Recent advances in near-field communication (NFC) technology aim to significantly improve the range and robustness of NFC connections. Traditionally, NFC communication requires precise alignment between the transmitting and receiving antennas, which typically operate within a few centimeters. This limitation has restricted the wide applicability of NFC in various contexts. In this work, we address these challenges by leveraging generative adversarial networks (GANs) to effectively restore signals affected by attenuation and distortion. By employing a GAN-based model suitable for wireless reception signal processing, we enhance the integrity of NFC signals, enabling robust communication at longer distances with less precise alignment. The proposed method demonstrates that the signal restoration at a distance of 5x the reference distance is very similar to the signal at the reference distance, while preserving the clock recovery and decoding performance of the receiver at the reference distance and maintaining security with a share key approach. This paper provides a comprehensive analysis of the integration of GAN techniques into NFC systems, offering insights into the implications of signal restoration and practical deployment considerations.

In recent advancements in sensor and artificial intelligence technologies, the reliability of gesture recognition has significantly improved, prompting various industrial fields to adopt this technology. However, most gesture recognition systems rely on optical methods because of their high accuracy, despite require complex and computationally intensive processes. Moreover, these systems are associated with high construction costs and are susceptible to environmental factors. This paper introduces a novel gesture recognition system, which effectively tracks and estimates gestures using cost-effective ultra-wideband (UWB) sensors and inertial measurement units (IMU). The system acquires position data of gesture through UWB sensors and includes essential data processing steps such as the detection and removal of abnormal data via IMU, data smoothing with a Kalman filter, and data normalization and scaling. Notably, normalization and scaling are achieved by converting the position data into grayscale images, ensuring the consistency of data features and enhancing gesture recognition accuracy across diverse users. The proposed system employs a convolutional neural network (CNN) model to estimate gestures from these images. Comparative analyses demonstrate that the proposed system exhibits superior gesture classification performance compared to systems utilizing a long-short term memory (LSTM) model and those employing the same CNN model without the aforementioned data processing steps. Therefore, this system is not only cost-effective but also efficiently tracks and estimates gestures, offering significant improvements over existing methods.

In general, as the moving distance increases, positioning accuracy degradation due to cumulative error is pointed out as a major problem in DR (Dead Reckoning). The distance-based positioning system has the advantage of high positioning accuracy depending on the sensor used. However, in environments where the use of infrastructure is restricted, such as security facilities or disaster environments, its utilization is limited, and Line of Sight (LOS) between devices must be guaranteed. To compensate for those limitations, we propose a framework for resetting the initial point of an object in DR. In order to reduce the position error that increases in proportion to the accumulated distance of DR, a method of resetting the starting point of DR to the position derived by distance-based trilateration was adopted. However, the process of resetting every moment when the trilateration-based position is derived can increase the system overhead and cause a positioning delay. Therefore, we derived the optimal starting point reset position and frequency by using Deep Reinforcement Learning (DRL). Through simulation, we verified that the proposed system improves the positioning accuracy compared to conventional DR through low resource consumption.

This paper suggests a novel method of detecting and estimating the position of Unmanned Aerial Vehicle (UAV) with a single monocular camera only. As the leverage of UAV is keep on increasing, the related research has been extremely developed. To successfully use a UAV in a variety of missions, a precise localization technique is essential. However, there is still a lack of research to accurately measure the vehicle's present altitude. Thus, this study conducted a simple but accurate altitude measurement method using a camera. First, UAV detection is initially proceeded by using a deep learning approach. After determining that the object displayed in the image is UAV, the altitude is calculated with a distance measuring formula using the camera's Field of View (FOV). Besides, zooming, cropping, and some image processing are performed to enhance the accuracy of the altitude value. As a result, average errors of less than 5% and errors of up to 60cm were obtained, which is an improvement over previous altitude measurement techniques. This method can calibrate the altitude of the UAV immediately in a relatively inexpensive and simple way.

As the interest in unmanned vehicles increases, much research is under way to improve their accuracy of location estimation. Among them, RTK-GPS is the most used in using GNSS. The RTK-GPS has been widely used for surveying and mapping. So it was usually used in static or low speed conditions. The RTCM message, which is the core of RTK-GPS, is usually provided and used in 1Hz. In this paper, we investigate whether the current transmission rate of RTCM message is good for unmanned vehicle (UV) usage and also analyze whether increase of the RTCM message transmission rate is possible. Then, we examine the effect of UV speed and RTCM message transmission rate on RTK-GPS. Finally, we discuss the challenges and solutions of increasing the RTCM message transmission rate.

This poster presents a virtual control interface for Unmanned Vehicle System (UVS), to improve scalability and accessibility of Human-Computer Interaction (HCI) in their maneuvering. After the first remote control vehicle was born, the remote control unit was paired with a single vehicle for safety and security. To overcome this constrained remote control design, we propose a concept that a single manufacturing stand-alone RC can control one or several unmanned vehicles (UVs), regardless of vehicle type, named RC Function Virtualization (RFV). We can abstract the RC input to a high-level set of control commands and apply it to the numerous types of UVs connected through a wireless network. Our contribution is the separation of the RC and UV pairs so that the user can control all types of UVs even mixed types of UVs. We implemented the prototype of the RFV system, and demonstrated with Unmanned Ground Vehicle (UGV), Unmanned Air Vehicle (UAV), and the combinations of them, with only one RC.

Over the past decade, techniques for remote control vehicles (RCVs) have progressed a lot, and RCVs are receiving huge attention in various fields. Since RCVs, such as drones, have high mobility, it is important for operators to control RCVs reliably. Thus, to keep monitoring and controlling RCVs, operators continuously exchange control packets with RCVs by wireless. However, control packets can be delayed or lost due to any communication or network problems, which may cause collisions or crashes. To overcome this limitation, in this paper, we propose DupCon, a new control packet transmission scheme. Considering characteristics of packets, DupCon duplicates only control packets, not data packets, and transmits the originals and their duplicates through different paths, respectively. We designed and implemented DupCon on real devices. Moreover, we conduct an analysis on DupCon to demonstrate the validity of DupCon theoretically. Furthermore, we conducted various experiments, and the results show that DupCon improves reliability and stability of real-time remote vehicle control.

