Many services rely on the Internet to provide their customers with immediate access to information. To provide a stable service to a large number of customers, a service provider needs to monitor demand fluctuations and adjust the number and the location of replica servers around the world. Unfortunately, Flash crowds make it quite difficult to determine good number and locations of replica servers because they must be repositioned very quickly to respond to rapidly changing demands. We are developing ExaPeer, an infrastructure for dynamically repositioning replica servers on the Internet on the basis of demand fluctuations. In this paper we introduce ExaPeer Server Reposition (EPSR), a mechanism that quickly finds appropriate number and locations of replica servers. EPSR is designed to be lightweight and responsive to Flash crowds. EPSR enables us to position replica servers so that no server becomes overloaded. Even though no dedicated server collects global information such as the distribution of clients or the load of all servers over the Internet, the peer-to-peer approach enables EPSR to find number and locations of replica servers quickly enough to respond to flash crowds. Simulation results demonstrate that EPSR locates high-demand areas, estimates their scale correctly and determines appropriate number and locations of replica servers even if the demand for a service increases/decreases rapidly.

This paper proposes a new multi-band received signal strength (MRSS) fingerprinting based indoor location system, which employs the frequency diversity on the conventional single-band received signal strength (RSS) fingerprinting based indoor location system. In the proposed system, the impacts of frequency diversity on the enhancements of positioning accuracy are analyzed. Effectiveness of the proposed system is proved by experimental approach, which was conducted in non line-of-sight (NLOS) environment under the area of 103 m2 at Yagami Campus, Keio University. WLAN access points, which simultaneously transmit dual-band signal of 2.4 and 5.2 GHz, are utilized as transmitters. Likewise, a dual-band WLAN receiver is utilized as a receiver. Signal distances calculated by both Manhattan and Euclidean were classified by K-Nearest Neighbor (KNN) classifier to illustrate the performance of the proposed system. The results confirmed that Frequency diversity attributions of multi-band signal provide accuracy improvement over 50% of the conventional single-band.

In ubiquitous sensor networks, the estimation accuracy of a node location is limited due to the presence of non-line-of-sight (NLOS) paths. To mitigate the NLOS effects, this letter proposes a simple algorithm where NLOS identification is carried out using angle-of-arrival (AOA). Simulation results show that the use of AOA improves NLOS identification rates and location estimation accuracy.

The conventional TDoA (Time Difference of Arrival)-based and RSS (Received Signal Strength)-based location schemes create large positioning errors because of the various wireless channel effects such as path loss, shadowing, and NLoS (Non-Line-of-Sight) components of the multipath channels. In this paper, we propose an improved wireless location scheme which performs a weighted combination of the TDoA and RSS location schemes to improve a detection probability in the mobile-WiMAX femto-cell environments.

Localization is one of the fundamental problems in many wireless sensor networks applications, but most of them require the node to equip special range-determining or angle-determining hardware in order to obtain the position related information. In this paper, we propose a concentric beacons localization algorithm which is a range-free approach. Four anchors are set in the four corners of the square target region, and emit localizing beacons at different power levels, with the information of their position and the estimated range of the beacon. The nodes in this region receive these beacons and compute their positions correspondingly. In region of different scale, we propose two alternative schemes. The one for small scale has lower calculation complexity, and the other has better stability on large scale applications. Simulation results show the estimation error is less than 0.4 times the beacon interval.

Mobile positioning using Received Signal Strength (RSS) measurements is regarded as a low cost solution which is applicable in a wide range of wireless networks. In this paper, we propose a cooperative RSS-based positioning algorithm, that relies on the promising idea of mobile to mobile communications in the next generation of cellular networks. Simulations performed in this paper indicate that utilizing the additional RSS data of the short range communications between Mobile Stations (MS's), enhances the accuracy of the traditional RSS-based positioning algorithms.

Tracking a large quantity of moving target tags simultaneously is essential for the localization and guidance of people in welfare facilities like hospitals and sanatoriums for the aged. The locating system using active RFID technology consists of a number of fixed RFID readers and tags carried by the target objects, or senior people. We compare the performances of several determination algorithms which use the power measurement of received signals emitted by the moving active RFID tags. This letter presents a study on the effect of collision in tracking large quantities of objects based on active RFID real time location system (RTLS). Traditional trilateration, fingerprinting, and well-known LANDMARC algorithm are evaluated and compared with varying number of moving tags through the SystemC-based computer simulation. From the simulation, we show the tradeoff relationship between the number of moving tags and estimation accuracy.

