Two-Level Rejuvenation for AndroidSmartphones and Its Optimization

Two-Level Rejuvenation for AndroidSmartphones and Its Optimization

The Android operating system (OS) is a sophisticatedman-made system and is the dominant OS in the current smart-phone market. Due to the accumulation of errors in the systeminternal state and the incremental consumption of resources, suchas the Dalvik heap memory of software applications and the physi-cal memory, software aging is observed frequently and recognizedas a chronic problem of Android smartphones. To mitigate thisproblem, we propose a two-level software rejuvenation, with thetwo levels referring to software applications and the OS, in this pa-per. Based on this strategy, a Markov regenerative process model isconstructed to evaluate the steady-state availability and to optimizethe time required to trigger rejuvenation for Android smartphones.The parameters of the model, such as the degradation rate and fail-ure rate of software applications and the Android OS, are obtainedvia our testing platform. Experiments on two real Android applica-tions show that the availability of an Android smartphone increasesby 10.81% and 10.18% for the two subjects in our experiments,respectively. An empirical study comparing our two-level strategywith one-level strategies (single application-level and system-levelrejuvenation) further verifies the effectiveness of our approach.
The Android operating system (OS) is a sophisticatedman-made system and is the dominant OS in the current smart-phone market. Due to the accumulation of errors in the systeminternal state and the incremental consumption of resources, suchas the Dalvik heap memory of software applications and the physi-cal memory, software aging is observed frequently and recognizedas a chronic problem of Android smartphones. To mitigate thisproblem, we propose a two-level software rejuvenation, with thetwo levels referring to software applications and the OS, in this pa-per. Based on this strategy, a Markov regenerative process model isconstructed to evaluate the steady-state availability and to optimizethe time required to trigger rejuvenation for Android smartphones.The parameters of the model, such as the degradation rate and fail-ure rate of software applications and the Android OS, are obtainedvia our testing platform. Experiments on two real Android applica-tions show that the availability of an Android smartphone increasesby 10.81% and 10.18% for the two subjects in our experiments,respectively. An empirical study comparing our two-level strategywith one-level strategies (single application-level and system-levelrejuvenation) further verifies the effectiveness of our approach.Index Terms—Android, Markov regenerative process (MRGP),multilevel software aging, software rejuvenatioN Code Shoppy
 

ATREMENDOUS increase in the number of smartphonesover the last fifteen years has been observed. Smartphonesassist people both in their personal and business activities, sim-plifying their lives in various ways, e.g., enabling people to sende-mails, browse the Internet, and play games. Thus, as the func-tionality and complexity of smartphones rapidly increase, usersexpect a highly reliable and responsive platform. According tothe International Data Corporation (IDC), Android commanded86.8% of the world’s smartphone market in 2016 [1]. Android applications are written in Java and run in their own separateaddress spaces, and the Android operating system (OS) keepstrack of the applications and supports, e.g., their memory man-agement, process management, and device management.This paper focuses on the mitigation of the software agingproblem for Android smartphones. Software aging refers to theprogressive performance degradation of long-time running soft-ware, which may lead to system slow down, system crashes,or undesirable hangs [2]. Typical causes of software aging arememory leaks [3], nonterminated threads, storage fragmenta-tion, unreleased locks, and shared-memory pool latching [4].Software aging is known to occur for Android smartphones andmay greatly affect a user’s experience, especially after a longperiod of usage. Typical examples reported by Google’s An-droid project [5] include the camera application crashing afterrunning for a long time [6], a smartphone responding poorlybecause of a memory leak in thesurfaceflingerprocess [7], andan out-of-memory error occurring after many iterations of theprocess of language switching [8]. Therefore, the study of soft-ware aging mitigation techniques for Android smartphones isnecessary to help prevent/postpone or eliminate performancedegradation, solve the issues related to memory consumptionand avoid unexpected failures for Android software applica-tions and the Android OS [9]–[11].To counteract software aging, a software recovery techniqueknown as software rejuvenation was introduced [4]. Softwarerejuvenation is a proactive fault management technique aimed atpreventing/postponing performance degradation and crash fail-ures. It involves occasionally terminating an application, clean-ing up the system internal state, and restarting the system toprevent/postpone the occurrence of future failures [12], [13].Android offers a technique called low memory killer (LMK),which can partially refresh the system state to realize the goalof software rejuvenation. That is, once the amount of free sys-tem memory is below a threshold, the LMK chooses a targetapplication and terminates its host process. Thus, the mem-ory associated with the process is reclaimed and can be reallo-cated [14]. Simultaneously, Android intelligently manages thephysical memory for caching applications. After a user exits anapplication that is running in the foreground, Android stores theapplications process in memory. Consequently, the next timethe user requires the old application, the Android OS does notneed to repeat the initialization work
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An Android Wear OS Framework forSensor Data and Network Interfaces

