Mobile cloud computing (MCC) refers to an infrastructure where data storage and processing occur remotely on powerful centralized cloud servers, rather than locally on mobile devices. This alleviates issues like limited battery, storage, and bandwidth on mobile devices. MCC provides advantages like lower costs, greater scalability, reliability, and availability of data and applications stored in the cloud. Popular MCC applications include mobile commerce, healthcare, gaming and more. Key challenges include low bandwidth, service availability, and computation offloading in dynamic environments. Security issues involve protecting user privacy and securing data in the cloud.
ENERGY EFFICIENT COMPUTING FOR SMART PHONES IN CLOUD ASSISTED ENVIRONMENTIJCNCJournal
In recent years, the employment of smart mobile phones has increased enormously and are concerned as an area of human life. Smartphones are capable to support immense range of complicated and intensive applications results shortened power capability and fewer performance. Mobile cloud computing is the newly rising paradigm integrates the features of cloud computing and mobile computing to beat the constraints of mobile devices. Mobile cloud computing employs computational offloading that migrates the computations from mobile devices to remote servers. In this paper, a novel model is proposed for dynamic task offloading to attain the energy optimization and better performance for mobile applications in the cloud environment. The paper proposed an optimum offloading algorithm by introducing new criteria such as benchmarking for offloading decision making. It also supports the concept of partitioning to divide the computing problem into various sub-problems. These sub-problems can be executed parallelly on mobile device and cloud. Performance evaluation results proved that the proposed model can reduce around 20% to 53% energy for low complexity problems and up to 98% for high complexity problems.
Cloud-based augmentation for mobile devices: Motivation, Taxonomy, and Open C...Saeid Abolfazli
Comprehensive Survey on Mobile Cloud Computing. The paper abstract is here:
Recently, Cloud-based Mobile Augmentation (CMA) approaches have gained remarkable ground from academia and industry. CMA is the state-of-the-art mobile augmentation model that employs resource-rich clouds to increase, enhance, and optimize computing capabilities of mobile devices aiming at execution of resource-intensive mobile applications. Augmented mobile devices envision to perform extensive computations and to store big data beyond their intrinsic capabilities with least footprint and vulnerability. Researchers utilize varied cloud-based computing resources (e.g., distant clouds and nearby mobile nodes) to meet various computing requirements of mobile users. However, employing cloud-based computing resources is not a straightforward panacea. Comprehending critical factors (e.g., current state of mobile client and remote resources) that impact on augmentation process and optimum selection of cloud-based resource types are some challenges that hinder CMA adaptability. This paper comprehensively surveys the mobile augmentation domain and presents taxonomy of CMA approaches. The objectives of this study is to highlight the effects of remote resources on the quality and reliability of augmentation processes and discuss the challenges and opportunities of employing varied cloud-based resources in augmenting mobile devices. We present augmentation definition, motivation, and taxonomy of augmentation types, including traditional and cloud-based. We critically analyze the state-of-the-art CMA approaches and classify them into four groups of distant fixed, proximate fixed, proximate mobile, and hybrid to present a taxonomy. Vital decision making and performance limitation factors that influence on the adoption of CMA approaches are introduced and an exemplary decision making flowchart for future CMA approaches are presented. Impacts of CMA approaches on mobile computing is discussed and open challenges are presented as the future research directions.
Techniques to Minimize State Transfer Cost for Dynamic Execution Offloading I...IJERA Editor
The recent advancement in cloud computing in cloud computing is leading to and excessive growth of the mobile devices that can become powerful means for the information access and mobile applications. This introducing a latent technology called Mobile cloud computing. Smart phone device supports wide range of mobile applications which require high computational power, memory, storage and energy but these resources are limited in number so act as constraints in smart phone devices. With the integration of cloud computing and mobile applications it is possible to overcome these constraints by offloading the complex modules on cloud. These restrictions may be alleviated by computation offloading: sending heavy computations to resourceful servers and receiving the results from these servers. Many issues related to offloading have been investigated in the past decade.
ERMO2 algorithm: an energy efficient mobility management in mobile cloud comp...IJECEIAES
Recently, mobile devices are becoming the primary platforms for every user who always roam around and access the cloud computing applications. Mobile cloud computing (MCC) combines the both mobile and cloud computing, which provides optimal services to the mobile users. In next-generation mobile environments, mainly due to the huge number of mobile users in conjunction with the small cell size and their portable information‟s, the influence of mobility on the network performance is strengthened. In this paper, we propose an energy efficient mobility management in mobile cloud computing (E2M2MC2) system for 5G heterogeneous networks. The proposed E2M2MC2 system use elective repeat multi-objective optimization (ERMO2) algorithm to determine the best clouds based on the selection metrics are delay, jitter, bit error rate (BER), packet loss, communication cost, response time, and network load. ERMO2 algorithm provides energy efficient management of user mobility as well as network resources. The simulation results shows that the proposed E2M2MC2 system helps in minimizing delay, packet loss rate and energy consumption in a heterogeneous network.
ENERGY EFFICIENT COMPUTING FOR SMART PHONES IN CLOUD ASSISTED ENVIRONMENTIJCNCJournal
In recent years, the employment of smart mobile phones has increased enormously and are concerned as an area of human life. Smartphones are capable to support immense range of complicated and intensive applications results shortened power capability and fewer performance. Mobile cloud computing is the newly rising paradigm integrates the features of cloud computing and mobile computing to beat the constraints of mobile devices. Mobile cloud computing employs computational offloading that migrates the computations from mobile devices to remote servers. In this paper, a novel model is proposed for dynamic task offloading to attain the energy optimization and better performance for mobile applications in the cloud environment. The paper proposed an optimum offloading algorithm by introducing new criteria such as benchmarking for offloading decision making. It also supports the concept of partitioning to divide the computing problem into various sub-problems. These sub-problems can be executed parallelly on mobile device and cloud. Performance evaluation results proved that the proposed model can reduce around 20% to 53% energy for low complexity problems and up to 98% for high complexity problems.
