Naomi Ramos

Department of Electrical and Computer Engineering
University of California, San Diego

Advisor: Prof. Sujit Dey

About Me Research Publications Resume Contact

Research Summary:

My most recent research work was on developing a device and network-aware scaling framework for efficient delivery of multimedia over wireless networks. In this work, I focus on adapting the application layer and determining the appropriate scaling level for each video stream based on device capability information, network capacity, and the desired service objective. The proposed framework improves aggregate quality satisfaction, increase bandwidth efficiency, and satisfy a greater number of clients simultaneously.

While my current research focuses on adapting the application layer, my previous research work has been working with the link layer. In this work, I focused on Quality of Service (QoS) provisioning over wireless networks. The main objective of my research was to develop an adaptive network-aware and application-aware link layer to support service differentiation and provide adequate QoS to end users. In particular, I was working on dynamic adaptation mechanisms in 802.11 Wireless LAN networks that take into account the current channel conditions and the needs of the applications. In addition to research in QoS, I have worked on link layer adaptation techniques for energy efficiency.

Projects & Abstracts:

A Device and Network-Aware Scaling Framework for Efficient Delivery of Scalable Video over Wireless Networks
Viewing multimedia content on wireless-enabled platforms has become more prevalent in recent years. Traditional wireless devices, such as cellular phones and PDAs, are becoming more multimedia-capable. Additionally, traditional multimedia platforms, such as PCs and TVs, are being designed to support wireless connectivity. With a wide range of platform capabilities, content service providers are now faced with the challenging problem of supporting multimedia delivery for a diverse set of devices. Recent work in scalable video coding (SVC) may provide a solution by enabling techniques that will allow devices to extract video streams scaled to match their capabilities. However, SVC can be significantly bandwidth inefficient. By sending the highest possible quality stream over the network, irrespective of the capabilities of the end-devices and the network capacity, SVC can limit the number of devices being served and reduce the aggregate quality satisfaction of the network. In this paper, we present a Device and Network-Aware Scaling (DeNAS) framework to address these problems. Based on device capability information, network capacity, and the desired service objective, DeNAS finds the suitable scaling level for each video stream prior to its delivery over the wireless network. We demonstrate the effectiveness of DeNAS through simulation and show that DeNAS is able to improve aggregate quality satisfaction, increase bandwidth efficiency, and satisfy a greater number of clients simultaneously.
Dynamic Adaptation Policies to Improve Quality of Service of Multimedia Applications in WLAN Networks

With the increased popularity of wireless broadband networks and the growing demand for multimedia applications, such as streaming video and teleconferencing, there is a need to support diverse multimedia services over the wireless medium. Recently pursued standardization efforts in IEEE 802.11e attempt to provide Quality of Service (QoS) differentiation mechanisms using two modes of medium access: polling-based and contention-based. However, there are a few limitations in the current approach with supporting inaccurate flow reservations, varying flow requirements, and congestion in contention-based access. In this paper, we address the above limitations by dynamically associating traffic flows appropriately to the two medium access modes and adjusting the duration of access in each mode. To show the effectiveness of our approach, we compare our adaptation policy with the 802.11e reference scheduler. We demonstrate that with our adaptation, the QoS of multimedia applications, in terms of delay and throughput metrics, can be significantly improved (2-4.5x).
ChaPLeT: Channel-dependent Packet Level Tuning for Service Differentiation in IEEE 802.11e

With the increased use of IEEE 802.11b wireless networks, there is a strong need to support diverse Quality of Service (QoS) requirements. Recent standardization efforts are being pursued in IEEE 802.11e to introduce a framework for QoS enhancements to the IEEE 802.11b standard. Although IEEE 802.11e provides a level of service differentiation by statically associating different QoS parameters for pre-defined traffic classes, this upcoming standard does not consider the problems introduced by varying channel conditions present in wireless networks.

In this project, we design a Channel-dependent Packet Level Tuning (ChaPLeT) mechanism to maintain service differentiation in the presence of channel variation. We propose the use of three parameters, namely fragmentation threshold, persistence factor, and defer countdown in enabling packet-level prioritization. Using a runtime adaptation policy implemented using the OPNET modeler, ChaPLeT dynamically configures the above parameters appropriately based on traffic class, as well as current channel conditions. We show the effectiveness of our approach with the OPNET Modeler by comparing our adaptation policy with the current IEEE 802.11e scheme.
Energy-Efficient Link Adaptations in IEEE 802.11b Wireless LAN

The growing popularity of Wireless LAN-based connectivity has increased the use of IEEE 802.11b as an edge access technology. However, with the ability to support high data rates and a wide range of applications, data access in these networks poses a significant demand on limited energy resources of mobile devices. In addition to the application demand, another factor that significantly affects the energy consumption is the varying channel conditions.

In order to alleviate the energy constraint, in this project we explore the potential for adaptations in the link layer, and present an energy efficient IEEE 802.11b Data Link Layer. We specifically study the effect of three parameters using the OPNET modeler: fragmentation threshold, transmission power, and retry limit on energy consumption. Based on the study, we design run-time adaptation policies and implement them using the OPNET modeler to monitor current channel conditions and battery constraints to appropriately set the parameter values dynamically. We demonstrate that significant energy savings can be achieved by enabling dynamic adaptation in the IEEE 802.11b Data Link Layer.