The exploding volumes of mobile video traffic call for deploying content caches inside mobile operator networks. With in-network caching, users’ requests for popular content can be served from a content cache deployed at mobile gateways in vicinity to the end user. This inherently reduces the load on the content servers and the backbone of operator's network. In light of the increasing trend in virtualization

In this paper, a high-availability data collection scheme based on multiple autonomous underwater vehicles (AUVs) (HAMA) is proposed to improve the performance of the sensor network and guarantee the high availability of the data collection service. Multi-AUVs move in the network and their trajectory is predefined. The nodes near the trajectory of an AUV directly send their data to the AUV while the

Unmanned Vehicles (UVs) have been being utilized for various applications, such as surveillance, search/rescue, and monitoring. The information they transmit is critical for decision-making. However, UVs are vulnerable to white-box attacks due to improvements in reverse engineering techniques and the openness of their software. Therefore, attackers with sufficient knowledge of a target UV can steal

Mobile data traffic is experiencing unprecedented increases due to the proliferation of highly capable smartphones, laptops and tablets, and mobile data offloading can be used to move traffic from cellular networks to other wireless infrastructures such as small-cell base stations. This work addresses the related issue of data allocation, by proposing a novel infrastructure independent method based

In this paper, we introduce a powerful hardware-based rogue access point (PrAP), which can relay back and forth traffic between a legitimate AP and a wireless station, and act as a man-in-the-middle attacker. Our PrAP is built of two dedicated wireless routers interconnected physically, and can relay traffic rapidly between a station and a legitimate AP. Through experiments, we demonstrate that the

With the wide spread of various smart devices and the proliferation of internet of things (IoT) sensors, the amount of traffic on mobile networks is rapidly increasing, and applications with extreme requirements are increasing. Network function virtualization (NFV) and mobile edge computing (MEC) are emerging as core technologies to satisfy users’ real-time service demands. Adapting NFV technology

Frame-based listen-before-talk (FB-LBT) has been adopted as one of the channel access mechanism for Wi-Fi/LTE coexistence. We aim to explore the limits of FB-LBT by developing theoretical models to characterize the FB-LBT channel access performance under the coexistence of LTE and Wi-Fi. We first derive a steady-state model to calculate the spectrum share occupied by LTE under the assumption that the

Recognizing representative living patterns in population is extremely valuable for urban planning and decision making. Thanks to the growing popularity of location-based applications and check-ins on social networking sites, Point of Interest (POI) of a location is quite often available in the trajectory data, which expresses user living semantics. However, adopting trajectory semantics for living

Recently, we experience the increasing prevalence of wearable cameras, some of which feature Wireless Local Area Network (WLAN) connectivity, and the abundance of mobile devices equipped with on-board camera and WLAN modules. Motivated by this fact, this work presents an indoor localization system that leverages both imagery and WLAN data for enabling and supporting a wide variety of envisaged location-aware

Beaconing is a fundamental networking service where each node broadcasts a packet to all its neighbors locally. Unfortunately, the problem Minimum Latency Beaconing Schedule (MLBS) in duty-cycled scenarios is not well studied. Existing works always have rigid assumption that each node is only active once per working cycle. Aiming at making the work more practical and general, MLBS problem in duty-cycled

Next-generation wireless networks promise to provide extremely high data rates, especially exploiting the so-called millimeter-wave frequency range. Gaining information from spectrum usage is becoming important to provide smart adaptation capabilities to future network protocol stacks. Issues such as deafness, misaligned antennas, or blockage may severely impact network performance, and their identification

Network Slicing (NS) is a key enabler of the upcoming 5G and beyond system, leveraging on both Network Function Virtualization (NFV) and Software Defined Networking (SDN), NS will enable a flexible deployment of Network Functions (NFs) belonging to multiple Service Function Chains (SFC) over various administrative and technological domains. Our novel architecture addresses the complexities and heterogeneities

Current interference management solutions for dense IEEE 802.11 Wireless Local Area Networks (WLANs) rely on locally measuring the cumulative interference at the Acess Point (AP) in charge of adjusting the spectrum resources to its clients. These solutions often result in coarse-grained spectrum allocation that often leaves many wireless users unsatisfied and increases the spectrum congestion problem

While much effort has been made to detect and measure the privacy leakage caused by the advertising (ad) libraries integrated in mobile applications, analytics libraries, which are also widely used in mobile apps have not been systematically studied for their privacy risks. Different from ad libraries, the main function of analytics libraries is to collect users’ in-app actions. Hence, by design analytics

Logistics monitoring is a fundamental application that utilizes RFID systems to manage numerous tagged-objects. Due to the frequent rearrangement of tagged-objects, a fast RFID-based tracking approach is highly desired for accurate logistics distribution. However, traditional RFID systems usually take tens of seconds to interrogate hundreds of RFID tags, not to mention the time delay involved to locate