Cloud-based augmentation for mobile devices: Motivation, Taxonomy, and Open C...Saeid Abolfazli
Comprehensive Survey on Mobile Cloud Computing. The paper abstract is here:
Recently, Cloud-based Mobile Augmentation (CMA) approaches have gained remarkable ground from academia and industry. CMA is the state-of-the-art mobile augmentation model that employs resource-rich clouds to increase, enhance, and optimize computing capabilities of mobile devices aiming at execution of resource-intensive mobile applications. Augmented mobile devices envision to perform extensive computations and to store big data beyond their intrinsic capabilities with least footprint and vulnerability. Researchers utilize varied cloud-based computing resources (e.g., distant clouds and nearby mobile nodes) to meet various computing requirements of mobile users. However, employing cloud-based computing resources is not a straightforward panacea. Comprehending critical factors (e.g., current state of mobile client and remote resources) that impact on augmentation process and optimum selection of cloud-based resource types are some challenges that hinder CMA adaptability. This paper comprehensively surveys the mobile augmentation domain and presents taxonomy of CMA approaches. The objectives of this study is to highlight the effects of remote resources on the quality and reliability of augmentation processes and discuss the challenges and opportunities of employing varied cloud-based resources in augmenting mobile devices. We present augmentation definition, motivation, and taxonomy of augmentation types, including traditional and cloud-based. We critically analyze the state-of-the-art CMA approaches and classify them into four groups of distant fixed, proximate fixed, proximate mobile, and hybrid to present a taxonomy. Vital decision making and performance limitation factors that influence on the adoption of CMA approaches are introduced and an exemplary decision making flowchart for future CMA approaches are presented. Impacts of CMA approaches on mobile computing is discussed and open challenges are presented as the future research directions.
Techniques to Minimize State Transfer Cost for Dynamic Execution Offloading I...IJERA Editor
The recent advancement in cloud computing in cloud computing is leading to and excessive growth of the mobile devices that can become powerful means for the information access and mobile applications. This introducing a latent technology called Mobile cloud computing. Smart phone device supports wide range of mobile applications which require high computational power, memory, storage and energy but these resources are limited in number so act as constraints in smart phone devices. With the integration of cloud computing and mobile applications it is possible to overcome these constraints by offloading the complex modules on cloud. These restrictions may be alleviated by computation offloading: sending heavy computations to resourceful servers and receiving the results from these servers. Many issues related to offloading have been investigated in the past decade.
ERMO2 algorithm: an energy efficient mobility management in mobile cloud comp...IJECEIAES
Recently, mobile devices are becoming the primary platforms for every user who always roam around and access the cloud computing applications. Mobile cloud computing (MCC) combines the both mobile and cloud computing, which provides optimal services to the mobile users. In next-generation mobile environments, mainly due to the huge number of mobile users in conjunction with the small cell size and their portable information‟s, the influence of mobility on the network performance is strengthened. In this paper, we propose an energy efficient mobility management in mobile cloud computing (E2M2MC2) system for 5G heterogeneous networks. The proposed E2M2MC2 system use elective repeat multi-objective optimization (ERMO2) algorithm to determine the best clouds based on the selection metrics are delay, jitter, bit error rate (BER), packet loss, communication cost, response time, and network load. ERMO2 algorithm provides energy efficient management of user mobility as well as network resources. The simulation results shows that the proposed E2M2MC2 system helps in minimizing delay, packet loss rate and energy consumption in a heterogeneous network.
Implementation of a decentralized real-time management system for electrical ...journalBEEI
Intelligent management of the electrical network is the implementation of an integrated system based on a reliable and secure communication architecture for transmitting end-to-end information between the equipment and the management system. The main objective of this work is to develop an intelligent telecontrol solution for the electrical distribution network combining communication techniques and an intelligent reconfiguration strategy. The solution is based on a graphic model and a secure communication architecture using the internet of things to ensure flexibility in terms of management of the intelligent network. This intelligent multi-criteria solution uses a secure communication architecture and the MQTT protocol to ensure system interoperability and security. The tests were carried out on the IEEE 33 bus network and consequently, an optimization of the losses and a clear improvement in the nodal voltage were recorded despite the variation of the electric charge.
EFFECTIVE BANDWIDTH ANALYSIS OF MIMO BASED MOBILE CLOUD COMPUTINGIJCI JOURNAL
Digital Disruption is all around us. Mobile is overtaking desktop, Social Media is beating search, Messaging Application are challenging e-mails and everything around us is becoming connected. Mobile devices especially the smart phones are fueling the culture of “Anytime, Anywhere, And Anything’’. Smartphone is not only ubiquitous but also the primary computing device for many .These paradigm shifts are fueled by the explosive growth of smart phones which has touched a volume of 1.6 billion units globally. Smartphone growth has also triggered the explosive growth of mobile applications and cloud computing .Together, Mobile cloud computing is now a potential technology for mobile services .MCC overcomes obstacles related to battery life, storage capacity and low bandwidth. Current smart phones uses 2x2 MIMO which gives a speed 300Mbps, by using massive MIMO technology speed can be enhanced up to 1Gbps. This paper gives a BER (Bit Error Ratio) analysis to prove that by increasing number of transmitting and receiving antennas the performance can be enhanced.
since our electrical system consists of many interconnections .in order to have a proper transmission we need grid if we incorporate some sensors it results in smart grid .today grid system consists of all interconnection tapping points
Contemporary Energy Optimization for Mobile and Cloud Environmentijceronline
Cloud and mobile computing applications are increasing heavily in terms of usage. These two areas extending usability of systems. This review paper gives information about cloud and mobile applications in terms of resources they consume and the need of choosing variety of features for users from several locations and the evolutionary provisions for service provider and end users. Both the fields are combined to provide good functionality, efficiency and effectiveness with mobile phones. The enhancement by considering power consumption by means of resource constrained nature of devices, communication media and cost effectiveness. This paper discuss about the concepts related to power consumption, underlying protocols and the other performance issues
Towards automated service-oriented lifecycle management for 5G networksEricsson
5G networks will be a key enabler for the Internet of Things by providing a platform for connecting a massive number of devices with heterogeneous sets of network quality requirements. In this environment, 5G network operators will have to solve the complex challenge of managing network services for diverse customer sectors (such as automotive, health or energy) with different requirements throughout their lifecycle.
