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

2006 ◽  
Vol 1 (2) ◽  
pp. 43-59 ◽  
Author(s):  
Hesham A. Ali ◽  
Tamer Ahmed Farrag
Keyword(s):  
Mobile Computing ◽  
High Performance ◽  
Ranking Algorithm

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

2009 ◽  
pp. 127-142
Author(s):  
Hesham A. Ali ◽  
Tamer Ahmed Farrag
Keyword(s):  
Mobile Computing ◽  
Mobile Devices ◽  
High Performance ◽  
Total Error ◽  
Access Point ◽  
Programming Approach ◽  
Proper Solution ◽  
Ranking Algorithm ◽  
Computing Environment ◽  
Event Based

Due to the rapidly increasing of the mobile devices connected to the internet, a lot of researches are being conducted to maximize the benefit of such integration. The main objective of this paper is to enhance the performance of the scheduling mechanism of the mobile computing environment by distributing some of the responsibilities of the access point among the available attached mobile devices. To this aim we investigate a scheduling mechanism framework that comprises an algorithm provides the mobile device with the authority to evaluate itself as a resource. The proposed mechanism is based on the proposing of “self ranking algorithm (SRA)” which provides a lifetime opportunity to reach a proper solution. This mechanism depends on event-based programming approach to start its execution in a pervasive computing environment. Using such mechanism will simplify the scheduling process by grouping the mobile devices according to their self -ranking value and assign tasks to these groups. Moreover, it will maximize the benefit of the mobile devices incorporated with the already existing grid systems by using their computational power as a subordinate value to the overall power of the system. Furthermore, we evaluate the performance of the investigated algorithm extensively, to show how it overcomes the connection stability problem of the mobile devices. Experimental results emphasized that, the proposed SRA has a great impact in reducing the total error and link utilization compared with the traditional mechanism.

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

2009 ◽  
pp. 3151-3167
Author(s):  
Hesham A. Ali ◽  
Tamer Ahmed Farrag
Keyword(s):  
Mobile Computing ◽  
Mobile Devices ◽  
High Performance ◽  
Total Error ◽  
Access Point ◽  
Programming Approach ◽  
Proper Solution ◽  
Ranking Algorithm ◽  
Computing Environment ◽  
Event Based

Due to the rapidly increasing number of mobile devices connected to the Internet, a lot of research is being conducted to maximize the benefit of such integration. The main objective of this article is to enhance the performance of the scheduling mechanism of the mobile computing environment by distributing some of the responsibilities of the access point among the available attached mobile devices. To this aim, we investigate a scheduling mechanism framework that comprises an algorithm that provides the mobile device with the authority to evaluate itself as a resource. The proposed mechanism is based on the “self ranking algorithm” (SRA), which provides a lifetime opportunity to reach a proper solution. This mechanism depends on an event-based programming approach to start its execution in a pervasive computing environment. Using such a mechanism will simplify the scheduling process by grouping mobile devices according to their self-ranking value and assigning tasks to these groups. Moreover, it will maximize the benefit of the mobile devices incorporated with the already existing Grid systems by using their computational power as a subordinate value to the overall power of the system. Furthermore, we evaluate the performance of the investigated algorithm extensively, to show how it overcomes the connection stability problem of the mobile devices. Experimental results emphasized that the proposed SRA has a great impact in reducing the total error and link utilization compared with the traditional mechanism.

scholarly journals Exploring Rotation and Scale Invariant Features in Image Pla- giarism Detection Using Manifold-Ranking Algorithm

2018 ◽  
Vol 7 (4) ◽  
pp. 2663
Author(s):  
Simindokht Jahangard
Keyword(s):  
High Performance ◽  
Nearest Neighbor ◽  
Feature Point ◽  
Ranking Algorithm ◽  
Scale Invariant ◽  
Manifold Ranking ◽  
Image Transforms ◽  
Scientific Papers ◽  
Supervised Methods

Plagiarism, as a crucial offense especially in academia, not only is well-known problem in text but also is becoming widespread in image. In this work, the performance of manifold-ranking, known as robust method among semi-supervised methods, has been investigated by using twelve different features. As its high performance is attributed to the quality of constructed graph, we applied robust k-regular nearest neighbor (k-RNN) graph in the framework of manifold-ranking based retrieval. Among all tested feature point detectors and descriptors, Root-SIFT, the feature point ones, due to it is invariant to an array of image transforms, is the most reliable feature for calculating image similarity. The database consisting of images from scientific papers containing four popular benchmark test images served to test these methods. 

scholarly journals Enhancing Dynamic Binary Translation in Mobile Computing by Leveraging Polyhedral Optimization

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Mingliang Li ◽  
Jianmin Pang ◽  
Feng Yue ◽  
Fudong Liu ◽  
Jun Wang ◽  
...  
Keyword(s):  
Mobile Computing ◽  
Mobile Devices ◽  
High Performance ◽  
Multicore Processors ◽  
Translation Efficiency ◽  
Binary Translation ◽  
Dynamic Binary Translation ◽  
Polyhedral Optimization ◽  
Computational Resources ◽  
Code Offloading

