Showing papers on "Mobile search published in 2017"
TL;DR: This survey makes an exhaustive review on the state-of-the-art research efforts on mobile edge networks, including definition, architecture, and advantages, and presents a comprehensive survey of issues on computing, caching, and communication techniques at the network edge.
Abstract: As the explosive growth of smart devices and the advent of many new applications, traffic volume has been growing exponentially. The traditional centralized network architecture cannot accommodate such user demands due to heavy burden on the backhaul links and long latency. Therefore, new architectures, which bring network functions and contents to the network edge, are proposed, i.e., mobile edge computing and caching. Mobile edge networks provide cloud computing and caching capabilities at the edge of cellular networks. In this survey, we make an exhaustive review on the state-of-the-art research efforts on mobile edge networks. We first give an overview of mobile edge networks, including definition, architecture, and advantages. Next, a comprehensive survey of issues on computing, caching, and communication techniques at the network edge is presented. The applications and use cases of mobile edge networks are discussed. Subsequently, the key enablers of mobile edge networks, such as cloud technology, SDN/NFV, and smart devices are discussed. Finally, open research challenges and future directions are presented as well.
782 citations
TL;DR: A real-time, context-aware collaboration framework that lies at the edge of the RAN, comprising MEC servers and mobile devices, and amalgamates the heterogeneous resources at theedge is envisions.
Abstract: MEC is an emerging paradigm that provides computing, storage, and networking resources within the edge of the mobile RAN. MEC servers are deployed on a generic computing platform within the RAN, and allow for delay-sensitive and context-aware applications to be executed in close proximity to end users. This paradigm alleviates the backhaul and core network and is crucial for enabling low-latency, high-bandwidth, and agile mobile services. This article envisions a real-time, context-aware collaboration framework that lies at the edge of the RAN, comprising MEC servers and mobile devices, and amalgamates the heterogeneous resources at the edge. Specifically, we introduce and study three representative use cases ranging from mobile edge orchestration, collaborative caching and processing, and multi-layer interference cancellation. We demonstrate the promising benefits of the proposed approaches in facilitating the evolution to 5G networks. Finally, we discuss the key technical challenges and open research issues that need to be addressed in order to efficiently integrate MEC into the 5G ecosystem.
700 citations
TL;DR: In this paper, the authors argue for network slicing as an efficient solution that addresses the diverse requirements of 5G mobile networks, thus providing the necessary flexibility and scalability associated with future network implementations.
Abstract: We argue for network slicing as an efficient solution that addresses the diverse requirements of 5G mobile networks, thus providing the necessary flexibility and scalability associated with future network implementations. We elaborate on the challenges that emerge when designing 5G networks based on network slicing. We focus on the architectural aspects associated with the coexistence of dedicated as well as shared slices in the network. In particular, we analyze the realization options of a flexible radio access network with focus on network slicing and their impact on the design of 5G mobile networks. In addition to the technical study, this article provides an investigation of the revenue potential of network slicing, where the applications that originate from this concept and the profit capabilities from the network operator�s perspective are put forward.
457 citations
TL;DR: This survey discusses advances in tracking and registration, since their functionality is crucial to any MAR application and the network connectivity of the devices that run MAR applications together with its importance to the performance of the application.
Abstract: The boom in the capabilities and features of mobile devices, like smartphones, tablets, and wearables, combined with the ubiquitous and affordable Internet access and the advances in the areas of cooperative networking, computer vision, and mobile cloud computing transformed mobile augmented reality (MAR) from science fiction to a reality. Although mobile devices are more constrained computationalwise from traditional computers, they have a multitude of sensors that can be used to the development of more sophisticated MAR applications and can be assisted from remote servers for the execution of their intensive parts. In this paper, after introducing the reader to the basics of MAR, we present a categorization of the application fields together with some representative examples. Next, we introduce the reader to the user interface and experience in MAR applications and continue with the core system components of the MAR systems. After that, we discuss advances in tracking and registration, since their functionality is crucial to any MAR application and the network connectivity of the devices that run MAR applications together with its importance to the performance of the application. We continue with the importance of data management in MAR systems and the systems performance and sustainability, and before we conclude this survey, we present existing challenging problems.
285 citations
TL;DR: The main security and privacy challenges in this field which have grown much interest among the academia and research community are presented and corresponding security solutions have been proposed and identified in literature by many researchers to counter the challenges.
