scholarly journals Approaches to Address the Operational Limitations of MANETs through Ad Hoc Mobile Cloud Computing Paradigm

2020 ◽  
Vol 14 (09) ◽  
pp. 153
Author(s):  
Muralidhar Kurni ◽  
Madhavi K
Keyword(s):  
Cloud Computing ◽  
Mobile Devices ◽  
Ad Hoc ◽  
Mobile User ◽  
Battery Life ◽  
Computing Platform ◽  
Computing Paradigm ◽  
Cloud Computing Service ◽  
Mobile Ad Hoc ◽  
Computing Platforms

Mobile Ad hoc Networks (MANETs) are getting essential to wireless communications because of the growing popularity of mobile devices. However, mobile devices face several challenges in their resources (eg., battery life, storage, and bandwidth) and communication (e.g., mobility and, security). Limited resources considerably impede the improvement of service qualities. MCC permits resources in cloud computing platforms to be used to overcome the dearth of native resources in mobile devices. However, this hinders a mobile user from taking part in a cloud computing service if a connection to the cloud computing platform is both unobtainable or too dear to afford. Therefore, an initial solution will be to use resources from nearby devices instantly. Such a paradigm is known as mobile ad hoc cloud computing where each mobile device can use the services and resources of its neighbor devices. This paper shortly explains the contributions done by us to overcome the three vital operational limitations of mobile devices namely connectivity, storage and, processing capability through the Mobile Ad Hoc Cloud Computing Paradigm. The potential promise of the proposed approaches is evaluated through simulations. Our proposals, taken together intend to increase the operational efficiency of MANETs.

scholarly journals Mobile Cloud Computing: Offloading Mobile Processing to the Cloud

2016 ◽  
Vol 9 (1) ◽  
pp. 90
Author(s):  
Sanjay P. Ahuja ◽  
Jesus Zambrano
Keyword(s):  
Cloud Computing ◽  
Energy Consumption ◽  
Mobile Devices ◽  
Response Times ◽  
Mobile Apps ◽  
Mobile Systems ◽  
Battery Life ◽  
Data Intensive ◽  
Computing Platforms ◽  
Computational Resources

<p class="zhengwen">The current proliferation of mobile systems, such as smart phones and tablets, has let to their adoption as the primary computing platforms for many users. This trend suggests that designers will continue to aim towards the convergence of functionality on a single mobile device (such as phone + mp3 player + camera + Web browser + GPS + mobile apps + sensors). However, this conjunction penalizes the mobile system both with respect to computational resources such as processor speed, memory consumption, disk capacity, and in weight, size, ergonomics and the component most important to users, battery life. Therefore, energy consumption and response time are major concerns when executing complex algorithms on mobile devices because they require significant resources to solve intricate problems.</p><p>Offloading mobile processing is an excellent solution to augment mobile capabilities by migrating computation to powerful infrastructures. Current cloud computing environments for performing complex and data intensive computation remotely are likely to be an excellent solution for offloading computation and data processing from mobile devices restricted by reduced resources. This research uses cloud computing as processing platform for intensive-computation workloads while measuring energy consumption and response times on a Samsung Galaxy S5 Android mobile phone running Android 4.1OS.</p>

scholarly journals An e-book hub service based on a cloud platform

2012 ◽  
Vol 13 (5) ◽  
pp. 39 ◽  
Author(s):  
Jinn-Shing Cheng ◽  
Echo Huang ◽  
Chuan-Lang Lin
Keyword(s):  
Cloud Computing ◽  
Mobile Devices ◽  
Information And Communication Technologies ◽  
Large Scale ◽  
Storage Capacity ◽  
Digital Content ◽  
Computing Platform ◽  
Cloud Computing Service ◽  
E Learning ◽  
Cloud Computing Platform

