Release Of Android Research Articles

Improving the Android Release Homologation Process through an Automated System applied to Security Maintenance Releases

Improving the Android Release Homologation Process through an Automated System applied to Security Maintenance Releases

Evolusi Sistem Operasi Android: Sebuah Tinjauan Literatur

In the past, mobile phones were only used to make calls, but with the introduction of smartphones, mobile phones have evolved into low-power handheld processing systems. This evolution is due to the operating system for mobile phones that make them sophisticated and have their own processing and storage. Today mobile phones provide many functions from making calls to sending messages, multimedia sharing, email, socializing applications, word processing, excel worksheets to various multiplayer games and much more. The operating systems for these handheld devices are iOS from Apple Inc, Windows from Windows Inc and Android from Google. Among competitors in the smartphone operating system industry, Android holds the largest market share in terms of units shipped worldwide and number of users. Android is an open source operating system based on the linux kernel where applications run on an application framework that controls activities supported by Dalvik libraries and virtual machines that compile and convert all java class files into a single file. There are several virtual machines running simultaneously on a single device that run different applications or application instances. The Android operating system provides memory management, process management to run applications and services. Every android release improves the user experience and brings enhanced features. This paper presents a study of the evolution that each release brings to the android operating system.

Comparison of Two Approaches to GNSS Positioning Using Code Pseudoranges Generated by Smartphone Device

The release of Android 7.0 has made raw GNSS positioning data available on smartphones and, as a result, this has allowed many experiments to be developed to evaluate the quality of GNSS positioning using mobile devices. This paper investigates the best positioning, using pseudorange measurement in the Differential Global Navigation Satellite System (DGNSS) and Single Point Positioning (SPP), obtained by smartphones. The experimental results show that SPP can be comparable to the DGNSS solution and can generally achieve an accuracy of one meter in planimetric positioning; in some conditions, an accuracy of less than one meter was achieved in the Easting coordinate. As far as altimetric positioning is concerned, it has been demonstrated that DGNSS is largely preferable to SPP. The aim of the research is to introduce a statistical method to evaluate the accuracy and precision of smartphone positioning that can be applied to any device since it is based only on the pseudoranges of the code. In order to improve the accuracy of positioning from mobile devices, two methods (Tukey and K-means) were used and applied, as they can detect and eliminate outliers in the data. Finally, the paper shows a case study on how the implementation of SPP on GIS applications for smartphones could improve citizen science experiments.

The Canadian Congenital Diaphragmatic Hernia Collaborative Mobile App: A National Guideline Implementation Strategy.

Coinciding with the publication of the Canadian congenital diaphragmatic hernia (CDH) Collaborative's clinical practice guidelines (CPG), we developed a mobile smartphone app to increase guideline utilization and promote knowledge translation. This mobile app was organized into sections corresponding to the phases of CDH care (prenatal, perinatal/postnatal, and child/adolescent), and contained 22 recommendations supported by evidence summaries, PubMed links, levels of evidence, and strength of expert consensus. Download statistics were collected from September 2018 to June 2020 after release of two iOS versions and an Android platform. Data regarding user numbers/location, most visited sections, and individual session details were analyzed. During the study period, the CDH app had 1,586 users predominantly from Canada (40%), United States (30%), and Brazil (12%). The Android release increased app visibility, particularly in Brazil, which had the largest number of new users. Of 3,723 sessions, roughly one-third were returning users. The average session duration and screens viewed/session was 4 minutes and seven screens, respectively. Postnatal ventilation was the most frequently visited subsection after prenatal diagnosis/risk stratification. Measurement of observed-to-expected lung head ratio was the most visited individual recommendation. The guideline compliance checklist was the most frequently accessed resource highlighting its utility. The CDH app is an innovative platform to disseminate guidelines. The increasing global reach of the app suggests worldwide CPG relevance. With additional features planned, the CDH app will continue to support clinical decision-making and empower patients and families as they navigate the short and long-term challenges associated with CDH. · Mobile smartphone technology provides an optimal platform for guideline dissemination.. · International uptake supports worldwide CPG relevance.. · Future initiatives include the development of patient and family resources..

A Comprehensive Analysis of the Android Permissions System

Android is one of the most essential and highly used operating systems. Android permissions system is a core security component that offers an access-control mechanism to protect system resources and users’ privacy. As such, it has experienced continuous change over each Android release. However, previous research on the permissions system has employed static analysis techniques. Furthermore, most of these studies are outdated, covering older versions of Android. This paper aims to discuss the permissions system intensively to provide a nutshell overview of the Android platform’s access-control mechanism. The paper presents a comprehensive analysis of the Android permissions system since it was introduced in 2008 until now, accompanied by a formal model of its components. The results of the analysis reveal a continuous growth in the number of permissions since the original release—a growth of seven times in some permission categories. A case study has been conducted for the last five years’ versions of the top Android apps to examine the permissions system’s evolution and its attendant security issues from the applications’ perspective. Some apps showed an increase in permissions usage of 73.33% by the 2020 release. Additionally, the results of the case study contribute to the understanding of permissions deployment by both vendors and developers. Finally, a discussion of the permission-based security enhancements discloses that the Android permissions system faces various security issues. In general, this paper provides researchers and academics an up-to-date, comprehensive, self-contained reference study of the Android permissions system.

