Improving multiple broadcasting of multimedia traffic in wireless ad-hoc networks

The increasing use of multimedia streaming applications in addition with advent of internet television and radio, demands from today's wireless networks to handle with reliability multiple broadcasting and multicasting sources. However, the way that 802.11 standard, which is the primary technology in wireless networking, handle this type of traffic raises a series of problems mainly related to the lack of an effective feedback mechanism. This lack in turn, limits the capability of random backoff process to eliminate collisions and reduce reliability and fairness. This inherited drawback of the standard is affecting the way broadcast and multicast traffic is transmitted as well as the overall performance of the network. In this paper initially we are highlighting the drawback of the IEEE 802.11 MAC algorithm in handling multiple stations “media type” data broadcasting in an ad-hoc wireless network. Then, we propose two different approaches in alleviating these problems. The first approach is the simple linear increase of the contention window (CW) while the second propose a linear increase of the CW implementing an exclusive backoff number allocation (EBNA) algorithm. In addition we are modifying the 802.11 medium access control (MAC) algorithm to use the clear to send to self (CTS-to-Self) protection mechanism prior to every transmission. Both the above techniques are simulated and compared with the classic 802.11 MAC. The results show that the overall performance of the network can be improved using these alternative MAC methods

Experimental Evaluation of Large Scale WiFi Multicast Rate Control

WiFi multicast to very large groups has gained attention as a solution for multimedia delivery in crowded areas. Yet, most recently proposed schemes do not provide performance guarantees and none have been tested at scale. To address the issue of providing high multicast throughput with performance guarantees, we present the design and experimental evaluation of the Multicast Dynamic Rate Adaptation (MuDRA) algorithm. MuDRA balances fast adaptation to channel conditions and stability, which is essential for multimedia applications. MuDRA relies on feedback from some nodes collected via a light-weight protocol and dynamically adjusts the rate adaptation response time. Our experimental evaluation of MuDRA on the ORBIT testbed with over 150 nodes shows that MuDRA outperforms other schemes and supports high throughput multicast flows to hundreds of receivers while meeting quality requirements. MuDRA can support multiple high quality video streams, where 90% of the nodes report excellent or very good video quality