Supported by the technological advancements in wireless communication systems, current mobile devices are capable of utilizing diverse radio interfaces. Furthermore, there are various networks around the mobile devices in heterogeneous networks. If the mobile devices are aware of the status of channels used by different communications, the devices can utilize a wide range of network options intelligently in heterogeneous networks. However, it is not easy for mobile devices to estimate the quality of channels used by different networks because of differences among communication standards. To overcome this limitation, we view the channel map used for Bluetooth communications from a new angle. In this paper, we propose a new scheme which utilizes the channel map to estimate channels' qualities of other standards, not of Bluetooth. Using the proposed scheme named BluS, mobile devices can estimate channels' qualities of standards using the 2.4 GHz ISM band. Therefore, the devices with BluS are able to make decisions more intelligently and properly in heterogeneous networks. We implemented BluS on off-the-shelf smartphones and conducted extensive experiments and analysis to verify the performance of BluS.

Today’s mobile devices mostly contain more than one wireless interface for Internet connection. Smartphones mostly have both LTE and Wi‐Fi for data communication through Internet. Although the availability of Wi‐Fi is incomparable to that of cellular network, its strength lies in the low cost and high data rate due to continuous PHY and MAC advancement of 802.11 protocol extensions. In this paper, we propose a device‐centric system that performs cost‐effective network connectivity to the mobile device by selectively activating Wi‐Fi communication according to the device mobility and corresponding history of Wi‐Fi usage. By analyzing the device mobility using attached sensors, the system selects appropriate Wi‐Fi that has been often used in that mobility state. The system was implemented in actual mobile devices that were used to several experiments we designed to prove high performance of the system.

Many varied mobile device networks have been developed with the advancement of communication and network technologies. Cellular data networks are currently the most widely used, and the number of cellular network subscriptions has increased steadily. Most recent wireless access technologies employ asymmetric uplinks and downlinks because mobile subscribers usually download contents from the Internet. Therefore, most cellular network service providers allocate more bandwidth to downlinks than uplinks for mobile subscribers. However, this asymmetry can have unexpected influence on network performance, particularly TCP performance. When the uplink interface is congested, TCP ACK packets are delayed by TCP data packets on the uplink, causing considerable TCP retransmissions on the downlink channel. Thus, downlink bandwidth cannot be fully utilized, which results in significantly degraded downlink throughput. To resolve this problem, this paper proposes a feedback scheme, network traffic chunk regulator (NCR). We analyzed the aforementioned problem through the empirical study, and we designed and implemented NCR based on the analysis. NCR adaptively controls TCP according to the degree of link usage asymmetry. We evaluate NCR performance through simulations and experiments with real devices. We verify that the proposed scheme allows the downlink traffic to not interfere with the aggressive uplink traffic. Thus, NCR increases total link utilization and aggregated throughput significantly, without imposing additional overhead on base or mobile stations.

In this paper, we design and implement an asynchronous multi-device acoustic localization system. Although the relative position and distance can be useful to many applications such as drone swarming, not much research has been conducted on the field. As synchronizing multiple devices can be difficult or even impossible with certain hardware, we devised an asynchronous algorithm that provides a high accuracy ranging and localization. A high performance ranging and localization technique that uses a relatively minor source, sound, can provide a new set of characteristics. Also, the proposed design uses multiple devices to enhance the performance of each and all of the ranging results. Our proposed algorithm can work on most commercial devices that have acoustic capability of emitting a specific sound and recording general sound. In this paper, the architecture of the entire system, the description of the algorithms, and the evaluation of the system are elaborated.

We propose a unified platform for multiple unmanned aerial vehicles (UAV). Recently, the UAV technology has seen a great development. However, the capability of single drone1 is yet limited by its physical features. To better enhance the capability of drones, we have devised and implemented a fleet based multi-UAV platform. Our proposed platform consists of powerful network functions and enhanced control and sensing algorithms, so that a unified fleet control can be accomplished. Further, it provides a platform for applications that require multiple UAVs working together. The network functions of the proposed platform achieves a strong connectivity and robustness, and a precise relative and absolute localization enables a fleet based control system. With the help of core modules, the proposed platform achieves a well controlled fleet flight and network management.

The demand of mobile traffic increases tremendously as various Internet services are provided to mobile phones and computing devices, making mobile carriers increase the capacity of their cellular network. Since current cell towers and auxiliary devices cannot carry an excessive amount of traffic, several mobile carriers try to install low cost wireless equipment such as a Wi-Fi access point (AP) in order to offload overloaded traffic on cell towers. However, APs are installed randomly unlike cell towers because they can be installed by anyone and anywhere. The randomized allocation of APs incurs interference that causes serious degradation of wireless communication quality. Therefore, it is necessary to design mobile devices to use the environment or channel that contains the least interference for proper Wi-Fi communication. In order to make a mobile device experience the best wireless download quality, this paper proposes a novel AP selection mechanism that selects an AP that contains the least interference level compared to others with different number of communicating devices and amount of traffic load. The proposed selection mechanism does not require any additional feedback from nearby devices or APs. Performance evaluation was done by using real mobile devices with open source platform called Android.

The 2.4 GHz ISM band is one of the most widely used radio bands, and many wireless communication techniques, such as IEEE 802.11, Bluetooth (BT), and ZigBee, use the band. Thus, the interference problem in the band has been an important issue. BT uses BT channel maps which indicate qualities of BT channels to reduce the interference. Fundamentally, the channel map is created after a connection between two BT devices is established, and it is designed to suit BT communications. Viewing the channel map from a new angle, we propose a new scheme which estimates channels' qualities of other standards, not of BT. The proposed scheme named BluS can create the channel map without any BT connection, and estimate channels' qualities of standards using the 2.4 GHz ISM band. We implemented BluS on off-the-shelf smartphones and conducted diverse experiments to verify the performance of BluS. Through the experiments, we confirm that BluS can estimate the channels' qualities accurately and that it is suitable for mobile devices because BluS uses low power.

In recent years, due to the technological development of various kinds of drones, also known as unmanned aerial vehicles (UAVs), drones have emerged as an effective solution for a wide area of applications. In such applications, employing multiple drones promises a better way to carry out a given mission than employing a single drone. To utilize multiple drones, all drones should establish a network that can provide connectivity among themselves. In this paper, we propose GCS-routing, a routing protocol for multiple drones employed by a ground control system (GCS). GCS-routing utilizes the information of drones that can be obtained from GCS, such as geographic information and per-drone flight schedules. The actual implementation of GCS-routing was applied to a fleet of drones, and evaluated in various aspects.