Dynamic binary translation (DBT) is gaining importance in mobile computing. Mobile Edge Computing (MEC) augments mobile devices with powerful servers, whereas edge servers and smartphones are usually based on heterogeneous architecture. To leverage high-performance resources on servers, code offloading is an ideal approach that relies on DBT. In addition, mobile devices equipped with multicore processors and GPU are becoming ubiquitous. Migrating x86_64 application binaries to mobile devices by using DBT can also make a contribution to providing various mobile applications, e.g., multimedia applications. However, the translation efficiency and overall performance of DBT for application migration are not satisfactory, because of runtime overhead and low quality of the translated code. Meanwhile, traditional DBT systems do not fully exploit the computational resources provided by multicore processors, especially when translating sequential guest applications. In this work, we focus on leveraging ubiquitous multicore processors to improve DBT performance by parallelizing sequential applications during translation. For that, we propose LLPEMU, a DBT framework that combines binary translation with polyhedral optimization. We investigate the obstacles of adapting existing polyhedral optimization in compilers to DBT and present a feasible method to overcome these issues. In addition, LLPEMU adopts static-dynamic combination to ensure that sequential binaries are parallelized while incurring low runtime overhead. Our evaluation results show that LLPEMU outperforms QEMU significantly on the PolyBench benchmark.

INTRODUCING THE EXTREMELY HETEROGENEOUS ARCHITECTURE

2012 ◽  
Vol 13 (03n04) ◽  
pp. 1250010
Author(s):  
SHAOSHAN LIU ◽  
WON W. RO ◽  
CHEN LIU ◽  
ALFREDO CRISTOBAL-SALAS ◽  
CHRISTOPHE CÉRIN ◽  
...  
Keyword(s):  
Cloud Computing ◽  
Power Consumption ◽  
Low Power ◽  
Mobile Computing ◽  
High Performance ◽  
Data Centers ◽  
General Purpose ◽  
The Other ◽  
Heterogeneous Architecture ◽  
Reduce Power Consumption

The computer industry is moving towards two extremes: extremely high-performance high-throughput cloud computing, and low-power mobile computing. Cloud computing, while providing high performance, is very costly. Google and Microsoft Bing spend billions of dollars each year to maintain their server farms, mainly due to the high power bills. On the other hand, mobile computing is under a very tight energy budget, but yet the end users demand ever increasing performance on these devices. This trend indicates that conventional architectures are not able to deliver high-performance and low power consumption at the same time, and we need a new architecture model to address the needs of both extremes. In this paper, we thus introduce our Extremely Heterogeneous Architecture (EHA) project: EHA is a novel architecture that incorporates both general-purpose and specialized cores on the same chip. The general-purpose cores take care of generic control and computation. On the other hand, the specialized cores, including GPU, hard accelerators (ASIC accelerators), and soft accelerators (FPGAs), are designed for accelerating frequently used or heavy weight applications. When acceleration is not needed, the specialized cores are turned off to reduce power consumption. We demonstrate that EHA is able to improve performance through acceleration, and at the same time reduce power consumption. Since EHA is a heterogeneous architecture, it is suitable for accelerating heterogeneous workloads on the same chip. For example, data centers and clouds provide many services, including media streaming, searching, indexing, scientific computations. The ultimate goal of the EHA project is two-fold: first, to design a chip that is able to run different cloud services on it, and through this design, we would be able to greatly reduce the cost, both recurring and non-recurring, of data centers\clouds; second, to design a light-weight EHA that runs on mobile devices, providing end users with improved experience even under tight battery budget constraints.

scholarly journals An Approach to Mobile Grid Platforms for the Development and Support of Complex Ubiquitous Applications

2011 ◽  
pp. 617-633
Author(s):  
Carlo Bertolli ◽  
Daniele Buono ◽  
Gabriele Mencagli ◽  
Marco Vanneschi
Keyword(s):  
Mobile Computing ◽  
Grid Computing ◽  
Pervasive Computing ◽  
High Performance ◽  
Programming Model ◽  
Research Field ◽  
Context Aware ◽  
Future Directions ◽  
Programming Framework ◽  
Time Critical

Several complex and time-critical applications require the existence of novel distributed, heterogeneous and dynamic platforms composed of a variety of fixed and mobile processing nodes and networks. Such platforms, that can be called Pervasive Mobile Grids, aim to merge the features of Pervasive Computing and High-performance Grid Computing onto a new emerging paradigm. In this Chapter we study a methodology for the design and the development of high-performance, adaptive and context-aware applications. We describe a programming model approach, and we compare it with other existing research works in the field of Pervasive Mobile Computing, discussing the rationales of the requirements and the features of a novel programming model for the target platforms and applications. In order to exemplify the proposed methodology we introduce our programming framework ASSISTANT, and we provide some interesting future directions in this research field.

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