In this paper we present hybrid positioning schemes that combine time of arrival (TOA) and angle of arrival (AOA) measurements from only two base stations (BSs) to locate the mobile station (MS) in non-line-of-sight (NLOS) environments. The proposed methods utilize two TOA circles and two AOA lines to find all the possible intersections to locate the MS without requiring a priori information about the NLOS error. The commonly known Taylor series algorithm (TSA) and the hybrid lines of position algorithm (HLOP) have convergence problems, and the relative positioning between the MS and the BSs greatly affects the location accuracy. The resulting geometry creates a situation where small measurement errors can lead to significant errors in the estimated MS location. Simulation results show that the proposed methods always perform better than TSA and HLOP for different levels of NLOS errors, particularly when the MS/BSs have an undesirable geometric layout.

In this article, we propose a vehicle positioning method that can estimate positions of cars even in areas where the GPS is not available. For the estimation, each car measures the relative distance to a car running in front, communicates the measurements with other cars, and uses the received measurements for estimating its position. In order to estimate the position even if the measurements are received with time-delay, we employed the time-delay tolerant Kalman filtering. For sharing the measurements, it is assumed that a car-to-car communication system is used. Then, the measurements sent from farther cars are received with larger time-delay. It follows that the accuracy of the estimates of farther cars become worse. Hence, the proposed method manages only the states of nearby cars to reduce computing effort. The authors simulated the proposed filtering method and found that the proposed method estimates the positions of nearby cars as accurate as the distributed Kalman filtering.

This paper presents a new methodology, Beacognition, for real-time discovery of the associations between a signal space and arbitrarily defined regions, termed as Semantically Meaningful Areas (SMAs), in the corresponding physical space. It lets the end users develop semantically meaningful location systems using standard 802.11 network beacons as they roam through their environment. The key idea is to discover the unique associations using a beacon popularity model. The popularity measurements are then used to localize the mobile devices. The beacon popularity is computed using an election' algorithm and a new recognition model is presented to perform the localization task. We have implemented such a location system in a five story campus building. The comparative results show significant improvement in localization by achieving on average 83% SMA and 88% Floor recognition rate in less than one minute per SMA training time.

Sensor node localization is an important issue in wireless sensor networks (WSNs) due to the dynamic nature of sensor deployment. Generally, in wireless sensor network localization, the absolute positions of certain anchor nodes are required based on the use of global positioning systems, then all the other nodes are approximately localized using various algorithms based on a coordinate system of the anchors. This paper proposes a neighbor position-based localization algorithm (NPLA) that can greatly enhance the positioning accuracy when compared with current overlapping connectivity localization algorithms that attempt to use the observation of connectivity to a set of anchors to determine a node's position. The proposed method localizes the sensor nodes using both the anchors' positions and neighbor node information. However, unlike existing overlapping-based methods, the proposed NPLA does not assume the same radio transmission range. A simulation study is used to demonstrate the positioning accuracy of the proposed method with different anchor and sensor node densities.

In this paper, we address the issue of mobile positioning and tracking after measurements have been made on the distances and possibly directions between an MS (mobile station) and its nearby base stations (BS's). The measurements can come from the time of arrival (TOA), the time sum of arrival (TSOA), the time difference of arrival (TDOA), and the angle of arrival (AOA). They are in general corrupted with measurement noise and NLOS (non-line-of-sight) error. The NLOS error is the dominant factor that degrades the accuracy of mobile positioning. Assuming specific statistic models for the NLOS error, however, we propose a scheme that significantly reduces its effect. Regardless of which of the first three measurement types (i.e. TOA, TSOA, or TDOA) is used, the proposed scheme computes the MS location in a mathematically unified way. We also propose a method to identify the TOA measurements that are not or only slightly corrupted with NLOS errors. We call them nearly NLOS-error-free TOA measurements. From the signals associated with TOA measurements, AOA information can be obtained and used to aid the MS positioning. Finally, by combining the proposed MS positioning method with Kalman filtering, we propose a scheme to track the movement of the MS.