Due to the constant performance upgrades and regular price reductions of mobile devices in recent years, users are able to take advantage of the various  devices to obtain digital content regardless of the limitations of time and place. The increasing use of e-books has stimulated new e-learning approaches. This research project developed an e-book hub service on a cloud computing platform in order to overcome the limitations of computing capability and storage capacity that are inherent in many mobile devices. The e-book hub service also allows users to automatically adjust the rendering of multimedia pages at different resolutions on terminal units such as smartphones, tablets, PCs, and so forth. We implemented an e-book hub service on OpenStack, which is a free and open-source cloud computing platform supported by multiple large firms. The OpenStack platform provides a large-scale distributed computing environment that allows users to build their own cloud systems in a public, private, or hybrid environment. Our e-book hub system offers content providers an easy-to-use cloud computing service with unlimited storage capacity, fluent playback, high usability and scalability, and high security characteristics to produce, convert, and manage their e-books. The integration of information and communication technologies has led the traditional publishing industry to new horizons with abundant digital content publications. Results from this study may help content providers create a new service model with increased profitability and enable mobile device users to easily get digital content, thereby achieving the goal of e-learning.<br /><br />

Performance analysis of Mobile Cloud Computing Architectures for mHealth app

2020 ◽  
Vol 2020 (3) ◽  
pp. 335-1-335-7
Author(s):  
D. Inupakutika ◽  
D. Akopian ◽  
P. Chalela ◽  
A. G. Ramirez
Keyword(s):  
Cloud Computing ◽  
Mobile Devices ◽  
Mobile Cloud Computing ◽  
Mobile User ◽  
Battery Life ◽  
Mobile Cloud ◽  
Medical Monitoring ◽  
Power And Energy ◽  
Analysis Of Performance

Mobile Health (mHealth) applications (apps) are being widely used to monitor health of patients with chronic medical conditions with the proliferation and the increasing use of smartphones. Mobile devices have limited computation power and energy supply which may lead to either delayed alarms, shorter battery life or excessive memory usage limiting their ability to execute resource-intensive functionality and inhibit proper medical monitoring. These limitations can be overcome by the integration of mobile and cloud computing (Mobile Cloud Computing (MCC)) that expands mobile devices' capabilities. With the advent of different MCC architectures such as implementation of mobile user-side tools or network-side architectures it is hence important to decide a suitable architecture for mHealth apps. We survey MCC architectures and present a comparative analysis of performance against a resource demanding representative testing scenario in a prototype mHealth app. This work will compare numerically the mobile cloud architectures for a case study mHealth app for Endocrine Hormonal Therapy (EHT) adherence. Experimental results are reported and conclusions are drawn concerning the design of the prototype mHealth app system using the MCC architectures.

A Mobile-Terminal-Oriented and Mobile-Cloud-Computing-Based Localized Scheduling Algorithm

2014 ◽  
Vol 989-994 ◽  
pp. 2111-2114
Author(s):  
Rui Xiang Liu ◽  
Yu Hong Zhang ◽  
Yan Tang
Keyword(s):  
Cloud Computing ◽  
Mobile Devices ◽  
Mobile Cloud Computing ◽  
Scheduling Algorithm ◽  
Mobile Terminal ◽  
Mobile Internet ◽  
Mobile Cloud ◽  
Computing Platform ◽  
Computing Platforms ◽  
Distributed Cloud

Mobile Cloud Computing utilizes cloud computing in the mobile internet. It takes the advantage of portability of mobile devices, and uses cloud computing to make up mobile devices' shortcomings, i.e., the capabilities of computation and storage. With the advent of cloud computing, more and more IT companies establish their own cloud computing platforms by using Hadoop, which gradually makes Hadoop a distributed cloud computing platform. By considering important attributes of mobile devices, e.g., low computation workload, high concurrency, and high real-time demand, we propose in this paper a local scheduling algorithm which is based on Hadoop mobile cloud computing, and we analyze the influence of response time and throughput on the system utility.

