses and distributed intelligence. This paper presents SmartProbe, a system that assesses the bottleneck capacity of Internet paths using smartphones, from a mobile crowdsourcing perspective. With SmartProbe measurement activities are more bandwidth efficient compared to similar systems, and a larger number of users can be supported. An application based on SmartProbe is also presented: georeferenced measurements are mapped and used to compare the performance of mobile broadband operators in wide areas. Results from one year of operation are included

Gateway Adaptive Pacing for TCP across Multihop Wireless Networks and the Internet

In this paper, we introduce an effective congestion control scheme for TCP over hybrid wireless/wired networks comprising a multihop wireless IEEE 802.11 network and the wired Internet. We propose an adaptive pacing scheme at the Internet gateway for wired-to-wireless TCP flows. Furthermore, we analyze the causes for the unfairness of oncoming TCP flows and propose a scheme to throttle aggressive wired-to-wireless TCP flows at the Internet gateway to achieve nearly optimal fairness. Thus, we denote the introduced congestion control scheme TCP with Gateway Adaptive Pacing (TCP-GAP). For wireless-to-wired flows, we propose an adaptive pacing scheme at the TCP sender. In contrast to previous work, TCP-GAP does not impose any control traffic overhead for achieving fairness among active TCP flows. Moreover, TCP-GAP can be incrementally deployed because it does not require any modifications of TCP in the wired part of the network and is fully TCP-compatible. Extensive simulations using ns-2 show that TCPGAP is highly responsive to varying traffic conditions, provides nearly optimal fairness in all scenarios and achieves up to 42% more goodput than TCP NewReno

Models and Protocols for Resource Optimization in Wireless Mesh Networks

Wireless mesh networks are built on a mix of fixed and mobile nodes interconnected via wireless links to form a multihop ad hoc network. An emerging application area for wireless mesh networks is their evolution into a converged infrastructure used to share and extend, to mobile users, the wireless Internet connectivity of sparsely deployed fixed lines with heterogeneous capacity, ranging from ISP-owned broadband links to subscriber owned low-speed connections. In this thesis we address different key research issues for this networking scenario. First, we propose an analytical predictive tool, developing a queuing network model capable of predicting the network capacity and we use it in a load aware routing protocol in order to provide, to the end users, a quality of service based on the throughput. We then extend the queuing network model and introduce a multi-class queuing network model to predict analytically the average end-to-end packet delay of the traffic flows among the mobile end users and the Internet. The analytical models are validated against simulation. Second, we propose an address auto-configuration solution to extend the coverage of a wireless mesh network by interconnecting it to a mobile ad hoc network in a transparent way for the infrastructure network (i.e., the legacy Internet interconnected to the wireless mesh network). Third, we implement two real testbed prototypes of the proposed solutions as a proof-of-concept, both for the load aware routing protocol and the auto-configuration protocol. Finally we discuss the issues related to the adoption of ad hoc networking technologies to address the fragility of our communication infrastructure and to build the next generation of dependable, secure and rapidly deployable communications infrastructures

Explicit congestion control algorithms for time-varying capacity media

Tese de doutoramento. Engenharia Electrotécnica e de Computadores. Faculdade de Engenharia. Universidade do Porto. 200