Peerapol Tinnakornsrisuphap

Characterization of queue fluctuations in probabilistic AQM mechanisms

We develop a framework for studying the interaction of a probabilistic active queue management (AQM) algorithm with a generic end-user congestion-control mechanism. We show that as the number of flows in the network increases, the queue dynamics can be accurately approximated by a simple deterministic process. In addition, we investigate the sources of queue fluctuations in this setup. We characterize two distinct sources of queue fluctuations; one is the deterministic oscillations which can be captured through the aforementioned deterministic process. The other source is the random fluctuations introduced by the probabilistic nature of the marking schemes. We discuss the relationship between these two types of fluctuations and provide insights into how to control them. Concrete examples in this framework are given for several popular algorithms such as Random Early Detection, Random Early Marking and Transmission Control Protocol.

Asymptotic behavior of heterogeneous TCP flows and RED gateway

We introduce a stochastic model of a bottleneck ECN/RED gateway under a large number of heterogeneous TCP flows, i.e., flows with diverse round-trip delays and session dynamics. We investigate the asymptotic behavior of the system and show that as the number of flows becomes large, the buffer dynamics and aggregate traffic simplify and can be accurately described by simple stochastic recursions independent of the number of flows, resulting in a scalable model. Based on the Central Limit analysis in the paper, we identify the sources of fluctuations in queue size and describe the relationship between the system parameters such as the marking function and variance of queue size. A closed-form approximation for the mean queue size as a function of system parameters is provided from a simple steady-state analysis. Numerical examples are provided to validate our results.

Indoor Positioning Using Femtocells

The ability to locate oneself indoors on a map and navigate to desired areas has a wide range of applications. GPS and macro cell tower based positioning are not very effective indoors due to poor signal quality or limited accuracy in location estimation. We propose to solve this problem by deploying an indoor network of femtocells and determining the position of a 3G mobile using the downlink and uplink signals. The measurement of signals from a group of femtocells at the mobile and the measurement of the mobiles transmitted signal at group of femtocells is used for triangulation of the mobiles position. It is shown that a combination of these methods with a cleverly designed transmission schedule involving time orthogonalization of the femtocell signals can enable accurate indoor positioning.

Coverage and capacity analysis of hybrid home networks

A hybrid home network is a network consisting of hybrid devices capable of both Wi-Fi and powerline communications. We provide a comparison of coverage and capacity between hybrid, standalone Wi-Fi, and standalone powerline networks. We demonstrate that hybrid networks improve both the coverage and the capacity of a home network to simultaneously support high definition video streaming and mobile devices. The analysis is extended to show that the benefits of hybrid networks are amplified when multi-hop topologies are supported.

On the behavior of ECN/RED gateways under a large number of TCP flows: Limit theorems

We consider a discrete-time stochastic model of an ECN/RED gateway where competing TCP sources share the link capacity. As the number of competing flows becomes large, the asymptotic queue behavior (normalized by the number of flows) at the gateway can be described by a simple recursion and the throughput behavior of individual TCP flows becomes asymptotically independent. A Central Limit Theorem complement is also presented, yielding a more accurate characterization of the asymptotic queue size. These results suggest a scalable yet accurate model of this complex large-scale stochastic feedback system, and crisply reveal the sources of queue fluctuations.

Lifetime-dependent battery usage optimization for grid-connected residential systems

Batteries are an important element for residences that are in grid-connected systems with energy procurement. They provide storage for local generation and a buffer against the inconsistent output from renewables such as rooftop solar. In addition, they can independently provide a medium for buying and selling retail energy. The growing deployment of reverse power-operation systems provides residences with the ability to buy and sell energy at the retail time-of-use rate. While the nonlinear models of chemical batteries have been extensively studied, they have not been applied to strategies for residential battery use. In this work, we develop a formulation for battery usage based on more realistic battery models, optimizing the benefit of discharging the battery. We design the scheme for the actual use of batteries in an energy-trading environment, considering the total cost of ownership and return on investment. Finally, we simulate the system in different geographic locations using the actual time-of-use pricing for each, and demonstrating return on investment in as few as 5 years.

Facilitating active hand-in using out-of-band link at femtocell

Active hand-in refers to the ability for a voice or data connection for a mobile on the macrocell to be seamlessly handed off to the target femtocell. The challenge for active hand-in is that a large number of femtocells share limited PN offsets in a geographical region and hence the target femtocell cannot be identified uniquely by its PN offset. An ideal solution would be one that requires no hardware or software changes to macro network or legacy mobiles. This paper discusses a method of using an out-of-band (OOB) radio integrated with the femtocell to assist in active hand-in by uniquely identifying the target femtocell with the help of OOB link identifiers.