A Grouped System Architecture for Smart Grids Based AMI Communications Over LTE ijwmn
A smart grid based Advanced Metering Infrastructure (AMI), is a technology that enables the utilities to
monitor and control the electricity consumption through a set of various smart meters (SMs) connected via
a two way communication infrastructure. One of the key challenges for smart grids is how to connect a
large number of devices. On the other hand, 4G Long Term Evolution (LTE), the latest standard for mobile
communications, was developed to provide stable service performance and higher data rates for a large
number of mobile users. Therefore, LTE is considered a promising solution for wide area connectivity for
SMs. In this paper, a grouped hierarchal architecture for SMs communications over LTE is introduced.
Then, an efficient grouped scheduling technique is proposed for SMs transmissions over LTE. The
proposed architecture efficiently solves the overload problem due to AMI traffic and guarantees a full
monitoring and control for energy consumption. The results of our suggested solution showed that LTE can
serve better for smart grids based AMI with particular grouping and scheduling scheme. In addition, the
presented technique can able to be used in urban areas having high density of SMs.
Cooperative hierarchical based edge-computing approach for resources allocati...IJECEIAES
Using mobile and Internet of Things (IoT) applications is becoming very popular and obtained researchers’ interest and commercial investment, in order to fulfill future vision and the requirements for smart cities. These applications have common demands such as fast response, distributed nature, and awareness of service location. However, these requirements’ nature cannot be satisfied by central systems services that reside in the clouds. Therefore, edge computing paradigm has emerged to satisfy such demands, by providing an extension for cloud resources at the network edge, and consequently, they become closer to end-user devices. In this paper, exploiting edge resources is studied; therefore, a cooperative-hierarchical approach for executing the pre-partitioned applications’ modules between edges resources is proposed, in order to reduce traffic between the network core and the cloud, where this proposed approach has a polynomial-time complexity. Furthermore, edge computing increases the efficiency of providing services, and improves end-user experience. To validate our proposed cooperative-hierarchical approach for modules placement between edge nodes’ resources, iFogSim toolkit is used. The obtained simulation results show that the proposed approach reduces network’s load and the total delay compared to a baseline approach for modules’ placement, moreover, it increases the network’s overall throughput.
HOW TO MANAGE URINARY INCONTINENCE?
When you are faced with a leaky bladder it is best to discuss the options to manage the condition with your doctor, even though you may feel a bit delicate at first to discuss the problem.
In Chennai there are several leading urology Centers that treat a variety of urinary disorders and there are speciality clinics that deal with urinary incontinence. One among the finest Nephrology and Urology Centers is Annai Arul Hospital with a separate department and a team of eminent nephrologists and urologist to treat all sorts of cases.
Implementation of a decentralized real-time management system for electrical ...journalBEEI
Intelligent management of the electrical network is the implementation of an integrated system based on a reliable and secure communication architecture for transmitting end-to-end information between the equipment and the management system. The main objective of this work is to develop an intelligent telecontrol solution for the electrical distribution network combining communication techniques and an intelligent reconfiguration strategy. The solution is based on a graphic model and a secure communication architecture using the internet of things to ensure flexibility in terms of management of the intelligent network. This intelligent multi-criteria solution uses a secure communication architecture and the MQTT protocol to ensure system interoperability and security. The tests were carried out on the IEEE 33 bus network and consequently, an optimization of the losses and a clear improvement in the nodal voltage were recorded despite the variation of the electric charge.
EFFECTIVE BANDWIDTH ANALYSIS OF MIMO BASED MOBILE CLOUD COMPUTINGIJCI JOURNAL
Digital Disruption is all around us. Mobile is overtaking desktop, Social Media is beating search, Messaging Application are challenging e-mails and everything around us is becoming connected. Mobile devices especially the smart phones are fueling the culture of “Anytime, Anywhere, And Anything’’. Smartphone is not only ubiquitous but also the primary computing device for many .These paradigm shifts are fueled by the explosive growth of smart phones which has touched a volume of 1.6 billion units globally. Smartphone growth has also triggered the explosive growth of mobile applications and cloud computing .Together, Mobile cloud computing is now a potential technology for mobile services .MCC overcomes obstacles related to battery life, storage capacity and low bandwidth. Current smart phones uses 2x2 MIMO which gives a speed 300Mbps, by using massive MIMO technology speed can be enhanced up to 1Gbps. This paper gives a BER (Bit Error Ratio) analysis to prove that by increasing number of transmitting and receiving antennas the performance can be enhanced.
since our electrical system consists of many interconnections .in order to have a proper transmission we need grid if we incorporate some sensors it results in smart grid .today grid system consists of all interconnection tapping points
Contemporary Energy Optimization for Mobile and Cloud Environmentijceronline
Cloud and mobile computing applications are increasing heavily in terms of usage. These two areas extending usability of systems. This review paper gives information about cloud and mobile applications in terms of resources they consume and the need of choosing variety of features for users from several locations and the evolutionary provisions for service provider and end users. Both the fields are combined to provide good functionality, efficiency and effectiveness with mobile phones. The enhancement by considering power consumption by means of resource constrained nature of devices, communication media and cost effectiveness. This paper discuss about the concepts related to power consumption, underlying protocols and the other performance issues
Towards automated service-oriented lifecycle management for 5G networksEricsson
5G networks will be a key enabler for the Internet of Things by providing a platform for connecting a massive number of devices with heterogeneous sets of network quality requirements. In this environment, 5G network operators will have to solve the complex challenge of managing network services for diverse customer sectors (such as automotive, health or energy) with different requirements throughout their lifecycle.