221 citations
TL;DR: This work compares two VM mobility modes, bulk and live migration, as a function of mobile cloud service requirements, determining that a high preference should be given to live migration and bulk migrations seem to be a feasible alternative on delay-stringent tiny-disk services, such as augmented reality support, and only with further relaxation on network constraints.
Abstract: Major interest is currently given to the integration of clusters of virtualization servers, also referred to as ‘cloudlets’ or ‘edge clouds’, into the access network to allow higher performance and reliability in the access to mobile edge computing services. We tackle the edge cloud network design problem for mobile access networks. The model is such that the virtual machines (VMs) are associated with mobile users and are allocated to cloudlets. Designing an edge cloud network implies first determining where to install cloudlet facilities among the available sites, then assigning sets of access points, such as base stations to cloudlets, while supporting VM orchestration and considering partial user mobility information, as well as the satisfaction of service-level agreements. We present link-path formulations supported by heuristics to compute solutions in reasonable time. We qualify the advantage in considering mobility for both users and VMs as up to 20% less users not satisfied in their SLA with a little increase of opened facilities. We compare two VM mobility modes, bulk and live migration, as a function of mobile cloud service requirements, determining that a high preference should be given to live migration, while bulk migrations seem to be a feasible alternative on delay-stringent tiny-disk services, such as augmented reality support, and only with further relaxation on network constraints.
203 citations
TL;DR: In this article, a D2D Crowd framework for 5G mobile edge computing is proposed, where a massive crowd of devices at the network edge leverage network-assisted D2DM collaboration for computation and communication resource sharing.
Abstract: In this article we propose a novel D2D Crowd framework for 5G mobile edge computing, where a massive crowd of devices at the network edge leverage network-assisted D2D collaboration for computation and communication resource sharing. A key objective of this framework is to achieve energy-efficient collaborative task executions at the network edge for mobile users. Specifically, we first introduce the D2D Crowd system model in detail, and then formulate the energy-efficient D2D Crowd task assignment problem by taking into account the necessary constraints. We next propose a graph-matching-based optimal task assignment policy, and further evaluate its performance through extensive numerical study, which shows superior performance of more than 50 percent energy consumption reduction over the case of local task executions. Finally, we also discuss the directions of extending the D2D Crowd framework by taking into account a variety of application factors.
169 citations
TL;DR: Results indicate the system and embedded decision algorithm are able to provide decisions on selecting wireless medium and cloud resources based on different context of the mobile devices, and achieve significant reduction on makespan and energy, with the improved service availability when compared with existing offloading schemes.
Abstract: Mobile cloud computing (MCC) has become a significant paradigm for bringing the benefits of cloud computing to mobile devices’ proximity. Service availability along with performance enhancement and energy efficiency are primary targets in MCC. This paper proposes a code offloading framework, called mCloud, which consists of mobile devices, nearby cloudlets and public cloud services, to improve the performance and availability of the MCC services. The effect of the mobile device context (e.g., network conditions) on offloading decisions is studied by proposing a context-aware offloading decision algorithm aiming to provide code offloading decisions at runtime on selecting wireless medium and appropriate cloud resources for offloading. We also investigate failure detection and recovery policies for our mCloud system. We explain in details the design and implementation of the mCloud prototype framework. We conduct real experiments on the implemented system to evaluate the performance of the algorithm. Results indicate the system and embedded decision algorithm are able to provide decisions on selecting wireless medium and cloud resources based on different context of the mobile devices, and achieve significant reduction on makespan and energy, with the improved service availability when compared with existing offloading schemes.
130 citations
TL;DR: The emerging concept of network slicing that is considered one of the most significant technology challenges for 5G mobile networking infrastructure is introduced, preliminary research efforts to enable end-to-end network slicing for 5Gs mobile networking are summarized, and application use cases that should drive the designs of the infrastructure of network sliced are discussed.
Abstract: The research and development (R&D) and the standardization of the 5th Generation (5G) mobile networking technologies are proceeding at a rapid pace all around the world. In this paper, we introduce the emerging concept of network slicing that is considered one of the most significant technology challenges for 5G mobile networking infrastructure, summarize our preliminary research efforts to enable end-to-end network slicing for 5G mobile networking, and finally discuss application use cases that should drive the designs of the infrastructure of network slicing.
