Efficient Next Generation Emergency Communications over Multi-Access Edge Computing

Markakis, Evangelos K.; Politis, Ilias; Lykourgiotis, Asimakis; Rebahi, Yacine; Mastorakis, George; Mavromoustakis, Constandinos X.; Pallis, Evangelos

doi:10.1109/mcom.2017.1700345

Cited by 51 publications

(21 citation statements)

References 9 publications

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“…• Besides the improvements in data rate, reliability, and latency of communication, the emerging 5G networks will better support emergency services, which have the stringent requirements on response time [32]. Nevertheless, in HetNets with all wired backhaul links, broken wired backhaul may not be recovered instantly; therefore, emergency services can be severely impacted due to the slow network recovery and low reliability [33].…”

Section: B Wireless Backhaulmentioning

confidence: 99%

Mobile Edge Computing With Wireless Backhaul: Joint Task Offloading and Resource Allocation

Pham

Chung

et al. 2019

IEEE Access

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Considered as a key technology in 5G networks, mobile edge computing (MEC) can support intensive computation for energy-constrained and computation-limited mobile users (MUs) through offloading various computation and service functions to the edge of mobile networks. In addition to MEC, wireless heterogeneous networks will play an important role in providing high transmission capacity for MUs in 5G, where wireless backhaul is a cost-effective and viable solution to solve the expensive backhaul deployment issue. In this paper, we consider a setting, where MUs can offload their computations to the MEC server through a small cell base station (SBS), the SBS connects to the macro BS through a wireless backhaul, and computation resource at the MEC server is shared among offloading MUs. First, we formulate a joint optimization problem with the goal of minimizing the system-wide computation overhead. This is a mixed-integer problem and hard to derive the optimal solution. To solve this problem, we propose to decompose it into two subproblems, namely the offloading decision subproblem and the joint backhaul bandwidth and computation resource allocation subproblem. An algorithm, namely JOBCA, is proposed to obtain a feasible solution to the original problem by solving two subproblems iteratively. Finally, numerical results are conducted to verify the performance improvement of the proposed algorithm over two baseline algorithms and the close performance of the proposed algorithm compared with the centralized exhaustive search. INDEX TERMS Computation offloading, heterogeneous networks, mobile edge computing, resource allocation, wireless backhaul.

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Section: B Wireless Backhaulmentioning

confidence: 99%

Mobile Edge Computing With Wireless Backhaul: Joint Task Offloading and Resource Allocation

Pham

Chung

et al. 2019

IEEE Access

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“…Lack of governance participation in technology adoption must be overcome (technical, procedural, legal and cultural challenges, especially in emerging markets). Different initiatives worldwide are addressing the need for specifying a stable IP-based next generation emergency communications framework, [21], [22]. Emergency communication is based on legacy telecommunication services.…”

Section: B Importance Of Regulation Framework In Digital Societymentioning

confidence: 99%

Towards Digital Transformation with 5G Technology

Banovic-Curguz¹,

Ilisevic²,

Budimir³

2019

IJEEC

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This paper presents a short review of recent research activities on 5G as the next generation of wireless technology, the requirements they are facing, user scenarios, functionalities, and KPIs (Key Performance Indicators) as a measure of assessing the performances of these systems. 5G technology also known as International Mobile Telecommunications 2020, (IMT-2020) will dramatically increase the capabilities of the Internet of Things, Vehicle-to-everything and will pave the way for massive machine-type communications. While it is not yet define how the ultimate 5G design will be, it is possible to identify the most important services, functionality and KPIs that will provide satisfactory solutions to innovative digital business models after 2020. It is expected that 5G standards be in focus of Regulation Agencies, mainly through socio-economic analysis. In emerging markets, socio-economic dimensions of wireless connectivity must be considered carefully since data will be basic asset in digital age. This paper also highlights the importance of changes in mindset of regulation framework in telecommunications sector. Strong understanding of digital transformation is crucial in order to stay competitive in dynamic changes in the future.

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“…Markakis et. al developed a multiaccess edge computing based IoT framework for supporting next-generation emergency services, and provided several use cases of remote healthcare monitoring and management [10]. Omoniwa et.…”

Section: Introductionmentioning

confidence: 99%

Learning-Based Context-Aware Resource Allocation for Edge-Computing-Empowered Industrial IoT

Liao

Zhou

Zhao

et al. 2020

IEEE Internet Things J.

239

104

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Edge computing provides a promising paradigm to support the implementation of industrial Internet of Things (IIoT) by offloading computational-intensive tasks from resourcelimited machine-type devices (MTDs) to powerful edge servers. However, the performance gain of edge computing may be severely compromised due to limited spectrum resources, capacity-constrained batteries, and context unawareness. In this paper, we consider the optimization of channel selection which is critical for efficient and reliable task delivery. We aim at maximizing the long-term throughput subject to longterm constraints of energy budget and service reliability. We propose a learning-based channel selection framework with service reliability awareness, energy awareness, backlog awareness, and conflict awareness, by leveraging the combined power of machine learning, Lyapunov optimization, and matching theory. We provide rigorous theoretical analysis, and prove that the proposed framework can achieve guaranteed performance with a bounded deviation from the optimal performance with global state information (GSI) based on only local and causal information. Finally, simulations are conducted under both single-MTD and multi-MTD scenarios to verify the effectiveness and reliability of the proposed framework.

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Efficient Next Generation Emergency Communications over Multi-Access Edge Computing

Cited by 51 publications

References 9 publications

Mobile Edge Computing With Wireless Backhaul: Joint Task Offloading and Resource Allocation

Mobile Edge Computing With Wireless Backhaul: Joint Task Offloading and Resource Allocation

Towards Digital Transformation with 5G Technology

Learning-Based Context-Aware Resource Allocation for Edge-Computing-Empowered Industrial IoT

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