scholarly journals Flexible computation offloading in a fuzzy-based mobile edge orchestrator for IoT applications

2020 ◽  
Vol 9 (1) ◽  
Author(s):  
VanDung Nguyen ◽  
Tran Trong Khanh ◽  
Tri D. T. Nguyen ◽  
Choong Seon Hong ◽  
Eui-Nam Huh
Keyword(s):  
Cloud Computing ◽  
Augmented Reality ◽  
Mobile Devices ◽  
Computing System ◽  
Mobile User ◽  
Computation Offloading ◽  
Context Aware ◽  
Computing Systems ◽  
Iot Applications ◽  
Service Times

AbstractIn the Internet of Things (IoT) era, the capacity-limited Internet and uncontrollable service delays for various new applications, such as video streaming analysis and augmented reality, are challenges. Cloud computing systems, also known as a solution that offloads energy-consuming computation of IoT applications to a cloud server, cannot meet the delay-sensitive and context-aware service requirements. To address this issue, an edge computing system provides timely and context-aware services by bringing the computations and storage closer to the user. The dynamic flow of requests that can be efficiently processed is a significant challenge for edge and cloud computing systems. To improve the performance of IoT systems, the mobile edge orchestrator (MEO), which is an application placement controller, was designed by integrating end mobile devices with edge and cloud computing systems. In this paper, we propose a flexible computation offloading method in a fuzzy-based MEO for IoT applications in order to improve the efficiency in computational resource management. Considering the network, computation resources, and task requirements, a fuzzy-based MEO allows edge workload orchestration actions to decide whether to offload a mobile user to local edge, neighboring edge, or cloud servers. Additionally, increasing packet sizes will affect the failed-task ratio when the number of mobile devices increases. To reduce failed tasks because of transmission collisions and to improve service times for time-critical tasks, we define a new input crisp value, and a new output decision for a fuzzy-based MEO. Using the EdgeCloudSim simulator, we evaluate our proposal with four benchmark algorithms in augmented reality, healthcare, compute-intensive, and infotainment applications. Simulation results show that our proposal provides better results in terms of WLAN delay, service times, the number of failed tasks, and VM utilization.

scholarly journals Selfish Caching and Facsimile Allocation over a Mobile Ad Hoc Network

2019 ◽  
Vol 8 (6S3) ◽  
pp. 1953-1958
Keyword(s):  
Mobile Devices ◽  
Ad Hoc Network ◽  
Ad Hoc ◽  
Mobile Ad Hoc Network ◽  
Peer To Peer ◽  
Selfish Nodes ◽  
Replica Allocation ◽  
Adhoc Networks ◽  
Mobile Ad Hoc ◽  
Few Vertices

Mobile adhoc networks (MANETs) have drawn attention to multitudinous consideration because of the univerality of mobile devices as well as the developments in wireless era. MANET is a peer-to-peer multi hop cellular wireless era community which does not have both difficult and speedy infrastructure and a relevant server. Every vertex of a MANET performs like a router and communicates with every unique. There exist numerous information duplication strategies which were presented to reduce the execution squalor. All are concluded that everyone cell vertices cooperate completely from the perspective of sharing their memory vicinity. But, via a few methods few vertices might additionally behave selfishly and determine simplest to cooperate in part or never with different vertices. The selfish vertices ought to then lessen the overall information approachability within the network. From this work, we try to take a look at the influence of selfish vertices in a mobile ad hoc community in terms of reproduction issuance i.e Selfish nodes are dealt with in replica allocation.

