Ryangsoo Kim

Prefetching-Based Data Dissemination in Vehicular Cloud Systems

In the last decade, vehicular ad hoc networks (VANETs) have been widely studied as an effective method for providing wireless communication connectivity in vehicular transportation systems. In particular, vehicular cloud systems (VCSs) have received abundant interest for the ability to offer a variety of vehicle information services. We consider the data dissemination problem of providing reliable data delivery services from a cloud data center to vehicles through roadside wireless access points (APs) with local data storage. Due to intermittent wireless connectivity and the limited data storage size of roadside wireless APs, the question of how to use the limited resources of the wireless APs is one of the most pressing issues affecting data dissemination efficiency in VCSs. In this paper, we devise a vehicle route-based data prefetching scheme, which maximizes data dissemination success probability in an average sense when the size of local data storage is limited and wireless connectivity is stochastically unknown. We propose a greedy algorithm and an online learning algorithm for deterministic and stochastic cases, respectively, to decide how to prefetch a set of data of interest from a data center to roadside wireless APs. Experiment results indicate that the proposed algorithms can achieve efficient data dissemination in a variety of vehicular scenarios.

Asynchronous Medium Access Protocol for Multi-User MIMO Based Uplink WLANs

Multi-user multiple-input multiple-output (MIMO) technology makes it possible for wireless nodes to successfully receive multiple packets from simultaneous transmitters in wireless networks. As it can provide more transmission opportunities without causing collisions, the network throughput performance can be dramatically improved. In this paper, we propose an asynchronous medium access control (MAC) protocol, which enables senders to independently start their transmissions if the access point (AP) can receive more simultaneous packets up to its multi-packet reception capability. This asynchronous protocol makes the multi-user MIMO channel more efficiently used, especially in wireless networks where transmission durations are dynamically varying due to different packet sizes and transmission rates. Through our performance analysis and extensive simulations, we show that the proposed asynchronous MAC protocol achieves significantly higher uplink throughput performance in multi-user MIMO wireless networks.

Power-saving strategy for balancing energy and delay performance in WLANs

In wireless local area networks (WLANs), power conservation for mobile devices is considered as one of the most important issues because it effectively prolongs the battery life of mobile devices. The IEEE 802.11 standard specifies a power-saving mode that allows mobile nodes to adaptively operate in sleep and wake modes to reduce the overall energy consumption. In the IEEE 802.11 power-saving mode, the access point (AP) can adjust the number of nodes in wake mode at every beacon interval. In this paper, we first investigate how the number of nodes in wake mode affects both energy consumption and delay performance in WLANs. We then propose a balanced power-saving strategy, which determines an appropriate number of nodes in wake mode based on a trade-off between energy consumption and packet delay. Through a performance analysis and extensive simulations, we show that our proposed scheme effectively reduces overall energy consumption while retaining low packet delay.

TDoA localization for wireless networks with imperfect clock synchronization

With the advent of an ubiquitous computing environment, the need to capture location information and incorporate it into applications has become urgent. In particular, time difference-of-arrival (TDoA) localization is considered to be a cost effective and accurate localization technique. However, the local clocks of the access points (APs) are required to be fully synchronized with each other. If clock offsets exist, TDoA localization can yield a poor localization performance. In this paper, we propose a TDoA-based localization technique that simultaneously estimates the client location and clock offsets of the APs. The simulation and experimental results show that the proposed localization algorithm alleviates the impact of imperfect clock synchronization among APs, thereby improving the localization accuracy.

Robust indoor localization based on hybrid Bayesian graphical models

In this paper, we study the problem of accurately estimating the location of indoor wireless devices which, due to its vast application areas, has continued to generate much interest both in the academia and industry. Specifically, we consider the location estimation problem and develop non-hybrid Bayesian location estimators for when received signal strength (RSS) and/or time of arrival (TOA) measurements between the target node (TN) and designated beacon nodes (BNs) in the network are obtainable. However, RSS- and TOA-based location estimators can be inaccurate when the RF-characteristics are not stable and time synchronization between the TN and BNs is not set up properly, respectively. To mitigate the disadvantages of these two location estimators, we propose the hybrid Bayesian location estimators. We show, through the results of extensive simulation experiments conducted that in comparison with the non-hybrid estimators, the hybrid Bayesian location estimators are more robust in the localization environment where RSS/TOA measurement precision varies.

Beacon selection for localisation in IEEE 802.11 wireless infrastructure

Given the widespread deployment of IEEE 802.11-based access points APs, received signal strength RSS-based localisation algorithms, which estimate the location of clients by measuring RSS at the installed APs, have drawn considerable attention. However, the accuracy of RSS-based localisation depends heavily on the RF and geometry characteristics between the client and the APs. In order to improve the localisation accuracy, the selection of an appropriate AP set without outliers is an important and challenging issue. In this paper, we first propose to use Cramer-Rao Bound, obtained from the average Fisher Information Matrix, as a criterion for selecting an appropriate AP set. Then, based on the proposed selection criterion, we develop a batch beacon selection algorithm that searches all the possible AP sets. Furthermore, to implement real-time mobile client localisation by alleviating computational complexity, we devise an online beacon selection algorithm.

Channel-aware repetitive data collection in wireless sensor networks

Summary Wireless sensor networking technology has been applied in practice to a variety of information-gathering infrastructures, where sensing data are repetitively delivered to a data collector within a session period. For efficient energy conservation, each sensor node can wait for a higher channel gain before it begins the transmission of sensing data and transmits them with a power that is inversely proportional to the channel gain. However, if the node waits for higher channel gain, switching to the sleeping mode takes a longer time. We formulate this channel-aware data transmission problem using an optimization problem with linear constraints. The numerical simulations indicate that the proposed method significantly reduces the energy consumption compared with other heuristic methods. Copyright

Inter-BS Interference-Aware Transmission Coordination for Millimeter Wave Networks

In millimeter-wave wireless networks, base stations (BSs) are capable of performing beamforming transmissions to deliver downlink data packets to user equipments. Despite the advantage of spatial diversity (through beamforming), as the number of BSs installed in the network increases, the packet delivery success probability may decrease because of the increasing interference from the beamforming transmissions of neighboring BSs. We propose the downlink transmission coordination methods that allow each BS to decide whether or not to perform a downlink transmission with respect to the level of inter-BS interferences.

Poster: Greedy data dissemination algorithm for infrastructure-to-vehicle services

This paper considers a data dissemination problem for vehicular cloud systems, in which delivery services from a data center provide data to vehicles through roadside wireless access points having local data storages. We propose a greedy data prefetching algorithm; by exploiting the completely predictable route information and the stochastic characteristics of the communication with APs, the algorithm predetermines how to distribute a set of data from a data center to local data storages, and minimizes the amount of data dissemination. The results from extensive simulations show that the proposed scheme can achieve efficient data dissemination in a variety of vehicular scenarios while minimizing the data transfer.

Poster: Drone Can Find Lost Smartphones

In this paper, we propose a single-drone-based localization for radio frequency (RF) sources in an outdoor environment. For fast and accurate localization, we propose a dynamic trajectory planning scheme, which guides the RF scanning drone toward a direction minimizing the geometric dilution of precision (GDOP) in order to minimize the uncertainty of location estimation for target RF sources.