A Grouped System Architecture for Smart Grids Based AMI Communications Over LTE ijwmn
A smart grid based Advanced Metering Infrastructure (AMI), is a technology that enables the utilities to
monitor and control the electricity consumption through a set of various smart meters (SMs) connected via
a two way communication infrastructure. One of the key challenges for smart grids is how to connect a
large number of devices. On the other hand, 4G Long Term Evolution (LTE), the latest standard for mobile
communications, was developed to provide stable service performance and higher data rates for a large
number of mobile users. Therefore, LTE is considered a promising solution for wide area connectivity for
SMs. In this paper, a grouped hierarchal architecture for SMs communications over LTE is introduced.
Then, an efficient grouped scheduling technique is proposed for SMs transmissions over LTE. The
proposed architecture efficiently solves the overload problem due to AMI traffic and guarantees a full
monitoring and control for energy consumption. The results of our suggested solution showed that LTE can
serve better for smart grids based AMI with particular grouping and scheduling scheme. In addition, the
presented technique can able to be used in urban areas having high density of SMs.
Cooperative hierarchical based edge-computing approach for resources allocati...IJECEIAES
Using mobile and Internet of Things (IoT) applications is becoming very popular and obtained researchers’ interest and commercial investment, in order to fulfill future vision and the requirements for smart cities. These applications have common demands such as fast response, distributed nature, and awareness of service location. However, these requirements’ nature cannot be satisfied by central systems services that reside in the clouds. Therefore, edge computing paradigm has emerged to satisfy such demands, by providing an extension for cloud resources at the network edge, and consequently, they become closer to end-user devices. In this paper, exploiting edge resources is studied; therefore, a cooperative-hierarchical approach for executing the pre-partitioned applications’ modules between edges resources is proposed, in order to reduce traffic between the network core and the cloud, where this proposed approach has a polynomial-time complexity. Furthermore, edge computing increases the efficiency of providing services, and improves end-user experience. To validate our proposed cooperative-hierarchical approach for modules placement between edge nodes’ resources, iFogSim toolkit is used. The obtained simulation results show that the proposed approach reduces network’s load and the total delay compared to a baseline approach for modules’ placement, moreover, it increases the network’s overall throughput.
HOW TO MANAGE URINARY INCONTINENCE?
When you are faced with a leaky bladder it is best to discuss the options to manage the condition with your doctor, even though you may feel a bit delicate at first to discuss the problem.
In Chennai there are several leading urology Centers that treat a variety of urinary disorders and there are speciality clinics that deal with urinary incontinence. One among the finest Nephrology and Urology Centers is Annai Arul Hospital with a separate department and a team of eminent nephrologists and urologist to treat all sorts of cases.
Colorectal cancer is one of the most common causes of cancer death worldwide. Most of the colorectal cancers are thought to arise from polypoid adenomas by metaplasia.
MOBILE CLOUD COMPUTING: ISSUE AND OPPORTUNITIES IN LIBRARIESOgunlana Kunle
Emerging technologies are always attractive to libraries. Like any other service delivery organizations, libraries and librarians engaged these technologies to provide services effectively and efficiently as well as making information delivery better. Most of these emerging technologies have changed the information-seeking behavior of library users and have put tremendous pressure on libraries to adopt these technologies such as Web 2.0, Web 3.0; library bookmark app, cloud computing and most recently Mobile Cloud Computing (MCC). Mobile cloud computing (MCC) was introduced to be a technology with the explosive growth of mobile applications and evolving cloud computing concept based on Infrastructure as a Service (IaaS) where both data storage and data processing operate outside of the mobile device. It is based on the concept of cloud where concentrated applications, resources, and services are accessed over the wireless network based on the web browser of the mobile phone. Despite its pervasiveness, storage capacity, scalability, reliability and, hype many libraries are yet to adopt mobile cloud computing due to various factors. Such factors are data security, privacy, failed accounts, trust, standards, organizational culture, service outage, data management, and others. Although the use of mobile devices posed a threat to library services, libraries and librarians can adopt these technologies in providing flexible, resilience and edge-cutting services to the users. This article addresses issues and functionalities, opportunities and benefits, challenges and risks of MCC.
Mobile Cloud Computing (MCC) is the combination of cloud computing, mobile computing and wireless networks to bring rich computational resources to mobile users, network operators, as well as cloud computing providers.
Cloud computing for mobile users can offloading computation save energyIEEEFINALYEARPROJECTS
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09849539085, 09966235788 or mail us - ieeefinalsemprojects@gmail.co¬m-Visit Our Website: www.finalyearprojects.org
Mobile cloud computing (MCC) at its simplest, refers to an infrastructure where both the data storage and data processing happen outside of the mobile device.
Mobile cloud computing (MCC) at its simplest, refers to an infrastructure where both the data storage and data processing happen outside of the mobile device.
Mobile cloud computing (MCC) at its simplest, refers to an infrastructure where both the data storage and data processing happen outside of the mobile device.
With a rapid growth of the mobile applications and development of cloud computing concept, mobile cloud
computing (MCC) has been introduced to be a potential technology for mobile services. MCC integrates the cloud
computing into the mobile environment and overcomes obstacles related to the performance, security etc discussed in
mobile computing. This paper gives an overview of the MCC including the definition, architecture, and applications. The
issues, existing solutions and approaches are presented.
Forklift Classes Overview by Intella PartsIntella Parts
Discover the different forklift classes and their specific applications. Learn how to choose the right forklift for your needs to ensure safety, efficiency, and compliance in your operations.
For more technical information, visit our website https://intellaparts.com
Immunizing Image Classifiers Against Localized Adversary Attacksgerogepatton
This paper addresses the vulnerability of deep learning models, particularly convolutional neural networks
(CNN)s, to adversarial attacks and presents a proactive training technique designed to counter them. We
introduce a novel volumization algorithm, which transforms 2D images into 3D volumetric representations.
When combined with 3D convolution and deep curriculum learning optimization (CLO), itsignificantly improves
the immunity of models against localized universal attacks by up to 40%. We evaluate our proposed approach
using contemporary CNN architectures and the modified Canadian Institute for Advanced Research (CIFAR-10
and CIFAR-100) and ImageNet Large Scale Visual Recognition Challenge (ILSVRC12) datasets, showcasing
accuracy improvements over previous techniques. The results indicate that the combination of the volumetric
input and curriculum learning holds significant promise for mitigating adversarial attacks without necessitating
adversary training.
