High Performance Scheduling Mechanism for Mobile Computing Based on Self-Ranking Algorithm (SRA)

Energy conservation in battery powered mobile devices that perform wireless multimedia streaming has been a significant research problem since last decade. This is because these mobile devices consume a lot of power while receiving, decoding and ultimately, presenting the multimedia content. What makes things worse is the fact that battery technologies have not evolved enough to keep up with the rapid advancement of mobile devices. This survey examines solutions that have been proposed during the last few years, to improve the energy efficiency of wireless multimedia streaming in mobile hand-held devices. We categorize the research work according to different layers of the Internet protocol stack they utilize. Then, we again regroup these studies based on different traffic scheduling and multimedia content adaptation mechanisms. The traffic scheduling category contains those solutions that optimize the wireless receiving energy without changing the actual multimedia content. The second category on the other hand, specifically modifies the content, in order to reduce the energy consumed by the wireless receiver and to decode and view the content. We compare them and provide evidence of the fact that some of these tactics already exist in modern smaprtphones and provide energy savings with real measurements. In addition, we discuss some relevant literature on the complementary problem of energy-aware multimedia delivery from mobile devices and contrast with our target approaches for multimedia transmission to mobile devices.

The value of a mobile communication device is its ability to organize and access important information quickly. Mobile devices are often associated with the cutting-edge technology of the last 4 years. Although having gained an increasing popularity over recent years, mobile devices have a history of 15 years. The first generation of mobile devices was the analog mobile phone. They were large and cumbersome, resembling a small briefcase. With the launch of the second generation, mobile phone units became smaller and easier to handle. Currently, third-generation phones are starting to be released, advancing in design and dynamic capabilities. By the year 2005, 76% of consumers will own an Internet compatible device, 66% will own a cell phone, 45% will own an Internet cell phone, and 10% will own a personal digitial assistant (Forrester, 2001). In today's information surge, business never stops. IDC Research has forecasted that an average of more than 36 billion person-to-person e-mails will be sent daily by 2005 (Juptner, 2001). Hence, mobile communication plays a major role in the success of most of today's business operations (Jones, 2001), and all businesses are continually faced with the challenge of engaging with the rapidly changing information technology age. One area of mobile communications that has been growing exponentially is mobile computing. Keywords: code division multiple access (CDMA); general packet radio service (GPRS); global positioning system (GPS); Internet cell phone; mobile communication device; personal digital assistant (PDA)

The value of a mobile communication device is its ability to organize and access important information quickly. Mobile devices are often associated with the cutting‐edge technology of the last 4 years. Although having gained an increasing popularity over recent years, mobile devices have a history of 15 years. The first generation of mobile devices was the analog mobile phone. They were large and cumbersome, resembling a small briefcase. With the launch of the second generation, mobile phone units became smaller and easier to handle. Currently, third‐generation phones are starting to be released, advancing in design and dynamic capabilities. By the year 2005, 76% of consumers will own an Internet compatible device, 66% will own a cell phone, 45% will own an Internet cell phone, and 10% will own a personal digitial assistant (Forrester, ). In today's information surge, business never stops. IDC Research has forecasted that an average of more than 36 billion person‐to‐person e‐mails will be sent daily by 2005 (Juptner, ). Hence, mobile communication plays a major role in the success of most of today's business operations (Jones, ), and all businesses are continually faced with the challenge of engaging with the rapidly changing information technology age. One area of mobile communications that has been growing exponentially is mobile computing.

Computer vision (CV) is widely expected to be the next big thing in mobile computing. The availability of a camera and a large number of sensors in mobile devices will enable CV applications that understand the environment and enhance people's lives through augmented reality. One of the problems yet to solve is how to transfer demanding state-of-the-art CV algorithms —designed to run on powerful desktop computers with several GPUs— onto energy-efficient, but slow, processors and GPUs found in mobile devices. To accommodate to the lack of performance, current CV applications for mobile devices are simpler versions of more complex algorithms, which generally run slowly and unreliably and provide a poor user experience. In this paper, we investigate ways to speed up demanding CV applications to run faster on mobile devices. We selected KinectFusion (KF) as a representative CV application. The KF application constructs a 3D model from the images captured by a Kinect. After porting it to an ARM platform, we applied several optimisation and parallelisation techniques using OpenCL to exploit all the available computing resources. We evaluated the impact on performance and power and demonstrate a 4× speedup with just a 1.38× power increase. We also evaluated the performance portability of our optimisations by running on a different platform, and assessed similar improvements despite the different multi-core configuration and memory system. By measuring processor temperature, we found overheating to be the main limiting factor for running such high-performance codes on a mobile device not designed for full continuous utilisation.

