Mapping of sensor nodes with servers in a mobile Health-Cloud environment

Das, Snigdha; Misra, Sudip; Khatua, Manas; Rodrigues, Joel J. P. C.

doi:10.1109/healthcom.2013.6720724

Cited by 17 publications

(6 citation statements)

References 10 publications

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“…• Minimises the sensor storage requirements Reliability of sensory data using MCC [52] • Consider the critical issues which makes a difference for sensory data and reliability of WSNs Mapping a sensor node with server [148] • Monitor patients based on the resource allocation framework…”

Section: Features Future Research Directionmentioning

confidence: 99%

Mobile Cloud Computing and Wireless Sensor Networks: A review, integration architecture, and future directions

et al. 2021

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In today's fast advancing world, sensors are used in various applications to provide complete data about different objects present around us. The sensor data when integrated with Mobile Cloud Computing (MCC) is used for further computation to provide useful results advanced warning, forecasting, planning, and plethora of other applications in this uncertain world. Few works have been proposed where sensor nodes are integrated with Wireless Sensor Networks (WSNs) which give a new direction in modern research for developing new technologies which help the users for fast access of sensory data over mobile devices. Herein, a systematic literature review of both MCC and WSNs are conducted and subsequently assimilated them via an architecture which is efficient and achievable within short time-span for a variety of applications. The MCC applications are reviewed from two main perspectives that are energy and information management. The communication aspect in MCC and WSNs has been discussed and the need for integration between the two has been justified in this work. The work done on mobility management in MCC and WSNs is reviewed. Also, the challenges in MCC-WSNs integration along with the comprehensive analysis and findings of the review are identified. Finally, the conclusion and specific future direction of research in this area are provided. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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Section: Features Future Research Directionmentioning

confidence: 99%

Mobile Cloud Computing and Wireless Sensor Networks: A review, integration architecture, and future directions

et al. 2021

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“…Doukas and Maglogiannis [38] also set up a mobile cloud system, which worked with sensors to provide real-time pervasive healthcare monitoring for the patients. Das et al [34] established a mobile sensor cloud system to undertake healthcare monitoring for patients and provided a dynamic scheme to map mobile sensors to servers as the patients, who wore sensors, moved from one place to another. In this way, the computing resource could be optimally allocated and the utilization ratio of servers was largely increased.…”

Section: A Sensors and Mobile Devicesmentioning

confidence: 99%

An Overview of Mobile Cloud Computing for Pervasive Healthcare

Wang

Jin

2019

IEEE Access

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Mobile devices, along with wearable sensors, allow patients to access healthcare services from anywhere at any time. The longstanding constraints of computational capability and storage space on mobile devices can be alleviated by outsourcing computation-or data-intensive tasks to remote cloud centers. Thus, mobile cloud computing (MCC) has been recognized as a promising approach to provide pervasive healthcare services to people in their daily life. As the development and adoption of MCC techniques in healthcare, new optimization strategies have been explored and studied to help mobile cloud healthcare services to be deployed in a more effective and efficient manner. In this survey, we demonstrate how MCC techniques have been extensively deployed in various healthcare applications and, specifically, describe the general architecture and design considerations one should take into account while designing an MCC for healthcare scenarios. Given a large number of factors that may affect the performance of the MCC and even result in catastrophic consequences in healthcare, this paper presents the state-of-the-art optimization methods on the MCC for meeting the diverse priorities and achieving the optimal tradeoff among multiple objectives. Finally, the security and privacy issues of the MCC in healthcare are also discussed. INDEX TERMS Mobile cloud computing, pervasive healthcare. optimization, offloading, security and privacy. NOMENCLATURE

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“…Amamou et al [27] discussed a service level agreement-aware dynamic bandwidth allocator (DBA), in which bandwidth is allocated among the VMs based on the application requirements. The mapping of cloud server and mobile users in MCC was studied by Das et al [28]. A varying QoS requirement problem for different data incentive applications in cloud computing systems was studied by Lin et al [29].…”

Section: Related Workmentioning

confidence: 99%

Quality-Assured Secured Load Sharing in Mobile Cloud Networking Environment

Das

Khatua

Misra

et al. 2019

IEEE Trans. Cloud Comput.

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In mobile cloud networks (MCNs), a mobile user is connected with a cloud server through a network gateway, which is responsible for providing the required quality-of-service (QoS) to the users. If a user increases its service demand, the connecting gateway may fail to provide the requested QoS due to the overloaded demand, while the other gateways remain underloaded. Due to the increase in load in one gateway, the sharing of load among all the gateways is one of the prospective solutions for providing QoS-guaranteed services to the mobile users. Additionally, if a user misbehaves, the situation becomes more challenging. In this paper, we address the problem of QoS-guaranteed secured service provisioning in MCNs. We design a utility maximization problem for quality-assured secured load sharing (QuaLShare) in MCN, and determine its optimal solution using auction theory. In QuaLShare, the overloaded gateway detects the misbehaving gateways, and, then, prevents them from participating in the auction process. Theoretically, we characterize both the problem and the solution approaches in an MCN environment. Finally, we investigate the existence of Nash Equilibrium of the proposed scheme. We extend the solution for the case of multiple users, followed by theoretical analysis. Numerical analysis establishes the correctness of the proposed algorithms.Index Terms-Mobile cloud networking, auction theory, Nash equilibrium, bandwidth distribution, load sharing. ! INTRODUCTIONN OW-A-DAYS mobile devices are inseparable components of our lives. Rapid reduction of hardware cost and the availability of numerous user-friendly applications such as health monitoring, gaming, entertainment, social networking, and trading applications make these devices more popular to the users. Despite the increase of usage of mobile devices, exploitation of their full functionalities is restricted by the limited energy supply, low bandwidth, low computational capacity, and seamless mobility. For overcoming these limitations, mobile devices are integrated with cloud computing in mobile cloud computing (MCC) systems. Mobile cloud networking (MCN), which one of the foundational aspects of MCC, is responsible for designing cost-efficient and secure service delivery across data communication networks. In MCN, a mobile user requests for expensive services to the cloud server though their respective interfacing gateways. The cloud server processes the service-requests, and, finally, provides the services to the users.

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Mapping of sensor nodes with servers in a mobile Health-Cloud environment

Cited by 17 publications

References 10 publications

Mobile Cloud Computing and Wireless Sensor Networks: A review, integration architecture, and future directions

Mobile Cloud Computing and Wireless Sensor Networks: A review, integration architecture, and future directions

An Overview of Mobile Cloud Computing for Pervasive Healthcare

Quality-Assured Secured Load Sharing in Mobile Cloud Networking Environment

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