Explore the innovative world of trenchless pipe repair with our comprehensive guide, "The Benefits and Techniques of Trenchless Pipe Repair." This document delves into the modern methods of repairing underground pipes without the need for extensive excavation, highlighting the numerous advantages and the latest techniques used in the industry.
Learn about the cost savings, reduced environmental impact, and minimal disruption associated with trenchless technology. Discover detailed explanations of popular techniques such as pipe bursting, cured-in-place pipe (CIPP) lining, and directional drilling. Understand how these methods can be applied to various types of infrastructure, from residential plumbing to large-scale municipal systems.
Ideal for homeowners, contractors, engineers, and anyone interested in modern plumbing solutions, this guide provides valuable insights into why trenchless pipe repair is becoming the preferred choice for pipe rehabilitation. Stay informed about the latest advancements and best practices in the field.
Event Management System Vb Net Project Report.pdfKamal Acharya
In present era, the scopes of information technology growing with a very fast .We do not see any are untouched from this industry. The scope of information technology has become wider includes: Business and industry. Household Business, Communication, Education, Entertainment, Science, Medicine, Engineering, Distance Learning, Weather Forecasting. Carrier Searching and so on.
My project named “Event Management System” is software that store and maintained all events coordinated in college. It also helpful to print related reports. My project will help to record the events coordinated by faculties with their Name, Event subject, date & details in an efficient & effective ways.
In my system we have to make a system by which a user can record all events coordinated by a particular faculty. In our proposed system some more featured are added which differs it from the existing system such as security.
Saudi Arabia stands as a titan in the global energy landscape, renowned for its abundant oil and gas resources. It's the largest exporter of petroleum and holds some of the world's most significant reserves. Let's delve into the top 10 oil and gas projects shaping Saudi Arabia's energy future in 2024.
Sachpazis:Terzaghi Bearing Capacity Estimation in simple terms with Calculati...Dr.Costas Sachpazis
Terzaghi's soil bearing capacity theory, developed by Karl Terzaghi, is a fundamental principle in geotechnical engineering used to determine the bearing capacity of shallow foundations. This theory provides a method to calculate the ultimate bearing capacity of soil, which is the maximum load per unit area that the soil can support without undergoing shear failure. The Calculation HTML Code included.
Hybrid optimization of pumped hydro system and solar- Engr. Abdul-Azeez.pdffxintegritypublishin
Advancements in technology unveil a myriad of electrical and electronic breakthroughs geared towards efficiently harnessing limited resources to meet human energy demands. The optimization of hybrid solar PV panels and pumped hydro energy supply systems plays a pivotal role in utilizing natural resources effectively. This initiative not only benefits humanity but also fosters environmental sustainability. The study investigated the design optimization of these hybrid systems, focusing on understanding solar radiation patterns, identifying geographical influences on solar radiation, formulating a mathematical model for system optimization, and determining the optimal configuration of PV panels and pumped hydro storage. Through a comparative analysis approach and eight weeks of data collection, the study addressed key research questions related to solar radiation patterns and optimal system design. The findings highlighted regions with heightened solar radiation levels, showcasing substantial potential for power generation and emphasizing the system's efficiency. Optimizing system design significantly boosted power generation, promoted renewable energy utilization, and enhanced energy storage capacity. The study underscored the benefits of optimizing hybrid solar PV panels and pumped hydro energy supply systems for sustainable energy usage. Optimizing the design of solar PV panels and pumped hydro energy supply systems as examined across diverse climatic conditions in a developing country, not only enhances power generation but also improves the integration of renewable energy sources and boosts energy storage capacities, particularly beneficial for less economically prosperous regions. Additionally, the study provides valuable insights for advancing energy research in economically viable areas. Recommendations included conducting site-specific assessments, utilizing advanced modeling tools, implementing regular maintenance protocols, and enhancing communication among system components.
2. What is Mobile Cloud Computing?
Mobile cloud computing (MCC) at its simplest,
refers to an infrastructure where both the data
storage and data processing happen outside of
the mobile device.
Mobile cloud applications move the computing
power and data storage away from the mobile
devices and into powerful and centralized
computing platforms located in clouds, which are
then accessed over the wireless connection
based on a thin native client.
3. Why Mobile Cloud Computing?
• Mobile devices face many resource challenges
(battery life, storage, bandwidth etc.)
• Cloud computing offers advantages to users by
allowing them to use infrastructure, platforms
and software by cloud providers at low cost and
elastically in an on-demand fashion.
• Mobile cloud computing provides mobile users
with data storage and processing services in
clouds, obviating the need to have a powerful
device configuration (e.g. CPU speed, memory
capacity etc), as all resource-intensive computing
can be performed in the cloud.
4. MCC Popularity
• According to a recent study by ABI Research,
more than 240 million business will use cloud
services through mobile devices by 2015.
• That traction will push the revenue of mobile
cloud computing to $5.2 billion.
• Mobile cloud computing is a highly promising
trend for the future of mobile computing.
6. MCC Architecture
• Mobile devices are connected to the mobile
networks via base stations that establish and control
the connections and functional interfaces between
the networks and mobile devices.
• Mobile users’ requests and information are
transmitted to the central processors that are
connected to servers providing mobile network
services.
• The subscribers’ requests are delivered to a cloud
through the Internet.
• In the cloud, cloud controllers process the requests
to provide mobile users with the corresponding
cloud services.
7. Advantages of MCC
• Extending battery lifetime:
– Computation offloading migrates large
computations and complex processing from
resource-limited devices (i.e., mobile devices) to
resourceful machines (i.e., servers in clouds).
– Remote application execution can save energy
significantly.
– Many mobile applications take advantages from
task migration and remote processing.
8. Advantages of MCC
• Improving data storage capacity and
processing power:
– MCC enables mobile users to store/access large
data on the cloud.
– MCC helps reduce the running cost for
computation intensive applications.