무선랜 비디오 멀티캐스트의 문제 발견 및 성능 향상 기법

학위논문 (박사)-- 서울대학교 대학원 공과대학 전기·컴퓨터공학부, 2017. 8. 최성현.Video multicast, streaming real-time videos via multicast, over wireless local area network (WLAN) has been considered a promising solution to share common venue-specific videos. By virtue of the nature of the wireless broadcast medium, video multicast basically enables scale-free video delivery, i.e., it can deliver a common video with the fixed amount of wireless resource regardless of the number of receivers. However, video multicast has not been widely enjoyed in our lives due to three major challenges: (1) power saving-related problem, (2) low reliability and efficiency, and (3) limited coverage. In this dissertation, we consider three research topics, i.e., (1) identification of practical issues with multicast power saving, (2) physical (PHY) rate and forward erasure correction code (FEC) rate adaptation over a single-hop network, and (3) multi-hop multicast, which deal with the three major challenges, respectively. Firstly, video multicast needs to be reliably delivered to power-saving stations, given that many portable devices are battery-powered. Accordingly, we investigate the impact of multicast power saving, and address two practical issues related with the multicast power saving. From the measurement with several commercial WLAN devices, we observe that many devices are not standard compliant, thus making video multicast performance severely degraded. We categorize such standard incompliant malfunctions that can result in significant packet losses. We also figure out a coexistence problem between video multicast and voice over Internet protocol (VoIP) when video receivers runs in power saving mode (PSM). The standard-compliant power save delivery of multicast deteriorates the VoIP performance in the same WLAN. We analyze the VoIP packet losses due to the coexistence problem, and propose a new power save delivery scheme to resolve the problem. We further implement the proposed scheme with an open source device driver, and our measurement results demonstrate that the proposed scheme significantly enhances the VoIP performance without sacrificing the video multicast performance. Second, multi-PHY rate FEC-applied wireless multicast enables reliable and efficient video multicast with intelligent selection of PHY rate and FEC rate. The optimal PHY/FEC rates depend on the cause of the packet losses. However, previous approaches select the PHY/FEC rates by considering only channel errors even when interference is also a major source of packet losses.We propose InFRA, an interference-aware PHY/FEC rate adaptation framework that (1) infers the cause of the packet losses based on received signal strength indicator (RSSI) and cyclic redundancy check (CRC) error notifications, and (2) determines the PHY/FEC rates based on the cause of packet losses. Our prototype implementation with off-the-shelf chipsets demonstrates that InFRA enhances the multicast delivery under various network scenarios. InFRA enables 2.3x and 1.8x more nodes to achieve a target video packet loss rate with a contention interferer and a hidden interferer, respectively, compared with the state-of-theart PHY/FEC rate adaptation scheme. To the best of our knowledge, InFRA is the first work to take the impact of interference into account for the PHY/FEC rate adaptation. Finally, collaborative relaying that enables selected receiver nodes to relay the received packets from source node to other nodes enhances service coverage, reliability, and efficiency of video multicast. The intelligent