Efficient techniques for energy optimization in Mobile Cloud Computing

Bahwaireth, Khadijah; Tawalbeh, Lo’ai; Basalamah, Anas; Jararweh, Yaser; Tawalbeh, Mohammad

doi:10.1109/aiccsa.2015.7507267

Cited by 15 publications

(6 citation statements)

References 22 publications

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“…Power consumption for edge IoT is another issue facing this approach of communication. Hence, authors in [22] has proposed various techniques in smart devices in order to prolong the energy life of edge nodes. Moreover, energy optimization is considered in [23] where profiling scheme is proposed in order to monitor the usage trends in mobile applications which would consequently lead to power optimization.…”

Section: Related Workmentioning

confidence: 99%

Edge IoT Networking

Alhaisoni¹

2020

IJACSA

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Data transmission has witnessed a new wave of emerging technologies such as IoT. This new way of communication could be done through smart communication such as smart sensors and actuators. Thus, data traffic keeps traversing to the main servers in order to accomplish the tasks at the sensors side. However, this way of communication has encountered certain issues related to network due to the nature of routing forth and back from the end users to the main servers. Subsequently, this incurs high delay and packet loss which successively degrades the overall Quality of Service (QoS). On the other hand, the new way of data transmission, which is called "edge IoT network", has not only helped on reducing the load over the network but also made the nodes to be more self-manage at the edge. However, this approach has some limitations due to the power consumption and efficiency, which would lead to node failure and data loss. Therefore, this paper presents a new model of combining network science and computer network in order to enhance the edge IoT efficiency. Simulation results have shown a clear evidence in improving the efficiency, communicability, degree, and overall closeness.

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Section: Related Workmentioning

confidence: 99%

Edge IoT Networking

Alhaisoni¹

2020

IJACSA

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“…Mobile Cloud Computing (MCC) [26] has become a crucial technology combined with edge computing to provide high performance and cloud services by the offloading tasks to the cloud via wireless networks. To support Aging in Place where real-time processing is required in minimal delay [28,29]. In Cloudlet based mobile cloud computing, where a cloudlet is a nearby server considered as a cloud resource with a fast network connection [30].…”

Section: Introductionmentioning

confidence: 99%

In-Home Floor Based Sensor System-Smart Carpet- to Facilitate Healthy Aging in Place (AIP)

Muheidat

Tawalbeh

2020

IEEE Access

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With the rapidly aging population, there is a need to detect elderly's activity, monitor their health, alert health care personnel, and provide real-time and long-term access to the generated sensor data. With the advances in sensor technologies, communication protocols, computing power, and cloud and edge services, it is now possible to build smart assistive living systems to improve people's lives. In this research, we present a Context-aware and private real-time reporting aging in place system. The proposed system, we call it smart carpet, consists of a sensor pad placed under a carpet; the electronics reads walking activity to provide an automated health monitoring and alert system. We extended the system's functionalities to improve its ability to detect falls, measure gait, and count the number of people traversing the carpet (socializing). In an urgent and time-sensitive situation, we need to provide a real-time notification. We propose a cooperative cloudlet model, where the sensors' data will be sent to the nearest Cloudlet for analysis and extracting real-time decisions in minimal delay. Results showed that our system could assist the elderly in detecting falls with 95% sensitivity and 85% specificity. Measuring and estimating their gait with a mean percentage error difference to GAITRite 1.43% in walking speed; hence, predicting a fall risk and counting people's plurality socializing with the elderly with an average accuracy of 100%. We evaluated our system's improvements in a controlled environment. We are looking forward to deploying the system in a nursing home(after the COVID-19 is over) for more data gathering and validations.

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“…Based on that, we can say that energy optimisation in mobile cloud systems is an essential need to obtain green MCC, and affects the performance and security of the stored data on those systems. There are many efficient techniques to reduce the power consumed by smart devices in mobile cloud environments presented in Bahwaireth et al (2015). In the same context, and to save energy in MCC, the authors in Al-Ayyoub et al (2015) proposed mathematical model for power consumption optimisation in large scale cloudlet-based mobile cloud systems.…”

Section: Related Workmentioning

confidence: 99%

Trust delegation-based secure mobile cloud computing framework

Tawalbeh

Ababneh

Jararweh

et al. 2017

IJICS

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Mobile devices are used to perform many useful tasks in our daily life. All around the world, many people are using their smart phones to communicate with others, identify their location, and do online shopping. These useful applications involve sharing personal and sensitive information. Also, the smart devices have many weaknesses, such as: limited battery life time, limited processing capacity and security issues. The mobile cloud computing (MCC) can be used to overcome these limitations. Using MCC improved the performance of many applications by conducting the processing at the cloud and sending back the results to the mobile device. But there are still many issues need to be addressed and considered when using MCC specially when dealing with applications that need live interaction and protecting the privacy. In this paper, we will study the main issues associated with mobile cloud computing models that include: security, performance, and quality of service. Then, we will present secure implementation of the cloudlet-based mobile cloud computing framework with its prototype that uses trust delegation technique to provide better security/performance tradeoffs.Keywords: mobile cloud computing; MCC; cloudlet; security; mobile devices; trust delegation. Trust delegation-based secure mobile cloud computing framework 37Reference to this paper should be made as follows: Tawalbeh, L.A., Ababneh, F., Jararweh, Y. and AlDosari, F. (2017) Fahd AlDosari received his PhD in 2010 from Bradford University, Bradford, UK. He is currently the Dean of College of Computer and Information Systems, Umm Al-Qura University, Makkah, Saudi Arabia. He has many publications in the areas of cloud computing, quality of service routing, simulation and modelling and adhoc networking. He is also a founder of expert houses in computing and higher education at Umm AlQura University. He is IEEE member.

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Efficient techniques for energy optimization in Mobile Cloud Computing

Cited by 15 publications

References 22 publications

Edge IoT Networking

Edge IoT Networking

In-Home Floor Based Sensor System-Smart Carpet- to Facilitate Healthy Aging in Place (AIP)

Trust delegation-based secure mobile cloud computing framework

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