– Mobile applications are not constrained by
storage capacity on the devices because their data
now is stored on the cloud.
9. Advantages of MCC
• Improving reliability and availability:
– Keeping data and application in the clouds reduces
the chance of lost on the mobile devices.
– MCC can be designed as a comprehensive data
security model for both service providers and users:
• Protect copyrighted digital contents in clouds.
• Provide security services such as virus scanning, malicious
code detection, authentication for mobile users.
– With data and services in the clouds, then are
always(almost) available even when the users are
moving.
10. Advantages of MCC
• Dynamic provisioning:
– Dynamic on-demand provisioning of resources on a
fine-grained, self-service basis
– No need for advanced reservation
• Scalability:
– Mobile applications can be performed and scaled to
meet the unpredictable user demands
– Service providers can easily add and expand a service
11. Advantages of MCC
• Multi-tenancy:
– Service providers can share the resources and
costs to support a variety of applications and large
no. of users.
• Ease of Integration:
– Multiple services from different providers can be
integrated easily through the cloud and the
Internet to meet the users’ demands.
12. MCC Applications
• Mobile Commerce:
– M-commerce allows business models for commerce
using mobile devices.
– Examples: Mobile financial, mobile advertising, mobile
shopping…
– M-commerce applications face various challenges (low
bandwidth, high complexity of devices, security, …)
– Integrated with cloud can help address these issues
– Example: Combining 3G and cloud to increase data
processing speed and security level.
13. MCC Applications
• Mobile Learning:
– M-learning combines e-learning and mobility
– Traditional m-learning has limitations on high cost of
devices/network, low transmission rate, limited
educational resources
– Cloud-based m-learning can solve these limitations
– Enhanced communication quality between students
and teachers
– Help learners access remote learning resources
– A natural environment for collaborative learning
14. MCC Applications
• Mobile Healthcare:
– M-healthcare is to minimize the limitations of traditional
medical treatment (eg. Small storage, security/privacy,
medical errors, …)
– M-healthcare provides mobile users with convenient
access to resources(eg. medical records)
– M-healthcare offers hospitals and healthcare organizations
a variety of on-demand services on clouds
– Examples:
• Comprehensive health monitoring services
• Intelligent emergency management system
• Health-aware mobile devices (detect pulse-rate, blood pressure,
level of alcohol etc)
• Pervasive access to healthcare information
• Pervasive lifestyle incentive management (to manage healthcare
expenses)
15. MCC Applications
• Mobile Gaming:
– M-game is a high potential market generating
revenues for service providers.
– Can completely offload game engine requiring large
computing resource (e.g., graphic rendering) to the
server in the cloud.
– Offloading can also save energy and increase game
playing time (eg. MAUI allows fine-grained energy-
aware offloading of mobile codes to a cloud)
– Rendering adaptation technique can dynamically
adjust the game rendering parameters based on
communication constraints and gamers’ demands
16. MCC Applications
• Assistive technologies:
– Pedestrian crossing guide for blind and visually-
impaired
– Mobile currency reader for blind and visually
impaired
– Lecture transcription for hearing impaired students
• Other applications:
– Sharing photos/videos
– Keyword-based, voice-based, tag-based searching
– Monitoring a house, smart home systems
– …
17. MCC Issues
• Mobile communication issues:
– Low bandwidth: One of the biggest issues, because
the radio resource for wireless networks is much
more scarce than wired networks
– Service availability: Mobile users may not be able to
connect to the cloud to obtain a service due to traffic
congestion, network failures, mobile signal strength
problems
– Heterogeneity: Handling wireless connectivity with
highly heterogeneous networks to satisfy MCC
requirements (always-on connectivity, on-demand
scalability, energy efficiency) is a difficult problem
18. MCC Issues
• Computing issues:
Computation offloading:
• One of the main features of MCC
• Offloading is not always effective in saving energy
• It is critical to determine whether to offload and
which portions of the service codes to offload
• Two types:
– Offloading in a static environment
– Offloading in a dynamic environment
19. Computation Offloading Approaches in
a Static Environment
• Kumar and Lu suggest a program partitioning
based on estimation of energy consumption
before execution
• Optimal program partitioning for offloading is
dynamically calculated based on the trade-off
between the communication and computation
costs at run time.
K. Kumar and Y. Lu, “Cloud Computing for Mobile
Users: Can Offloading Computation Save Energy,”
IEEE Computer, vol. 43, no. 4, April 2010.
20. Computation Offloading Approaches in
a Static Environment
• Li et al. present an offloading scheme based on
profiling information about computation time and data
sharing at the level of procedure calls.
• A cost graph is constructed and a branch-and-bound
algorithm is applied to minimize the total energy
consumption of computation and the total data
communication cost.
Z. Li, C. Wang, and R. Xu, “Computation offloading to save
energy on handheld devices: a partition scheme,” in Proc
2001 Intl Conf on Compilers, architecture, and synthesis
for embedded systems (CASES), pp. 238-246, Nov 2001.
21. Computation Offloading Approaches in
a Static Environment
• Chen et al. present an approach to decide which
components of Java programs should be offloaded.
• First divide a Java program into methods and compute
execution costs for these methods.
• Then compare the local execution costs of each method
with the estimated remote execution costs to make an
optimal execution decision.
G. Chen, B. T. Kang, M. Kandermir, N. Vijaykrishnan, M. J.
Irwin, and R. Chandranouli, “Studying energy trade offs in
offloading computation/compilation in Java-enabled mobile
devices,” IEEE Transactions on Parallel and Distributed
Systems, 15(9):795-806, Sept 2004.
22. Computation Offloading Approaches in
a Static Environment
• Wang and Li propose a polynomial time algorithm to find an
optimal program partition.
• First partition a program into distributed subprograms by
producing a program abstraction.
• Then, task allocations and data transfer of the abstract memory
locations are determined subject to the control and data flow
defined over the abstraction.
• The abstraction is divided into clusters and a heuristic algorithm is
applied to find the optimal partition to minimize the execution cost
of the program.
