M&lt;sup&gt;2&lt;/sup&gt;C&lt;sup&gt;2&lt;/sup&gt;: A mobility management system for mobile cloud computing

Mitra, Karan; Saguna, Saguna; Åhlund, Christer; Granlund, Daniel

doi:10.1109/wcnc.2015.7127708

Cited by 22 publications

(15 citation statements)

References 12 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In the future, IoT based healthcare architectures such as IReHMo will be used to recognize complex activities [21] of patients to enable improved remote healthcare services. Further, such complex activity recognition will generate large-scale data that needs to be processed using cloud services available closest to the end-user [22] to minimize end-to-end latency and ensure timely response from healthcare services.…”

Section: Discussionmentioning

confidence: 99%

IReHMo: An efficient IoT-based remote health monitoring system for smart regions

Khoi

Saguna

Mitra

et al. 2015

2015 17th International Conference on E-Health Networking, Application &Amp; Services (HealthCom)

Self Cite

View full text Add to dashboard Cite

Abstract-The ageing population worldwide is constantly rising, both in urban and regional areas. There is a need for IoTbased remote health monitoring systems that take care of the health of elderly people without compromising their convenience and preference of staying at home. However, such systems may generate large amounts of data. The key research challenge addressed in this paper is to efficiently transmit healthcare data within the limit of the existing network infrastructure, especially in remote areas. In this paper, we identified the key network requirements of a typical remote health monitoring system in terms of real-time event update, bandwidth requirements and data generation. Furthermore, we studied the network communication protocols such as CoAP, MQTT and HTTP to understand the needs of such a system, in particular the bandwidth requirements and the volume of generated data. Subsequently, we have proposed IReHMo -an IoT-based remote health monitoring architecture that efficiently delivers healthcare data to the servers. The CoAP-based IReHMo implementation helps to reduce up to 90% volume of generated data for a single sensor event and up to 56% required bandwidth for a healthcare scenario. Finally, we conducted a scalability analysis to determine the feasibility of deploying IReHMo in large numbers in regions of north Sweden.

show abstract

Section: Discussionmentioning

confidence: 99%

IReHMo: An efficient IoT-based remote health monitoring system for smart regions

Khoi

Saguna

Mitra

et al. 2015

2015 17th International Conference on E-Health Networking, Application &Amp; Services (HealthCom)

Self Cite

View full text Add to dashboard Cite

show abstract

“…However, there is a dearth of literature that considers joint cloud and network selection. Mitra et al in [39] proposed a system for cloud and network selection while users are on the move in heterogeneous access networks. However, these methods are also limited.…”

Section: 23mentioning

confidence: 99%

“…However, their model does not consider big data application hosting. Mitra et al [39] proposed M2C2, a system that can support mobile patients for requiring real-time health care. Their system considers cloud and network selection as a joint optimisation problem and supports the selection of suitable cloud and suitable network.…”

Section: Qos For Real-time Patient Monitoringmentioning

confidence: 99%

See 1 more Smart Citation

Remote health care cyber‐physical system: quality of service (QoS) challenges and opportunities

Shah¹,

Yavari²,

Mitra

et al. 2016

IET cyber-phys. syst.

Self Cite

View full text Add to dashboard Cite

There is a growing emphasis to find alternative non-traditional ways to manage patients to ease the burden on health care services largely fuelled by a growing demand from sections of population that is ageing. In-home remote patient monitoring applications harnessing technological advancements in the area of Internet of things (IoT), semantic web, data analytics, and cloud computing have emerged as viable alternatives. However, such applications generate large amounts of real-time data in terms of volume, velocity, and variety thus making it a big data problem. Hence, the challenge is how to combine and analyse such data with historical patient data to obtain meaningful diagnoses suggestions within acceptable time frames (considering quality of service (QoS)). Despite the evolution of big data processing technologies (e.g. Hadoop) and scalable infrastructure (e.g. clouds), there remains a significant gap in the areas of heterogeneous data collection, real-time patient monitoring, and automated decision support (semantic reasoning) based on well-defined QoS constraints. In this study, the authors review the state-of-the-art in enabling QoS for remote health care applications. In particular, they investigate the QoS challenges required to meet the analysis and inferencing needs of such applications and to overcome the limitations of existing big data processing tools.

show abstract

“…However, there is a dearth of literature that considers joint cloud and network selection. Authors in [17] proposed a system for cloud and network selection while users are on the move in heterogeneous access networks. However, these methods are also limited.…”

Section: Qos-aware Cloud and Network Selection And Orchestrationmentioning

confidence: 99%

Orchestrating Quality of Service in the Cloud of Things Ecosystem

Jayaraman¹,

Mitra²,

Saguna³

et al. 2015

2015 IEEE International Symposium on Nanoelectronic and Information Systems

Self Cite

View full text Add to dashboard Cite

Abstract-Cloud of Things (CoT) is a vision inspired byInternet of Things (IoT) and cloud computing where the IoT devices are connected to the clouds via the Internet for data storage, processing, analytics and visualization. CoT ecosystem will encompass heterogeneous clouds, networks and devices to provide seamless service delivery, for example, in smart cites. To enable efficient service delivery, there is a need to guarantee a certain level of quality of service from both cloud and networks perspective. This paper discusses the Cloud of Things, cloud computing, networks and new quality of service management research issues arising due to realisation of CoT ecosystem vision.

show abstract

M<sup>2</sup>C<sup>2</sup>: A mobility management system for mobile cloud computing

Cited by 22 publications

References 12 publications

IReHMo: An efficient IoT-based remote health monitoring system for smart regions

IReHMo: An efficient IoT-based remote health monitoring system for smart regions

Remote health care cyber‐physical system: quality of service (QoS) challenges and opportunities

Orchestrating Quality of Service in the Cloud of Things Ecosystem

Contact Info

Product

Resources

About