selection of sender nodes (source and relays) and their transmission parameters (PHY rate and the number of packets to send) is the key to optimize the performance. We propose EV-CAST, an interference and energy-aware video multicast system using collaborative relays, which entails online network management based on interference-aware link characterization, an algorithm for joint determination of sender nodes and transmission parameters, and polling-based relay protocol. In order to select most appropriate set of the relay nodes, EV-CAST considers interference, battery status, and spatial reuse, as well as other factors accumulated over last decades. Our prototype-based measurement results demonstrate that EV-CAST outperforms the state-of-the-art video multicast schemes. In summary, from Chapter 2 to Chapter 4, the aforementioned three pieces of the research work, i.e., identification of power saving-related practical issues, InFRA for interference-resilient single-hop multicast, and EV-CAST for efficient multi-hop multicast, will be presented, respectively.1 Introduction 1 1.1 Video Multicast over WLAN 1 1.2 Overview of Existing Approaches 4 1.2.1 Multicast Power Saving 4 1.2.2 Reliability and Efficiency Enhancement 4 1.2.3 Coverage Extension 5 1.3 Main Contributions 7 1.3.1 Practical Issues with Multicast Power Saving 7 1.3.2 Interference-aware PHY/FEC Rate Adaptation 8 1.3.3 Energy-aware Multi-hop Multicast 9 1.4 Organization of the Dissertation 10 2 Practical Issues with Multicast Power Saving 12 2.1 Introduction 12 2.2 Multicast & Power Management Operation in IEEE 802.11 14 2.3 Inter-operability Issue 15 2.3.1 Malfunctions of Commercial WLAN Devices 17 2.3.2 Performance Evaluation 20 2.4 Coexistence Problem of Video Multicast and VoIP 21 2.4.1 Problem Statement 21 2.4.2 Problem Identification: A Measurement Study 23 2.4.3 Packet Loss Analysis 27 2.4.4 Proposed Scheme 32 2.4.5 Performance Evaluation 33 2.5 Summary 37 3 InFRA: Interference-Aware PHY/FEC Rate Adaptation for Video Multicast over WLAN 39 3.1 Introduction 39 3.2 Related Work 42 3.2.1 Reliable Multicast Protocol 42 3.2.2 PHY/FEC rate adaptation for multicast service 44 3.2.3 Wireless Video Transmission 45 3.2.4 Wireless Loss Differentiation 46 3.3 Impact of Interference on Multi-rate FEC-applied Multicast 46 3.3.1 Measurement Setup 47 3.3.2 Measurement Results 47 3.4 InFRA: Interference-aware PHY/FEC Rate Adaptation Framework 49 3.4.1 Network Model and Objective 49 3.4.2 Overall Architecture 50 3.4.3 FEC Scheme 52 3.4.4 STA-side Operation 53 3.4.5 AP-side Operation 61 3.4.6 Practical Issues 62 3.5 Performance Evaluation 65 3.5.1 Measurement Setup 66 3.5.2 Small Scale Evaluation 67 3.5.3 Large Scale Evaluation 70 3.6 Summary 74 4 EV-CAST: Interference and Energy-aware Video Multicast Exploiting Collaborative Relays 75 4.1 Introduction 75 4.2 Factors for Sender Node and Transmission Parameter Selection 78 4.3 EV-CAST: Interference and Energy-aware Multicast Exploiting Collaborative Relays 80 4.3.1 Network Model and Objective 80 4.3.2 Overview 81 4.3.3 Network Management 81 4.3.4 Interference and Energy-aware Sender Nodes and Transmission Parameter Selection (INFER) Algorithm 87 4.3.5 Assignment, Polling, and Re-selection of Relays 93 4.3.6 Discussion 95 4.4 Evaluation 96 4.4.1 Measurement Setup 96 4.4.2 Micro-benchmark 98 4.4.3 Macro-benchmark 103 4.5 Related Work 105 4.5.1 Multicast Opportunistic Routing 105 4.5.2 Multicast over WLAN 106 4.6 Summary 106 5 Conclusion 108 5.1 Research Contributions 108 5.2 Future Research Directions 109 Abstract (In Korean) 121Docto