C. Wang and Z. Li, “A computation offloading scheme on handheld
devices,” Journal of Parallel and Distributed Computing, Special issue
on middleware, 64(6):740-746. June 2004.
23. Computation Offloading Approaches in
a Static Environment
• Hunt and Scott present an automatic distributed
partitioning system (ADPS) called Coign, which
automatically transforms a program into distributed
applications without accessing the source codes.
• Coign constructs a graph model of the application’s
inter-component communication through scenario-
based profiling to find the best distribution.
G. C. Hunt and M. L. Scott, “The Coign automatic
distributed partitioning system,” in Proc 3rd Symposium
on Operating systems design and implementation (OSDI),
pp. 187-200, Feb 1999.
24. Computation Offloading Approaches in
a Static Environment
• Xian et al. propose an offloading method which does
not require the estimation of execution time.
• Online statistics of the comp time are used to compute
optimal timeout and if the computation is not finished
within timeout, it is offloaded to the server.
• Saves up to 17% more energy than existing methods.
C. Xian, Y. H. Lu, and Z. Li, “Adaptive computation
offloading for energy conservation on battery-powered
systems,” in Intl Conf on Parallel and Distributed Systems,
vol. 2, pp. 1, December 2009.
25. Computation Offloading Issues in a
Dynamic Environment
• Offloading in a dynamic network environment (e.g.,
changing connection status and bandwidth) is harder.
• Environment changes can cause additional problems.
• The transmitted data may not reach the destination
• The data executed on the server could be lost when it
has to be returned to the sender.
26. Computation Offloading Approaches in
a Dynamic Environment
• Ou et al. analyze offloading systems in wireless
environments
• They consider three circumstances of executing an
application to estimate the efficiency of offloading.
– performed locally (without offloading)
– performed in ideal offloading systems (without failures)
– performed with the presence of offloading and failure
recoveries (re-offload after failure)
S. Ou, K. Yang, A. Liotta, and L. Hu. “Performance Analysis
of Offloading Systems in Mobile Wireless Environments,”
in Proc IEEE Intl Conf on Communications (ICC), pp. 1821,
August 2007.
27. Computation Offloading Approaches in
a Dynamic Environment
• Chun and Maniatis present a system to partition an
application in three steps: application structuring,
partitioning choice, and security.
– Programs are structured to be seamlessly and dynamically
executed between mobile and cloud.
– The application decides what modules to run at the client and at
the server dynamically at a runtime.
– The system will choose a suitable partitioning policy so that the
total energy consumption is minimized.
– Modules containing sensitive data will be executed locally.
B-G. Chun and P. Maniatis, “Dynamically partitioning applications
between weak devices and clouds,” in Proceedings of the 1st ACM
Workshop on Mobile Cloud Computing & Services: Social Networks
and Beyond (MCS), no. 7, June 2010.
28. Computation Offloading Approaches in
a Dynamic Environment
• MAUI is an architecture to dynamically partition an
application at a runtime in three steps.
• First, use code portability to create two versions of a mobile
application (for mobile device and cloud).
• Second, use programing reflection to identify which
methods are marked ‘remoteable’ or not and type safety to
extract only the program state needed by the ‘remoteable’
methods. Then, send the necessary program state to the
cloud.
E. Cuervo, A. Balasubramanian, Dae-ki Cho, A. Wolman, S.
Saroiu, R. Chandra, and P. Bahl, “MAUI: Making Smartphones
Last Longer with Code offload,” in Proc 8th Intl Conf on Mobile
Systems, Applications, and Services, pp. 49-62, June 2010.
29. Computation Offloading Approaches in
a Dynamic Environment
• Angin and Bhargava propose a computation offloading framework
based on mobile agents.
• During installation of the mobile application on the device, it is
partitioned by the application partitioner component.
• When the user launches the application, the offloading manager
component of the framework first contacts a cloud registry to
locate virtual machine instances in the cloud to offload application
partitions to.
• Then these application partitions are packaged in mobile agents
and sent over the network to the selected instances to start
running, and the application task is completed with agent
collaboration without further management by the mobile platform.
P. Angin, B. Bhargava. “An Agent-based optimization framework for
mobile-cloud computing,” Journal of Wireless Mobile Networks,
Ubiquitous Computing, and Dependable Applications, vol. 4, no. 2,
2013.
30. MCC Security Issues
• Protecting user privacy and data/application
secrecy from adversaries is key to establish
and maintain consumers’ trust in the mobile
platform, especially in MCC.
• MCC security issues have two main categories:
– Security for mobile users
– Securing data on clouds
31. Security for Mobile Users
• Mobile devices are exposed to numerous security
threats like malicious codes and their
vulnerability.
• GPS can cause privacy issues for subscribers.
• Security for mobile applications:
– Installing and running security software are the
simplest ways to detect security threats.
– Mobile devices are resource constrained, protecting
them from the threats is more difficult than that for
resourceful devices.
32. Mobile User Security Approaches
• Oberheide et al. present an approach to move the threat
detection capabilities to clouds.
• An extension of the CloudAV platform consisting of host
agent and network service components.
• Host agent runs on mobile devices to inspect the file
activity on a system.
• If an identified file is not available in a cache of previous
analyzed files, this file will be sent to the incloud network
service for verification.
• The second major component of CloudAV is a network
service that is responsible for file verification
J. Oberheide, K. Veeraraghavan, E. Cooke, J. Flinn, and F.
Jahanian. “Virtualized in-cloud security services for mobile
devices,” in Proc 1st Workshop on Virtualization in Mobile
Computing (MobiVirt), pp. 31-35, June 2008.
33. Mobile User Security Approaches
• Portokalidis et al. present a paradigm in which attack
detection for a smartphone is performed on a remote
server in the cloud.
• The smartphone records only a minimal execution
trace, and transmits it to the security server in the
cloud.
G. Portokalidis, P. Homburg, K. Anagnostakis, and H. Bos,
“Paranoid Android: versatile protection for smartphones,”
in Proc 26th Annual Computer Security Application
Conference (ACSAC), pp. 347-356, September 2010.