Cloud Computing for Global Software Development

2015 ◽  
pp. 897-908 ◽  
Author(s):  
Thamer Al-Rousan
Keyword(s):  
Cloud Computing ◽  
Software Development ◽  
Process Model ◽  
Risk Model ◽  
Cost Effective ◽  
Information And Communications Technology ◽  
Global Software Development ◽  
Computing Paradigm ◽  
It Systems ◽  
Computing Platforms

The cloud computing paradigm offers an innovative and promising vision concerning Information and Communications Technology. Actually, it provides the possibility of improving IT systems management and is changing the way in which hardware and software are designed and purchased. This paper introduces challenges in Global Software Development (GSD) and application of cloud computing platforms as a solution to some problems. Even though cloud computing provides compelling benefits and cost-effective options for GSD, new risks and difficulties must be taken into account. Thus, the paper presents a study about the risk issues involved in cloud computing. It highlights the different types of risks and how their existence can affect GSD. It also proposes a new risk management process model. The risk model employs new processes for risk analysis and assessment. Its aim is to analyse cloud risks quantitatively and, consequently, prioritise them according to their impact on different GSD objectives.

A Survey of Probabilistic Broadcast Schemes in Mobile Ad Hoc Networks

2018 ◽  
pp. 269-282
Author(s):  
Muneer Bani Yassein ◽  
Mohammed Shatnawi ◽  
Nesreen l-Qasem
Keyword(s):  
Ad Hoc Networks ◽  
Mobile Ad Hoc Networks ◽  
Mobile Devices ◽  
Routing Protocols ◽  
Ad Hoc ◽  
Probabilistic Broadcast ◽  
Mobile Ad Hoc ◽  
Broadcast Schemes ◽  
Hoc Networks ◽  
Wireless Mobile

Mobile ad hoc networks (MANETs) is a collection of wireless mobile devices that dynamically communicates with each other as a self-configuration without the need of centralized administration or fixed infrastructure. In this paper, we interested to introduce the different broadcast methods based on the probabilistic scheme which is simple implement code with speed broadcast and to reduce a storm broadcast problem effects and to alleviate redundancy through rebroadcast by using different routing protocols such as (AODV, DSR, LAR, PAR) that we interested in MANETs.

A User’s Profile Model for Cloud Computing Service

2013 ◽  
Vol 774-776 ◽  
pp. 1729-1733 ◽  
Author(s):  
Wu Bin Ma ◽  
Ming Xin Liu ◽  
Su Deng ◽  
Hong Bin Huang
Keyword(s):  
Cloud Computing ◽  
User Models ◽  
Profile Model ◽  
Computing Platform ◽  
Model Based ◽  
Cloud Computing Service ◽  
Cloud Computing Platform

Personalization of model-based cloud computing platform based on specialized user models has become more important in order to preserve the effectiveness of their service as the amount of available content increases. In this paper, a users profile model is imported to the cloud computing. We propose a method of modeling users profile for cloud computing, and establish a simple users profile. At last, we use this model in the Google App Engine for searching some service to prove that importing the users profile model is useful and efficient for cloud computing service.

A Trust Model of P2P in Cloud Computing Environment

2013 ◽  
Vol 278-280 ◽  
pp. 1962-1965
Author(s):  
Song Fei ◽  
Xiao Jing Wang ◽  
Zhe Cui
Keyword(s):  
Cloud Computing ◽  
Trust Model ◽  
Computing Environment ◽  
Trust Mechanism ◽  
Cloud Computing Environment ◽  
Computing Platform ◽  
Cloud Computing Service ◽  
Cross Platform ◽  
Cloud Computing Platform ◽  
P2p Technology

Proposed a new trust model based on P2P technology in the cloud computing environment. The model takes into account more than one cloud computing platform, that is, considering the different cloud computing service provider provide the service of a cross-cloud platform. Such cross-platform cloud (Cross Cloud) can be called the composite cloud computing platform or cloud associated cloud computing platform.The nodes in the cloud computing environment are divided into two categories: customers and providers. According to the different roles of these two nodes, we designed a different trust mechanism, to divide the trust domain with independent single cloud, considered node independence and manageability of domain to process trust choice and trust update, and proposed a new kind of cloud computing service - trust recommendation service.

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