In modern medical service, various medical devices are used. Among these instruments, endoscope is one the most common, and versatile device, which can be used in various situations. Endoscopy is the best screening and diagnostic method allowing physician to examine the patients inner body without causing any harm. However, the narrow view of endoscopic images causes hardship to endoscopists in the procedure of discriminating abnormal from normal tissues. In this paper, we propose a lesion detection gastroscopy system with mosaic image that can assist endoscopist in identifying the lesions. To precisely classify the lesions, we devise a novel classification method named as DSA and visualize the abnormal region clearly to assist endoscopists for lesion detection.

Wireless multi-hop networks are scalable in that devices can easily connect to the network. Such scalability is also required in IoT. However, wireless multi-hop network mostly suffers from high probability of transmission failure due to interference, and nodes connected to the network often experience connection loss and subsequent segment loss which node mobility and routing update incur. Due to the fact that the congestion is not a sole reason for segment loss in wireless multi-hop network, the congestion control of TCP should consider momentary link instability, which unnecessarily reduces transmission speed. For this reason, this paper suggests adjustment of slow-start threshold (ssthresh) value which is used for congestion control algorithm. The adjustment algorithm is called adaptive ssthresh decision ASD algorithm that is to reduce unnecessary decrease of transmission speed in wireless multi-hop network.

With the rapid proliferation of drones, there have been numbers of opportunities and challenges in drone application research area. One of the highlighted topics about the drones is constructing an ad-hoc network of drones and utilizing each as an access point (AP) to build an instant network infrastructure. However, there has been no research about drones optimal position improving network service quality of end users. We analyze the drone-based network infrastructure in terms of the network capacity allocation, and propose a drone formation algorithm that determines the 3D geographic location of each drone. Since each drone is hovering in the air while acting as an AP, its altitude must be also considered for the efficiency and performance of wireless communication. We assume the signal propagation model of the drone to be the shape of a sphere and define the relationship between the altitude and the coverage area of the drone. With this property, our algorithm finds the appropriate coordinates of drones one by one. Through the mathematical analysis, we show that the proposed algorithm can make drone-based network infrastructure provide reliable and user-satisfying network service.

In this paper, we propose a novel anti-phishing scheme, image code-based anti-phishing scheme ICAP, for securing mobile access through an image code. The proposed scheme can protect mobile users from phishing attack and side-glance attack which are threats to mobile environment. The proposed scheme employs the image code as the interaction between a mobile device and a server. This image code can maintain the quality of user-interface and protect the user from the side-glance attack. The proposed scheme basically uses the quick response code, which is a famous image code and has the human-unreadable property. Moreover, we propose two novel algorithms based on image code to improve our basic scheme; image key encryption, and image code identity-based encryption. The proposed scheme can choose one of two algorithms for its objective, and each algorithm has its own advantage. Image key encryption is a symmetric algorithm that can improve the transmission and encryption delay and reduces the power consumption. Image code identity-based encryption is an identity-based encryption algorithm which has the advantage of identity-based encryption. Our implementation result shows that our ICIP scheme can defend the phishing attack and side-glance attack, and shows the superiority of delay, power consumption, and accuracy. Copyright © 2016 John Wiley & Sons, Ltd.

These days, since many mobile devices support Wi-Fi, the number of Wi-Fi hotspots are increasing. At the same time, the number of places where users can use wireless LAN are increasing. Unlike the cellular network, the traffic of wireless LAN may not be distributed evenly because there is no supervisor to control the network traffic. In addition, due to the low throughput and the high packet error rate in wireless communication, the network traffic may converge at some Access Points (APs) which take a role of connecting wired and wireless communication interfaces. Therefore, congestion can easily happen at APs in wireless LAN. However, received signal strength indicator (RSSI) frequently used does not mean the network state of AP, and existing sender-based congestion detection and control protocols cannot recognize accurately where the congestion occurs. Therefore, current mobile devices continuously use the connected AP even if it is congested after the association. In this paper, we propose MACoD, the low power AP congestion detection system for mobile devices, in order to resolve aforementioned problems. Furthermore, by conducting diverse simulations, actual experiments, and power consumption analysis, we validate that MACoD can detect congestion effectively and that it is suitable for mobile devices.

Today's smartphones and tablet PCs are equipped with various sensor units and wireless capabilities along with high performance computing units, which make these mobile devices capable of providing a wide range of services. Because of such characteristics, mobile devices consume more network traffic and frequently use multiple Internet services at the same time. The performance degradation of a foreground service happens frequently due to concurrently running background services in a mobile device. In this paper, we propose NetPIS, Network Performance Isolation Scheme for QoE, which resolves the aforementioned problem by applying the concept of performance isolation to the foreground service. NetPIS is the receiver-based scheme suitable for mobile devices without any modification on senders. Furthermore, unlike most performance isolation implemented by virtual machines, we suggest a scheme that does not require virtualization that might be heavy for mobile devices. The proposed scheme was implemented on a smartphone by modifying the kernel, and various experiments were conducted to evaluate the advanced system behavior of NetPIS.

The rapid development of UAV technology has opened up numerous applications. Further, cooperating drones\footnote{In this paper, we refer to all types of UAVs as drones.} possess a great potential in various areas of applications. Yet, there has not been a platform for a fleet of drones. It is rather difficult to control multiple drones through a single ground control station. In fact, drones need to consistently exchange flight information to maintain the formation of the fleet and follow the commands given from the GCS. Thus, drones need a robust network established among the fleet to provide a fleet control. In this paper, we propose Net-Drone, a multi-drone platform for applications that require cooperation of multiple drones. Net-Drone is equipped with strong network functionalities to provide a control system for a fleet of drones. Through case studies conducted with a prototype implementation, the proposed system is demonstrated. Video of the conducted case study can be found in http://youtu.be/lFaWsEmiQvw.

No abstract available.

In this paper, we design and implement an asynchronous multi-device acoustic localization system. Although the relative position and distance can be useful to many applications such as drone swarming, not much research has been conducted on the field. As synchronizing multiple devices can be difficult or even impossible with certain hardware, we devised an asynchronous algorithm that provides a high accuracy ranging and localization. A high performance ranging and localization technique that uses a relatively minor source, sound, can provide a new set of characteristics. Our proposed algorithm can work on most commercial devices that have acoustic capabilities.