An Improved Hatch Filter Algorithm towards Sub-Meter Positioning Using only Android Raw GNSS Measurements without External Augmentation Corrections

In May 2016, the availability of GNSS raw measurements on smart devices was announced by Google with the release of Android 7. It means that developers can access carrier-phase and pseudorange measurements and decode navigation messages for the first time from mass-market Android-devices. In this paper, an improved Hatch filter algorithm, i.e., Three-Thresholds and Single-Difference Hatch filter (TT-SD Hatch filter), is proposed for sub-meter single point positioning with raw GNSS measurements on Android devices without any augmentation correction input, where the carrier-phase smoothed pseudorange window width adaptively varies according to the three-threshold detection for ionospheric cumulative errors, cycle slips and outliers. In the mean time, it can also eliminate the inconsistency of receiver clock bias between pseudorange and carrier-phase by inter-satellite difference. To eliminate the effects of frequent smoothing window resets, we combine TT-SD Hatch filter and Kalman filter for both time update and measurement update. The feasibility of the improved TT-SD Hatch filter method is then verified using static and kinematic experiments with a Nexus 9 Android tablet. The result of the static experiment demonstrates that the position RMS of TT-SD Hatch filter is about 0.6 and 0.8 m in the horizontal and vertical components, respectively. It is about 2 and 1.6 m less than the GNSS chipset solutions, and about 10 and 10 m less than the classical Hatch filter solution, respectively. Moreover, the TT-SD Hatch filter can accurately detect the cycle slips and outliers, and reset the smoothed window in time. It thus avoids the smoothing failure of Hatch filter when a large cycle-slip or an outlier occurs in the observations. Meanwhile, with the aid of the Kalman filter, TT-SD Hatch filter can keep continuously positioning at the sub-meter level. The result of the kinematic experiment demonstrates that the TT-SD Hatch filter solution can converge after a few minutes, and the 2D error is about 0.9 m, which is about 64%, 89%, and 92% smaller than that of the chipset solution, the traditional Hatch filter solution and standard single point solution, respectively. Finally, the TT-SD Hatch filter solution can recover a continuous driving track in this kinematic test.

Breaking and fixing the Android Launching Flow

The security model of the Android OS is based on the effective combination of a number of well-known security mechanisms (e.g. statically defined permissions for applications, the isolation offered by the Dalvik Virtual Machine, and the well-known Linux discretionary access control model). Although each security mechanism has been extensively tested and proved to be effective in isolation, their combination may suffer from unexpected security flaws. We show that this is actually the case by presenting a severe vulnerability in Android related to the application launching flow. This vulnerability is based on a security flaw affecting a kernel-level socket (namely, the Zygote socket). We also present an exploit of the vulnerability that allows a malicious application to mount a severe Denial-of-Service attack that makes the Android devices become totally unresponsive. Besides explaining the vulnerability (which affects all versions of Android up to version 4.0.3) we propose two fixes. One of the two fixes has been adopted in the official release of Android, starting with version 4.1. We empirically assess the impact of the vulnerability as well as the efficacy of the countermeasures on the end user. We conclude by extending our security analysis to the whole set of sockets, showing that other sockets do not suffer from the same vulnerability as the Zygote one.

Carry on regardless [android operating system

One feature of a disruptive technology is that it should work its magic in ways even its creators did not intend. So much could be said about the increasing use of Android, the Google-backed open source operating system (OS), in embedded systems. Even as Android displaces Microsoft Windows and other proprietary OSs in applications that run across the embedded market from TVs and set-top boxes to military communications via medical and industrial, Google remains profoundly disinterested. Such players that influence its thinking about the development of any dessert-themed Android release remain Tier 1 players in mobile handsets and tablets. Everything else is a sideshow.

안드로이드 달빅과 자바 가상머신의 성능비교

본 논문에서는 안드로이드에 탑재되는 가상머신인 달빅(Dalvik) 가상머신의 성능을 벤치마크를 구현하여 측정하고 기존 임베디드 자바 가상머신과의 성능을 비교한다. 달빅 가상머신의 성능 측정을 위하여 가상머신 성능 측정에 널리 사용되는 SPECJVM 벤치마크를 사용하였다. 달빅과의 성능 비교를 위하여 임베디드 자바 가상머신인 SUN Java 임베디드 버전을 비교 대상으로 선정하여 동일한 벤치마크를 사용하여 실행시간을 비교하였다. 성능 측정은 스마트폰 개발 하드웨어인 오드로이드(Odroid)에 가상머신과 벤치마크 프로그램들을 포팅하여 이루어 졌다. 또한, 달빅 가상머신의 최근 버전에서 구현되지 않은 적시(Just-In-Time) 컴파일 기능을 달빅에 추가하여 성능 개선 정도를 분석하였다. 분석 결과 안드로이드 달빅 가상머신은 SUN 가상머신 성능의 15% 수준을 보였으며, 적시 컴파일 기법을 적용한 달빅은 63% 수준에 도달함을 보였다. In this paper we analyzed performance of Andriod's Davik virtual machine(VM) using standard benchmark and compared the result with the embedded Java virtual machine. We used a well known benchmark suit named SPECJVM for the measurement. For the fair comparison, Sun Java embedded JVM is ported and the same benchmark is ported on it. The Odriod smartphone hardware platform is used as the target hardware. We have added a Just-In-Time compiler to Dalvik, which is not supported in the recent Android release, and measured performance improvement. The experiment result show that Dalvik achieved 15% and Dalvik with JIT shows 63% of the Sun's JVM performance.

The Androids are coming

With the release of Android, the battle is on for the mobile operating system market. The first thing to say about Android is that it is built on a Linux kernel (version 2.6 for those familiar with the open-source code). Google's grand plan is based on promising something that sounds almost too good to be true. Google is offering a free-to-use yet versatile OS that could help handset makers reduce time-to-market for new devices. Android is also a fully open, customisable OS that could help cellular operators differentiate their service propositions while lowering the cost of innovative devices. Android is also an open invitation to mobile software developers to write exciting third-party applications. Finally, Android may give mobile phone users an Internet experience on their handsets to rival that which they've come to expect from their PCs.