The emergence of vehicular networking enables distributed cooperative computation among nearby vehicles and infrastructures to achieve various applications that may need to handle mass data by a short deadline. In this paper, we investigate the fundamental problems of a cooperative vehicle-infrastructure system (CVIS): how does vehicular communication and networking affect the benefit gained from cooperative

This paper proposes a theoretical framework for estimating a target-object shape, the location of which is not given. The framework uses mobile distance sensors and speed meters typically mounted on vehicles, the locations of which are also unknown. Each sensor continuously measures the distance from it to the target object. The proposed framework does not require any positioning function, anchor-location

Crowdsensing requires scalable privacy-preserving authentication that allows users to send anonymously sensing reports, while enabling eventual anonymity revocation in case of user misbehavior. Previous research efforts already provide efficient mechanisms that enable conditional privacy through pseudonym systems, either based on Public Key Infrastructure (PKI) or Group Signature (GS) schemes. However

Although data has become an important kind of commercial goods, there are few appropriate online platforms to facilitate the trading of mobile crowd-sensed data so far. In this paper, we present the first architecture of mobile crowd-sensed data market, and conduct an in-depth study of the design problem of online data pricing and reward sharing. To build a practical mobile crowd-sensed data market

We propose a new MAC protocol for IoT applications, called Bird-MAC, which is highly energy efficient in the applications where IoT sensors report monitoring status in a quasi-periodic manner, as in structural health monitoring and static environmental monitoring. Two key design ideas of Bird-MAC are: (a) no need of early-wake-up of transmitters and (b) taking the right balance between synchronization

Cognitive radio-enabled vehicular nodes as unlicensed users can competitively and opportunistically access the radio spectrum provided by a licensed provider and simultaneously use a dedicated channel for vehicular communications. In such cognitive vehicular networks, channel access optimization plays a key role in making the most of the spectrum resources. In this paper, we present the competition

In this paper, we discuss the effects on throughput and fairness of dynamic channel bonding (DCB) in spatially distributed high-density wireless local area networks (WLANs). First, we present an analytical framework based on continuous-time Markov networks (CTMNs) for depicting the behavior of different DCB policies in spatially distributed scenarios, where nodes are not required to be within the carrier

Visible light communication (VLC)-based indoor localization approaches enjoy many advantages, such as utilizing ubiquitous lighting infrastructure, high location accuracy, and no interruption to RF-based devices. However, existing VLC-based localization methods lack a real-time backward channel from the device to landmarks and necessitate computation at the device, which make them unsuitable for real-time

Edge devices with sensing, storage, and communication resources (e.g., smartphones, tablets, connected vehicles, and IoT nodes) are increasingly penetrating our daily lives. Many novel applications can be created through sharing data among nearby peer edge devices. In such applications, caching data at some edge devices can greatly improve data availability, retrieval robustness, and delivery latency

Given the increasing popularity, mobile devices are exploited to enhance active driving safety nowadays. Among all safety services provided for vehicles, tracking the rotation angle of steering wheel in real time can monitor the vehicles’ dynamics and drivers’ behaviors at the same time. In this paper, we propose a steering tracking system, SteerTrack , which tracks the rotation angle of the steering

Utilizing the intelligence at the network edge, edge computing paradigm emerges to provide time-sensitive computing services for Internet of Things. In this paper, we investigate sustainable computation offloading in an edge-computing system that consists of energy harvesting-enabled mobile devices (MDs) and a dispatcher. The dispatcher collects computation tasks generated by IoT devices with limited

Device-free localization (DFL) methods use measured changes in the received signal strength (RSS) between many pairs of RF nodes to provide location estimates of a person inside the wireless network. Fundamental challenges for RSS DFL methods include having a model of RSS measurements as a function of a person's location, and maintaining an accurate model as the environment changes over time. Current

Wireless cameras are widely deployed in surveillance systems for security guarding. However, the privacy concerns associated with unauthorized videotaping, are drawing increasing attention recently. Existing detection methods for unauthorized wireless cameras are either limited by their detection accuracy or requiring dedicated devices. In this paper, we propose DeWiCam , a lightweight and effective

The live video streaming services have been suffered from the limited backhaul capacity of the cellular core network and occasional congestions due to the cloud-based architecture. Mobile Edge Computing (MEC) brings the services from the centralized cloud to nearby network edge to improve the Quality of Experience (QoE) of cloud services, such as live video streaming services. Nevertheless, the resource

In this paper, we present an analytical model for the scheduled access mechanism of IEEE 802.15.6 based Wireless Body Area Network (WBAN) taking into account the impact of non-ideal transmission channel. We provide a thorough analysis and closed form expressions for the frame delay, reliability of data transfer, throughput, energy consumption, and Energy Efficiency (EE) of the sensor nodes with medium