Even though people of all social standings use current mobile devices in the wide spectrum of purpose from entertainment tools to communication means, some issues with real-time video streaming in hostile wireless environment still exist. In this article, we introduce CoSA , a link-aware real-time video streaming system for mobile devices. The proposed system utilizes a 3D camera to distinguish the region of importance (ROI) and non-ROI region within the video frame. Based on the link-state feedback from the receiver, the proposed system allocates a higher bandwidth for the region that is classified as ROI and a lower bandwidth for non-ROI in the video stream by reducing the video's bit rate. We implemented CoSA in a real test-bed where the IEEE 802.11 is employed as a medium for wireless networking. Furthermore, we verified the effectiveness of the proposed system by conducting a thorough empirical study. The results indicate that the proposed system enables real-time video streaming while maintaining a consistent visual quality by dynamically reconfiguring video coding parameters according to the link quality.

With rapid proliferation of mobile devices, it is common to see users using mobile devices for multimedia interaction. Users are not only viewing the contents, but also utilizing it as a medium for expressing their thoughts into a new way of storytelling. However, the way of creating contents via the mobile device is not novel, but simply follows the traditional media production approach. In this paper, we present EMVideo, which is a novel collaboration framework for creating multimedia contents through the mobile device. We believe that the proposed framework can be utilized as an innovative method for digital storytelling and a novel application for social networking.

User's multimedia interaction is facing a paradigm shift from 2D to 3D videos. Nonetheless, it is still difficult to watch 3D videos with a mobile device. With current technological barrier in wireless networking, it is hardly imagined that the timely transmission for a 3D video streaming could be feasible with the mobile device. In this paper, we propose ReMA, a novel 3D video distribution system based on a lightweight compression, a linkadaptive transmission scheme, and a network-side assistance for processing capability. ReMA consists of a 3D data transmitter, a receiver, and an infrastructure for generating and distributing 3D videos. We implemented the proposed system in a real testbed and conducted a thorough empirical evaluation study. Based on the empirical results, the proposed system presents a great promise in streaming 3D video in real-time to the mobile device.

The demand of mobile traffic increases tremendously as various Internet services are provided to mobile phones and computing devices, making mobile carriers to increase capacity of cellular network. Since current cell towers and auxiliary devices cannot carry excessive amount of traffic, several mobile carriers try to install low cost wireless equipments such as Wi-Fi access points (AP) so that some part of mobile traffic can be offloaded to these wireless nodes. Unlike cell towers, APs are installed randomly since there is no specific allocation policy for these license-exempt band equipment that are open to everyone. Since the randomized allocation of APs incur interference that causes serious degradation of wireless communication quality, it is necessary to design mobile devices to communicate in the environment or channel that contains the least interference. In order to make a mobile device experience the best wireless download quality, this paper proposes a novel AP selection mechanism that selects an AP that contains the least interference level compared to others with different number of communicating devices and amount of traffic load. Proposed selection mechanism does not require any additional feedback from nearby devices or APs. Performance evaluation is done by using real mobile devices with open source platform called Android.

Many users want to preserve their visual record of the moment that they want to commemorate. Nonetheless, it is still challenging to remember the actual emotional feeling for that moment even by looking at the old picture. There are methods such as to tag or hide the message within the image. However, tradeoffs exist by attaching additional data for the former method and the quality of the image is degraded for the latter one. It is difficult to avoid these two tradeoffs. In this paper, we propose D-mago to preserve the moment to remember as an image, which is consists of the visual information and the emotional feeling without binding extra data or degrading the quality of the image. To further verify the benefit of our proposed algorithm, we conducted series of evaluation studies to see the effectiveness of the proposed scheme. The results indicate that D-mago overcomes the preceding tradeoffPs by maintaining PSNR above 40 dB.

In this paper, we deal with vulnerabilities in IEEE 802.11 DCF protocol itself and its interaction with transmission control protocol (TCP) protocol. Selfish configurations at medium access control or TCP layer give an increased bandwidth share for selfish stations, and malicious operations disturb overall network operations. We first analyzed the bandwidth allocation for each station under the assumption that all the stations behave well by obeying the protocol. We then expressed the bandwidth allocation with the traffic constraints in network calculus theory in order to guarantee the fair access for well-behaving stations in the presence of misbehaving stations. Based on the network calculus model, we constructed the framework of protecting well-behaving stations from malicious or selfish behaviors, called NetPro. We then built up the proposed NetPro framework in a simulation environment and an empirical test-bed, and we carried out a performance evaluation study. The results indicate that the proposed network calculus-based protection framework successfully secures well-behaving stations from selfish or malicious misbehaviors.

Popular location-based services through smart-phones and other portable devices have brought the tracking of user mobility to the attention in wireless community and have increased its importance continuously. Although the incremental development of GPS technology made the measurement of speed and location of the device more accurate, speed itself cannot fully express the mobility and therefore limits its use in Human and Computer Interaction (HCI). HCI makes user-oriented services possible by interacting computing devices with an user through certain types of I/Os such as keyboards, touch pads and various sensors. It is true that the location and speed of user provides fundamental mobility information for service generators in the world of HCI, but now it is time to give a little deeper aspect of giving user mobility beyond the term speed. In this paper, we scrutinize sensing device motility resulted from human motion and its impact on user mobility estimation, called mobility state, in order to provide conceptual and comprehensive means of mobility including speed. Then we propose Device & User mobility Tracking Algorithm (DUTA) that accurately assess the mobility state without incurring unnecessary power consumption.

Programmable wireless devices which can perceive the current radio environment, decide available spectra, and dynamically change the radio access method, and networking protocols have been proposed to improve spectrum usage, interference mitigation, and connectivity. However, these transitions are currently lacking at upper layers. In this paper, we propose an upper layer cognitive system beyond channel sensing effectiveness and spectrum utilization achieved in adjusting PHY and MAC parameter settings. The proposed cognitive video streaming system achieves end-to-end goals at an upper video layer: quality of experience, service continuity, and survivability. Based on the link state of the receiver, the proposed system identifies areas of importance in the image stream, allocates higher bandwidth for the important areas compared to the other areas which is adjusted to use the less bandwidth with CoSA encoder and decoder, and receive the link state feedback from the receiver. To further understand the CoSA's benefit, we implemented two real test-beds for the cognitive video streaming system where the one uses conventional IEEE 802.11 networking technologies and the other employs a software defined radio platform, and performed a performance evaluation study in order to see the effectiveness of the proposed scheme. The results indicate that the proposed system can dynamically change actual data rates according to SINR feedback, which results in at least 180% improvement of transmission time compared to conventional method, while maintaining PSNR range between 30 to 40 dB with eminently reduced data size.

