4,335 research outputs found
Auction-based Bandwidth Allocation Mechanisms for Wireless Future Internet
An important aspect of the Future Internet is the efficient utilization of
(wireless) network resources. In order for the - demanding in terms of QoS -
Future Internet services to be provided, the current trend is evolving towards
an "integrated" wireless network access model that enables users to enjoy
mobility, seamless access and high quality of service in an all-IP network on
an "Anytime, Anywhere" basis. The term "integrated" is used to denote that the
Future Internet wireless "last mile" is expected to comprise multiple
heterogeneous geographically coexisting wireless networks, each having
different capacity and coverage radius. The efficient management of the
wireless access network resources is crucial due to their scarcity that renders
wireless access a potential bottleneck for the provision of high quality
services. In this paper we propose an auction mechanism for allocating the
bandwidth of such a network so that efficiency is attained, i.e. social welfare
is maximized. In particular, we propose an incentive-compatible, efficient
auction-based mechanism of low computational complexity. We define a repeated
game to address user utilities and incentives issues. Subsequently, we extend
this mechanism so that it can also accommodate multicast sessions. We also
analyze the computational complexity and message overhead of the proposed
mechanism. We then show how user bids can be replaced from weights generated by
the network and transform the auction to a cooperative mechanism capable of
prioritizing certain classes of services and emulating DiffServ and time-of-day
pricing schemes. The theoretical analysis is complemented by simulations that
assess the proposed mechanisms properties and performance. We finally provide
some concluding remarks and directions for future research
Green Cellular Networks: A Survey, Some Research Issues and Challenges
Energy efficiency in cellular networks is a growing concern for cellular
operators to not only maintain profitability, but also to reduce the overall
environment effects. This emerging trend of achieving energy efficiency in
cellular networks is motivating the standardization authorities and network
operators to continuously explore future technologies in order to bring
improvements in the entire network infrastructure. In this article, we present
a brief survey of methods to improve the power efficiency of cellular networks,
explore some research issues and challenges and suggest some techniques to
enable an energy efficient or "green" cellular network. Since base stations
consume a maximum portion of the total energy used in a cellular system, we
will first provide a comprehensive survey on techniques to obtain energy
savings in base stations. Next, we discuss how heterogeneous network deployment
based on micro, pico and femto-cells can be used to achieve this goal. Since
cognitive radio and cooperative relaying are undisputed future technologies in
this regard, we propose a research vision to make these technologies more
energy efficient. Lastly, we explore some broader perspectives in realizing a
"green" cellular network technologyComment: 16 pages, 5 figures, 2 table
Economics of intelligent selection of wireless access networks in a market-based framework : a game-theoretic approach
The Digital Marketplace is a market-based framework where network operators offer communications services with competition at the call level. It strives to address a tussle between the actors involved in a heterogeneous wireless access network. However, as with any market-like institution, it is vital to analyze the Digital Marketplace from the strategic perspective to ensure that all shortcomings are removed prior to implementation. In this paper, we analyze the selling mechanism proposed in the Digital Marketplace. The mechanism is based on a procurement first-price sealed-bid auction where the network operators represent the sellers/bidders, and the end-user of a wireless service is the buyer. However, this auction format is somewhat unusual as the winning bid is a composition of both the network operator’s monetary bid and their reputation rating. We create a simple economic model of the auction, and we show that it is mathematically intractable to derive the equilibrium bidding behavior when there are N network operators, and we make only generic assumptions about the structure of the bidding strategies. We then move on to consider a scenario with only two network operators, and assume that network operators use bidding strategies which are linear functions of their costs. This results in the derivation of the equilibrium bidding behavior in that scenario
A Comprehensive Survey of Potential Game Approaches to Wireless Networks
Potential games form a class of non-cooperative games where unilateral
improvement dynamics are guaranteed to converge in many practical cases. The
potential game approach has been applied to a wide range of wireless network
problems, particularly to a variety of channel assignment problems. In this
paper, the properties of potential games are introduced, and games in wireless
networks that have been proven to be potential games are comprehensively
discussed.Comment: 44 pages, 6 figures, to appear in IEICE Transactions on
Communications, vol. E98-B, no. 9, Sept. 201
Fair task allocation in transportation
Task allocation problems have traditionally focused on cost optimization.