Impulse Radio (IR)-Ultra Wideband (UWB) enables accurate ranging due to very short duration pulses. Therefore, UWB may provide accurate positioning capability. In order to relax the complexity in circuit implementation, UWB system with low resolution analog digital converters (ADCs) has been investigated. In this paper, the accuracy of UWB positioning with comparators is investigated through experiment. The accuracy of positioning with comparators is compared to that with 8 [bit] ADCs, and effectiveness of the system with the comparators is confirmed within the area of 1.81.8 [m].

Localization of mobile terminals has received considerable attention in wireless communications. In this letter, we present a covariance shaping least squares (CSLS) estimator using time-of-arrival measurements of the signal from the mobile station received at three or more base stations. It is shown that the CSLS estimator yields better performance than the other LS estimators at low signal-to-noise ratio conditions.

Free-space optical communication systems can provide high-speed, improved capacity, cost effective and easy to deploy wireless networks. Experimental investigation on the next generation free-space optical (FSO) communication system utilizing seamless connection of free-space and optical fiber links is presented. A compact antenna which utilizes a miniature fine positioning mirror (FPM) for high-speed beam control and steering is described. The effect of atmospheric turbulence on the beam angle-of-arrival (AOA) fluctuations is shown. The FPM is able to mitigate the power fluctuations at the fiber coupling port caused by this beam angle-of-arrival fluctuations. Experimental results of the FSO system capable of offering stable performance in terms of measured bit-error-rate (BER) showing error free transmission at 2.5 Gbps over extended period of time and improved fiber received power are presented. Also presented are performance results showing stable operation when increasing the FSO communication system data rate from 2.5 Gbps to 10 Gbps as well as WDM experiments.

The location information of ubiquitous objects is one of the key issues for context-aware systems. Therefore, several positioning systems to obtain precise location information have been researched. However, they have scalability and flexibility problems because they need completely configured space with a large number of sensors. To avoid the problems, we proposed a self-organizing location estimation method that uses ad hoc networks and Self-Organizing Maps and needs no prepared space with a large number of sensors. But, as in other similar precise localization methods, the proposed method needs advanced distance measurements unavailable to conventional wireless communication systems. In this paper, the self-organizing location estimation method's modification for distance measurement that uses received signal strength available to conventional wireless communication systems but which fluctuates uncertainly, is described and location estimation accuracy with the modified method is shown.

Today, pedestrian navigation systems for mobile phones use 2-dimensional maps as a navigation media in general. But 3-dimensional maps or scenery images are easier to understand for users than 2-dimensional maps. To use 3-dimensional maps or scenery guidance, the measuring accuracy of user position is essential to understand guidance images. In this paper, we will present a pedestrian navigation system using real scenery photographs as a navigation media, and based on experiments we will report the evaluation result of influence of positioning accuracy on the understandability of navigation. It is shown that 3 meters or less error of positioning is tolerable for pedestrian navigation systems using scenery images.

In this letter, a new blind anti-jammer pre-processor is proposed for GPS receivers to alleviate performance degradation due to strong jammers. Since strong jammers have been successfully removed before despreading, the proposed scheme can effectively extract the signals-of-interest, leading to significant performance enhancement as compared with conventional methods.

The sizes of recent Java-based server-side applications, like J2EE containers, have been increasing continuously. Past techniques for improving the performance of Java applications have targeted relatively small applications. Moreover, when the methods of these small target applications are invoked, they are not usually distributed over the entire memory space. As a result, these techniques cannot be applied efficiently to improve the performance of current large applications. We propose a dynamic code repositioning approach to improve the hit rates of instruction caches and translation look-aside buffers. Profiles of method invocations are collected when the application performs with its heaviest processor load, and the code is repositioned based on these profiles. We also discuss a method-splitting technique to significantly reduce the sizes of methods. Our evaluation of a prototype implementing these techniques indicated 5% improvement in the throughput of the application.

One conventional technique for source localization is to utilize the time-difference-of-arrival (TDOA) measurements of a signal received at spatially separated sensors. A simple TDOA-based location algorithm that combines the advantages of two efficient positioning methods is developed. It is demonstrated that the proposed approach can give optimum performance in geolocation via satellites at different noise conditions.