129 citations
TL;DR: Two existing approaches that quantify crowd-sensed data trustworthiness, based on statistical and vote-based user reputation scores are studied and a new metric—collaborative reputation scores—is introduced to expand this definition.
Abstract: Ubiquity of mobile devices with rich sensory capabilities has given rise to the mobile crowd-sensing (MCS) concept, in which a central authority (the platform) and its participants (mobile users) work collaboratively to acquire sensory data over a wide geographic area. Recent research in MCS highlights the following facts: 1) a utility metric can be defined for both the platform and the users, quantifying the value received by either side; 2) incentivizing the users to participate is a non-trivial challenge; 3) correctness and truthfulness of the acquired data must be verified, because the users might provide incorrect or inaccurate data, whether due to malicious intent or malfunctioning devices; and 4) an intricate relationship exists among platform utility, user utility, user reputation, and data trustworthiness, suggesting a co-quantification of these inter-related metrics. In this paper, we study two existing approaches that quantify crowd-sensed data trustworthiness, based on statistical and vote-based user reputation scores. We introduce a new metric—collaborative reputation scores—to expand this definition. Our simulation results show that collaborative reputation scores can provide an effective alternative to the previously proposed metrics and are able to extend crowd sensing to applications that are driven by a centralized as well as decentralized control.
126 citations
TL;DR: In this article, the performance of edge content caching for mobile video streaming is analyzed using frequency-domain and entropy analysis approaches, and an efficient caching strategy based on the measurement insights and experimentally evaluate its performance.
Abstract: Today’s Internet has witnessed an increase in the popularity of mobile video streaming, which is expected to exceed 3/4 of the global mobile data traffic by 2019. To satisfy the considerable amount of mobile video requests, video service providers have been pushing their content delivery infrastructure to edge networks—from regional content delivery network (CDN) servers to peer CDN servers (e.g., smartrouters in users’ homes)—to cache content and serve users with storage and network resources nearby. Among the edge network content caching paradigms, Wi-Fi access point caching and cellular base station caching have become two mainstream solutions. Thus, understanding the effectiveness and performance of these solutions for large-scale mobile video delivery is important. However, the characteristics and request patterns of mobile video streaming are unclear in practical wireless network. In this paper, we use real-world data sets containing 50 million trace items of nearly 2 million users viewing more than 0.3 million unique videos using mobile devices in a metropolis in China over two weeks, not only to understand the request patterns and user behaviors in mobile video streaming, but also to evaluate the effectiveness of Wi-Fi and cellular-based edge content caching solutions. To understand the performance of edge content caching for mobile video streaming, we first present temporal and spatial video request patterns, and we analyze their impacts on caching performance using frequency-domain and entropy analysis approaches. We then study the behaviors of mobile video users, including their mobility and geographical migration behaviors, which determine the request patterns. Using trace-driven experiments, we compare strategies for edge content caching, including least recently used (LRU) and least frequently used (LFU), in terms of supporting mobile video requests. We reveal that content, location, and mobility factors all affect edge content caching performance. Moreover, we design an efficient caching strategy based on the measurement insights and experimentally evaluate its performance. The results show that our design significantly improves the cache hit rate by up to 30% compared with LRU/LFU.
TL;DR: This article provides a systematic literature review of the existing studies on mobile UI design patterns to give an overview of recent studies on the mobile designs and provides an analysis on what topics or areas have insufficient information and what factors are concentrated upon.
Abstract: Mobile platforms have called for attention from HCI practitioners, and, ever since 2007, touchscreens have completely changed mobile user interface and interaction design. Some notable differences between mobile devices and desktops include the lack of tactile feedback, ubiquity, limited screen size, small virtual keys, and high demand of visual attention. These differences have caused unprecedented challenges to users. Most of the mobile user interface designs are based on desktop paradigm, but the desktop designs do not fully fit the mobile context. Although mobile devices are becoming an indispensable part of daily lives, true standards for mobile UI design patterns do not exist. This article provides a systematic literature review of the existing studies on mobile UI design patterns. The first objective is to give an overview of recent studies on the mobile designs. The second objective is to provide an analysis on what topics or areas have insufficient information and what factors are concentrated upon. This article will benefit the HCI community in seeing an overview of present works, to shape the future research directions.
TL;DR: The need for the deep customization of mobile networks at different granularity levels is discussed: per network, per application, per group of users, per individual users, and even per data of users.
