Dynamic Backhaul Resource Allocation: An Evolutionary Game Theoretic Approach

Loumiotis, Ioannis; Adamopoulou, Evgenia; Demestichas, Konstantinos; Stamatiadi, T.; Theologou, M.

doi:10.1109/tcomm.2013.122213.13-0405

Cited by 23 publications

(22 citation statements)

References 15 publications

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“…r c k,i denotes the delivery rate of user k served by eRRH i, ∀k ∈ K i , ∀i ∈ K R , for cache-level transmission. In problem (6), constraint (6b) shows that the delivery rate r c k,i is bounded by the achievable data rate R c k,i . Constraint (6c) denotes that the number of delivery data cannot exceed the cached file size S. Constraint (6d) means the maximum transmit power constraint on the beamforming vectors.…”

Section: A Cache-level Transmissionmentioning

confidence: 99%

“…Note that when the delay τ is zero, problem (10) becomes the optimization problem of precoding matrices for traditional cloudbased coordinated joint transmission system under the constraints of the fronthaul capacity, the size of data files, and the maximum transmit power of eRRHs. 5 We assume that the BBU can obtain the values of r c k,i , ∀k ∈ KU, ∀i ∈ KR, according to the cache state information {c f,i } f ∈F ,i∈K R and the transmission scheme adopted by each eRRH, i.e., (6). 6 Note that different from [12]- [15], [24], and [25], the size of transmitted files in cache-level transmission is included in the constraints (10d).…”

Section: B Network-level Transmissionmentioning

confidence: 99%

“…5 We assume that the BBU can obtain the values of r c k,i , ∀k ∈ KU, ∀i ∈ KR, according to the cache state information {c f,i } f ∈F ,i∈K R and the transmission scheme adopted by each eRRH, i.e., (6). 6 Note that different from [12]- [15], [24], and [25], the size of transmitted files in cache-level transmission is included in the constraints (10d). This provides a chance to increase transmit rate of untransmitted files, i.e., improve the system delivery rate.…”

Section: B Network-level Transmissionmentioning

confidence: 99%

“…To design an autonomous optimization, we replace the achievable rate R c k,i in constraints (6b) with an approximated achievable rate R c k,i = log 2 1 + γ c k,i , ∀k ∈ K i , ∀i ∈ K R . Thus, instead of directly addressing problem (6), the problem of beamformer optimization for the cache-level transmission is formulated as a series of parallel decentralized optimization problems given by (18)…”

Section: B Decentralized Optimization For Cache-level Transmissionmentioning

confidence: 99%

See 3 more Smart Citations

Two-Level Transmission Scheme for Cache-Enabled Fog Radio Access Networks

Huang

et al. 2019

IEEE Trans. Commun.

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In this paper, we investigate the downlink transmission for cache-enabled fog radio access networks aiming at maximizing the delivery rate under the constraints of fronthaul capacity, maximum transmit power, and size of files. To reduce the delivery latency and the burden on fronthaul links and make full use of the local cache and baseband signal processing capabilities of enhanced remote radio heads (eRRHs), a two-level transmission scheme including cache-level and network-level transmission is proposed. In cache-level transmission, only requested files cached at the local cache are transmitted to the corresponding users. The duration of cache-level transmission is the delay caused by the transfer between the baseband unit (BBU) and eRRHs as well as the signal processing at the BBU. The remaining requested files are jointly transmitted to the corresponding users at network-level transmission. For cachelevel transmission, a centralized optimization algorithm is firstly presented and then a decentralized optimization algorithm is provided to avoid the exchange of signaling among eRRHs. Meanwhile, another centralized optimization algorithm is presented to tackle the optimization problem for networklevel transmission. All presented algorithms are proved to converge to the Karush-Kuhn-Tucker (KKT) solutions of the problems. Numerical results are provided to validate the effectiveness of the proposed transmission scheme as well as evaluating the system performance. Index TermsS. He is with the

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Section: A Cache-level Transmissionmentioning

confidence: 99%

Section: B Network-level Transmissionmentioning

confidence: 99%

Section: B Network-level Transmissionmentioning

confidence: 99%

Section: B Decentralized Optimization For Cache-level Transmissionmentioning

confidence: 99%

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Two-Level Transmission Scheme for Cache-Enabled Fog Radio Access Networks

Huang

et al. 2019

IEEE Trans. Commun.

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“…The room now notices that one player is a bit taller and faster than the other so it starts putting the objects a bit closer to him, so that he can keep up [18]. The game then adapts the difficulty level and the target according to the achievements of the players so that to keep high the excitement level perceived by the console through the sensing devices [19].…”

Section: Related Workmentioning

confidence: 99%

A design and implementation of a framework for games in IoT

Kim

2017

J Supercomput

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Interconnection of the sensing and actuating devices providing the ability to share information across platform through a unified framework for enabling innovative applications. This is achieved by seamless ubiquitous sensing, data analytics and information representation as the unifying framework. Extending the current internet with interconnected objects and devices and their virtual representation has been a growing trend in recent years. Internet of Things (IoT) services are becoming a popular services. This will be supported challenges in a large of aspects such as smart health, green energy, smart home and personalized applications. So, the IoT plays more and more important issue in lifestyle through entertainment such as Games. As of yet, there has not been much research done on IoT environment games as a service. In this paper, we propose schemes of the design and implantation of IT convergence framework for games as a service of IoT. First of all, we discussed what to consider when design and implementation of IT convergence framework for games through contents using user's mobile devices and various sensors in IoT environment and suggest related techniques. Then, we showed the possibility of games in the IoT environment by creating games and measuring the interactions of users in the IoT environment.

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Distributed MPC Based on Distributed Evolutionary Game for Leaderless Formation Control

Zhou

Huang

et al. 2022

Proceedings of 2021 5th Chinese Conference on Swarm Intelligence and Cooperative Control

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Dynamic Backhaul Resource Allocation: An Evolutionary Game Theoretic Approach

Cited by 23 publications

References 15 publications

Two-Level Transmission Scheme for Cache-Enabled Fog Radio Access Networks

Two-Level Transmission Scheme for Cache-Enabled Fog Radio Access Networks

A design and implementation of a framework for games in IoT

Distributed MPC Based on Distributed Evolutionary Game for Leaderless Formation Control

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