A Dynamic and Adaptive Transmission Scheme for Both Solving Uplink/Downlink Unfairness and Performance Anomaly Problems in a Multi-Rate WLAN

Abstract: Uplink/downlink fairness and performance efficiency are both considerable issues in an IEEE 802.11 multi-rate Wireless Local Area Network (WLAN). The IEEE 802.11 Distributed Coordination Function (DCF) provides equal medium access probability to all transmitters that cause the access point (AP) to obtain less bandwidth than that of the wireless mobile stations to download traffic when the number of mobile stations is larger than one. Furthermore, the WLAN with infrastructure mode also has the performance anomaly problem that the system throughput was seriously degraded by the transmissions of lower date rate transmitters in a multi-rate environment. In the past studies, many mechanisms have been proposed to solve the uplink/downlink unfairness problem, such as the transmission opportunity mechanism (TXOP), the multiple backoff timer mechanism (MBT) and the asymmetric access point mechanism (AAP). In order to improve the performance efficiency, contention window differentiation mechanism (CWD), packet size differentiation mechanism (PSD) and interframe gap differentiation mechanism (IFG) have been proposed recently. The proposed mechanisms, however, did not take both uplink/downlink unfairness and performance anomaly problems into consideration at the same time. In fact, the two problems occur simultaneously in practical WLAN environments. In this paper, we propose a dynamic and adaptive transmission scheme (DAT) to deal with the both problems. Each wireless mobile station will consider its data rate to decide the number of packets to transmit when it gets the privilege to access medium. Moreover, the AP has more right to download more packets for the purpose of balancing total uplink traffic. The system throughput of the proposed DAT is discussed and validated by the simulations and analytical results. The simulations also show that the proposed DAT outperforms the previous mechanisms

Seamless Guidance System Combining GPS, BLE Beacon, and NFC Technologies

Users rely increasingly on Location-Based Services (LBS) and automated navigation/guidance systems nowadays. However, while such services are easily implemented in outdoor environments using Global Positioning System (GPS) technology, a requirement still exists for accurate localization and guidance schemes in indoor settings. Accordingly, the present study proposes a system based on GPS, Bluetooth Low Energy (BLE) beacons, and Near Field Communication (NFC) technology. Through establishing graphic information and the design of algorithm, this study develops a guidance system for indoors and outdoors on smart phones, wishing to give user perfect smart life through this system. The proposed system is implemented on a smart phone and evaluated on a student campus environment. The experimental results confirm the ability of the proposed app to switch automatically from an outdoor mode to an indoor mode and to guide the user to requested target destination via the shortest possible route

An Indoor Guidance System Combining Near Field Communication and Bluetooth Low Energy Beacon Technologies

Users rely increasingly on Location-Based Services (LBS) and automated navigation/guidance systems nowadays. However, while such services are easily implemented in outdoor environments using Global Positioning System (GPS) technology, a requirement still exists for accurate localization and guidance schemes in indoor settings. Accordingly, the present study presents a methodology based on GPS, Bluetooth Low Energy (BLE) beacons, and Near Field Communication (NFC) technology. Through establishing graphic information and the design of algorithm, this study develops a guidance system for indoor and outdoor on smartphones, with aim to provide users a smart life through this system. The presented system is implemented on a smartphone and evaluated on a student campus environment. The experimental results confirm the ability of the presented app to switch automatically from an outdoor mode to an indoor mode and to guide the user to the requested target destination via the shortest possible route

A Distributed Algorithm for Fast Mining Frequent Patterns in Limited and Varying Network Bandwidth Environments

Data mining is a set of methods used to mine hidden information from data. It mainly includes frequent pattern mining, sequential pattern mining, classification, and clustering. Frequent pattern mining is used to discover the correlation among various sets of items within large databases. The rapid upward trend in data size slows the mining of frequent patterns. Numerous studies have attempted to develop algorithms that operate in distributed computing environments to accelerate the mining process. FLR-mining (Fast, Load balancing and Resource efficient mining algorithm) is one of the fastest methods of mining with efficient consideration of load balancing and resources. FLR-mining can automatically determine the appropriate number of computing nodes. However, FLR-mining and existing methods assume that the network bandwidth is constant. In practical distributed and many-task computing systems, this assumption fails because there are packet collisions caused by many mining tasks that run in a simultaneous manner. Therefore, a method that can consider the varying network bandwidth is necessary. In this study, we propose a method that can rapidly mine frequent patterns under the varying network bandwidth. The proposed method can also determine the appropriate number of computing nodes to efficiently utilize computing resources and achieve load balancing. Through empirical evaluation, the proposed method is shown to deliver excellent performance in terms of execution efficiency and load balancing