Grid computing using wireless networks is receiving increasing attention and is expected to become a critical part of future grid computing. However, the inherent challenges of mobile environments such as mobility management, disconnected operation, device heterogeneity, service discovery, and resource sharing are significant issues in mobile grid computing. To achieve the best performance in a mobile grid computing environment, the mobile devices with the lowest probability of mobility should be selected for use first. We therefore focus on the idle state of mobile devices and use IP-paging scheme to identify the idle mobile devices. For this, we propose a user-defined checkpoint technique for task migration, which is based on the information of when a mobile device will leave the network or stop due to low battery. Our checkpoint technique performs checkpoints by two conditions: when a mobile device leaves its current cell and when it turns off due to low battery capacity.KeywordsMobile GridIP-PagingTask MigrationCheckpoints

Mobile and handheld devices are becoming an integral part of people’s work, life and entertainment. These lightweight pocket-sized devices offer great mobility, acceptable computation power and friendly user interfaces. As people are making business transactions and managing their online bank accounts via handheld devices, they are concerned with the security level that mobile devices and systems provide. In this chapter we will discuss whether these devices, equipped with very limited computation power compared to full-sized computers, can make equivalent security services available to users. We focus on the security designs and technologies of hardware, operating systems and applications for mobile and handheld devices.

MCC, or mobile cloud computing, is a new field. Mobile cloud computing is becoming a crucial component for mobile devices due to reliability and portability as data processing and storage take place outside of the mobile due to the widespread use of mobile devices and the variety of apps. It helps mobile devices conserve battery life and processing power, which is important for highpower mobile devices. Mobile cloud computing offers consumers to make calculations and use cloud services on their mobile devices. It is essential to gain a full understanding of current models and emerging trends because mobile Cloud computing is still in its infancy. The purpose of this survey is to identify and describe the main risks and obstacles associated with mobile cloud computing while alsoshowcasing emerging trends in this area.

These days, peoples expected to move around carrying their mobile devices, talking to friends, completing their work, accessing emails etc. His/her pictures, work, study, even relationship (friends, and family) all is in the mobile device. Therefore, mobile devices (especially smart phones) become an ideal target for different attacks. Mobile computing also becomes important in enterprises and organizations. Therefore, it is important to illustrate the state of art on vulnerabilities and threats on mobile device. This chapter is addressed to explain mobile computing concept, features, architecture, operating systems, and risks to mobile devices. Mobile operating system structureand characteristicsare demonstrated. The author also illustrates mobile security issues, and type of threats to mobile devices. Finally, features and security models of two popular smartphone operating systems, Android and iOS, are illustrated. It was found that the security models of these two smartphones is immature and do not meet the enterprises security policies.

These days, peoples expected to move around carrying their mobile devices, talking to friends, completing their work, accessing emails etc. His/her pictures, work, study, even relationship (friends, and family) all is in the mobile device. Therefore, mobile devices (especially smart phones) become an ideal target for different attacks. Mobile computing also becomes important in enterprises and organizations. Therefore, it is important to illustrate the state of art on vulnerabilities and threats on mobile device. This chapter is addressed to explain mobile computing concept, features, architecture, operating systems, and risks to mobile devices. Mobile operating system structureand characteristicsare demonstrated. The author also illustrates mobile security issues, and type of threats to mobile devices. Finally, features and security models of two popular smartphone operating systems, Android and iOS, are illustrated. It was found that the security models of these two smartphones is immature and do not meet the enterprises security policies.

The explosive growth in the number of mobile devices such as Internet-enabled cellular phones, wireless handheld devices, wireless laptops, and tablet PCs has driven the corresponding growth in applications for mobile computing. These applications usually belong to one of two classes: collaborative applications and individual application. While collaborative applications require several mobile devices to work together and include peer-to-peer computing and grid computing, individual applications are local to the mobile device and its user. In this paper, we present a framework that allows mobile devices to collaboratively work on a computationally-expensive problem. Such a problem is decomposed into smaller tasks and distributed across other mobile devices willing to share their computational power with others. This framework is based on the paradigm of grid computing applied to the domain of wireless mobile devices. This paper presents our current implementation of the framework architecture and simulation of its functionality. Also, we focus on the issues of mobility, QoS and network stability and their effect on the performance of our collaborative problem-solving framework.