Traffic and mobility management in large-scale networks of small cells

The growth in user demand for higher mobile data rates is driving Mobile Network Operators (MNOs) and network infrastructure vendors towards the adoption of innovative solutions in areas that span from physical layer techniques (e.g., carrier aggregation, massive MIMO, etc.) to the Radio Access Network and the Evolved Packet Core, amongst other. In terms of network capacity, out of a millionfold increase since 1957, the use of wider spectrum (25x increase), the division of spectrum into smaller resources (5x), and the introduction of advanced modulation and coding schemes (5x) have played a less significant role than the improvements in system capacity due to cell size reduction (1600x). This justifies the academic and industrial interest in short-range, low-power cellular base stations, such as small cells. The shift from traditional macrocell-based deployments towards heterogeneous cellular networks raises the need for new architectural and procedural frameworks capable of providing a seamless integration of massive deployments of small cells into the existing cellular network infrastructure. This is particularly challenging for large-scale, all-wireless networks of small cells (NoS), where connectivity amongst base stations is provided via a wireless multi-hop backhaul. Networks of small cells are a cost-effective solution for improving network coverage and capacity in high user-density scenarios, such as transportation hubs, sports venues, convention centres, dense urban areas, shopping malls, corporate premises, university campuses, theme parks, etc. This Ph.D. Thesis provides an answer to the following research question: What is the architectural and procedural framework needed to support efficient traffic and mobility management mechanisms in massive deployments of all-wireless 3GPP Long-Term Evolution networks of small cells? In order to do so, we address three key research challenges in NoS. First, we present a 3GPP network architecture capable of supporting large-scale, all-wireless NoS deployments in the Evolved Packet System. This involves delegating core network functions onto new functional entities in the network of small cells, as well as adapting Transport Network Layer functionalities to the characteristics of a NoS in order to support key cellular services. Secondly, we address the issue of local location management, i.e., determining the approximate location of a mobile terminal in the NoS upon arrival of an incoming connection from the core network. This entails the design, implementation, and evaluation of efficient paging and Tracking Area Update mechanisms that can keep track of mobile terminals in the complex scenario of an all-wireless NoS whilst mitigating the impact on signalling traffic throughout the local NoS domain and towards the core network. Finally, we deal with the issue of traffic management in large-scale networks of small cells. On the one hand, we propose new 3GPP network procedures to support direct unicast communication between LTE terminals camped on the same NoS with minimal involvement from functional entities in the Evolved Packet Core. On the other hand, we define a set of extensions to the standard 3GPP Multicast/Broadcast Multimedia Service (MBMS) in order to improve the quality of experience of multicast/broadcast traffic services in high user-density scenarios.El crecimiento de la demanda de tasas de transmisión más altas está empujando a los operadores de redes móviles y a los fabricantes de equipos de red a la adopción de soluciones innovadoras en áreas que se extienden desde técnicas avanzadas de capa física (agregación de portadoras, esquemas MIMO masivos, etc.) hasta la red de acceso radio y troncal, entre otras. Desde 1957 la capacidad de las redes celulares se ha multiplicado por un millón. La utilización de mayor espectro radioeléctrico (incremento en factor 25), la división de dicho espectro en recursos más pequeños (factor 5) y la introducción de esquemas avanzados de modulación y codificación (factor 5) han desempeñado un papel menos significativo que las mejoras en la capacidad del sistema debidas a la reducción del tamaño de las celdas (factor 1600). Este hecho justifica el interés del mundo académico y de la industria en estaciones base de corto alcance y baja potencia, conocidas comúnmente como small cells. La transición de despliegues tradicionales de redes celulares basados en macroceldas hacia redes heterogéneas pone de manifiesto la necesidad de adoptar esquemas arquitecturales y de procedimientos capaces de proporcionar una integración transparente de despliegues masivos de small cells en la actual infraestructura de red celular. Este aspecto es particularmente complejo en el caso de despliegues a gran escala de redes inalámbricas de small cells (NoS, en sus siglas en inglés), donde la conectividad entre estaciones base se proporciona a través de una conexión troncal inalámbrica multi-salto. En general, las redes de small cells son una solución eficiente para mejorar la cobertura y la capacidad de la red celular en entornos de alta densidad de usuarios, como núcleos de transporte, sedes de eventos deportivos, palacios de congresos, áreas urbanas densas, centros comerciales, edificios corporativos, campus universitarios, parques temáticos, etc. El objetivo de esta Tesis de Doctorado es proporcionar una respuesta a la siguiente pregunta de investigación: ¿Cuál es el esquema arquitectural y de procedimientos de red necesario para soportar mecanismos eficientes de gestión de tráfico y movilidad en despliegues masivos de redes inalámbricas de small cells LTE? Para responder a esta pregunta nos centramos en tres desafíos clave en NoS. En primer lugar, presentamos una arquitectura de red 3GPP capaz de soportar despliegues a gran escala de redes inalámbricas de small cells en el Evolved Packet System, esto es, el sistema global de comunicaciones celulares LTE. Esto implica delegar funciones de red troncal en nuevas entidades funcionales desplegadas en la red de small cells, así como adaptar funcionalidades de la red de transporte a las características de una NoS para soportar servicios celulares clave. En segundo lugar, nos centramos en el problema de la gestión de movilidad local, es decir, determinar la localización aproximada de un terminal móvil en la NoS a la llegada de una solicitud de conexión desde la red troncal. Esto incluye el diseño, la implementación y la evaluación de mecanismos eficientes de paging y Tracking Area Update capaces de monitorizar terminales móviles en el complejo escenario de redes de small cells inalámbricas que, a la vez, mitiguen el impacto sobre el tráfico de señalización en el dominio local de la NoS y hacia la red troncal. Finalmente, estudiamos el problema de gestión de tráfico en despliegues a gran escala de redes inalámbricas de small cells. Por un lado, proponemos nuevos procedimientos de red 3GPP para soportar comunicaciones unicast directas entre terminales LTE registrados en la misma NoS con mínima intervención por parte de entidades funcionales en la red troncal. Por otro lado, definimos un conjunto de extensiones para mejorar la calidad de la experiencia del servicio estándar 3GPP de transmisión multicast/broadcast de tráfico multimedia (MBMS, en sus siglas en inglés) en entornos de alta densidad de usuarios

