Execution Of Mobile Applications Research Articles

A fault‐tolerant dynamic scheduling method on hierarchical mobile edge cloud computing

AbstractMobile edge cloud computing has been a promising computing paradigm, where mobile users could offload their application workloads to low‐latency local edge cloud resources. However, compared with remote public cloud resources, conventional local edge cloud resources are limited in computation capacity, especially when serve large number of mobile applications. To deal with this problem, we present a hierarchical edge cloud architecture to integrate the local edge clouds and public clouds so as to improve the performance and scalability of scheduling problem for mobile applications. Besides, to achieve a trade‐off between the cost and system delay, a fault‐tolerant dynamic resource scheduling method is proposed to address the scheduling problem in mobile edge cloud computing. The optimization problem could be formulated to minimize the application cost with the user‐defined deadline satisfied. Specifically, firstly, a game‐theoretic scheduling mechanism is adopted for resource provisioning and scheduling for multiprovider mobile applications. Then, a mobility‐aware dynamic scheduling strategy is presented to update the scheduling with the consideration of mobility of mobile users. Moreover, a failure recovery mechanism is proposed to deal with the uncertainties during the execution of mobile applications. Finally, experiments are designed and conducted to validate the effectiveness of our proposal. The experimental results show that our method could achieve a trade‐off between the cost and system delay.

Process state synchronization-based application execution management for mobile edge/cloud computing

Mobile cloud computing (MCC) and mobile edge computing (MEC) facilitate the mobile devices to augment their capabilities by utilizing the resources and services offered by Cloud and Edge Cloud, respectively. However, due to mobility, network connection becomes unstable that causes application execution disruption. Such disruption increases the execution time and in some cases restrain the mobile devices from getting execution results from the cloud. This research work analyzes the impact of user mobility on the execution of cloud-based mobile applications. We propose a Process State Synchronization (PSS)-based execution management to solve the aforementioned problem. We analytically compute a sufficient condition on synchronization interval that ensure reduction in mobile application execution time under PSS in case of disconnection. Similarly, we compute the upper bound on synchronization interval whereby a larger synchronization interval did not result in significant benefits in terms of execution time for the mobile application. The analytical results were confirmed by the sample implementation of PSS with the computed synchronization intervals. Moreover, we also compare the performance of proposed solution with the state-of-the-art solutions. The results show that the PSS-based execution outperforms the other contemporary solutions.

PMC2O: Mobile cloudlet networking and performance analysis based on computation offloading

The increase of smart mobile device (SMD) results in explosive growth in mobile traffic and provokes mobile users to leverage more and more compute-intensive applications through SMD. Framework of seamless mobile application execution and networking based on edge computing resources is proved to be one of the promising trends in future mobile Internet. Focusing on networking of Ad hoc cloudlet, this paper proposed a dynamic cloudlet self-networking framework based on component offloading (PMC2O). Taking node mobility into account, dynamic cloudlet behaviour is investigated, and an optimized allocation algorithm called SA-UM is presented to reduce the complexity of resolution space on component allocation algorithm. Proactive Remove decision algorithm based on Node Resource Cooperative Sharing Degree (PRDA-NRCSD) is put forward to improve user experience and optimize the load balancing of a mobile cloudlet.

Model-driven framework to support evolution of mobile applications in multi-cloud environments

Purpose The development of mobile applications in multiple clouds environment is a complex task because of the lack of platform standards in cloud computing and mobile computing. The source code involves various proprietary programming libraries for different platforms. However, functionalities are inevitably changed over time, as well as the platform. Therefore, a great deal of development effort is required, when changes need to be made at functional and platform level. This paper aims to propose SIMON, a framework that eases complexity of the development to support software evolution. Design/methodology/approach SIMON shields the developer from the complexity of mobile and cloud platforms in the development of mobile applications in multiple clouds environment. The framework uses model of application design to automate the development and support execution of mobile applications in system environment that needs integration to the number of data sources located on multiple clouds. The framework is composed of prefabricated components that support function changeability and platform adaptability. Findings The framework is examined with the development of a sample application. After it is evaluated with scenarios that involve changing at functional and platform levels, the result shows significant reducing of the development effort by comparing with the other approaches. Originality/value The framework facilitates the implementation of mobile applications in the software system that involves integration to multiple clouds, and it supports software evolution with lesser development effort.

