Smartphone users often want to customize the positions and functions of physical buttons to accommodate their own usage patterns; however, this is unfeasible for electronic mobile devices based on COTS (Commercial Off-The-Shelf) due to high production costs and hardware design constraints. In this letter, we present the design and implementation of customized virtual buttons that are localized using only common built-in sensors of electronic mobile devices. We develop sophisticated strategies firstly to detect when a user taps one of the virtual buttons, and secondly to locate the position of the tapped virtual button. The virtual-button scheme is implemented and demonstrated in a COTS-based smartphone. The feasibility study shows that, with up to nine virtual buttons on five different sides of the smartphone, the proposed virtual buttons can operate with greater than 90% accuracy.

Softwarized networks are expected to be utilized as a core network for the 5th Generation (5G) mobile services. For the mobile core network architecture, service chaining is expected to be utilized for dynamically steering traffic across multiple network functions. In this paper, for dynamic multipath service chaining, we propose a greedy-based VNF placement algorithm. This method can provide multipath service chaining so as to utilize the node resources such as CPU effectively while decreasing the cost about bandwidth and transmission delay. The proposed algorithm consists of four difference algorithms, and VNFs are placed appropriately with those algorithm. Our proposed algorithm obtains near optimal solution for the formulated optimization problem with a greedy algorithm, and hence multipath service chains can be provided dynamically. We evaluate the performance of our proposed method with simulation and compare its performance with the performances of other methods. In numerical examples, it is shown that our proposed algorithm can provide multipath service chains appropriately so as to utilize the limited amount of node resources effectively. Moreover, it is shown that our proposed algorithm is effective for providing service chaining dynamically in large-scale network.

In this paper, we consider the partial gathering problem of mobile agents in arbitrary networks. The partial gathering problem is a generalization of the (well-investigated) total gathering problem, which requires that all the agents meet at the same node. The partial gathering problem requires, for a given positive integer g, that each agent should move to a node and terminate so that at least g agents should meet at each of the nodes they terminate at. The requirement for the partial gathering problem is no stronger than that for the total gathering problem, and thus, we clarify the difference on the move complexity between them. First, we show that agents require Ω(gn+m) total moves to solve the partial gathering problem, where n is the number of nodes and m is the number of communication links. Next, we propose a deterministic algorithm to solve the partial gathering problem in O(gn+m) total moves, which is asymptotically optimal in terms of total moves. Note that, it is known that agents require Ω(kn+m) total moves to solve the total gathering problem in arbitrary networks, where k is the number of agents. Thus, our result shows that the partial gathering problem is solvable with strictly fewer total moves compared to the total gathering problem in arbitrary networks.

The next generation mobile system “5G” are under research, development and standardization for a service start of around year 2020. It is likely to use frequency bands higher than existing bands to have wider bandwidth for high throughput services. This paper reviews technical issues on higher frequency bands applying mobile systems including system trials and use case trials. It identifies expectations for antennas & propagation studies toward 5G era.

This paper proposes a radio propagation prediction method that uses point cloud data based on a hybrid of the ray-tracing (RT) method and an effective roughness (ER) model in urban environments for the fifth generation mobile communications system using high frequency bands. The proposed prediction method incorporates propagation characteristics that consider diffuse scattering from surface irregularities. The validity of the proposed method is confirmed by comparisons of measurement and prediction results gained from the proposed method and a conventional RT method based on power delay and angular profiles. From predictions based on the power delay and angular profiles, we find that the proposed method, assuming the roughness of σh=1mm, accurately predicts the propagation characteristics in the 20GHz band for urban line-of-sight environments. The prediction error for the delay spread is 2.1ns to 9.7ns in an urban environment.

Smartphones for wireless communication typically consist of a large area frontal liquid crystal display (LCD), which incorporates a metal back plate, and a back cover chassis made from metal. Leveraging this structure a new approach to construct antennas for smartphones is proposed where the complete metal back cover chassis and LCD back plate are used as the radiating element and ground plane. In the design a feedline is connected between the metal back cover chassis and LCD back plate, along with shorts at various locations between the two metal plates, to control the resonance frequency of the resulting antenna. Multiple-band operation is possible without the need for any slots in the plates for radiation. Results show that antenna frequency reconfigurability can be achieved when switching function is added to the shorts so that several wireless communication bands can be covered. This approach is different from existing metallic frame antenna designs currently available in the market. A design example is provided which uses one PIN diode for the switching shorts and the target frequency bands are 740-780MHz and 900-1000MHz & 1700-1900MHz. The optimization of LC matchings and concerns of hand effects and metallic components between the chassis and LCD metal back plate are also addressed.