This paper proposes an energy management framework for cellular heterogeneous networks (HetNets) supported by dynamic solar powered drones. A HetNet composed of a macrocell base station (BS), micro cell BSs, and drone small cell BSs are deployed to serve the networks’ subscribers. The drones can land at pre-planned locations defined by the mobile operator and at the macrocell BS site where they can

Breath monitoring helps assess the general personal health and gives clues to chronic diseases. Yet, current breath monitoring technologies are inconvenient and intrusive. For instance, typical breath monitoring devices need to attach nasal probes or chest bands to users. Wireless sensing technologies have been applied to monitor breathing using radio waves without physical contact. Those wireless

In camera sensor networks (CSNs), full view coverage, meaning that any direction of any point in the operational region is covered by at least one camera sensor, plays a significant role in object identification. While prior work is dedicated to static CSNs for the sake of critical condition to achieve full view coverage, such performance still remains unknown in mobile CSNs. In this paper, we take

In this paper, we investigate the problem of asynchronous coded caching in fog radio access networks (F-RANs). To minimize the fronthaul load, the encoding set collapsing rule and encoding set partition method are proposed to establish the relationship between the coded-multicasting contents for asynchronous and synchronous coded caching. Furthermore, a decentralized asynchronous coded caching scheme

Two critical quality factors for mobile devices (e.g., smartphones, tablets) are battery life and user-perceived performance of User Interface (UI) events, e.g., responsiveness of user action events and frame rate of video playback events. Unfortunately, state-of-the-art solutions have at least one of the following three limitations: 1) they cannot efficiently handle concurrent UI events of multiple

It is now commonly agreed that future 5G Networks will build upon the network slicing concept. The ability to provide virtual, logically independent “slices” of the network will also have an impact on the models that will sustain the business ecosystem. Network slicing will open the door to new players: the infrastructure provider, which is the owner of the infrastructure, and the tenants, which may

Machine learning algorithms, which form the core intelligence of wearables, traditionally deduce a computational model from a set of training data to detect events of interest. However, in the dynamic environment in which wearables operate, the accuracy of a computational model drops whenever changes in configuration or context of the system occur. In this paper, using transfer learning as an organizing

LED-Camera Visible Light Communication (VLC) is gaining increasing attention, thanks to its readiness to be implemented with Commercial Off-The-Shelf devices and its potential to deliver pervasive data services indoors. Nevertheless, existing LED-Camera VLC systems employ mainly low-order modulations such as On-Off Keying (OOK) given the simplicity of their implementation, yet such rudimentary modulations

Dynamic spectrum sharing between licensed incum- bent users (IUs) and unlicensed wireless industries has been well recognized as an efficient approach to solving spectrum scarcity as well as creating spectrum markets. Recently, both U.S. and European governments called a ruling on opening up spectrum that was initially licensed to sensitive military/federal systems. However, this introduces serious

Energy-efficient location tracking with battery-powered devices using energy harvesting necessitates duty-cycling of GPS to prolong the system lifetime. We propose an energy- and mobility-aware scheduling framework that adapts to real-world dynamics to achieve optimal long-term tracking performance. To forecast energy, the framework uses an exponentially weighted moving average filter to compute a

Wireless video streaming has become an extremely popular application in recent years. Internet video streaming to mobile devices, however, faces several challenges, e.g., unstable wireless connections, long latency, high jitter and etc. Bitrate adaptive streaming and video transcoding solutions are widely used to address the above-mentioned issues, however, there are still several shortcomings of these

Task allocation is a major challenge in Mobile Crowd Sensing (MCS). While previous task allocation approaches follow either the opportunistic or participatory mode, this paper proposes to integrate these two complementary modes in a two-phased hybrid framework called HyTasker. In the offline phase, a group of workers (called opportunistic workers) are selected, and they complete MCS tasks during their

This paper presents an application-transparent execution context for mobile operating systems that reflects the criticality of current execution on user interactivity. We track Android/Linux system-level events including semantic syscalls, UI actions, and standard inter-process and intra-process communication interfaces that signal the initiation and propagation of interactivity-related executions

Network densification over space and spectrum is expected to be key to enabling the requirements of next generation mobile systems. The pitfall is that radio resource allocation becomes substantially more complex. In this paper we propose LaSR, a practical multi-connectivity scheduler for OFDMA-based multi-RAT systems. LaSR makes optimal discrete control actions by solving a sequence of simple optimization