In this paper the authors intend to demonstrate the utilization of remote experimentation (RE) using mobile computational devices in the Science areas of the elementary school, with the purpose to develop practices that will help in the assimilation process of the subjects taught in classroom seeking to interlink them with the daily students' activities. Allying mobility with RE we intend to minimize the space-temporal barrier giving more availability and speed in the information access. The implemented architecture utilizes technologies and freely distributed softwares with open code resources besides remotes experiments developed in the Laboratory of Remote Experimentation (RExLab) of Federal University of Santa Catarina (UFSC), in Brazil, through the physical computation platform of the “open hardware” of self-construction type. The utilization of open code computational tools and the integration of hardware to the 3D virtual worlds, accessible through mobile devices, give to the project an innovative face with a high potential for reproducibility and reusability.

We discuss an interconnectivity framework for data and content delivery to mobile devices that allows data of higher priority to reach the mobile unit in the shortest time possible. Two possible scenarios are presented; one that connects the servers in an N-cube configuration network, and another that shows the same N servers connected in a grid type network. The goal is to minimize the rate of data jumps from server to server until it reaches the mobile device. As the mobile user travels, the mobile device registers itself with the next server and the session is migrated from the old server to the new one without interruptions, in an analogous way, cell phones move from one cell to another. Starting with the idea that all data is not equal (in importance/priority), this article suggest a framework topology for intelligent mobile computing that guarantees data will reach the mobile device in a minimum amount of time, assuring at the same time the privacy of transmission. The integration of this type of technology into the 3r d Generation (3G), and 4t h Generation (4G) mobile computing is also discussed. Pervasive computing is rapidly emerging as the next generation of computing with the underlying premise of simplicity (of use), minimal technical expertise, reliability, and intuitive interactions. As technology continues to advance and mobile devices become more and more omnipresent, the aim towards achieving easier computing, more availability and prevalence is becoming a given. Through the clever use of advanced technologies, the new generation of intelligent mobile computing has the opportunity to serve user needs via prevalent computing devices that are ever more transportable and connected to an increasingly ubiquitous network structure. Mobile communication is changing as the trends of media convergence including the Internet and its related electronic communication technologies and satellite communications collide into one. A change is being ushered by the 3G (3r d Generation) mobile technology with the usability and usefulness of information delivered to mobile devices taking on added features. For example, multimedia messaging, as opposed to voice transmissions, being delivered to cell phones has rendered such mobile devices an integral part of people’s lives and a core part of how they conduct their daily business rather than an add on tool (Buckingham, 2001). The 3G mobile phone system aims at unifying the disparate standards of current second generation wireless systems. The idea is to eliminate the different types of global networks being adopted with a single standard network. This will allow for the delivery of multimedia content and propagation through the network without the need for conversion from one standard to another. 3G systems need smaller cells thus the need for more base stations (mostly due to their operating frequency, power requirements, and modulation) and in many cases will not be feasible to install them in areas where population is not so dense (i.e., rural areas) (Garber, 2002). Because of these requirements and conditions, a better way to deliver the communication must be established. However, global access to such mobile devices will create data delivery challenges and servers can become clogged with unwanted communication, like that of wired Internet access. The need for moving relevant data to mobile devices in the shortest time possible becomes of utmost importance.

Enhancing generalization of computation offloading policies in novel mobile edge computing environments by exploiting experience utility

The resource exchanging is the key function in mobile computing environment. We have the limitation of the capacity for every single mobile device. The only way for efficient use of limited resources is exchanging them each other in mobile environment. In this paper, a mutual resource exchanging model in mobile computing is proposed. Furthermore, two applications of the model are shown. The first one is a universal battery. It enables us to exchange resources of electricity from one to another mobile device. The second application is bandwidth resource sharing among mobile devices. It provides the mobility of bandwidth from devices with surplus network connectivity to other devices that requires more network bandwidth. By this model, flexible and elastic usability can be implemented on mobile devices in mobile computing environment.

Enhanced time-constraint aware tasks scheduling mechanism based on predictive optimization for efficient load balancing in smart manufacturing