Run Time Application Repartitioning in Dynamic Mobile Cloud Environments

As mobile computing increasingly interacts with the cloud, a number of approaches, e.g., MAUI and CloneCloud, have been proposed, aiming to offload parts of the mobile application execution to the cloud. To achieve a good performance by using these approaches, they particularly focus on the application partitioning problem, i.e., to decide which parts of an application should be offloaded to the cloud and which parts should be executed on mobile devices such that the execution cost is minimized. Most works on this problem assume that the offloading cost of each part of the application remains the same as the application is running. Unfortunately, this assumption does not hold in dynamic mobile cloud environments, where the device and network connection status may fluctuate, and thus affects the offloading cost. With the varying offloading cost, the one time partitioning of the application may yield significant performance degradations. In this paper, we study application repartitioning problem which considers updating the partition periodically during the course of application execution. We first propose a framework for run time application repartitioning in dynamic mobile cloud environments. Based on this framework, we take the dynamic network connection to clouds as a case study, and design an online solution, Foreseer, to solve the mobile cloud application repartitioning problem. We evaluate our solution based on real world data traces that are collected in a campus WiFi hotspot testbed. The result shows that our method can achieve significantly shorter completion time over previous approaches.

웹/모바일-어플리케이션 접속 지표와 TCS 교통량의 상관관계 연구

최근 스마트폰의 빠른 보급으로 누구나 언제 어디서든 자유로운 네트워크 접속이 가능해졌다. 이는 통행 전은 물론 통행 중 교통정보 검색이 매우 편리해졌음을 의미한다. 고속도로 교통정보 탐색 행태의 기반이 되는 상관성 분석을 위하여, 웹과 모바일-앱의 접속 지표에 대한 정상성 여부를 검증하고, TCS 교통량과의 상관관계를 실증적으로 분석하는 것이 본 연구의 목적이다. 그 결과 첫째, 시간대별 웹/모바일-앱의 접속 지표에 대한 ADF-검정, PP-검정 결과, 로그변환이나 차분변환 없이도 시계열의 정상성 조건을 만족하는 것으로 나타났다. 둘째, 고속도로 진출입 교통량과의 피어슨 상관계수를 검토한 결과, 웹/모바일-앱의 모든 접속 지표는 뚜렷한 양적 상관관계를 보였다. 단, 트럭의 TCS 진입 교통량은 상관관계가 거의 없는 것으로 나타났다. 셋째, 시계열 변수 사이에 존재하는 발생시간의 시차 관계(동행성, 선행성, 후행성)를 규명하기 위해 교차분석을 수행한 결과, 모바일 이용자는 모든 웹 접속 지표보다 선행하고 있었으며, 모바일 실행횟수는 모든 웹 접속 지표와 동행함을 발견하였다. 넷째, 고속도로의 진입 교통량에 선행하는 웹/모바일-앱 접속 지표는 존재하지 않았으며, 웹 페이지뷰/방문자/신규방문자/재방문자, 모바일 실행횟수는 오히려 고속도로 진입 총 교통량과 비교시 1시간의 후행 시차에서 상관관계가 가장 높게 나타났다. 향후 분석의 공간적 범위와 시간적 범위를 세분화하고 교통정보 이용자의 위치정보를 활용할 수 있다면, 경로 전환 시점/비율과 같은 개별 통행행태까지도 예측할 수 있게 될 것으로 판단된다. In the recent years, the internet has become accessible without limitation of time and location to anyone with smartphones. It resulted in more convenient travel information access both on the pre-trip and en-route phase. The main objective of this study is to conduct a stationary test for traffic information web/mobile application access indexes from TCS (Toll Collection System); and analyzing the relationship between the web/mobile application access indexes and actual traffic volume on expressways, in order to analyze searching behavior of expressway related travel information. The key findings of this study are as follows: first, the results of ADF-test and PP-test confirm that the web/mobile application access indexes by time periods satisfy stationary conditions even without log or differential transformation. Second, the Pearson correlation test showed that there is a strong and positive correlation between the web/mobile application access indexes and expressway entry and exit traffic volume. In contrast, truck entry traffic volume from TCS has no significant correlation with the web/mobile application access indexes. Third, the time gap relationship between time-series variables (i.e., concurrent, leading and lagging) was analyzed by cross-correlation tests. The results indicated that the mobile application access leads web access, and the number of mobile application execution is concurrent with all web access indexes. Lastly, there was no web/mobile application access indexes leading expressway entry traffic volumes on expressways, and the highest correlation was observed between webpage view/visitor/new visitor/repeat visitor/application execution counts and expressway entry volume with a lag of one hour. It is expected that specific individual travel behavior can be predicted such as route conversion time and ratio if the data are subdivided by time periods and areas and utilizing traffic information users' location.

An energy-efficient scheduling scheme for time-constrained tasks in local mobile clouds

Mobile Cloud Computing (MCC) enables mobile devices to use resource providers other than mobile devices themselves to host the execution of mobile applications. Various mobile cloud architectures and scheduling algorithms have been studied recently. However, how to utilize MCC to enable mobile devices to run complex real-time applications while keeping high energy efficiency remains a challenge. In this paper, firstly, we introduce the local mobile clouds formed by nearby mobile devices and give the mathematical models of the mobile devices and their applications. Secondly, we formulate the scheduling problem in local mobile clouds. After describing the resource discovery scheme and the adaptive, probabilistic scheduling algorithm, we finally validate the performance of the proposed algorithm by simulation experiments.