In this paper, we propose a new asymptotically stabilizing control law for a four-wheeled vehicle with a steering limitation. We adopt a locally semiconcave control Lyapunov function (LS-CLF) for the system. To overcome the nonconvexity of the input-constraint set, we utilize a saturation function and a signum function in the control law. The signum function makes the vehicle velocity nonzero except at the origin so that the angular velocity can be manipulated within the input constraint. However, the signum function may cause a chattering phenomenon at certain points of the state far from the origin. Thus, we integrate a lazy-switching mechanism for the vehicle velocity into the control law. The mechanism makes a sign of the vehicle velocity maintain, and the new control input also decreases the value of the LS-CLF. We confirm the effectiveness of our method by a computer simulation and experiments.

In this paper, we propose a highly efficient mobile visual search algorithm. For descriptor extraction process, we propose a low complexity feature detection which utilizes the detected local key points of the coarse octaves to guide the scale space construction and feature detection in the fine octave. The Gaussian and Laplacian operations are skipped for the unimportant area, and thus the computing time is saved. Besides, feature selection is placed before orientation computing to further reduce the complexity of feature detection by pre-discarding some unimportant local points. For the image retrieval process, we design a high-performance reranking method, which merges both the global descriptor matching score and the local descriptor similarity score (LDSS). In the calculating of LDSS, the tf-idf weighted histogram matching is performed to integrate the statistical information of the database. The results show that the proposed highly efficient approach achieves comparable performance with the state-of-the-art for mobile visual search, while the descriptor extraction complexity is largely reduced.

We propose a feature design method for a mobile visual search based on binary features and a bag-of-visual words framework. In mobile visual search, detection error and quantization error are unavoidable due to viewpoint changes and cause performance degradation. Typical approaches to visual search extract features from a single view of reference images, though such features are insufficient to manage detection and quantization errors. In this paper, we extract features from multiview synthetic images. These features are selected according to our novel reliability measure which enables robust recognition against various viewpoint changes. We regard feature selection as a maximum coverage problem. That is, we find a finite set of features maximizing an objective function under certain constraints. As this problem is NP-hard and thus computationally infeasible, we explore approximate solutions based on a greedy algorithm. For this purpose, we propose novel constraint functions which are designed to be consistent with the match conditions in the visual search method. Experiments show that the proposed method improves retrieval accuracy by 12.7 percentage points without increasing the database size or changing the search procedure. In other words, the proposed method enables more accurate search without adversely affecting the database size, computational cost, and memory requirement.

Digitization of analog terrestrial TV broadcasting has recently been accelerated in many countries, and the effective utilization of vacant frequencies has also been investigated for new systems in each country. In Japan, a portion of vacant frequencies in the VHF-high band was allocated to the public broadband mobile communication (PBB) system. To evaluate the current PBB system and develop future broadband communication systems in this band, it is important to analyze the propagation channel more accurately. In this study, we characterize the propagation channel for 200MHz band broadband mobile communication systems, using measured channel impulse responses (CIRs). In the characterization process, the Saleh-Valenzuela (S-V) model is utilized to extract channel model parameters statistically. When evaluating the fluctuation of path power gain, we also propose to model the fluctuation of path power gain using the generalized extreme value distribution instead of the conventional log-normal distribution. The extracted CIR model parameters are validated by cumulative distribution function of root-means-square delay spread and maximum excess delay, comparing simulation result to measurement result. From the extracted CIR model parameters, we clarified the characteristics of 200MHz band broadband mobile communication systems in non-line-of-sight environments based on S-V model with the proposed channel model.

Data breach and data destruction attack have become the critical security threats for the ICT (Information and Communication Technology) infrastructure. Both the Internet service providers and users are suffering from the cyber threats especially those to confidential data and private information. The requirements of human social activities make people move carrying confidential data and data breach always happens during the transportation. The Internet connectivity and cryptographic technology have made the usage of confidential data much secure. However, even with the high deployment rate of the Internet infrastructure, the concerns for lack of the Internet connectivity make people carry data with their mobile devices. In this paper, we describe the main patterns of data breach occur on mobile devices and propose a secure in-depth file system concealed by GPS-based mounting authentication to mitigate data breach on mobile devices. In the proposed in-depth file system, data can be stored based on the level of credential with corresponding authentication policy and the mounting operation will be only successful on designated locations. We implemented a prototype system using Veracrypt and Perl language and confirmed that the in-depth file system worked exactly as we expected by evaluations on two locations. The contribution of this paper includes the clarification that GPS-based mounting authentication for a file system can reduce the risk of data breach for mobile devices and a realization of prototype system.