Reliable Multicast transport of the video over the WiFi network

Le transport multicast est une solution efficace pour envoyer le même contenu à plusieurs récepteurs en même temps. Ce mode est principalement utilisé pour fournir des flux multimédia en temps réel. Cependant, le multicast classique de l IEEE 802.11 n'utilise aucun mécanisme d acquittement. Ainsi, l échec de réception implique la perte définitive du paquet. Cela limite la fiabilité du transport multicast et impact la qualité des applications vidéo. Pour résoudre ce problème, 802.11v et 802.11aa sont définis récemment. Le premier amendement propose Direct Multicast Service (DMS). D'autre part, le 802.11aa introduit GroupCast with Retries (GCR). GCR définit deux nouvelles politiques de retransmission : Block Ack (BACK) et Unsolicited Retry (UR).Dans cette thèse, nous évaluons et comparons les performances de 802.11v/aa. Nos résultats montrent que tous les nouveaux protocoles multicast génèrent un overhead de transmission important. En outre, DMS a une scalabilité très limitée, et GCR-BACK n'est pas approprié pour des grands groupes multicast. D autre part, nous montrons que DMS et GCR-BACK génèrent des latences de transmission importantes lorsque le nombre de récepteurs augmente. Par ailleurs, nous étudions les facteurs de pertes dans les réseaux sans fil. Nous montrons que l'indisponibilité du récepteur peut être la cause principale des pertes importantes et de leur nature en rafales. En particulier, nos résultats montrent que la surcharge du processeur peut provoquer un taux de perte de 100%, et que le pourcentage de livraison peut être limité à 35% lorsque la carte 802.11 est en mode d économie d'énergie.Pour éviter les collisions et améliorer la fiabilité du transport multicast, nous définissons le mécanisme Busy Symbol (BS). Nos résultats montrent que BS évite les collisions et assure un taux de succès de transmission très important. Afin d'améliorer davantage la fiabilité du trafic multicast, nous définissons un nouveau protocole multicast, appelé Block Negative Acknowledgement (BNAK). Ce protocole opère comme suit. L AP envoi un bloc de paquets suivi par un Block NAK Request (BNR). Le BNR permet aux membres de détecter les données manquantes et d envoyer une demande de retransmission, c.à.d. un Block NAK Response (BNAK). Un BNAK est transmis en utilisant la procédure classique d accès au canal afin d'éviter toute collision avec d'autres paquets. En plus, cette demande est acquittée. Sous l'hypothèse que 1) le récepteur est situé dans la zone de couverture du débit de transmission utilisé, 2) les collisions sont évitées et 3) le terminal a la bonne configuration, très peu de demandes de retransmission sont envoyées, et la bande passante est préservée. Nos résultats montrent que BNAK a une très grande scalabilité et génère des délais très limités. En outre, nous définissons un algorithme d'adaptation de débit pour BNAK. Nous montrons que le bon débit de transmission est sélectionné moyennant un overhead très réduit de moins de 1%. En plus, la conception de notre protocole supporte la diffusion scalable de lavvidéo. Cette caractéristique vise à résoudre la problématique de la fluctuation de la bande passante, et à prendre en considération l'hétérogénéité des récepteurs dans un réseau sans fil.The multicast transport is an efficient solution to deliver the same content to many receivers at the same time. This mode is mainly used to deliver real-time video streams. However, the conventional multicast transmissions of IEEE 802.11 do not use any feedback policy. Therefore missing packets are definitely lost. This limits the reliability of the multicast transport and impacts the quality of the video applications. To resolve this issue, the IEEE 802.11v/aa amendments have been defined recently. The former proposes the Direct Multicast Service (DMS). On the other hand, 802.11aa introduces Groupcast with Retries (GCR) service. GCR defines two retry policies: Block Ack (BACK) and Unsolicited Retry (UR).In this thesis we evaluate and compare the performance of 802.11v/aa. Our simulation results show that all the defined policies incur an important overhead. Besides, DMS has a very limited scalability, and GCR-BACK is not appropriate for large multicast groups. We show that both DMS and GCR-BACK incur important transmission latencies when the number of the multicast receivers increases. Furthermore, we investigate the loss factors in wireless networks. We show that the device unavailability may be the principal cause of the important packet losses and their bursty nature. Particularly, our results show that the CPU overload may incur a loss rate of 100%, and that the delivery ratio may be limited to 35% when the device is in the power save mode.To avoid the collisions and to enhance the reliability of the multicast transmissions, we define the Busy Symbol (BS) mechanism. Our results show that BS prevents all the collisions and ensures a very high delivery ratio for the multicast packets. To further enhance the reliability of this traffic, we define the Block Negative Acknowledgement (BNAK) retry policy. Using our protocol, the AP transmits a block of multicast packets followed by a Block NAK Request (BNR). Upon reception of a BNR, a multicast member generates a Block NAK Response (BNAK) only if it missed some packets. A BNAK is transmitted after channel contention in order to avoid any eventual collision with other feedbacks, and is acknowledged. Under the assumption that 1) the receiver is located within the coverage area of the used data rate, 2) the collisions are avoided and 3) the terminal has the required configuration, few feedbacks are generated and the bandwidth is saved. Our results show that BNAK has a very high scalability and incurs very low delays. Furthermore, we define a rate adaptation scheme for BNAK. We show that the appropriate rate is selected on the expense of a very limited overhead of less than 1%. Besides, the conception of our protocol is defined to support the scalable video streaming. This capability intends to resolve the bandwidth fluctuation issue and to consider the device heterogeneity of the group members.BORDEAUX1-Bib.electronique (335229901) / SudocSudocFranceF

