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Motivated by this development, this paper addresses the dynamic resource allocation in a multi‑slice multi‑tier multi‑domain network with dif‑ ferent network players. (...) We propose two schemes: a multi‑tier multi‑domain slice user matching game scheme and a distributed backtracking multiplayer multi‑domain game scheme in solving the transformed maximum utility optimisation problem. (...) In Fig. 1(a)‑(c), we illustrate ators (BOs), and Vehicular‑Content Providers (VCPs) have the traditional, single, and multi‑domains multi‑tenant become critical industry players.
Language:English
Score: 2154624.6 - https://www.itu.int/en/publica...6/files/basic-html/page69.html
Data Source: un
S5.2 Assessment of spatial intervention of public spaces by locative augmented reality games players Fadzidah Abdullah and Mohd Faredzuan Mohd Noor (International Islamic University Malaysia, Malaysia); Mohd Raziff Abdul Razak (British Malaysian Institute, University Kuala Lumpur, Malaysia) Augmented Reality (AR) games appear to have had a massive growth in the era of the Fourth Industrial Revolution (IR 4.0). (...) Nevertheless, there is a question of whether public spaces are suitable for the spatial intervention of locative AR games players. Spatial intervention may become an issue among the public regarding accessibility, permeability, openness, centrality, and sense of security. This paper assesses the public perceptions of the spatial intervention of public spaces by locative AR games players. Researchers conducted this research by using both qualitative and quantitative approaches.
Language:English
Score: 2122574.8 - https://www.itu.int/en/publica.../files/basic-html/page219.html
Data Source: un
Motivated by this development, this paper addresses the dynamic resource allocation in a multi-slice multi-tier multi-domain network with different network players. (...) We propose two schemes: a multi-tier multi-domain slice user matching game scheme and a distributed backtracking multiplayer multi-domain game scheme in solving the transformed maximum utility optimisation problem. We compare the multi-tier multi-tenant multi-domain game scheme with a Genetic Algorithm (GA) Intelligent Latency-Aware Resource (GI-LARE) allocation scheme, and a static slicing resource allocation scheme via Monte Carlo simulation.
Language:English
Score: 2090528.5 - https://www.itu.int/pub/S-JNL-VOL2.ISSUE6-2021-A04
Data Source: un
Motivated by this development, this paper addresses the dynamic resource allocation in a multi‑slice multi‑tier multi‑domain network with different network players. (...) We propose two schemes: a multi‑tier multi‑domain slice user matching game scheme and a distributed backtracking multiplayer multi‑domain game scheme in solving the transformed maximum utility optimisation problem. We compare the multi‑tier multi‑tenant multi‑domain game scheme with a Genetic Algorithm (GA) Intelligent Latency‑Aware Resource (GI‑LARE) allocation scheme, and a static slicing resource allocation scheme via Monte Carlo simulation.
Language:English
Score: 2076019.1 - https://www.itu.int/en/publica...6/files/basic-html/page10.html
Data Source: un
 Page 88 - ITU Journal Future and evolving technologies Volume 2 (2021), Issue 6 – Wireless communication systems in beyond 5G era           Basic HTML Version Table of Contents View Full Version Page 88 - ITU Journal Future and evolving technologies Volume 2 (2021), Issue 6 – Wireless communication systems in beyond 5G era P. 88 ITU Journal on Future and Evolving Technologies, Volume 2 (2021), Issue 6 Table 4 – B2B transactions of the respective network players in a 2‑domain deployment. Band. (MHz) 100MHz Scenario 200MHz Scenario 300MHz Scenario 400MHz Scenario Domain InP 1 InP 2 InP 1 InP 2 InP 1 InP 2 InP 1 InP 2 MVNO1 bid 437.1377 416.7932 492.0228 435.2518 461.5252 458.9901 494.4473 402.9160 MVNO2 bid 435.8644 414.8111 451.9532 401.4996 411.4039 409.5608 439.6148 355.7059 MVNO1 Res. (...) In this paper, we have addressed the resource allocation problem in an M‑TTSD network. We have proposed a multi‑tier multi‑domain slice user matching game and also a distributed backtracking multiplayer multi‑ domain game scheme to facilitate a business‑to‑business resource transaction framework and to ensure maximum network utility. (...) The slice users were associated with access points in the respective tiers of the different domains by the concept of the multi‑tier multi‑domain matching game, and then network players bid for resources from higher hierarchical players via the concept of distributed multiplayer backtracking. 76 © International Telecommunication Union, 2021     83     84     85     86     87     88     89     90     91     92     93          
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Score: 2018408.4 - https://www.itu.int/en/publica...6/files/basic-html/page88.html
Data Source: un
The role of video games Games have long been a way to evaluate the advancement of Artificial Intelligence (AI), showing just how “intelligent” computer algorithms are by pitting them against top human players in contests of strategy. (...) In 2016, Google’s AlphaGo algorithm beat one of the best players of the Chinese board game Go. Earlier this month, OpenAI’s algorithm bested a team of human players in the multi-player online battle game  Dota 2 . (...) A core idea of game design – and part of the reason many enjoy playing – is that players are learning all the time, he says.