The increasing complexity of smartphone applications and services necessitate high battery consumption, but the growth of smartphones' battery capacity is not keeping pace with these increasing power demands. To overcome this problem, researchers gave birth to the Mobile Cloud Computing (MCC) research area. In this paper, we advance on previous ideas, proposing and implementing a Near Field Communication

Today's mobile battery-powered communication devices require that users access chargers via wired and, recently, wireless recharging facilities. For a device departing from a location with a given energy “budget”, a plausible strategy is to seek a charger location once the energy is exhausted. We present a model of mobile nodes that captures the paths followed by the nodes with depleted energy seeking

Human identification and monitoring are critical in many applications, such as surveillance, evacuation planning. Human identification and monitoring are not an easy task in the case of a large and densely populated crowd. However, none of the existing solutions consider seamless localization, identification, and tracking of the crowd for surveillance in both indoor and outdoor environments with significant

Received signal strength based respiration rate monitoring is emerging as an alternative non-contact technology. These systems make use of the radio measurements of short-range commodity wireless devices, which vary due to the inhalation and exhalation motion of a person. The success of respiration rate estimation using such measurements depends on the signal-to-noise ratio, which alters with properties

Gait has been proposed as a feature for mobile device pairing across arbitrary positions on the human body. Results indicate that the correlation in gait-based features across different body locations is sufficient to establish secure device pairing. However, the population size of the studies is limited and powerful attackers with e.g. capability of video recording are not considered. We present a

For opportunistic routing in independent duty cycled wireless sensor networks (WSNs), a sender dynamically determines a relay candidate set depending on the real-time network conditions. Due to independent and varying duty cycle length, the sender may handle different waking-up orders of the potential forwarders when it tries to forward data packets at different time instants. Conventional opportunistic

The explosive usage of mobile devices enables conducting electronic transactions involving direct signature on such devices. Thus, user signature verification becomes critical to ensure the success deployment of online transactions such as approving legal documents and authenticating financial transactions. Existing approaches mainly focus on user verification targeting the unlocking of mobile devices

Sensors (e.g., light, gyroscope, and accelerometer) and sensing-enabled applications on a smart device make the applications more user-friendly and efficient. However, the current permission-based sensor management systems of smart devices only focus on certain sensors and any App can get access to other sensors by just accessing the generic sensor Application Programming Interface (API). In this way

We propose practical sets of rules for adapting Clear Channel Assessment (CCA) and Transmit Power (TP) parameters by simulating ensembles of randomly generated wireless networks and collecting throughput statistics. The rules’ performances depend strongly on network topology, with increases in throughput in many cases. However, networks with a high clustering coefficient are often adversely effected

This paper considers a device-based Fog Radio Access Network (F-RAN), where users’ smart devices (denoted by F-UEs) can be exploited to cache popular files so as to communicate them when requested by other F-UEs among them. This architecture restricts the involvement of the central baseband processing unit (BBU) to serving those F-UEs not immediately served by their peers, thus offloading the BBU's

Caching popular videos at mobile edge servers (MESs) has been confirmed as a promising method to improve mobile users (MUs) perceived quality of experience (QoE) and to alleviate the server load. However, with the multiple bitrate encoding techniques prevalently employed in modern streaming services, caching deployment is challenging for the following three facts: (1) cooperative caching should be

Due to the unavailability of Vehicle-to-Infrastructure (V2I) communication in current transportation systems, Traffic Light Detection (TLD) is still considered an important module in autonomous vehicles and Driver Assistance Systems (DAS). To overcome low flexibility and accuracy of vision-based heuristic algorithms and high power consumption of deep learning-based methods, we propose a lightweight

Due to their on-body and ubiquitous nature, wearables can generate a wide range of unique sensor data creating countless opportunities for deep learning tasks. We propose DeepWear, a deep learning (DL) framework for wearable devices to improve the performance and reduce the energy footprint. DeepWear strategically offloads DL tasks from a wearable device to its paired handheld device through local

Recently, wireless edge caching has emerged as a promising technology for future wireless networks to cope with exponentially increasing demands for high data rate and low latency multimedia services by proactively storing contents at the network edge. Here, we aim to design efficient cache placement and delivery strategies for an orthogonal frequency division multiple access (OFDMA)-based cache-enabled

The in-band full-duplexing is a promising technique to boost wireless network throughput by allowing a node to transmit and receive simultaneously. This paper provides a comprehensive investigation on the hidden-node problem that arises in the full-duplex (FD) enabled carrier-sensing multiple-access (CSMA) networks. In particular, we first provide the fundamental conditions that guarantee successful

Crowdsensing paradigm facilitates a wide range of data collection, where great efforts have been made to address its fundamental issues of matching workers to their assigned tasks and processing the collected data. In this paper, we reexamine these issues by considering the spatio-temporal worker mobility and task arrivals, which more fit the actual situation. Specifically, we study the location-aware