Showing papers by "Samir R. Das published in 2012"

Geo-fencing: geographical-fencing based energy-aware proactive framework for mobile devices

Abstract: Location-based services (LBSs) are often based on an area or place as opposed to an accurate determination of the precise location. However, current mobile software frameworks are geared towards using specific hardware devices (e.g., GPS or 3G or WiFi interfaces) for as precise localization as possible using that device, often at the cost of a significant energy drain. Further, often the location information is not returned promptly enough. To address this problem, we design a framework for mobile devices, called Geo-fencing. The proposed framework is based on the observation that users move from one place to another and then stay at that place for a while. These places can be, for example, airports, shopping centers, home, offices and so on. Geo-fencing defines such places as geographic areas bounded by polygons. It assumes people simply move from fence to fence and stay inside fences for a while. The framework is coordinated with available communication chips and sensors based on their energy usage and accuracy provided. The essential goal is to determine when users check in or out of fences in an energy effiecient fashion so that appropriate LBS can be triggered. Windows based smartphones are used to prototype Geo-fencing. Validations are conducted with the resulting traces of outdoor and indoor activities of several users for several months. The results show that Geo-fencing provides an effective framework for use with LBSs with a significant energy saving for mobile devices.

Understanding spatial relationships in resource usage in cellular data networks

Abstract: We conduct a detailed measurement analysis to investigate the spatial characteristics of network resource usage using a large-scale data set collected ‘in situ’ in a nationwide 3G cellular data network. The data set spans over thousands of base stations. We first characterize the spatial correlation in radio resource usage using different statistical techniques. The analysis shows existence of significant spatial correlation that varies during the day, peaking during the middle of the day and waning in the middle of the night. We also use the notion of spectral clustering to show how base stations can be clustered based on how correlated they are in terms of radio resource usage. We show that this produces spatially connected clusters. We also show that only a few clusters exist when clustered optimally. Finally, we use the concept of Granger causality to understand the underlying functional connectivity and flow of influence in the network. We show that roughly one-third of neighboring base station pairs exhibit statistically significant Granger causality, and long causal paths exist in the network. Our observations can lead to development of new techniques for network monitoring and resource management in future cellular data networks.

Opportunistic traffic scheduling in cellular data networks

Abstract: Cellular data networks are experiencing a serious capacity crunch in the face of exponential increase in mobile data traffic volume. New traffic management techniques are needed to improve network and user perceived performance. In this work, we consider the existence of a higher-layer, agent-based scheduling system that could potentially delay scheduling of low priority flows at peak loads. The priorities are assumed to be user or application tagged, either automatically or manually. The general goal is to potentially move the low priority flows in time and space opportunistically to reduce the overall resource needs. We develop and evaluate two scheduling schemes - one based on a straightforward greedy method that requires real-time load monitoring and the other based on model-based estimation of traffic loads and subscriber mobility based on historical data. Simulation results using a large-scale cellular network trace data collected inside a nationwide network show the potential of these approaches in reducing base station resource requirements. This indirectly demonstrates that if providers can incentivize subscribers to tag certain flows as low priority, they can potentially accommodate a significant number of additional subscribers in the same network without expending any additional resource.

BRAVE: bit-rate adaptation in vehicular environments

Abstract: Rate selection in a wireless network is the problem of estimating the current channel conditions and determining the best physical layer bit rate for the outgoing frames in order to maximize the current throughput. All rate adaptation algorithms in literature arrive at an estimate of the current channel conditions by considering the recent history often in the order of seconds. In vehicular WiFi access networks, the constantly changing wireless channel conditions make the channel history quickly irrelevant. We develop BRAVE - an SNR-based rate adaptation algorithm, which only considers short history (500 ms) to make rate selection decisions. We show that a coarse-grained training approach is sufficient to estimate the SNR thresholds for rate selection as opposed to previous approaches that train on a per environment or a per AP basis. We study three frame-based rate adaptation algorithms and a popular SNR-based rate adaptation algorithm along with BRAVE and highlight their shortcomings in the rapidly changing vehicular WiFi access environment. In order to compare the algorithms under repeatable channel conditions, we also develop and use a novel emulation methodology where a software radio-based programmable noise generator is used to emulate varying link quality under vehicular mobility. We show that BRAVE performs significantly better than several prominent frame-based and the SNR-based rate adaptation algorithms.

btFICA MAC Protocol for High Data Rate WLANs

Abstract: In this paper we develop a new MAC protocol for improving network throughput and hence, channel utilization in wireless LANs that can support very high PHY layer data rates (> 1Gbps). We call our new MAC protocol Busy Tone Assisted Fine-Grained Channel Access (btFICA). btFICA is based upon the framework of a prominent state-of-the-art PHY/MAC scheme for high data rate WLANs, called Fine-Grained Channel Access (FICA). While the rationale behind the FICA scheme appears effective for enhancing channel utilization in high data rate WLANs, a recent study shows that problems, such as deafness, muteness and a form of hidden terminal problem, can easily arise with the FICA MAC protocol. These problems can degrade the network performance, if left unaddressed. This motivates us to develop our btFICA MAC protocol that uses an additional busy tone antenna. btFICA comprehensively solves all of the three problems faced by the FICA MAC protocol, while maintaining the beneficial aspects of the original FICA scheme. Finally, we show via extensive simulations, that btFICA significantly outperforms the original FICA scheme and 802.11 DCF, in different network topologies and traffic scenarios, in terms of channel utilization, per-user-throughput and fairness.

Understanding the FICA MAC Protocol in High Data Rate WLANs

Abstract: Recently wireless radios and hardware technologies have been developed that allow operation on very wide channels and that can support very high physical layer data rates (1Gbps and up). However, it is proven that the conventional 802.11 CSMA/CA MAC protocol causes a drastic under-utilization of such high-speed channels. In order to improve channel utilization, a new scheme, called, Fine-Grained Channel Access (FICA), has been recently put forward. While the FICA approach appears more promising than the other proposed schemes for high data rate WLANs, it has not been studied extensively before. Hence, in this paper, we focus on the FICA MAC protocol, and we study this protocol thoroughly in different traffic scenarios and network topologies. We identify, for the first time, some of the serious problems that can arise with the FICA MAC protocol. We call these problems deafness, muteness and a form of hidden terminal problem. We quantify the impact of these problems on the performance of FICA via extensive simulations. Our results show that under some typical scenarios, FICA can perform even worse than the conventional 802.11 DCF, in terms of channel utilization, per-user-throughput or fairness. The insights obtained in this paper motivates the need for addressing FICA's problems and paves the path for future development of better new MAC protocols for high data rate WLANs.