Android app developers sometimes copy code snippets posted on a question-and-answer (Q&A) website and use them in their apps. However, if a code snippet has vulnerabilities, Android apps containing the vulnerable snippet could also have the same vulnerabilities. Despite this, the effect of such vulnerable snippets on the Android apps has not been investigated in depth. In this paper, we investigate the correspondence between the vulnerable code snippets and vulnerable apps. we collect code snippets from a Q&A website, extract possibly vulnerable snippets, and calculate similarity between those snippets and bytecode on vulnerable apps. Our experimental results show that 15.8% of all evaluated apps that have SSL implementation vulnerabilities (Improper host name verification), 31.7% that have SSL certificate verification vulnerabilities, and 3.8% that have WEBVIEW remote code execution vulnerabilities contain possibly vulnerable code snippets from Stack Overflow. In the worst case, a single problematic snippet has caused 4,844 apps to contain a vulnerability, accounting for 31.2% of all collected apps with that vulnerability.

Permission warnings and privacy policy enforcement are widely used to inform mobile app users of privacy threats. These mechanisms disclose information about use of privacy-sensitive resources such as user location or contact list. However, it has been reported that very few users pay attention to these mechanisms during installation. Instead, a user may focus on a more user-friendly source of information: text description, which is written by a developer who has an incentive to attract user attention. When a user searches for an app in a marketplace, his/her query keywords are generally searched on text descriptions of mobile apps. Then, users review the search results, often by reading the text descriptions; i.e., text descriptions are associated with user expectation. Given these observations, this paper aims to address the following research question: What are the primary reasons that text descriptions of mobile apps fail to refer to the use of privacy-sensitive resources? To answer the research question, we performed empirical large-scale study using a huge volume of apps with our ACODE (Analyzing COde and DEscription) framework, which combines static code analysis and text analysis. We developed light-weight techniques so that we can handle hundred of thousands of distinct text descriptions. We note that our text analysis technique does not require manually labeled descriptions; hence, it enables us to conduct a large-scale measurement study without requiring expensive labeling tasks. Our analysis of 210,000 apps, including free and paid, and multilingual text descriptions collected from official and third-party Android marketplaces revealed four primary factors that are associated with the inconsistencies between text descriptions and the use of privacy-sensitive resources: (1) existence of app building services/frameworks that tend to add API permissions/code unnecessarily, (2) existence of prolific developers who publish many applications that unnecessarily install permissions and code, (3) existence of secondary functions that tend to be unmentioned, and (4) existence of third-party libraries that access to the privacy-sensitive resources. We believe that these findings will be useful for improving users' awareness of privacy on mobile software distribution platforms.

After large-scale disasters, information sharing among people becomes more important than usual. This, however, is extremely difficult to achieve in disaster zones due to serious damage to the existing network infrastructure, power outages, and high traffic congestion. For the quick provision of alternative networks to serve heavy communication demands after disasters, establishing local area networks (LANs) consisting of portable servers with data storage has been considered as one of the most promising solutions. Based on the established LAN and a data server in each area, people can share many kinds of disaster-related information such as emergency information and supply/demand information via deployed neighboring servers. However, due to the lack of stable Internet connection, these servers are isolated and cannot be synchronized in real time. To enable and guarantee more efficient information sharing across the whole disaster-hit area, data stored on each server should be synchronized without the Internet. Our solution is to propose an intermittent data synchronization scheme that uses moving vehicles as relays to exchange data between isolated servers after disasters. With the objective of maximizing the total number of synchronized high priority data under the capability constraints of mobile relays, we first propose a data allocation scheme (DAS) from a server to a mobile relay. After that, we propose a trajectory planning scheme for the relays which is formulated as a Mixed Integer Linear Fractional Programming (MILFP) problem, and an algorithm to solve it efficiently. Extensive simulations and comparisons with other methods show the superior performance of our proposals.

As IoT services become more popular, mobile networks will have to accommodate a wide variety of devices that have different requirements such as different bandwidth limitations and latencies. This paper describes edge distributed mobile network architectures for the IoT era based on dedicated network technology and multi-access edge computing technology, which have been discussed in 3GPP and ETSI. Furthermore, it describes two context-aware control methods that will make mobile networks on the network architecture more efficient, reliable, and real-time: autonomous and distributed mobility management and bandwidth-guaranteed transmission rate control in a networked control system.