Learning for Network Applications and Control

The emergence of new Internet applications and technologies have resulted in an increased complexity as well as a need for lower latency, higher bandwidth, and increased reliability. This ultimately results in an increased complexity of network operation and management. Manual management is not sufficient to meet these new requirements. There is a need for data driven techniques to advance from manual management to autonomous management of network systems. One such technique, Machine Learning (ML), can use data to create models from hidden patterns in the data and make autonomous modifications. This approach has shown significant improvements in other domains (e.g., image recognition and natural language processing). The use of ML, along with advances in programmable control of Software- Defined Networks (SDNs), will alleviate manual network intervention and ultimately aid in autonomous network operations. However, realizing a data driven system that can not only understand what is happening in the network but also operate autonomously requires advances in the networking domain, as well as in ML algorithms. In this thesis, we focus on developing ML-based network architectures and data driven net- working algorithms whose objective is to improve the performance and management of future networks and network applications. We focus on problems spanning across the network protocol stack from the application layer to the physical layer. We design algorithms and architectures that are motivated by measurements and observations in real world or experimental testbeds. In Part I we focus on the challenge of monitoring and estimating user video quality of experience (QoE) of encrypted video traffic for network operators. We develop a system for REal-time QUality of experience metric detection for Encrypted Traffic, Requet. Requet uses a detection algorithm to identify video and audio chunks from the IP headers of encrypted traffic. Features extracted from the chunk statistics are used as input to a random forest ML model to predict QoE metrics. We evaluate Requet on a YouTube dataset we collected, consisting of diverse video assets delivered over various WiFi and LTE network conditions. We then extend Requet, and present a study on YouTube TV live streaming traffic behavior over WiFi and cellular networks covering a 9-month period. We observed pipelined chunk requests, a reduced buffer capacity, and a more stable chunk duration across various video resolutions compared to prior studies of on-demand streaming services. We develop a YouTube TV analysis tool using chunks statistics detected from the extracted data as input to a ML model to infer user QoE metrics. In Part II we consider allocating end-to-end resources in cellular networks. Future cellular networks will utilize SDN and Network Function Virtualization (NFV) to offer increased flexibility for network infrastructure operators to utilize network resources. Combining these technologies with real-time network load prediction will enable efficient use of network resources. Specifically, we leverage a type of recurrent neural network, Long Short-Term Memory (LSTM) neural networks, for (i) service specific traffic load prediction for network slicing, and (ii) Baseband Unit (BBU) pool traffic load prediction in a 5G cloud Radio Access Network (RAN). We show that leveraging a system with better accuracy to predict service requirements results in a reduction of operation costs. We focus on addressing the optical physical layer in Part III. Greater network flexibility through SDN and the growth of high bandwidth services are motivating faster service provisioning and capacity management in the optical layer. These functionalities require increased capacity along with rapid reconfiguration of network resources. Recent advances in optical hardware can enable a dramatic reduction in wavelength provisioning times in optical circuit switched networks. To support such operations, it is imperative to reconfigure the network without causing a drop in service quality to existing users. Therefore, we present a ML system that uses feedforward neural networks to predict the dynamic response of an optically circuit-switched 90-channel multi-hop Reconfigurable Optical Add-Drop Multiplexer (ROADM) network. We show that the trained deep neural network can recommend wavelength assignments for wavelength switching with minimal power excursions. We extend the performance of the ML system by implementing and testing a Hybrid Machine Learning (HML) model, which combines an analytical model with a neural network machine learning model to achieve higher prediction accuracy. In Part IV, we use a data-driven approach to address the challenge of wireless content delivery in crowded areas. We present the Adaptive Multicast Services (AMuSe) system, whose objective is to enable scalable and adaptive WiFi multicast. Specifically, we develop an algorithm for dynamic selection of a subset of the multicast receivers as feedback nodes. Further, we describe the Multicast Dynamic Rate Adaptation (MuDRA) algorithm that utilizes AMuSe’s feedback to optimally tune the physical layer multicast rate. Our experimental evaluation of MuDRA on the ORBIT testbed shows that MuDRA outperforms other schemes and supports high throughput multicast flows to hundreds of nodes while meeting quality requirements. We leverage the lessons learned from AMuSe for WiFi and use order statistics to address the performance issues with LTE evolved Multimedia Broadcast/Multicast Service (eMBMS). We present the Dynamic Monitoring (DyMo) system which provides low-overhead and real-time feedback about eMBMS performance to be used for network optimization. We focus on the Quality of Service (QoS) Evaluation module and develop a Two-step estimation algorithm which can efficiently identify the SNR Threshold as a one time estimation. DyMo significantly outperforms alternative schemes based on the Order-Statistics estimation method which relies on random or periodic sampling