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Score: 1854841 - https://www.itu.int/hub/2020/0...nce-deliver-real-world-impact/
Data Source: un
In based resource allocation for a multi‑slice multi‑tenant Section 3, we focus on the system model. (...) The proposed Markov‑based algorithm was presents the multi‑domain multi‑tenant auction games able to characterise and model the stochastic behaviour framework. (...) A Tchebycheff technique game‑based schemes were proposed for resource alloca‑ was employed in solving the Multi‑Objective resource al‑ tion between an InP (seller) and MVNOs (buyers). location Optimisation Problem (MOOP).
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Score: 1830464.3 - https://www.itu.int/en/publica...6/files/basic-html/page71.html
Data Source: un
Moreover, we discuss the computational complexity of distributed re‑ ∈ cursive backtracking for multiplayer multi‑domain game Assume that from the values obtained in , the number algorithms, and lastly, the M‑TTSD resource allocation. occurs times, the number occurs times, the 2 1 1 2 number occurs times, and so on. (...) With beingalargenumber, thefrequency ofthevalue approaches its probability such that: 8.2 Computational complexity of the dis‑ ≈ . (47) tributed recursive backtracking multiplayer multi‑domain Hence, substituting (47) into (44), we have The complexity of the distributed recursive backtrack‑ ing multiplayer multi‑domain game algorithm is given by 1 ( ) = = (48) (|ℐ| ⋅ (| | + | |)). (...) Where 3: Simulate the multi‑tenant multi‑tier multi‑domain denotes the number of tiers in a domain network.
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Score: 1819958.6 - https://www.itu.int/en/publica...6/files/basic-html/page83.html
Data Source: un
SP k URLLC USERS URLLC USERS URLLC USERS URLLC USERS URLLC USERS URLLC USERS URLLC USERS eMBB USERS eMBB USERS eMBB USERS eMBB USERS eMBB USERS eMBB USERS eMBB USERS mMTC USERS mMTC USERS mMTC USERS mMTC USERS mMTC USERS mMTC USERS mMTC USERS (a) Traditional Multi‑Tenancy (b) Single‑Domain Multi‑Tenant NS (c) Multi‑Domain Multi‑Tenant NS Fig. 1 – Illustration of the domain type of network slicing. lexibility of the network architecture. (...) Other than the traditional two‑player network ap‑ age extension, scalability, and network resource optimi‑ proach, we consider a multi‑tenant multi‑domain sation. network with entities comprising InPs, MVNOs, and Ef icient resource management is pivotal to the opti‑ SPs, respectively. To this end, a three‑stage multi‑ mal operation of the M‑TTSD network [5, 6].
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Score: 1811285 - https://www.itu.int/en/publica...6/files/basic-html/page70.html
Data Source: un
Games and gaming have evolved from dedicated, single-game units to massively multiplayer online role-player games with millions of players. (...) Quite surpris- ingly, women players now outnumber men in some age ranges by a considerable margin.1 Game development studios give away their applications free-to-play in the hope the player buys virtual goods in the game, upgrades or game extensions. (...) isn=6964 ITU-T Technology Watch > Trends in Video Games and Gaming (September 2011) 7 A huge number of active players, high level of game detail and the sophisticated interaction features (e.g. multi-user voice chat) can pose a challenge to servers and networks.
Language:English
Score: 1798618 - https://www.itu.int/dms_pub/it.../23/01/T23010000140002PDFE.pdf
Data Source: un