The introduction of a drone-based mobile sink into wireless sensor networks (WSNs), which has flexible mobility to move to each sensor node and gather data with a single-hop transmission, makes cumbersome multi-hop transmissions unnecessary, thereby facilitating data gathering from widely-spread sensor nodes. However, each sensor node spends significant amount of energy during their idle state where they wait for the mobile sink to come close to their vicinity for data gathering. In order to solve this problem, in this paper, we apply a wake-up receiver to each sensor node, which consumes much smaller power than the main radio used for data transmissions. The main radio interface is woken up only when the wake-up receiver attached to each node detects a wake-up signal transmitted by the mobile sink. For this mobile and on-demand data gathering, this paper proposes a route control framework that decides the mobility route for a drone-based mobile sink, considering the interactions between wake-up control and physical layer (PHY) and medium access control (MAC) layer operations. We investigate the optimality and effectiveness of the route obtained by the proposed framework with computer simulations. Furthermore, we present experimental results obtained with our test-bed of a WSN employing a drone-based mobile sink and wake-up receivers. All these results give us the insight on the role of wake-up receiver in mobile and on-demand sensing data gathering and its interactions with protocol/system designs.

We propose a method for efficiently detecting phishing attacks in mobile environments. When a user visits a website of a certain URL, the proposed method first compares the URL to a generated whitelist. If the URL is not in the whitelist, it detects if the site is a phishing site based on the results of Google search with a carefully refined URL. In addition, the phishing detection is performed only when the user provides input to the website, thereby reducing the frequency of invoking phishing detection to decrease the amount of power used. We implemented the proposed method and used 8315 phishing sites and the same number of legitimate websites for evaluating the performance of the proposed method. We achieved a phishing detection rate of 99.22% with 81.22% reduction in energy consumption as compared to existing approaches that also use search engine for phishing detection. Moreover, because the proposed method does not employ any other algorithm, software, or comparison group, the proposed method can be easily deployed.

Because mobile users demand a high quality and energy-friendly video delivery service that efficiently uses wireless resources, we introduce an energy-efficient video delivery system by applying moving route navigation and playout buffer control based on the mobile throughput history data. The proposed system first determines the optimal travel route to achieve high-speed and energy-efficient communications. Then when a user enters a high throughput area, our system temporarily extends the video playout buffer size, and the user aggressively downloads video segments via a high-speed and energy-efficient wireless connection until the extended buffer is filled. After leaving this area, the user consumes video segments from the extended buffer in order to keep smooth video playback without wireless communications. We carry out computer simulations, laboratory and field experiments and confirm that the proposed system can achieve energy-efficient mobile video delivery.

Throughput prediction is one of the promising techniques to improve the quality of service (QoS) and quality of experience (QoE) of mobile applications. To address the problem of predicting future throughput distribution accurately during the whole session, which can exhibit large throughput fluctuations in different scenarios (especially scenarios of moving user), we propose a history-based throughput prediction method that utilizes time series analysis and machine learning techniques for mobile network communication. This method is called the Hybrid Prediction with the Autoregressive Model and Hidden Markov Model (HOAH). Different from existing methods, HOAH uses Support Vector Machine (SVM) to classify the throughput transition into two classes, and predicts the transmission control protocol (TCP) throughput by switching between the Autoregressive Model (AR Model) and the Gaussian Mixture Model-Hidden Markov Model (GMM-HMM). We conduct field experiments to evaluate the proposed method in seven different scenarios. The results show that HOAH can predict future throughput effectively and decreases the prediction error by a maximum of 55.95% compared with other methods.

With the rapid increase in demand for mobile data, mobile network operators are trying to expand wireless network capacity by deploying wireless local area network (LAN) hotspots on to which they can offload their mobile traffic. However, these network-centric methods usually do not fulfill the interests of mobile users (MUs). Taking into consideration many issues such as different applications' deadlines, monetary cost and energy consumption, how the MU decides whether to offload their traffic to a complementary wireless LAN is an important issue. Previous studies assume the MU's mobility pattern is known in advance, which is not always true. In this paper, we study the MU's policy to minimize his monetary cost and energy consumption without known MU mobility pattern. We propose to use a kind of reinforcement learning technique called deep Q-network (DQN) for MU to learn the optimal offloading policy from past experiences. In the proposed DQN based offloading algorithm, MU's mobility pattern is no longer needed. Furthermore, MU's state of remaining data is directly fed into the convolution neural network in DQN without discretization. Therefore, not only does the discretization error present in previous work disappear, but also it makes the proposed algorithm has the ability to generalize the past experiences, which is especially effective when the number of states is large. Extensive simulations are conducted to validate our proposed offloading algorithms.