Recently, the release of trace data sets from several wireless network communities has stimulated much research on empirical mobility models in wireless local area networks. Many of these models have tried to extract the user mobile features from the trace data and establish the mobility model that can be used to infer or determine user mobile patterns. However, these models have ambiguously used user association patterns and user mobile patterns in realizing mobility models, where the association patterns can be perceived directly from the trace data and the user mobile patterns can be filtered from the former. The limitation of the resulting mobility model is that it depends too much on the placement of access points (APs), and thus, it is limited to represent general user mobility. In this paper, we build a dual mobility model (DMM) to describe user association patterns and mobile patterns separately, based on the observation that user association patterns do not always reflect the true user mobile patterns in a densely deployed network but they correspond to the mobile patterns in a sparsely deployed network. Specifically, we first characterized the false-positive registration patterns that result from misunderstanding multiple AP signals. We then extracted those patterns from the original trace data to construct a dense mobility model that describes the user association patterns in dense networks. With the remaining trace data (positive mobile patterns), we built a sparse mobility model that regards the association patterns as mobile patterns. In the sparse modeling, we executed user profiling to accurately characterize user mobile patterns according to user's moving coverage and speed. Finally, we validated that the DMM model with user profiling is statistically more precise than the other mobility model.

In recent years, it has been widely believed in the community that the link reliability is strongly related to received signal strength indicator (RSSI) [or signal-to-interference-plus-noise ratio (SINR)] and external interference makes it unpredictable, which is different from the previous understanding that there is no tight relationship between the link reliability and RSSI (or SINR), but multipath fading causes the unpredictability. However, both cannot fully explain why the unpredictability appears in the link state. In this paper, we unravel the following questions: 1) What causes frame losses that are directly related to intermediate link states? 2) Is RSSI or SINR a right criterion to represent the link reliability? 3) Is there a better measure to assess the link reliability? We first configured a testbed for performing a real measurement study to identify the causes of frame losses, and observed that link reliability depends on an intraframe SINR distribution, not a single value of RSSI (or SINR). We also learned that an RSSI value is not always a good indicator to estimate the link state. We then conducted a further investigation on the intraframe SINR distribution and the relationship between the SINR and link reliability with the ns-2 simulator. Based on these results, we finally propose an interference modeling framework for estimating link states in the presence of wireless interferences. We envision that the framework can be used for developing link-aware protocols to achieve their optimal performance in a hostile wireless environment.

The interconnection among all the components in Smart Grid may expose the customer information that are collected and processed in the smart meter or EMS. The privacy issue becomes more serious when customers collaborated on the power consumption. Even though many research efforts have been focused on enhancing the privacy in both the smart metering infrastructure and the interaction between the customer and the other domains, the privacy on the information exchange among customers has been neglected. In this paper, we propose the security framework of supporting the privacy with anonymity based on a hybrid identity based cryptography scheme, when customers exchange their information to trade their contracted power.

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.

Even though many GPS-free localization algorithms have been proposed to provide reliable positions with high levels of accuracy, most of them, such as centroid, fingerprint, or their variant versions, should require three or more Access Points (APs) to provide sufficient signals for the device. Thus when enough number of APs do not exist in the proximity of the device, the level of position accuracy is deteriorated. In this paper, we present a localization framework of populating virtual access points for localization in sparse wireless networks that can estimate the device position in the environment where the device cannot obtain GPS signal nor sufficient number of AP beacon frames. The proposed framework first gathers beacon frames of adjacent APs periodically and stores the frame information into a device database, then it chooses an adequate number of adjacent APs from the database, and finally it performs a localization algorithm with the chosen APs. To verify the accuracy and robustness of the proposed system, we conducted an experiment in an indoor environment where the deficient number of APs provide their own information, and compared the proposed framework with the original localization algorithm. The results indicate that the proposed framework can pinpoint the current location with acceptable errors in wireless networks with sparse coverage.

A Bayesian navigation system is designed to enhance the performance of the position estimate for a pedestrian in urban canyon environments using particle filtering and digital compass on Smartphone. The particle filtering is used to correct the inaccurate GPS positioning data (position and direction) caused by the strong multipath in the urban areas. The digital compass readings are employed to correct the directional measurements of the positioning information estimated by the particle filtering, but they need to be calibrated with another particle filtering and GPS since they are subject to cumulative errors. In this demo, we demonstrate a real implementation of the proposed Bayesian navigation system on the iPhone 4S. The demo shows the enhanced performance of the new navigation scheme compared to using only GPS signals.

Great interest and much research have emerged to implement and improve the smart grid. Even though the communication network realizes or improves end-to-end smartness at every part of the smart grid, the advanced metering infrastructure (AMI) enhances the smartness more effectively by enabling a two-way communication between customers and the Control Center. We have many possible solutions for the underlying networks for the AMI system, and yet, wireless mesh networks (WMNs) draw much attention in the community because of their flexibility and robustness. One of the most important issues to consider is how to solve the well-known bottleneck problem of WMNs. In this paper, we propose the E-fee scheme to securely protect the collaboration among nodes in the AMI system when WMNs are employed as the underlying network of the system. Then we conduct a theoretical analysis on the protection capability and we also see the results of a performance evaluation study to verify if the E-fee scheme can address the problem. The results indicate that the E-fee scheme is a secure and fair bandwidth allocation technique for the AMI system based on WMSs.

A particle filter is a sequential Monte Carlo method that is superior in estimating the state of a dynamic system under nonlinear/non-Gaussian circumstance. Due to its nature, a particle filter has been regarded as an appropriate algorithm for localization. However, conventional problems, such as sample impoverishment and degeneracy problem, have not been perfectly solved yet. To solve these problems in mobile wireless environment, we propose an enhanced localization scheme, called Gaussian kernel density estimation-based particle filtering (GKPF), which calculates the target distribution (for location estimation) based on nonparametric technique. In order to estimate the target distribution, the GKPF algorithm creates both unimodal and multimodal distributions based on particle representations, and it calculates a pdf for each distribution with Gaussian kernel-density estimation. Simulation study indicates that the proposed GKPE scheme can accurately estimate the location in mobile wireless environment.

In this paper, we propose a distributed, infrastructure-free algorithm for supporting self-localization and location-tracking of portable devices in home networks that do not rely on any positioning infrastructure, such as GPS (Global Positioning System). The proposed algorithm employs the received signal strength (RSS) to estimate the current position of each portable device and then elaborates the position with the box-based sequential Monte Carlo (BSMC) method. Simulation results indicate that the proposed algorithm is superior to the well-received Centroid algorithm in terms of the distance estimation error.