Abstract: 5G mobile systems are expected to meet different strict requirements beyond the traditional operator use cases. Effectively, to accommodate needs of new industry segments such as healthcare and manufacturing, 5G systems need to accommodate elasticity, flexibility, dynamicity, scalability, manageability, agility, and customization along with different levels of service delivery parameters according to the service requirements. This is currently possible only by running the networks on top of the same infrastructure, the technology called network function virtualization, through this sharing of the development and infrastructure costs between the different networks. In this article, we discuss the need for the deep customization of mobile networks at different granularity levels: per network, per application, per group of users, per individual users, and even per data of users. The article also assesses the potential of network slicing to provide the appropriate customization and highlights the technology challenges. Finally, a high-level architectural solution is proposed, addressing a massive multi-slice environment.
TL;DR: A mobile service provisioning architecture named a mobile service sharing community is proposed and a service composition approach by utilizing the Krill-Herd algorithm is proposed, which can obtain superior solutions as compared with current standard composition methods in mobile environments.
Abstract: The advances in mobile technologies enable mobile devices to perform tasks that are traditionally run by personal computers as well as provide services to the others. Mobile users can form a service sharing community within an area by using their mobile devices. This paper highlights several challenges involved in building such service compositions in mobile communities when both service requesters and providers are mobile. To deal with them, we first propose a mobile service provisioning architecture named a mobile service sharing community and then propose a service composition approach by utilizing the Krill-Herd algorithm. To evaluate the effectiveness and efficiency of our approach, we build a simulation tool. The experimental results demonstrate that our approach can obtain superior solutions as compared with current standard composition methods in mobile environments. It can yield near-optimal solutions and has a nearly linear complexity with respect to a problem size.
Journal Article•
TL;DR: Mobile cloud computing maps cloud computing ideas and overcomes obstacles that deal with performance such as battery life, CPU, storage, bandwidth, environment that means heterogeneity, scalability, availability and security discussed in mobile computing.
Abstract: Mobile devices such as smart phones and tablets have become an essential part of our lives, because of their powerful capabilities Along with the explosive growth of the mobile applications and up-raising cloud computing concept, mobile cloud computing appears to be a new potential technology for mobile services Mobile cloud computing maps cloud computing ideas and overcomes obstacles that deal with performance such as battery life, CPU, storage, bandwidth, environment that means heterogeneity, scalability, availability and security discussed in mobile computing To solve these problems by accessing cloud computing platforms To access these platforms is not always guaranteed to be available and is too expensive to access themTo overcome this issue by creating a virtual cloud computing platform using mobile phones
TL;DR: This article aims to provide an integrated picture of this emerging field to bridge multiple disciplines and hopefully to inspire future research.
Abstract: The worldwide rollout of 4G LTE mobile communication networks has accelerated the proliferation of the mobile Internet and spurred a new wave of mobile applications on smartphones. This new wave has provided mobile operators an enormous opportunity to collect a huge amount of data to monitor the technical and transactional aspects of their networks. Recent research on mobile big data mining have shown its great potential for diverse purposes ranging from improving traffic management, enabling personal and contextual services, to monitoring city dynamics and so on. The mobile big data research has a multi-disciplinary nature that demands distinct knowledge from mobile communications, signal processing, and data mining. The research field of mobile big data has emerged quickly in recent years, but is somewhat fragmented. This article aims to provide an integrated picture of this emerging field to bridge multiple disciplines and hopefully to inspire future research.
04 Jun 2017
TL;DR: The experimental results indicate that the performance of LPWAN is surprisingly susceptible to mobility, even to minor human mobility, and the effect of mobility significantly escalates as the distance to the gateway increases.
Abstract: In the past decade, we have witnessed explosive growth in the number of low-power embedded and Internet-connected devices, reinforcing the new paradigm, Internet of Things (IoT) The low power wide area network (LPWAN), due to its long-range, low-power and low-cost communication capability, is actively considered by academia and industry as the future wireless communication standard for IoT However, despite the increasing popularity of `mobile IoT', little is known about the suitability of LPWAN for those mobile IoT applications in which nodes have varying degrees of mobility To fill this knowledge gap, in this paper, we conduct an experimental study to evaluate, analyze, and characterize LPWAN in both indoor and outdoor mobile environments Our experimental results indicate that the performance of LPWAN is surprisingly susceptible to mobility, even to minor human mobility, and the effect of mobility significantly escalates as the distance to the gateway increases These results call for development of new mobility-aware LPWAN protocols to support mobile IoT
TL;DR: A mobility analytical framework for big mobile data is introduced, based on real data traffic collected from second-, third- and fourth-generation networks, which covered nearly 7 million people and reveals the changing of city hotspots, the movement patterns during peak hours, and people with similar history trajectories, which uncover the common rules that exist among huge populations in a city.
