Media Cloud Service Scheduling Optimization for Resource-Intensive Mobile Application

2018 ◽  
Vol 27 (04) ◽  
pp. 1850008 ◽  
Author(s):  
Chunlin Li ◽  
Jing Zhang ◽  
Yi Chen
Keyword(s):  
Mobile Application ◽  
Scheduling Algorithm ◽  
Cloud Service ◽  
Distributed Scheduling ◽  
Mobile Users ◽  
Scheduling Optimization ◽  
Service Scheduling ◽  
The Media ◽  
Streaming Service ◽  
Media Cloud

How to reduce energy consumption, improve resource utilization and put forward efficient resource management model so as to improve the media cloud performance and mobile users’ quality of service (QoS) is the problem needed to be addressed. Our proposed media cloud distributed scheduling model aims to maximize the utility of media cloud. The media cloud distributed scheduling policy for resource-intensive mobile application includes media service provisioning and cloud resource scheduling among media cloud datacenter. The media cloud service scheduling optimization algorithms include two sub-algorithms. The practical example of video streaming service for mobile users is also given. The experiments study the performance of media cloud distributed scheduling algorithm and related algorithms. The experiment results show that proposed algorithm has better performance than related algorithms.

scholarly journals Cloud Service Scheduling Algorithm Research and Optimization

2017 ◽  
Vol 2017 ◽  
pp. 1-7 ◽  
Author(s):  
Hongyan Cui ◽  
Xiaofei Liu ◽  
Tao Yu ◽  
Honggang Zhang ◽  
Yajun Fang ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Ant Colony Optimization ◽  
Task Scheduling ◽  
Scheduling Algorithm ◽  
Cloud Service ◽  
Ant Colony ◽  
General Distribution ◽  
Process Time ◽  
Service Scheduling ◽  
Output Performance

We propose a cloud service scheduling model that is referred to as the Task Scheduling System (TSS). In the user module, the process time of each task is in accordance with a general distribution. In the task scheduling module, we take a weighted sum of makespan and flowtime as the objective function and use an Ant Colony Optimization (ACO) and a Genetic Algorithm (GA) to solve the problem of cloud task scheduling. Simulation results show that the convergence speed and output performance of our Genetic Algorithm-Chaos Ant Colony Optimization (GA-CACO) are optimal.

COORDINATED DISTRIBUTED SCHEDULING IN WIRELESS MESH NETWORK

2012 ◽  
Vol 3 (3) ◽  
pp. 368-374
Author(s):  
Usha Kumari ◽  
Udai Shankar
Keyword(s):  
Network Performance ◽  
Mesh Networks ◽  
Mac Protocol ◽  
Scheduling Algorithm ◽  
Ieee 802.16 ◽  
Distributed Scheduling ◽  
Mesh Network ◽  
Fourth Generation ◽  
Network Nodes ◽  
Wireless Mesh

IEEE 802.16 based wireless mesh networks (WMNs) are a promising broadband access solution to support flexibility, cost effectiveness and fast deployment of the fourth generation infrastructure based wireless networks. Reducing the time for channel establishment is critical for low latency/interactive Applications. According to IEEE 802.16 MAC protocol, there are three scheduling algorithms for assigning TDMA slots to each network node: centralized and distributed the distributed is further divided into two operational modes coordinated distributed and uncoordinated distributed. In coordinated distributed scheduling algorithm, network nodes have to transmit scheduling message in order to inform other nodes about their transfer schedule. In this paper a new approach is proposed to improve coordinated distributed scheduling efficiency in IEEE 802.16 mesh mode, with respect to three parameter Throughput, Average end to end delay and Normalized Overhead. For evaluating the proposed networks efficiency, several extensive simulations are performed in various network configurations and the most important system parameters which affect the network performance are analyzed

scholarly journals Perancangan E-Modul “ALKI” Pada Mata Pelajaran Kimia Bagi Siswa Kelas X Berbasis Mobile di SMAN 1 Mapat Tunggul

2021 ◽  
Vol 6 (2) ◽  
pp. 93-104
Author(s):  
Aisyah Amini ◽  
Riri Okra
Keyword(s):  
Mobile Application ◽  
Development Stage ◽  
Test Results ◽  
Research Model ◽  
Design Development ◽  
Process Testing ◽  
Development Life Cycle ◽  
Multimedia Development ◽  
The Media ◽  
Chemical Materials

ALKI is an e-module that serves as a learning medium for grade X students majoring in MIA at SMAN 1 MAPAT TUNGGUL. E-module ALKI was created with the aim of assisting teachers in delivering materials and helping students understand more about chemical materials by repeating lessons, working on exercises, and strengthening memory by playing flashcards. The thing behind the design of alki e-module is the lack of motivation to learn students, difficulty and the absence of internet network in Mapat Tunggul area, students should not take home the package book, the smartphone owned by students is not used to study, and when doing homework with the help of the internet most students just copy the answer without understanding the origin of the answer. This research method is Research and Development (R&D) with a 4-D research model (four-D) that is with define, Design, Development, and Disseminate stages. In the Development stage, the development stage of ALKI e-module media is carried out. The media development model used in this study is MDLC(Multimedia Development Life Cycle) luther-sutopo version which consists of 6 stages, namely conception, design, material collection, manufacturing process, testing and distribution. The result of the research is a mobile-based ALKI e-module product. With 0.81 validity test results declared valid,0.93 Practicality test results are practiced very practically,and 0.80 effectiveness test results are declared very effective. So, it can be concluded that alki e-module based on mobile application as a learning medium has been valid, practical and effective.

scholarly journals An Efficient Framework to Improve QoS of CSP using Enhanced Minimal Resource Optimization based Scheduling Algorithm

2018 ◽  
Vol 12 (3) ◽  
pp. 1179
Author(s):  
Ravi Mahadevan ◽  
Neelamegam Anbazhagan
Keyword(s):  
Processing Time ◽  
Service Providers ◽  
Scheduling Algorithm ◽  
Cloud Service ◽  
Daily Basis ◽  
Resource Optimization ◽  
Cloud Environment ◽  
Bandwidth Utilization ◽  
Scheduling Policy ◽  
Minimal Resource

<span>Online Nowadays, the enterprises &amp; individuals are contributing their workloads on cloud service providers which are going to increase on daily basis. There are   large amount CSP are available to offer virtualized and dynamic resource on pay and use basis. However, there are almost CSP failed to maintain quality of service (QOS) and minimal resource optimization. Some of the existing approaches are highly dedicated on scheduling policy but, it does not considered reliable services with optimized QOS. To offer best solution of above problem, the framework proposes Enhanced Minimal Resource Optimization based Scheduling Algorithm to minimize the resources and maintain the QOS.  The method avoids delay in Request-Response model in cloud environment. To avoid overload for resource allocation, the proposed design utilized optimized scheduling policy.  Proposed mechanisms utilized optimized service brokering policy to reduce the delay response in cloud environment. The framework also help cloud user to prefer best CSP according to their prior services. The method offers rising trend of resource based structure to reduce the placement churn extensively. Proposed system utilized efficient scheduling policy to transmit data request to CSP with minimal data processing time. The entire utilization is to improve the QOS of cloud service provider in the features of multi-dimensional resource. Based on experimental evaluations, proposed technique improves the CPT (Computation Processing Time) 301.72 milliseconds, BU (Bandwidth Utilization) 20 Mbps, CPUU (CPU Utilization) 5% &amp; MRU (Memory Resource Utilization) 3% on given input parameters compare than existing methodology.</span>

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