An Android Wear OS Framework forSensor Data and Network Interfaces


Wearable devices like smartwatches conquer themarket and simplify our everyday life. Mostly, these devices areconnected to our mobile phones, helping us to make communica-tion easier and faster. However, wearable devices feature plentyof sensors and network interfaces that are mostly unused. Thus,the question arises on how to use this potential to improve thefunctionality and user experience of handset applications.This paper presents a framework for the Android operat-ing system which enables us to retrieve information from thewearable device and store and use it on the handheld device.The primary focus lies on sensor and network interfaces, andas a result, this information can be considered for furthercomputations. We offer the framework as an Android librarywhich can be included in all Android projects.We evaluate the framework by conducting network perfor-mance tests as well as tests regarding CPU, memory and batteryusage, and achieve promising results. Concluding, we can saythat the wearable technology offers lots of opportunities forpresent and future Android projects. Due to the different typesof framework services, we achieve the goal of providing a broadbase of information that can be utilized by all developers.

Today, there are many wearable devices on the market whichsimplify our everyday life. This technology includes deviceslike activity trackers, smart glasses, and smartwatches. Mostly,these devices are connected to our smartphone, helping us tomake communication in our public life easier and faster.Wearable devices feature an abundance of sensors andnetwork interfaces that mostly remain unchallenged. Thisis due to the habits of an average user which are mainlycharacterized by getting notifications of incoming messagesor receiving weather news. Thus, the question arises how touse a wearable device’s hidden potential, mainly to improvethe functionality and user experience of handset applications.Furthermore, this research will try to explore the possibilitiesand limits current wearable devices bring to be able to assesstheir capabilities.To this end, the idea came up to design a solution that makesit possible to use corresponding wearable functions efficiently.The design should enable developers and users to accesswearable interfaces and sensors remotely via mobile phone.The so far unchallenged wearable should thus become a newsource of information from which we can obtain additionaldata. Using this additional data raises the possibility to developnew functions and improve existing ones on the mobile phone.We motivate the realization of this idea by the challenges inour network applicationopptain[4].opptainis an applicationfor Android that uses Opportunistic Networking [7] for localdata exchange.opptainmanages its data exchange betweenclients via Wi-Fi. If a network node is a hotspot in thenetwork, it can only accept incoming requests but not scanfor available participants at the same time; and if two hotspotsmeet, they will not see each other. A problem is the Wi-Fichip on Android devices, which can only either be hotspotor client at the same time. With the help of a second Wi-Fimodule, the one in the wearable device, we can solve thisproblem. In general, the framework creates a solid base ofinformation generated by our wearable. We can use thisinformation for similar problems without being limited toWi-Fi or specific topics like Opportunistic Networking. Acommon field of research is the use of the wearables’ bodysensors [2]. These can be used to monitor vital signs ofpatients and automatically call for help in emergencies.Code Shoppy
The contribution of this work is a library that can beintegrated into present and future Android projects. Theintuitive usage of this framework allows future developersto focus on realizing their idea rather than dealing withimplementation difficulties to gain desired data. Theimplementation allows the user to access network interfacesand sensor and control element functions of the wearableand to transfer corresponding data to the mobile application.Through the various services that can be accessed, we createa broad information base on the side of the mobile phonewhich can be involved in future computation. This additionalknowledge enables the user to make better decisions thatfinally improve the usability and functionality of the mobileapplication itself. Considering that most customer complainsaddress functionality problems or functionality request [6],the need for our framework is emphasized.https://codeshoppy.com/android-app-ideas-for-students-college-project.html