Abstract: Due to the pervasiveness of mobile devices, a vast amount of geolocated data is generated, which allows us to gain deep insight into human behavior. Among other data sources, the analysis of data traffic from mobile Internet enables the study of mobile subscribers' movements over long time periods at large scales, which is paramount to research over a wide range of disciplines, e.g., sociology, transportation, epidemiology, networking, etc. However, to efficiently analyze the massive data traffic from the view of user mobility, several technical challenges have to be tackled before releasing the full potential of such data sources, including data collection, trajectory construction, data noise removing, data storage, and methods for analyzing user mobility. This paper introduces a mobility analytical framework for big mobile data, based on real data traffic collected from second-, third- and fourth-generation networks, which covered nearly 7 million people. To construct a user's history trajectories, we apply different rules to extract users' locations from different data sources and reduce oscillations between the cell towers. The comparison of mobility characteristics between our mobile data and other existing data sources shows the large potential of mobile Internet data traffic to study human mobility. In addition, our experiments discover the changing of city hotspots, the movement patterns during peak hours, and people with similar history trajectories, which uncover the common rules that exist among huge populations in a city.
TL;DR: In this survey, in-depth and comprehensive coverage on the features, sources and applications of mobile big data, as well as the current state-of-the-art, challenges and opportunities for research and development in this field are provided, with an emphasis on the user modeling, infrastructure supporting, data management, and knowledge discovery aspects.
Abstract: In the past decade, the smart phone evolution has accelerated the proliferation of the mobile Internet and spurred a new wave of mobile applications, leading to an unprecedented mobile data volume generated from the mobile devices, content servers, and network operators, which are mainly nonstructured. In this big data era, such nonstructured data fragments are pieced together such that, drastically differing from the traditional practice where services determine and define the data, data is becoming a proactive entity that may drive and even create new services. Compared with the so-termed 5V characteristics of generic big data, namely volume, variety, velocity, veracity, and value, mobile big data is distinct in its unique multidimensional, personalized, multisensory, and real-time features. In this survey, we provide in-depth and comprehensive coverage on the features, sources and applications of mobile big data, as well as the current state-of-the-art, challenges and opportunities for research and development in this field, with an emphasis on the user modeling, infrastructure supporting, data management, and knowledge discovery aspects.
TL;DR: In this article, the possession of shopping applications (hereafter, apps) and the purchase via shopping apps are examined and the implications for mobile retailing research and practice are discussed.
20 May 2017
TL;DR: It is observed that the battery of the mobile device can last up to approximately an extra hour if the applications are developed with energy-aware practices, paving the way for a set of guidelines for energy- aware automatic refactoring techniques.
Abstract: Mobile and wearable devices are nowadays the de facto personal computers, while desktop computers are becoming less popular. Therefore, it is important for companies to deliver efficient mobile applications. As an example, Google has published a set of best practices to optimize the performance of Android applications. However, these guidelines fall short to address energy consumption. As mobile software applications operate in resource-constrained environments, guidelines to build energy efficient applications are of utmost importance. In this paper, we studied whether or not a set of best performance-based practices have an impact on the energy consumed by Android applications. In an experimental study with six popular mobile applications, we observed that the battery of the mobile device can last up to approximately an extra hour if the applications are developed with energy-aware practices. This work paves the way for a set of guidelines for energy-aware automatic refactoring techniques.
TL;DR: A mobile network architecture enabled by big data analytics is proposed, which is capable of efficient resource orchestration, content distribution, and radio access network optimization and effectively bridges the latency gap between big data cloud computing and real-time network optimization.
Abstract: Mobile communication networks are more and more characterized by the integration of distributed and centralized computing and storage resources. Big data capability thus available throughout such networks will not only deliver enhanced system performance, but also profoundly impact the design and standardization of the next-generation network architecture, protocol stack, signaling procedure, and physical- layer processing. In this article, a mobile network architecture enabled by big data analytics is proposed, which is capable of efficient resource orchestration, content distribution, and radio access network optimization. The protocol stack configuration at each access point and the processing optimization of each layer are presented. Key physical layer designs including reference signals and frame structure are discussed. Moreover, utilizing signals in the transform domains, such as delay, Doppler, and angle, may bring enlarged coherence time of the effective channels. It enables much simpler physical layer design, and effectively bridges the latency gap between big data cloud computing and real-time network optimization.