Recently, it has been received in the community that the link reliability is strongly related to RSSI (or SINR) and the external interference makes it unpredictable, but the unpredictability has not been fully explained yet. In order to examine the causes of the unpredictable link state, we first configured an empirical testbed, performed a measurement study, and observed that the link reliability actually depends on an intra-frame SINR distribution. We also discovered that a RSSI (or SINR) value is not always a good indicator to estimate the link state. Based on these results, we propose a modeling framework for estimating the link state in the presence of the wireless interference. We vision that the framework can be used for developing link-aware protocols to achieve their optimal performance in a hostile wireless environment.

Quality of service (QoS) provisioning is one of the most important criteria in newly emerging UWB WPANs, as they are expected to support a wide variety of applications from time-constrained, multimedia streaming to throughput-hungry, content transfer applications. Recently, the WiMedia Alliance has announced the PHY/MAC specification together with the common radio platform for UWB WPANs. The WiMedia MAC uses the contention-free reservation-based access, which supports isochronous traffic with distributed reservation protocol (DRP), and the contention-based access, which provides service differentiation for best effort and variable-rate real-time traffic with prioritized channel access (PCA), similar to the enhanced distributed coordinated access (EDCA) in IEEE 802.11e. In this paper, we conduct a comprehensive theoretical analysis and show that with the currently recommended parameter setting, EDCA cannot provide adequate QoS. In particular, without responding to the system dynamics (e.g., taking account of the number of active stations in each class), EDCA cannot allocate bandwidth in a deterministic proportional manner and the system bandwidth is underutilized. After identifying the deficiency of EDCA, we propose an enhanced QoS-provisioning framework for the PCA scheme that dynamically controls channel access to adjust allocated bandwidth depending on the change of application's bit rate, i.e., variable-rate real-time traffic. We show that in this framework, 1) variable-rate real-time traffic is adaptively guaranteed of deterministic bandwidth via a contention-based reservation access method; 2) best effort traffic is provided with deterministic proportional QoS; and 3) moreover, the bandwidth utilization in PCA is maximized. By deterministic proportional QoS, we mean that the proposed protocol will maintain the ratio, rj, of per-station throughput attained by a station of class j to that attained by a station of class 1 at the targeted value, and yet, the real amount of network bandwidth is changing according to the current available network bandwidth. We have also validated and evaluated the QoS provisioning capability and practicality of the proposed PCA framework both via simulation and an empirical study with the Multiband Atheros Driver for WiFi (MADWifi) Linux driver for Wireless LAN devices with the Atheros chipset.

In this paper, we examine user registration patterns in empirical WLAN traces, and identify elusive associations that are abused as user movements. The examination shows that about 90% of transitions are irrelevant to actual user movements. In order to refine the elusive movements, we investigate the geographical relationships among APs and propose a filtering framework for removing them from the trace data. We then analyze the impact of the false movements on an empirical mobility model. The numerical results indicate that the proposed framework improves the fidelity of the empirical mobility model.

We propose an efficient request-based uplink bandwidth allocation algorithm for variable-rate real-time service in broadband wireless access networks. By introducing a notion of target delay under the framework of dual feedback, the proposed algorithm can regulate delay while minimizing delay jitter and bandwidth waste.

Many protocol particulars developed for the wireless mesh networks, such as multi-path routing, channel assignment, topology control, assume that a network-wide collaboration is available to establish connections to the network outside. However, the collaboration can be easily discouraged in the presence of selfish behaviors, referred to as free-riding. In this paper, we propose a framework, PReSENt, to promote and make more secure the practices of collaboration among nodes by securing a compensation to the collaboration. When the PReSENt is enabled in wireless mesh networks, a node accumulates credits, an amount quantifying its resource provision when it provides its resource for other nodes. The nodes consuming the resource publish rewards, an amount quantifying their resource usage. The credits are used to guarantee the resource sharing for the provider from the customers in the future, whose amount is proportional to its relative contribution to the network-wide collaboration. The rewards are used to validate their corresponding credits in order to prevent false accumulations of the credits in selfish nodes. We formally define the underlying security model of the PReSENt and prove that the PReSENt is secure in the random oracle model. We then implement the PReSENt in J-Sim to illustrate its operational behaviors with respect to correct and secure resource sharing.

The performance of carrier sense multiple access (CSMA) wireless networks heavily depends on the level of spatial reuse, i.e., how many concurrent transmissions are allowed. Spatial reuse is primarily determined by physical carrier sense, and a key parameter for physical carrier sense is the carrier sense threshold. Our focus is on how to control the carrier sense threshold for improving network performance. We present a noncooperative game-theoretic framework, which leads to a fully distributed algorithm for tuning the carrier sense threshold. We introduce a utility function of each node, which is a nondecreasing concave function of the carrier sense threshold. A pricing function is further introduced to mitigate severe interference among nodes. The cost function is defined as the difference between the pricing and the utility functions. We prove that the noncooperative carrier sense game admits a unique Nash equilibrium (NE) under some technical conditions.We derive sufficient conditions that ensure the convergence of the synchronous and asynchronous update algorithms. Based on the analysis, we propose a fully distributed algorithm, entitled noncooperative carrier sense update algorithm (NCUA). Our simulation study indicates that NCUA outperforms standard CSMA with respect to the per-node throughput by 10-50%.

In this paper, we propose a feedback framework of providing fairness and service differentiation according to location information for TCP traffic in IEEE 802.11 Hot Spots. In the framework, we introduce location access price (LAP) to denote both the network-wide and per-location channel utilization, which is delivered to TCP senders and used to adjust their sending rate. We implemented the proposed framework in ns-2 simulator, and conducted a simulation study so as to evaluate its performance. The simulation results indicate that the proposed framework can provide location-based service differentiation in IEEE 802.11 Hot Spots.

The emerging broadband wireless access (BWA) technology based on IEEE 802.16 is one of the most promising solutions to provide ubiquitous wireless access to the broadband service at low cost. This paper proposes an efficient uplink bandwidth request-allocation algorithm for variable-rate realtime services in IEEE 802.16 BWA networks. In order to minimize bandwidth wastage without degrading quality of service (QoS), we introduce a notion of target delay and propose dual feedback architecture. The proposed algorithm calculates the amount of bandwidth request such that the delay is regulated around the desired level to minimize delay violation and delay jitter for real-time services. Also, it can maximize utilization of wireless channel by making use of dual feedback, where the bandwidth request is adjusted based on the information about the backlogged amount of traffic in the queue and the rate mismatch between packet arrival and service rates. Due to the dual feedback architecture, the proposed scheme responds quickly to the variation of traffic load and is robust to the change of network condition. We analyze the stability of the proposed algorithm from a control-theoretic viewpoint and derive a simple design guideline based on the analysis. By implementing the algorithm in OPNET simulator, we evaluate its performance in terms of queue regulation, optimal bandwidth allocation, delay controllability, and robustness to traffic characteristics.

