66,847 research outputs found
Application-Oriented Flow Control: Fundamentals, Algorithms and Fairness
This paper is concerned with flow control and resource allocation problems in computer networks in which real-time applications may have hard quality of service (QoS) requirements. Recent optimal flow control approaches are unable to deal with these problems since QoS utility functions generally do not satisfy the strict concavity condition in real-time applications. For elastic traffic, we show that bandwidth allocations using the existing optimal flow control strategy can be quite unfair. If we consider different QoS requirements among network users, it may be undesirable to allocate bandwidth simply according to the traditional max-min fairness or proportional fairness. Instead, a network should have the ability to allocate bandwidth resources to various users, addressing their real utility requirements. For these reasons, this paper proposes a new distributed flow control algorithm for multiservice networks, where the application's utility is only assumed to be continuously increasing over the available bandwidth. In this, we show that the algorithm converges, and that at convergence, the utility achieved by each application is well balanced in a proportionally (or max-min) fair manner
Power allocation in wireless multi-user relay networks
In this paper, we consider an amplify-and-forward wireless relay system where multiple source nodes communicate with their corresponding destination nodes with the help of relay nodes. Conventionally, each relay equally distributes the available resources to its relayed sources. This approach is clearly sub-optimal since each user experiences dissimilar channel conditions, and thus, demands different amount of allocated resources to meet its quality-of-service (QoS) request. Therefore, this paper presents novel power allocation schemes to i) maximize the minimum signal-to-noise ratio among all users; ii) minimize the maximum transmit power over all sources; iii) maximize the network throughput. Moreover, due to limited power, it may be impossible to satisfy the QoS requirement for every user. Consequently, an admission control algorithm should first be carried out to maximize the number of users possibly served. Then, optimal power allocation is performed. Although the joint optimal admission control and power allocation problem is combinatorially hard, we develop an effective heuristic algorithm with significantly reduced complexity. Even though theoretically sub-optimal, it performs remarkably well. The proposed power allocation problems are formulated using geometric programming (GP), a well-studied class of nonlinear and nonconvex optimization. Since a GP problem is readily transformed into an equivalent convex optimization problem, optimal solution can be obtained efficiently. Numerical results demonstrate the effectiveness of our proposed approach
A Utility Proportional Fairness Radio Resource Block Allocation in Cellular Networks
This paper presents a radio resource block allocation optimization problem
for cellular communications systems with users running delay-tolerant and
real-time applications, generating elastic and inelastic traffic on the network
and being modelled as logarithmic and sigmoidal utilities respectively. The
optimization is cast under a utility proportional fairness framework aiming at
maximizing the cellular systems utility whilst allocating users the resource
blocks with an eye on application quality of service requirements and on the
procedural temporal and computational efficiency. Ultimately, the sensitivity
of the proposed modus operandi to the resource variations is investigated
Allocation of Heterogeneous Resources of an IoT Device to Flexible Services
Internet of Things (IoT) devices can be equipped with multiple heterogeneous
network interfaces. An overwhelmingly large amount of services may demand some
or all of these interfaces' available resources. Herein, we present a precise
mathematical formulation of assigning services to interfaces with heterogeneous
resources in one or more rounds. For reasonable instance sizes, the presented
formulation produces optimal solutions for this computationally hard problem.
We prove the NP-Completeness of the problem and develop two algorithms to
approximate the optimal solution for big instance sizes. The first algorithm
allocates the most demanding service requirements first, considering the
average cost of interfaces resources. The second one calculates the demanding
resource shares and allocates the most demanding of them first by choosing
randomly among equally demanding shares. Finally, we provide simulation results
giving insight into services splitting over different interfaces for both
cases.Comment: IEEE Internet of Things Journa
A Game-Theoretic Approach to Energy-Efficient Resource Allocation in Device-to-Device Underlay Communications
Despite the numerous benefits brought by Device-to-Device (D2D)
communications, the introduction of D2D into cellular networks poses many new
challenges in the resource allocation design due to the co-channel interference
caused by spectrum reuse and limited battery life of User Equipments (UEs).
Most of the previous studies mainly focus on how to maximize the Spectral
Efficiency (SE) and ignore the energy consumption of UEs. In this paper, we
study how to maximize each UE's Energy Efficiency (EE) in an
interference-limited environment subject to its specific Quality of Service
(QoS) and maximum transmission power constraints. We model the resource
allocation problem as a noncooperative game, in which each player is
self-interested and wants to maximize its own EE. A distributed
interference-aware energy-efficient resource allocation algorithm is proposed
by exploiting the properties of the nonlinear fractional programming. We prove
that the optimum solution obtained by the proposed algorithm is the Nash
equilibrium of the noncooperative game. We also analyze the tradeoff between EE
and SE and derive closed-form expressions for EE and SE gaps.Comment: submitted to IET Communications. arXiv admin note: substantial text
overlap with arXiv:1405.1963, arXiv:1407.155
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