TL;DR: Simulation results show that the proposed method outperforms the exiting counterparts with a higher hit ratio and lower delay of delivering video contents, and leveraging the backward induction method, the optimal strategy of each player in the game model is proposed.
Abstract: To improve the performance of mobile video delivery, caching layered videos at a site near to mobile end users (e.g., at the edge of mobile service provider's backbone) was advocated because cached videos can be delivered to mobile users with a high quality of experience, e.g., a short latency. How to optimally cache layered videos based on caching price, the available capacity of cache nodes, and the social features of mobile users, however, is still a challenging issue. In this paper, we propose a novel edge caching scheme to cache layered videos. First, a framework to cache layered videos is presented in which a cache node stores layered videos for multiple social groups, formed by mobile users based on their requests. Due to the limited capacity of the cache node, these social groups compete with each other for the number of layers they request to cache, aiming at maximizing their utilities while all mobile users in each group share the cost involved in the cache of video contents. Second, a Stackelberg game model is developed to study the interaction among multiple social groups and the cache node, and a noncooperative game model is introduced to analyze the competition among mobile users in different social groups. Third, leveraging the backward induction method, the optimal strategy of each player in the game model is proposed. Finally, simulation results show that the proposed method outperforms the exiting counterparts with a higher hit ratio and lower delay of delivering video contents.
TL;DR: This paper formally models this problem of mobile service selection for composition in terms of energy consumption and constructs energy consumption computation models that adopts the genetic algorithm to resolve it.
Abstract: Due to the limits of battery capacity of mobile devices, how to select cloud services to invoke in order to reduce energy consumption in mobile environments is becoming a critical issue. This paper addresses the problem of mobile service selection for composition in terms of energy consumption. It formally models this problem and constructs energy consumption computation models. Energy consumption aggregation rules for composite services with different structures are presented. It adopts the genetic algorithm to resolve it. A replanning mechanism is also proposed to deal with the changeable conditions and user behavior. A series of experiments are conducted to evaluate the performance of our method. The results show that our service selection method significantly outperforms traditional methods. Even if the conditions or user behavior is changeable, this method is still effective to recommend services. Moreover, the service selection method performs good scalability as the experimental scale increases.
TL;DR: Using mobile devices in clinical settings and the patterns of use and impact this has on doctors in the workplace and how negatively or positively it impacts at the point of care are studied.
Abstract: Background Mobile device use has become almost ubiquitous in daily life and therefore includes use by doctors in clinical settings. There has been little study as to the patterns of use and impact this has on doctors in the workplace and how negatively or positively it impacts at the point of care. Aim To explore how doctors use mobile devices in the clinical setting and understand drivers for use. Methods A mixed methods study was used with doctors in a paediatric and adult teaching hospital in 2013. A paper-based survey examined mobile device usage data by doctors in the clinical setting. Focus groups explored doctors' reasons for using or refraining from using mobile devices in the clinical setting, and their attitudes about others' use. Results The survey, completed by 109 doctors, showed that 91% owned a smartphone and 88% used their mobile devices frequently in the clinical setting. Trainees were more likely than consultants to use their mobile devices for learning and accessing information related to patient care, as well as for personal communication unrelated to work. Focus group data highlighted a range of factors that influenced doctors to use personal mobile devices in the clinical setting, including convenience for medical photography, and factors that limited use. Distraction in the clinical setting due to use of mobile devices was a key issue. Personal experience and confidence in using mobile devices affected their use, and was guided by role modelling and expectations within a medical team. Conclusion Doctors use mobile devices to enhance efficiency in the workplace. In the current environment, doctors are making their own decisions based on balancing the risks and benefits of using mobile devices in the clinical setting. There is a need for guidelines around acceptable and ethical use that is patient-centred and that respects patient privacy.
03 Apr 2017
TL;DR: An anti-tracking mechanism that enable the users to access an online service through a mobile app without risking their privacy, and is able to preserve the privacy of the user by reducing the leaking identifiers of apps by 27.41% on average, while it imposes a practically negligible latency of less than 1 millisecond per request.