34. Privacy Issues in MCC
• Location based services (LBS) faces a privacy
issue on mobile users’ provide private
information such as their current location.
• This problem becomes even worse if an
adversary knows user’s important
information.
35. Privacy Issues in MCC
• Zhangwei and Mingjun propose the location trusted server
(LTS) approach.
• After receiving mobile users’ requests, LTS gathers their
location information and cloaks the information called
“cloaked region” to conceal user’s information.
• The “cloaked region” is sent to LBS, so LBS knows only
general information about the users but cannot identify
them.
• H. Zhangwei and X. Mingjun, “A Distributed Spatial Cloaking
Protocol for Location Privacy,” in Proc 2nd Intl Conf on
Networks Security Wireless Communications and Trusted
Computing (NSWCTC), vol. 2, pp. 468, June 2010.
36. Context-aware Mobile Cloud Services
• It is important to fulfill mobile users’ satisfaction
by monitoring their preferences and providing
appropriate services to each of the users.
• Context-aware mobile cloud services try to utilize
the local contexts (e.g., data types, network
status, device environments, and user
preferences) to improve the quality of service
(QoS).
37. Mobile Service Clouds
• Samimi et al. build the Mobile Service Cloud model.
• When a customer uses a service, the request firstly goes to
a service gateway which will choose an appropriate primary
proxy to meet the requirements and then sends the result
to the user.
• In disconnection, MSCs will establish transient proxies for
mobile devices to monitor the service path, and support
dynamic reconfiguration.
• The model addresses the disconnection issue and can
maintain the QoS at an acceptable level.
F. A. Samimi, P. K. Mckinley, and S. M. Sadjadi, “Mobile Service
Clouds: A Self-Managing Infrastructure for Autonomic Mobile
Computing Services,” in Proceedings of the 2nd International
Workshop on Self-Managed Networks, Systems & Services
(SelfMan), vol. 3996, pp. 130-141, 2006.
38. Context-aware Mobile Cloud
Services
• La and Kim propose an algorithm to choose a context-aware
adapter.
• The algorithm first determines the gaps occurring in the given
contexts. A gap is defined as a result of context changes.
• Then, the algorithm determines a cause of predefined gaps before
saving the current states of the service invocation for
disconnection.
• For each identified gap, this algorithm will choose an appropriate
adapter for the mobile user.
H. H. La and S. D. Kim, “A Conceptual Framework for Provisioning
Context-aware Mobile Cloud Services,” in Proceedings of the 3rd IEEE
International Conference on Cloud Computing (CLOUD), pp. 466,
August 2010.
39. Open Issues in MCC
• Network Access Management:
– An efficient network access management not only
improves link performance but also optimizes
bandwidth usage.
– Cognitive radio can be expected as a solution to
achieve the wireless access management.
– Can automatically changes its transmission or
reception parameters, in a way where the wireless
communications can have spectrum agility in terms of
selecting available wireless channels opportunistically.
– Integrated with MCC for better spectrum utilization
40. Open Issues in MCC
• Quality of Service:
– How to ensure QoS is still a big issue, especially on
network delay.
– CloneCloud and Cloudlets are expected to reduce the
network delay.
– CloneCloud uses nearby computers or data centers to
increase the speed of smart phone applications.
– The idea is to clone the entire set of data and
applications from the smartphone onto the cloud and
to selectively execute some operations on the clones,
reintegrating the results back into the smartphone.
41. Open Issues in MCC
• Quality of Service:
– A cloudlet is a trusted, resource-rich computer or
cluster of computers which is well-connected to the
Internet and available for use by nearby mobile
devices with on one-hop wireless connection.
– Mobile users may meet the demand for real-time
interactive response by low-latency, one-hop, high-
bandwidth wireless access to the cloudlet.
– Can help mobile users overcome the limits of cloud
computing as WAN latency and low bandwidth.
42. Open Issues in MCC
• Pricing:
– MCC involves with both mobile service provider
(MSP) and cloud service provider (CSP) with
different services management, customers
management, methods of payment and prices.
– This will lead to many issues.
– The business model including pricing and revenue
sharing has to be carefully developed for MCC.
43. Open Issues in MCC
• Standard Interface:
– Interoperability becomes an important issue when
mobile users need to interact with the cloud.
– Web interfaces may not be the best option.
– It is not specifically designed for mobile devices.
– May have more overhead.
– Compatibility among devices for web interface could
be an issue.
– Standard protocol, signaling, and interface for
interacting between mobile users and cloud would be
required. (HTML5 & CSS3)
44. Open Issues in MCC
• Service Convergence:
– Services will be differentiated according to the types, cost,
availability and quality.
– A single cloud may not be enough to meet mobile user’s
demands.
– New scheme is needed in which the mobile users can utilize
multiple cloud in a unified fashion.
– The scheme should be able to automatically discover and
compose services for user.
– Sky computing is a model where resources from multiple clouds
providers are leveraged to create a large scale distributed
infrastructure.
– The mobile sky computing will enable providers to support a
cross-cloud communication and enable users to implement
mobile services and applications.
– Service integration (i.e., convergence) would need to be
explored.
45. References
• Le Guan, Xu Ke, Meina Song, and Junde Song, “A Survey of
Research on Mobile Cloud Computing”, IEEE/ACIS 10th
International Conference on Computer and Information
Science (ICIS), 2010, pp. 387-392.
• Xiaopeng Fan, Jiannong Cao, and Haixia Mao. “A Survey of
Mobile Cloud Computing,” ZTE Communications, 9(1):4-8,
Mar 2011.
• Hoang T. Dinh, Chonho Lee, Dusit Niyato, and Ping Wang. “A
survey of Mobile Cloud Computing: Architecture,
Applications, and Approaches”, Wireless Communication
and Mobile Computing.
• http://www.csie.ndhu.edu.tw/~showyang/MCloud2012/04
MobileCloudSurvey.pdf
• Chetan S., Gautam Kumar, K. Dinesh, Mathew K. and
Abhimanyu M.A., “Cloud Computing for Mobile World,”
2010. (http://chetan.ueuo.com/projects/CCMW.pdf)