Exploring a Context-based Network Access Control for Mobile Devices

Abstract Significant advancement in mobile devices coupled with high speed networks have shifted personal computing towards pervasive environments. Mobile devices currently offer many value-added applications and services such as emailing, messaging, navigation, social networking, finance, and entertainment. Typically, such value-added applications have access to users’ personal information and are capable of gathering and transmitting trust sensitive information, hence posing security risks and/or privacy concerns. In this paper, we propose a context-based analytic hierarchy process (AHP) framework for eliciting context information and adapting this information with network access control measures for mobile devices. The framework enforces the execution of mobile applications inside security incubators to control the communication between mobile applications and mobile device resources. Mobile applications’ access requests are analyzed based on user's context information collected from the mobile device sensors and the application network access control configuration. We use the Facebook mobile application, as a test case, to evaluate our proposed framework. Evaluation results have demonstrated the efficacy of the framework in providing network access control measures based on real-time assessment of user's context.

Optimization of Tasks in Mobile Cloud Computing

cloud computing is a new platform for the execution of mobile applications where cloud performs the stimulating computing-intensive tasks and storing data in place of the mobile devices and provides them an illusion of infinite computing resources. This research work considers a cloud based mobile computing system consisting of virtual machines (as resources), cloudlets (as requests) and broker, where the broker assigns user cloudlet requests to virtual machines to be processed by the servers. It has been a great challenge to design and build an effective load balancing algorithm for the broker which spreads the service request load on virtual machines while utilizing the resources to the maximum. In this paper, a scheduling model to optimize the load based on maximum resource utilization rate using genetic algorithm for scheduling requests is proposed where the computing capacity of a datacenter is divided into number of tiers. Simulation results shows that the proposed work can effectively cope with the load imbalance problem in mobile cloud computing. KeywordsBalancing, Cloudlets, Virtual Machines, Response Time.

Development of Energy-aware Mobile Applications Based on Resource Outsourcing

Smart connected devices such as smartphones and tablets are battery-operated to facilitate their mobility. Therefore, low power consumption is a critical requirement for mobile hardware and for the software designed for such devices. In addition to efficient power management techniques and new battery technologies based on nanomaterials, cloud computing has emerged as a promising technique for reducing energy consumption as well as augmenting the computational and memory capabilities of mobile devices. In this study, we designed and implemented a framework that allows for the energy-efficient execution of mobile applications by partially offloading the workload of a mobile device onto a resourceful cloud. This framework comprises a development toolkit, which facilitates the development of mobile applications capable of supporting computation offloading, and a runtime infrastructure for deployment in the cloud. Using this framework, we implemented three different mobile applications and demonstrated that considerable energy savings can be achieved compared with local processing for both resource-intensive and lightweight applications, especially when using high-speed networks such as Wi-Fi and Long-Term Evolution.

A Survey of Mobile Cloud Computing for Extending Energy of Mobile Devices

Mobile cloud computing will wear down gaining quality among users, the researchers predicts these troubles by execution of mobile applications on application suppliers external to the mobile device. During this paper, we have a tendency to gift a wide survey of mobile cloud computing, whereas prominence the particular considerations in mobile cloud computing square measure as follows. (a) Highlights the present state in Application of cloud computing usage in real time world. (b) Identifies the problems in testing bandwidth and (c) provides a optimizing of the offloading that saves energy

GemDroid

As the demand for feature-rich mobile systems such as smartphones and tablets has outpaced other computing systems and is expected to continue at a faster rate, it is projected that SoCs with tens of cores and hundreds of IPs (or accelerator) will be designed to provide unprecedented level of features and functionality in future. Design of such mobile systems with required QoS and power budgets along with other design constraints will be a daunting task for computer architects since any ad hoc, piece-meal solution is unlikely to result in an optimal design. This requires early exploration of the complete design space to understand the system-level design trade-offs. To the best of our knowledge, there is no such publicly available tool to conduct a holistic evaluation of mobile platforms consisting of cores, IPs and system software. This paper presents GemDroid, a comprehensive simulation infrastructure to address these concerns. GemDroid has been designed by integrating the Android open-source emulator for facilitating execution of mobile applications, the GEM5 core simulator for analyzing the CPU and memory centric designs, and models for several IPs to collectively study their impact on system-level performance and power. Analyzing a spectrum of applications with GemDroid, we observed that the memory subsystem is a vital cog in the mobile platform because, it needs to handle both core and IP traffic, which have very different characteristics. Consequently, we present a heterogeneous memory controller (HMC) design, where we divide the memory physically into two address regions, where the first region with one memory controller (MC) handles core-specific application data and the second region with another MC handles all IP related data. The proposed modifications to the memory controller design results in an average 25% reduction in execution time for CPU bound applications, up to 11% reduction in frame drops, and on average 17% reduction in CPU busy time for on-screen (IP bound) applications.