Abstract: The vast majority of online services nowadays, provide both a mobile friendly website and a mobile application to their users. Both of these choices are usually released for free, with their developers, usually gaining revenue by allowing advertisements from ad networks to be embedded into their content. In order to provide more personalized and thus more effective advertisements, ad networks usually deploy pervasive user tracking, raising this way significant privacy concerns. As a consequence, the users do not have to think only their convenience before deciding which choice to use while accessing a service: web or app, but also which one harms their privacy the least. In this paper, we aim to respond to this question: which of the two options protects the users' privacy in the best way apps or browsers? To tackle this question, we study a broad range of privacy related leaks in a comparison of several popular apps and their web counterpart. These leaks may contain not only personally identifying information (PII) but also device-specific information, able to cross-application and cross-site track the user into the network, and allow third parties to link web with app sessions. Finally, we propose an anti-tracking mechanism that enable the users to access an online service through a mobile app without risking their privacy. Our evaluation shows that our approach is able to preserve the privacy of the user by reducing the leaking identifiers of apps by 27.41% on average, while it imposes a practically negligible latency of less than 1 millisecond per request.
01 Feb 2017
TL;DR: The research is a detailed study on 3G, 4G, and 5G network technologies and it can assure 5G is capable of managing the mobile traffic.
Abstract: In the recent decades, wireless communication system development has been changing enormously. The Wireless application services are increasing quickly and the service provider is very hard to manage the user requested services. As per the Ericson mobility report on 2016 utters in 2021, the worldwide mobile subscriptions will accomplish 9,000 million, then W-CDMA and HSPA subscriptions will reach 3,100 million and LTE will attain 4,300 million subscriptions, so in upcoming years 3G and 4G technologies will difficult to handle the mobile traffics. 5G subscriptions are expecting to be commercial technology from 2020 onwards and it can assure 5G is capable of managing the mobile traffic. The purpose of the research is a detailed study on 3G, 4G, and 5G network technologies.
TL;DR: A cohesive end-to-end architecture is proposed, fully exploiting Information-Centric Networking together with the Mobile Follow-Me Cloud approach, for enhancing the migration of content-caches located at the edge of cloudified mobile networks.
TL;DR: A novel green video transmission (GVT) algorithm that uses video clustering and channel assignment to assist in video transmission and demonstrates a superior video transmission performance compared with the existing methods.
Abstract: Video transmission is an indispensable component of most applications related to the mobile cloud networks (MCNs). However, because of the complexity of the communication environment and the limitation of resources, attempts to develop an effective solution for video transmission in the MCN face certain difficulties. In this paper, we propose a novel green video transmission (GVT) algorithm that uses video clustering and channel assignment to assist in video transmission. A video clustering model is designed based on game theory to classify the different video parts stored in mobile devices. Using the results of video clustering, the GVT algorithm provides the function of channel assignment, and its assignment process depends on the content of the video to improve channel utilization in the MCN. Extensive simulations are carried out to evaluate the GVT with several performance criteria. Our analysis and simulations show that the proposed GTV demonstrates a superior video transmission performance compared with the existing methods.
TL;DR: This article shows, together with standardization aspects, how combining C-RAN and D2D technologies can help to solve the delay issue and fulfill most of the targets specified for 5G networks in terms of delay, capacity, energy efficiency, mobility, and cost.
Abstract: With the surge in smartphone sensing, wireless networking, and mobile social networking techniques, mobile crowdsensing (MCS) has become a promising paradigm for 5G networks. An MCS system's service quality heavily depends on the platform, which brings the users under a common cloud with very low delay. Therefore, MCS needs a new platform that brings the best not only from the user's perspective, but also from the operator's perspective. In this article, we propose a novel architecture for MCS by combining two technologies, those being C-RAN and D2D. C-RAN is a promising enabling technology that can at the same time cope with the ever increasing mobile traffic demand and reduce the surging costs experienced by service operators. In spite of the many advantages offered by C-RAN, one of the main concerns for operators is its associated fronthaul delay. To handle such delay, we come across this D2D solution in C-RAN networks. D2D is adopted as an effective candidate for very low delay between links and has already provided evidence of its potential for novel business opportunities. This article shows, together with standardization aspects, how combining C-RAN and D2D technologies can help to solve the delay issue and fulfill most of the targets specified for 5G networks in terms of delay, capacity, energy efficiency, mobility, and cost.