Software Defined Storage for cooperative Mobile Edge Computing systems

Albadarneh, Jafar; Jararweh, Yaser; Al‐Ayyoub, Mahmoud; Al-Smadi, Mohammad; Fontes, Ramon dos Reis

doi:10.1109/sds.2017.7939160

Cited by 15 publications

(6 citation statements)

References 19 publications

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“…Badarneh et al [15] use advanced ASP and database platforms, adopt a three-layer structure model, give basic module design and implementation methods, add multiple roles, and develop and design an online education platform. It will directly affect the efficiency and level of online education management and the level of informatization of online education management.…”

Section: Related Workmentioning

confidence: 99%

The Construction of University Network Education System Based on Mobile Edge Computing in the Era of Big Data

Zhu

2022

Wireless Communications and Mobile Computing

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This article first established a university network education system model based on physical failure repair behavior at the big data infrastructure layer and then examined in depth the complex common causes of multiple data failures in the big data environment caused by a single physical machine failure, all based on the principle of mobile edge computing. At the application service layer, a performance model based on queuing theory is first established, with the amount of available resources as a conditional parameter. The model examines important events in mobile edge computing, such as queue overflow and timeout failure. The impact of failure repair behavior on the random change of system dynamic energy consumption is thoroughly investigated, and a system energy consumption model is developed as a result. The network education system in colleges and universities includes a user login module, teaching resource management module, student and teacher management module, online teaching management module, student achievement management module, student homework management module, system data management module, and other business functions. Later, the theory of mobile edge computing proposed a set of comprehensive evaluation indicators that characterize the relevance, such as expected performance and expected energy consumption. Based on these evaluation indicators, a new indicator was proposed to quantify the complex constraint relationship. Finally, a functional use case test was conducted, focusing on testing the query function of online education information; a performance test was conducted in the software operating environment, following the development of the test scenario, and the server’s CPU utilization rate was tested while the software was running. The results show that the designed network education platform is relatively stable and can withstand user access pressure. The performance ratio indicator can effectively assist the cloud computing system in selecting a more appropriate option for the migrated traditional service system.

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Section: Related Workmentioning

confidence: 99%

The Construction of University Network Education System Based on Mobile Edge Computing in the Era of Big Data

Zhu

2022

Wireless Communications and Mobile Computing

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“…We conducted experiments with 802.11, as provided by Mininet-WiFi; however, the proposed architecture is independent of the underlying wireless technology and can be implemented in 5G networks. Research on multi-access edgedominated networks has already been conducted and PoC experiments have been presented that use the SDN control features and wireless emulation medium supported by Mininet-WiFi [27]- [30].…”

Section: Proof-of-concept Experimental Evaluationmentioning

confidence: 99%

SDN Enhanced Multi-Access Edge Computing (MEC) for E2E Mobility and QoS Management

Shah

Gregory

et al. 2020

IEEE Access

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Multi-access Edge Computing (MEC) is a key enabler of the fifth-generation (5G) mobile cellular networks. MEC enables Ultra-reliable and Low-latency Communications (URLLC) by bringing the data and computational resources closer to the mobile users. As 5G deployments commence in earnest, researchers have turned their attention to various aspects of edge computing in an effort to leverage the new capabilities offered by 5G. In this paper, we propose the integration of Software Defined Networking (SDN) and cloud-native virtualization techniques, such as containers, with the MEC architecture, to facilitate the orchestration and management of Mobile Edge Hosts (MEH). The proposed architecture focuses on the endto-end mobility support required to maintain service continuity when mobile users relocate from one MEH to another. SDN is proposed as a reliable, programmatic paradigm to provide mobile edge orchestration and dynamic configuration of the underlying network for improved service continuity and quality of experience. The proposed architecture is validated through vehicle-to-everything simulations that highlight the advantage of the centralized network intelligence and the modularity and portability offered by SDN and containers. INDEX TERMS Software defined networking, mobility management, multi-access edge computing, 5G, cloud-native, containerization, URLLC.

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“…The MEC application migration between edges of different MNOs, with service continuity guaranteed, is still an open issue [41]. According to the available processing capabilities at the edge and the service requirements, the Infrastructure Manager could either decide to trigger a scale-up operation in the edge server and/or enforce cooperation among nearby edge servers [42], if the closest MEC server is overloaded.…”

Section: Mobility Managementmentioning

confidence: 99%

“…Despite experimenting with 802.11 and not an actual 5G protocol suite, the wireless emulation and SDN control features of Mininet-WiFi allow valuable PoC experiments on a subset of the functionalities of the envisioned framework on top of programmable, multi-access, and edge-dominated network infrastructures, as previously presented in [14,42,44]. In particular, the functionalities required for V2N connectivity of a vehicle with a V2X AS were emulated, due to the end-to-end scope and relevance in the case of cross-operator mobility.…”

Section: Proof-of-concept Experimental Evaluationmentioning

confidence: 99%

Slicing on the Road: Enabling the Automotive Vertical through 5G Network Softwarization

Campolo

Fontes

Molinaro

et al. 2018

Sensors

Self Cite

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The demanding requirements of Vehicle-to-Everything (V2X) applications, such as ultra-low latency, high-bandwidth, highly-reliable communication, intensive computation and near-real time data processing, raise outstanding challenges and opportunities for fifth generation (5G) systems. By allowing an operator to flexibly provide dedicated logical networks with (virtualized) functionalities over a common physical infrastructure, network slicing candidates itself as a prominent solution to support V2X over upcoming programmable and softwarized 5G systems in a business-agile manner. In this paper, a network slicing framework is proposed along with relevant building blocks and mechanisms to support V2X applications by flexibly orchestrating multi-access and edge-dominated 5G network infrastructures, especially with reference to roaming scenarios. Proof of concept experiments using the Mininet emulator showcase the viability and potential benefits of the proposed framework for cooperative driving use cases.

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Software Defined Storage for cooperative Mobile Edge Computing systems

Cited by 15 publications

References 19 publications

The Construction of University Network Education System Based on Mobile Edge Computing in the Era of Big Data

The Construction of University Network Education System Based on Mobile Edge Computing in the Era of Big Data

SDN Enhanced Multi-Access Edge Computing (MEC) for E2E Mobility and QoS Management

Slicing on the Road: Enabling the Automotive Vertical through 5G Network Softwarization

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