2,479 research outputs found
Energy-Efficient Resource Allocation in Wireless Networks with Quality-of-Service Constraints
A game-theoretic model is proposed to study the cross-layer problem of joint
power and rate control with quality of service (QoS) constraints in
multiple-access networks. In the proposed game, each user seeks to choose its
transmit power and rate in a distributed manner in order to maximize its own
utility while satisfying its QoS requirements. The user's QoS constraints are
specified in terms of the average source rate and an upper bound on the average
delay where the delay includes both transmission and queuing delays. The
utility function considered here measures energy efficiency and is particularly
suitable for wireless networks with energy constraints. The Nash equilibrium
solution for the proposed non-cooperative game is derived and a closed-form
expression for the utility achieved at equilibrium is obtained. It is shown
that the QoS requirements of a user translate into a "size" for the user which
is an indication of the amount of network resources consumed by the user. Using
this competitive multiuser framework, the tradeoffs among throughput, delay,
network capacity and energy efficiency are studied. In addition, analytical
expressions are given for users' delay profiles and the delay performance of
the users at Nash equilibrium is quantified.Comment: Accpeted for publication in the IEEE Transactions on Communication
Design and Implementation of Distributed Resource Management for Time Sensitive Applications
In this paper, we address distributed convergence to fair allocations of CPU
resources for time-sensitive applications. We propose a novel resource
management framework where a centralized objective for fair allocations is
decomposed into a pair of performance-driven recursive processes for updating:
(a) the allocation of computing bandwidth to the applications (resource
adaptation), executed by the resource manager, and (b) the service level of
each application (service-level adaptation), executed by each application
independently. We provide conditions under which the distributed recursive
scheme exhibits convergence to solutions of the centralized objective (i.e.,
fair allocations). Contrary to prior work on centralized optimization schemes,
the proposed framework exhibits adaptivity and robustness to changes both in
the number and nature of applications, while it assumes minimum information
available to both applications and the resource manager. We finally validate
our framework with simulations using the TrueTime toolbox in MATLAB/Simulink
Trade & Cap: A Customer-Managed, Market-Based System for Trading Bandwidth Allowances at a Shared Link
We propose Trade & Cap (T&C), an economics-inspired mechanism that incentivizes users to voluntarily coordinate their consumption of the bandwidth of a shared resource (e.g., a DSLAM link) so as to converge on what they perceive to be an equitable allocation, while ensuring efficient resource utilization. Under T&C, rather than acting as an arbiter, an Internet Service Provider (ISP) acts as an enforcer of what the community of rational users sharing the resource decides is a fair allocation of that resource. Our T&C mechanism proceeds in two phases. In the first, software agents acting on behalf of users engage in a strategic trading game in which each user agent selfishly chooses bandwidth slots to reserve in support of primary, interactive network usage activities. In the second phase, each user is allowed to acquire additional bandwidth slots in support of presumed open-ended need for fluid bandwidth, catering to secondary applications. The acquisition of this fluid bandwidth is subject to the remaining "buying power" of each user and by prevalent "market prices" â both of which are determined by the results of the trading phase and a desirable aggregate cap on link utilization. We present analytical results that establish the underpinnings of our T&C mechanism, including game-theoretic results pertaining to the trading phase, and pricing of fluid bandwidth allocation pertaining to the capping phase. Using real network traces, we present extensive experimental results that demonstrate the benefits of our scheme, which we also show to be practical by highlighting the salient features of an efficient implementation architecture.National Science Foundation (CCF-0820138, CSR-0720604, EFRI-0735974, CNS-0524477, and CNS-0520166); Universidad Pontificia Bolivariana and COLCIENCIASâInstituto Colombiano para el Desarrollo de la Ciencia y la TecnologĂa âFrancisco Jose Ì de Caldasâ
Exchange of Services in Networks: Competition, Cooperation, and Fairness
Exchange of services and resources in, or over, networks is attracting
nowadays renewed interest. However, despite the broad applicability and the
extensive study of such models, e.g., in the context of P2P networks, many
fundamental questions regarding their properties and efficiency remain
unanswered. We consider such a service exchange model and analyze the users'
interactions under three different approaches. First, we study a centrally
designed service allocation policy that yields the fair total service each user
should receive based on the service it others to the others. Accordingly, we
consider a competitive market where each user determines selfishly its
allocation policy so as to maximize the service it receives in return, and a
coalitional game model where users are allowed to coordinate their policies. We
prove that there is a unique equilibrium exchange allocation for both game
theoretic formulations, which also coincides with the central fair service
allocation. Furthermore, we characterize its properties in terms of the
coalitions that emerge and the equilibrium allocations, and analyze its
dependency on the underlying network graph. That servicing policy is the
natural reference point to the various mechanisms that are currently proposed
to incentivize user participation and improve the efficiency of such networked
service (or, resource) exchange markets.Comment: to appear in ACM Sigmetrics 201
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