However, more and more attention is being given to cases in which cost should
not always be the sole or major consideration. In this paper we study a fair
task allocation problem in transportation where an optimal allocation not only
has low cost but more importantly, it distributes tasks as even as possible
among heterogeneous participants who have different capacities and costs to
execute tasks. To tackle this fair minimum cost allocation problem we analyze
and solve it in two parts using two novel polynomial-time algorithms. We show
that despite the new fairness criterion, the proposed algorithms can solve the
fair minimum cost allocation problem optimally in polynomial time. In addition,
we conduct an extensive set of experiments to investigate the trade-off between
cost minimization and fairness. Our experimental results demonstrate the
benefit of factoring fairness into task allocation. Among the majority of test
instances, fairness comes with a very small price in terms of cost
Game theory for collaboration in future networks
Cooperative strategies have the great potential of improving network performance and spectrum utilization in future networking environments. This new paradigm in terms of network management, however, requires a novel design and analysis framework targeting a highly flexible networking solution with a distributed architecture. Game Theory is very suitable for this task, since it is a comprehensive mathematical tool for modeling the highly complex interactions among distributed and intelligent decision makers. In this way, the more convenient management policies for the diverse players (e.g. content providers, cloud providers, home providers, brokers, network providers or users) should be found to optimize the performance of the overall network infrastructure. The authors discuss in this chapter several Game Theory models/concepts that are highly relevant for enabling collaboration among the diverse players, using different ways to incentivize it, namely through pricing or reputation. In addition, the authors highlight several related open problems, such as the lack of proper models for dynamic and incomplete information games in this area.info:eu-repo/semantics/acceptedVersio
Energy-Aware Competitive Power Allocation for Heterogeneous Networks Under QoS Constraints
This work proposes a distributed power allocation scheme for maximizing
energy efficiency in the uplink of orthogonal frequency-division multiple
access (OFDMA)-based heterogeneous networks (HetNets). The user equipment (UEs)
in the network are modeled as rational agents that engage in a non-cooperative
game where each UE allocates its available transmit power over the set of
assigned subcarriers so as to maximize its individual utility (defined as the
user's throughput per Watt of transmit power) subject to minimum-rate
constraints. In this framework, the relevant solution concept is that of Debreu
equilibrium, a generalization of Nash equilibrium which accounts for the case
where an agent's set of possible actions depends on the actions of its
opponents. Since the problem at hand might not be feasible, Debreu equilibria
do not always exist. However, using techniques from fractional programming, we
provide a characterization of equilibrial power allocation profiles when they
do exist. In particular, Debreu equilibria are found to be the fixed points of
a water-filling best response operator whose water level is a function of
minimum rate constraints and circuit power. Moreover, we also describe a set of
sufficient conditions for the existence and uniqueness of Debreu equilibria
exploiting the contraction properties of the best response operator. This
analysis provides the necessary tools to derive a power allocation scheme that
steers the network to equilibrium in an iterative and distributed manner
without the need for any centralized processing. Numerical simulations are then
used to validate the analysis and assess the performance of the proposed
algorithm as a function of the system parameters.Comment: 37 pages, 12 figures, to appear IEEE Trans. Wireless Commu
Spectrum Coordination in Energy Efficient Cognitive Radio Networks
Device coordination in open spectrum systems is a challenging problem,
particularly since users experience varying spectrum availability over time and
location. In this paper, we propose a game theoretical approach that allows
cognitive radio pairs, namely the primary user (PU) and the secondary user
(SU), to update their transmission powers and frequencies simultaneously.
Specifically, we address a Stackelberg game model in which individual users
attempt to hierarchically access to the wireless spectrum while maximizing
their energy efficiency. A thorough analysis of the existence, uniqueness and
characterization of the Stackelberg equilibrium is conducted. In particular, we
show that a spectrum coordination naturally occurs when both actors in the
system decide sequentially about their powers and their transmitting carriers.
As a result, spectrum sensing in such a situation turns out to be a simple
detection of the presence/absence of a transmission on each sub-band. We also
show that when users experience very different channel gains on their two
carriers, they may choose to transmit on the same carrier at the Stackelberg
equilibrium as this contributes enough energy efficiency to outweigh the
interference degradation caused by the mutual transmission. Then, we provide an
algorithmic analysis on how the PU and the SU can reach such a spectrum
coordination using an appropriate learning process. We validate our results
through extensive simulations and compare the proposed algorithm to some
typical scenarios including the non-cooperative case and the
throughput-based-utility systems. Typically, it is shown that the proposed
Stackelberg decision approach optimizes the energy efficiency while still
maximizing the throughput at the equilibrium.Comment: 12 pages, 10 figures, to appear in IEEE Transactions on Vehicular
Technolog
Game theory for cooperation in multi-access edge computing
Cooperative strategies amongst network players can improve network performance and spectrum utilization in future networking environments. Game Theory is very suitable for these emerging scenarios, since it models high-complex interactions among distributed decision makers. It also finds the more convenient management policies for the diverse players (e.g., content providers, cloud providers, edge providers, brokers, network providers, or users). These management policies optimize the performance of the overall network infrastructure with a fair utilization of their resources. This chapter discusses relevant theoretical models that enable cooperation amongst the players in distinct ways through, namely, pricing or reputation. In addition, the authors highlight open problems, such as the lack of proper models for dynamic and incomplete information scenarios. These upcoming scenarios are associated to computing and storage at the network edge, as well as, the deployment of large-scale IoT systems. The chapter finalizes by discussing a business model for future networks.info:eu-repo/semantics/acceptedVersio
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