A cloudlet architecture using mobile devices

El-Barbary, Abd El-Hameed G.; El-Sayed, Layla A. A.; Aly, H. H.; El-Derini, M.N.

doi:10.1109/aiccsa.2015.7507145

Cited by 12 publications

(5 citation statements)

References 13 publications

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“…Technique RSS [2,21], ToA [22][23][24], TDoA [25], AoA [26,27], AoD [28] Fingerprinting [29] Measurements Addresses some of the problems related to non-line-of-sight and multipath propagation [29] Does not require exact locations of access points [30] Disadvantages More difficult regarding synchronization of receiver/ transmitter-side times and accuracy of short-range flight time measurements For angle calculation, complex hardware is required to determine the angle of arrival Poor positioning accuracy in real-world indoor environments because of a complex accurate propagation model [30,31] Multipath is an issue with signal propagation Time-consuming and laborious Accurate fingerprint data depends on the autonomic construction of a fingerprint database When real-world indoor environments change significantly, the fingerprint database has to be rebuilt [29] 3. Utilizing mobile device connectivity to nearby cloud servers enables a cloudlet to overcome the distant wide-area network latency and cellular energy consumption problems [37]. 4.…”

Section: Signal Propagation Mode Location Fingerprinting Methodsmentioning

confidence: 99%

Wi-Fi indoor positioning and navigation: a cloudlet-based cloud computing approach

Khanh

Nguyen

Pham

et al. 2020

Hum. Cent. Comput. Inf. Sci.

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Increasing demands for location-based services require accurate wireless indoor location information. Location-based services include indoor navigation for people or robots, personnel, asset tracking, guiding blind people, factory automation, workplace safety, locating patients in a hospital, and location-based advertising [1]. Additionally, such services are becoming essential in various other fields such as mobile commerce, parcel or vehicle tracking, discovering the nearest shops or restaurants, and social

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Section: Signal Propagation Mode Location Fingerprinting Methodsmentioning

confidence: 99%

Wi-Fi indoor positioning and navigation: a cloudlet-based cloud computing approach

Khanh

Nguyen

Pham

et al. 2020

Hum. Cent. Comput. Inf. Sci.

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“…Several units of multi-core computers forms a cloudlet that is connected to remotely located cloud servers. Cloudlet is brought as a promising solution as concerns distant wide area networks (WAN) latency and cellular energy consumption by utilizing cellular data connectivity to the cloud server [11]. The prime focus of cloudlet is to bring cloud technologies closer to the end user that provide support to resource and latency sensitive applications [95].…”

Section: Related Concepts and Technologiesmentioning

confidence: 99%

“…In 2015, El-Barbary et al [11] proposed DroidCloudlet that is based on commodity mobile devices. DroidCloudlet is legitimized with resourcerich mobile devices that takes the load of resource-constraint mobile devices.…”

Section: Energy Efficiencymentioning

confidence: 99%

Mobile Edge Computing: A Survey

Abbas

Zhang

Taherkordi

et al. 2018

IEEE Internet Things J.

2,033

743

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Mobile edge computing (MEC) is an emergent architecture where cloud computing services are extended to the edge of networks into the mobile base stations. As a promising edge technology, it can be applied to mobile, wireless and wireline scenarios, using software and hardware platforms, located at the network edge in the vicinity of end users. MEC provides seamless integration of multiple application service providers and vendors towards mobile subscribers, enterprises and other vertical segments. It is an important component in the proposed 5G architecture that supports variety of innovative applications and services where ultra low latency is required. However, there are some challenges exists in the MEC eco system. To address these challenges, first off need to understand the network infrastructure of MEC, cloud and cellular network.Some questions and problems are addressed in this thesis that outlines the importance and challenges of MEC deployment. Impact of MEC integration with the traditional mobile and cloud network appears in this paper. A survey has been presented that contributes in general understanding of mobile edge computing (MEC). Readers will have an overview of MEC, such as definition, advantages, architectures and applications. Moreover, related research and future directions are pointed out in this thesis. Finally, security and privacy issues and their possible solutions are also discussed.iii This thesis is dedicated to my late Parents who were my first teachers. Without their support, guidance, and infinite wisdom, I would not have made it this far. My fervor towards professionalism is all colored by them.Also I would like to dedicate with my heart-felt and deepest gratitude to my siblings, I am blessed beyond belief. Their love and support means more to me than they will ever know.iv First and foremost, I thank Allah the Almighty for giving me health, strength and courage to complete my master thesis and eventually my Master in Network and System Administration at UiO.

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“…Recently to take advantage of the Cloud-computing efficiency, the edge and Fog computing paradigms have been introduced to bring Cloud services closer to end users Bonomi et al (2012), Yi et al (2015). These services are leveraged directly at the edge of the network such as access points, routers or cloudlets Premsankar et al (2018), El-Barbary et al (2015). One of the core applications that are benefiting from these technologies is the e-health domain.…”

Section: Introductionmentioning

confidence: 99%