We propose a virtual bidirectional connection for efficient bandwidth allocation to downlink TCP data and uplink acknowledgment (ACK) in mobile WiMAX networks based on IEEE 802.16. We observed that, in serving a downlink TCP flow, the standard bandwidth-request/allocation mechanism inevitably results in additional delay to transmit uplink TCP ACK, which increases round trip time of downlink TCP flow and decreases its throughput accordingly. To resolve this problem, we propose a hybrid approach combining proactive bandwidth allocation with piggyback bandwidth request. The proposed framework removes the unnecessary bandwidth-request delay, and also decreases signaling overhead involved in the bandwidth-request. Simulation results show that this approach significantly increases downlink TCP throughput and uplink bandwidth efficiency.

The limited number of orthogonal channels and autonomous installations of hot spots and home wireless networks often leave neighboring 802.11 basic service sets (BSSs) operating on the same or overlapping channels, therefore interfering with each other. However, the 802.11 medium access control (MAC) does not work well in resolving inter-BSS interference due to the well-known hidden/exposed-receiver problem, which has been haunting the research community for more than a decade. In this paper, we propose SELECT, an effective and efficient self-learning collision avoidance strategy to address the hidden/exposed-receiver problem in 802.11 wireless networks. SELECT is based on the observation that carrier sense with received signal strength (RSS) measurements at the sender and the receiver can be strongly correlated. A SELECT-enabled sender exploits such correlation using an automated online learning algorithm and makes an informed judgment of the channel availability at the intended receiver. SELECT achieves collision avoidance at packet-level time granularity, involves zero communication overhead, and easily integrates with the 802.11 distributed coordination function (DCF). Our evaluation in analysis, simulations, and prototype experiments show that SELECT addresses the hidden/exposed-receiver problem well. In typical hidden/exposed-receiver scenarios, SELECT improves the throughput by up to 140 percent and the channel access success ratio by up to 302 percent while almost completely eliminating contention-induced data packet drops.

In this paper, we investigate the issue of per-station fairness in TCP over IEEE 802.11-compliant wireless local area networks (WLANs), especially in Wi-Fi hot spot. It is asserted that the hot spot suffers from the unfairness among stations in exploiting the wireless medium. The source of this unfairness is analyzed from two aspects, TCP-induced asymmetry and MAC-induced asymmetry; the former causes TCP congestion control with a cumulative acknowledgment mechanism to prefer the sending stations to receiving stations, while the later exacerbates the unfairness problem in the hot spots. We investigate the interaction between TCP congestion control and MAC contention control, and propose a cross-layer feedback approach to assure per-station fairness and to ensure high channel utilization. In this approach, we introduce the notion of channel access cost to quantify the system-wide traffic load and per-station channel usage. The access cost is estimated at the MAC in an access point and conveyed to the TCP sender. Then, the TCP sender adjusts its sending rate based on the access cost, so as to assure per-station fairness. The simulation results indicate that the proposed approach can provide both per-station fairness and high channel utilization, irrespective of network configurations.

The limited number of orthogonal channels and the autonomous installations of hotspots and home wireless networks often leave neighboring 802.11 basic service sets (BSS's) operating on the same or overlapping channels, therefore interfering with each other. However, the 802.11 MAC does not work well in resolving inter-BSS interferences due to the well-known hidden/exposed receiver problem, which has been haunting in the research community for more than a decade. In this paper we propose SELECT, an effective and efficient self-learning collision avoidance strategy to address the open hidden/exposed receiver problem in wireless networks. SELECT is based on the observation that carrier sense with received signal strength (RSS) measurements at the sender and the receiver are strongly correlated. A SELECT-enabled sender exploits such correlation using automated on-line learning algorithm, and makes informed judgment of the channel availability at the intended receiver. SELECT achieves collision avoidance at packetlevel time granularity, involves zero communication overhead, requires no hardware support beyond what is available in offthe -shelf 802.11 devices, and easily integrates with the 802.11 DCF. Our evaluation in both analysis and simulations show that SELECT addresses the hidden/exposed receiver problem well. In typical hidden/exposed receiver scenarios SELECT improves the throughput by up to 140% and channel access success ratio by up to 302%, while almost completely eliminating contention-induced data packet drops.

Quality of service (QoS) provisioning is one of the most important criteria in newly emerging UWB-operated WPANs, as they are expected to support a wide variety of applica- tions from time-constrained, multimedia streaming to throughput- hungry, content transfer applications. As such, the Enhanced Distributed Coordinated Access (EDCA) mechanism has been adopted by MultiBand OFDM Alliance in its UWB MAC proposal. In this paper, we conduct a rigorous, comprehensive, theoretical analysis and show that with the currently recommended parame- ter setting, EDCA cannot provide adequate QoS. In particular, without responding to the system dynamics (e.g., taking into account of the number of active class-i stations), EDCA cannot allocate bandwidth in a deterministic proportional manner and the system bandwidth is under-utilized. After identifying the deficiency of EDCA, we propose, in compliance with the EDCA-incorporated UWB MAC protocol proposed in (15) (20), a framework, along with a set of theoretically grounded methods for controlling medium access with determin- istic QoS for UWB networks. We show that in this framework, 1) real-time traffic is guaranteed of deterministic bandwidth via a contention-based reservation access method; 2) best-effort traffic is provided with deterministic proportional QoS; and moreover, 3) the bandwidth utilization is maximized. We have also validated and evaluated the QoS provisioning capability and practicality of the proposed MAC framework both via simulation and empirically by leveraging the MADWifi (Multiband Atheros Driver for WiFi) Linux driver for Wireless LAN devices with the Atheros chipset.

Along with the success of IEEE 802.11-compliant WLANs, the Distributed Coordinated Function (DCF) specified as the contention-based medium access mechanism in IEEE 802.11 has been widely used to support applications in new regimes. A thorough understanding of the characteristics of IEEE 802.11 DCF is therefore a research focus. DCF assumes the binary exponential backoff algorithm (BEBA). Several existing models that characterize BEBA as a p-persistent scheme have ignored several subtle protocol details. This has practically constrained the models from being applied in a broader range of configurations, e.g., small contention window, and from being further extended, e.g. 802.11e EDCA.In this paper, we develop an analytical model that captures the subtlety, and faithfully describes the channel activities as governed by DCF. Based on the devised model, we perform a rigorous analysis on the saturation throughput performance in a single-hop WLAN. We also identify, by clearly defining and thus being able to differentiate the two terms, attempt probability and transmission probability, an erroneous extension made to Bianchi's model [3]. All the findings are corroborated by ns-2 simulation.

