Get Social Group Utility Maximization PDF

By Xiaowen Gong, Xu Chen, Lei Yang, Junshan Zhang

ISBN-10: 3319123211

ISBN-13: 9783319123219

ISBN-10: 331912322X

ISBN-13: 9783319123226

This SpringerBrief explains the best way to leverage cellular clients' social relationships to enhance the interactions of cellular units in cellular networks. It develops a social team application maximization (SGUM) framework that captures assorted social ties of cellular clients and numerous actual coupling of cellular units. Key themes comprise random entry keep an eye on, strength regulate, spectrum entry, and placement privateness. This short additionally investigates SGUM-based energy regulate video game and random entry keep an eye on video game, for which it establishes the socially-aware Nash equilibrium (SNE). It then examines the serious SGUM-based spectrum entry video game, and pseudonym switch online game for custom-made place privateness. The authors suggest destiny paintings on extending the SGUM framework to adverse social ties, to illustrate relevance to protection functions and span the continuum among zero-sum video game (ZSG) and non-cooperative online game (NCG). Social crew software Maximization goals researchers and pros engaged on cellular networks and social networks. Advanced-level scholars in electric engineering and laptop technological know-how also will locate this fabric necessary for his or her comparable courses.

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Tan, Pricing-based decentralized spectrum access control in cognitive radio networks. IEEE/ACM Trans. Netw. 21(2), 522–535, (2013) 3. X. Chen, J. Huang, Database-assisted distributed spectrum sharing. IEEE J. Sel. Areas Commun. 31(11), 2349–2361, (2013) 4. N. M. C. M. Buddhikot, Interferenceaware channel assignment in multi-radio wireless mesh networks. INFOCOM 6, 1–12 (2006) 5. D. S. Shapley, Potential games. Games Econ. Behav. 14(1), 124–143, (1996) 6. M. C. Liew, Z. Shao, C. Kai, Markov approximation for combinatorial network optimization.

That is, when θ → ∞, the optimal solutions that maximize the potential function Φ(a) will be selected with probability one. 8) enables us to obtain the close-form solution, which facilitates the distributed algorithm design later. 8) is given as qa∗ = exp (θ Φ(a)) . 9), we then design a self-organizing algorithm such that the asynchronous channel selection updates of the users form a Markov chain (with the system state as the channel selection profile a of all users). 9), we can approach the Nash equilibrium channel selection profile that maximizes the potential function by setting a large enough parameter θ .

1 The social welfare of the Pareto-optimal SNE for SA-PCG is no less than that of the best SNE for SO-PCG. 1 guarantees that the social welfare of the Pareto-optimal SNE is no less than the benchmark SNE for SO-PCG. In Sect. 6, numerical results will demonstrate that the Pareto-optimal SNE is efficient, with a performance gain up to 20 % over the benchmark. 2 5 SGUM-based Pseudonym Change for Personalized Location Privacy Distributed Computation of Pareto-optimal SNE The Pareto-optimal SNE computed by Algorithm 2 can be achieved in a distributed manner.

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Social Group Utility Maximization by Xiaowen Gong, Xu Chen, Lei Yang, Junshan Zhang


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