ACM HotMobile 2013 demo

A key concern in utilizing external resources for mobile application execution is a potential loss of data privacy. User data needs to be shipped to possibly untrusted remote nodes for execution. We introduce the concept of data partitioning, where in the user can conveniently identify the sensitive parts of the data, which is then prevented from being shipped to untrusted remote servers.

A framework for partitioning and execution of data stream applications in mobile cloud computing

The contribution of cloud computing and mobile computing technologies lead to the newly emerging mobile cloud computing paradigm. Three major approaches have been proposed for mobile cloud applications: 1) extending the access to cloud services to mobile devices; 2) enabling mobile devices to work collaboratively as cloud resource providers; 3) augmenting the execution of mobile applications on portable devices using cloud resources. In this paper, we focus on the third approach in supporting mobile data stream applications. More specifically, we study how to optimize the computation partitioning of a data stream application between mobile and cloud to achieve maximum speed/throughput in processing the streaming data. To the best of our knowledge, it is the first work to study the partitioning problem for mobile data stream applications, where the optimization is placed on achieving high throughput of processing the streaming data rather than minimizing the makespan of executions as in other applications. We first propose a framework to provide runtime support for the dynamic computation partitioning and execution of the application. Different from existing works, the framework not only allows the dynamic partitioning for a single user but also supports the sharing of computation instances among multiple users in the cloud to achieve efficient utilization of the underlying cloud resources. Meanwhile, the framework has better scalability because it is designed on the elastic cloud fabrics. Based on the framework, we design a genetic algorithm for optimal computation partition. Both numerical evaluation and real world experiment have been performed, and the results show that the partitioned application can achieve at least two times better performance in terms of throughput than the application without partitioning.

Hybrid contextual cloud in ubiquitous platforms comprising of smartphones

Nowadays, smartphones are gaining popularity due to cutting edge technology added on top of wearability. Unfortunately, offering such performance does not come cheap: the energy requirements of mobile phones tend to stretch beyond the extents of modern battery technology, which, ironically, is reaching the theoretical physical limit. At this crossroads, mobile device manufacturers and software engineers alike, have to take energy efficiency into consideration. Most research in this sense has mostly been oriented at tweaking and restricting resource utilisation. However, recent endeavours have been focusing on mobile cloud computing where all battery-sensitive computation is offloaded into clouds. We believe such endeavours will eventually prove insufficient, therefore we introduce a novel collaboration solution for mobile devices, namely HYCCUPS. The main idea behind the HYCCUPS framework is to take advantage of the pervasive nature of smartphones as to offer offloading the execution of mobile applications in an opportunistic hybrid computing cloud.

Review On Google Android a Mobile Platform

At present smart phone usage is increasing dramatically. Globally, if a usage comparison can be carried out between cell phone and smart phone devices. Smart phone is a personnel device which provides entertainment, information, making call and writing SMS. Customization makes cell phone a smart phone (installation and uninstallation of application). The increasing importance of smart phone devices has triggered intense competition among technology giants to capture the bigger market share for mobile platform. So Google launched Android, an open source mobile platform for smart phone devices consisting of a Linux Kernel, runtime environment, development framework, libraries and key applications. Since its official public release, Android has captured the market. This paper intends to explore conventional approach of mobile application execution, an approach of mobile application execution in Android & comparison between Android OS (Google), iOS (Apple) & Blackberry OS (RIM).

PLANNING TO OPTIMIZE THE UMTS CALL SETUP FOR THE EXECUTION OF MOBILE APPLICATIONS

The third generation of mobile communication, the so-called UMTS, makes a broad variety of applications for mobile terminals available. This endeavor is the maintenance of several applications on one terminal: Radio bearers have restrictions in the quality of service (QoS) for applications due to limited resources. And the cell setup for the execution of several mobile applications may lead to unacceptable waiting periods for the user. As example considers WAP access, where the connection to the gateway takes, in general, approximately half a minute. This period increases if one is using several applications on one mobile terminal. Another hinderance is an insufficient QoS availability during the call setup. Here, the execution of the mobile application is shutdown. In this paper, the optimization of the call setup for several mobile applications is investigated. The optimization applies scheduling to order and optimize the execution of the modules for UMTS for the call setup. This application is new for scheduling in artificial intelligence (AI). The premise is the modularization of the UMTS call setup based on agent technology, since the call setup of radio is basically a continuous process in the field of electrical engineering. As a result, the user has a shorter waiting period until the execution of several mobile applications is started and thus mobile terminals can be used more flexibly. Experiments for the execution of up to 20 mobile applications on the same mobile terminal demonstrate the optimization.