In this paper, we examine the feasibility of incorporating network calculus based models in simulating TCP/IP networks. By exploiting network calculus properties, we characterize how TCP congestion control - additive increase and multiplicative decrease (AIMD), together with the queue management strategy used in routers, regulates TCP flows. We first divide the time axis into intervals (each of which consists of multiple round-trip times), and derive a TCP AIMD throughput model which derives the attainable throughput of a TCP flow, given the number of collisions in an interval. Then based on the derived throughput model, we define a set of network calculus based theorems that give upper and lower bounds on the attainable TCP throughput in each interval. Finally, we implement network calculus (NC) based simulation in ns-2, conduct simulation in both the packet mode and the network calculus-based mode, and measure the performance gain (in terms of the execution time thus reduced) and the error discrepancy (in terms of the discrepancy between NC-based simulation results and packet-level simulation results). The simulation results indicate an order of magnitude or more (maximally 30 times) improvement in execution time and the performance improvement becomes more pronounced as the network size increases (in perspective of network capacities and number of flows). The error discrepancy between NC-based simulation and packet-level simulation, on the other hand, is minimally 1-2% and maximally 8-12% in a wide spectrum of network topologies and traffic loads employed in this study. The simulation results also indicate the superiority of NC-based simulation over fluid model based simulation (the latter realized using the time stepped hybrid simulation).

In this paper, we develop a fast simulation framework for IEEE 802.11-operated wireless LANs (WLANs), in which a large number of packets are abstracted as a single fluid chunk, and their behaviors are approximated with analytic fluid models and figured into the simulation. We first derive the analytical model that characterizes data transmission activities in IEEE 802.11-operated WLANs with/without the RTS/CTS mechanism. All the control overhead incurred in the physical and MAC layers, as well as system parameters specified in IEEE 802.11 [12] are faithfully figured in. We validate the model with simulation in cases in which the network is and is not saturated. We then implement, with the use of the time stepping technique [21], the fast simulation framework for WLANs in ns-2 [2], and conduct a comprehensive simulation study to evaluate the framework in terms of speed-up and errors incurred under a variety of network configurations.The simulation results indicate that the proposed framework is indeed effective in simulating IEEE 802.11-operated WLANs. It achieves as much as two orders of magnitude improvement in terms of execution time as compared to packet-level simulation. The performance improvement is more pronounced when the number of wireless nodes, the number of applications running on each wireless node, or the number of WLANs increases. The relative error, on the other hand, falls within 2% in all cases, as long as the value of the time step is appropriately determined.

In this paper, we develop a model-based frame scheduling scheme, called MFS, to enhance the capacity of IEEE 802.11-operated wireless local area networks (WLANs) for both transmission control protocol (TCP) and user datagram protocol (UDP) traffic. In MFS each node estimates the current network status by keeping track of the number of collisions it encounters between its two consecutive successful frame transmissions, and computes accordingly the current network utilization. The result is then used to determine a scheduling delay to be introduced before a node attempts to transmit its pending frame. MFS does not require any change in IEEE 802.11, but instead lays a thin layer between the LL and medium access control (MAC) layers. In order to accurately calculate the current utilization in WLANs, we develop an analytical model that characterizes data transmission activities in IEEE 802.11-operated WLANs with/without the request to send/clear to send (RTS/CTS) mechanism, and validate the model with ns-2 simulation. All the control overhead incurred in the physical and MAC layers, as well as system parameters specified in IEEE 802.11, are figured in. We conduct a comprehensive simulation study to evaluate MFS in perspective of the number of collisions, achievable throughput, intertransmission delay, and fairness in the cases of TCP and UDP traffic. The simulation results indicate that the performance improvement with respect to the protocol capacity in a WLAN of up to 300 nodes is 1) as high as 20% with the RTS/CTS and 70% without the RTS/CTS in the case of UDP traffic and 2) as high as 10% with the RTS/CTS and 40% without the RTS/CTS in the case of TCP traffic. Moreover, the intertransmission delay in MFS is smaller and exhibits less variation than that in IEEE 802.11; the fairness among wireless nodes in MFS is better than, or equal to, that in IEEE 802.11.

In this paper, we develop a model-based frame scheduling scheme, called MFS, to enhance the capacity of IEEE 802.11-operated wireless LANs (WLANs). In MFS each node estimates the current network status by keeping track of the number of collisions it encounters between its two consecutive successful frame transmissions, and, based on the the estimated information, computes the current network utilization. The result is then used to determine a scheduling delay that is introduced (with the objective of avoiding collision) before a node attempts for transmission of its pending frame. In order to accurately calculate the current utilization in WLANs, we develop an analytical model that characterizes data transmission activities in IEEE 802.11-operated WLANs with/without the RTS/CTS mechanism, and validate the model with ns-2 simulation. All the control overhead incurred in the physical and MAC layers, as well as system parameters specified in IEEE 802.11 are figured in.We have conducted a comprehensive simulation study to evaluate MFS in perspective of number of collisions, achievable throughput, and inter-transmission delay. The simulation results indicate that the performance improvement with respect to protocol capacity can be as high as 20% with RTS/CTS and 150% without RTS/CTS, in a WLAN of up to 300 nodes. In addition, the inter-transmission delay in MFS is smaller and exhibits less variation than that in IEEE 802.11.

We introduce nanoProtean, a new router operating system and execution environment that reduces system overhead, making it possible to process the packets produced by gigabit networks. The ovearhead decreases as the offered load per packet increases due to the following features in nanoProtean (i) a completely preemptable operating system, (ii) efficient management of the system's job queue, and (iii) system support for fine-grain sharing of processing time amongst packets. These features are a result of a novel integration of efficient thread scheduling for multiprocessors and interrupt handling. Experimental analysis used to test our systems scalability uses a technique to emulate processing requests generated in real-time at 802.3z (gigabit) line speeds and greater. Our results demonstrate 2 Gbps routing; with MAE-East tables on two processors, and system overheads decreasing from 3.6 /spl mu/s per packet to 1.64 /spl mu/s per packet on one processor. By reducing the system overhead, we also demonstrate that nanoProtean enables active networking in a router supporting gigabit connections.