An Approach to Grid Scheduling by Using Condor-G Matchmaking Mechanism

Grid is a distributed environment that integrates computing, storage and other resources in order to enable execution of applications that cannot be run on a single resource. Such environment requires advanced scheduling system in order to efficiently execute users’ applications. In this paper, we give an overview of issues related to grid scheduling. We describe in details one of the most mature solutions – Condor-G Matchmaking mechanism. Furthermore, we propose our own approach to building grid scheduling system based on Condor-G Matchmaking

Large Scale Learning for Food Image Classification

Since health care on foods is drawing people's attention recently, in this paper we propose a computer vision based food recognition system could be used to estimate food for diabetes patients. This study proposes a methodology for automatic food recognition, based on the Bag of Features (BoF) model. We present an approach to find out the group and location of objects in images. The system computes dense local features using scale invariant features. It performs very fast classification of each pixel in an image. For the design and valuation of the proposed system, a image dataset with nearly 5010 food images was created and organized into 11 classes. This system has achieved the accuracy of 78%.of objects in images. The system computes dense local features using scale invariant features. It performs very fast classification of each pixel in an image. For the design and valuation of the proposed system, a image dataset with nearly 5010 food images was created and organized into 11 classes. This system has achieved the accuracy of 78%. DOI: 10.17762/ijritcc2321-8169.15031

Optimization of Composite Cloud Service Processing with Virtual Machines

By leveraging virtual machine (VM) technology, we optimize cloud system performance based on refined resource allocation, in processing user requests with composite services. Our contribution is three-fold. (1) We devise a VM resource allocation scheme with a minimized processing overhead for task execution. (2) We comprehensively investigate the best-suited task scheduling policy with different design parameters. (3) We also explore the best-suited resource sharing scheme with adjusted divisible resource fractions on running tasks in terms of Proportional-Share Model (PSM), which can be split into absolute mode (called AAPSM) and relative mode (RAPSM). We implement a prototype system over a cluster environment deployed with 56 real VM instances, and summarized valuable experience from our evaluation. As the system runs in short supply, Lightest Workload First (LWF) is mostly recommended because it can minimize the overall response extension ratio (RER) for both sequential-mode tasks and parallel-mode tasks. In a competitive situation with over-commitment of resources, the best one is combining LWF with both AAPSM and RAPSM. It outperforms other solutions in the competitive situation, by 16+% w.r.t. the worst-case response time and by 7.4+% w.r.t. the fairness.published_or_final_versio

Resource Brokering in Grid Computing

Grid Computing has emerged in the academia and evolved towards the bases of what is currently known as Cloud Computing and Internet of Things (IoT). The vast collection of resources that provide the nature for Grid Computing environment is very complex; multiple administrative domains control access and set policies to the shared computing resources. It is a decentralized environment with geographically distributed computing and storage resources, where each computing resource can be modeled as an autonomous computing entity, yet collectively can work together. This is a class of Cooperative Distributed Systems (CDS). We extend this by applying characteristic of open environments to create a foundation for the next generation of computing platform where entities are free to join a computing environment to provide capabilities and take part as a collective in solving complex problems beyond the capability of a single entity. This thesis is focused on modeling “Computing” as a collective performance of individual autonomous fundamental computing elements interconnected in a “Grid” open environment structure. Each computing element is a node in the Grid. All nodes are interconnected through the “Grid” edges. Resource allocation is done at the edges of the “Grid” where the connected nodes are simply used to perform computation. The analysis put forward in this thesis identifies Grid Computing as a form of computing that occurs at the resource level. The proposed solution, coupled with advancements in technology and evolution of new computing paradigms, sets a new direction for grid computing research. The approach here is a leap forward with the well-defined set of requirements and specifications based on open issues with the focus on autonomy, adaptability and interdependency. The proposed approach examines current model for Grid Protocol Architecture and proposes an extension that addresses the open issues in the diverged set of solutions that have been created

Interorganizational Information Systems: Systematic Literature Mapping Protocol

Organizations increasingly need to establish partnerships with other organizations to face environment changes and remain competitive. This interorganizational relationship allows organizations to share resources and collaborate to handle business opportunities better. This technical report present the protocol of the systematic mapping performed to understand what is an IOIS and how these systems support interorganizational relationships