In this paper, we study utility-based maximization for resource allocation in the downlink direction of centralized wireless networks We consider two types of traffic, ie, best effort and hard QoS, and develop some essential theorems for optimal wireless resource allocation We then propose three allocation schemes The performance of the proposed schemes is evaluated via simulations The results show that optimal wireless resource allocation is dependent on traffic types, total available resource, and channel quality, rather than solely dependent on the channel quality or traffic types as assumed in most existing work

Utility-based resource allocation in wireless networks

In this paper, we study utility-based resource allocation for soft QoS traffic in infrastructure-based wireless networks. Soft QoS traffic here refers to the traffic which demands certain amount of bandwidth for normal operation but allows some flexibility when the given bandwidth is close to the preferred value. The resource requirement of soft QoS traffic can be described with sigmoid utility function. Our objective is to maximize the total utility of all soft QoS flows without going through a wireless bidding process. We develop essential theorems as the design guidelines for this problem, and then propose a sub-optimal, polynomial time solution based on the developed theorems. We prove that the difference in the performance of our mechanism and the optimal solution is bounded. The performance of the proposed solution is evaluated via simulations. The results show that our solution can adapt to any types of soft QoS flows. Specifically, it acts like a hard QoS system and allocates resource in a fairness-oriented manner when the utility functions of flows are unit-step functions; on the other hand, when the utility functions are concave, it behaves like a best effort system and allocates resource in a throughput-oriented way.

Utility-based radio resource allocation for QoS traffic in wireless networks

This paper studies the problem of utility maximization for clients with delay based QoS requirements in wireless networks. We adopt a model used in a previous work that characterizes the QoS requirements of clients by their delay constraints, channel reliabilities, and delivery ratio requirements. In this work, we assume that the utility of a client is a function of the delivery ratio it obtains. We treat the delivery ratio for a client as a tunable parameter by the access point (AP), instead of a given value as in the previous work. We then study how the AP should assign delivery ratios to clients so that the total utility of all clients is maximized. 
We apply the techniques introduced in two previous papers to decompose the utility maximization problem into two simpler problems, a CLIENT problem and an ACCESS-POINT problem. We show that this decomposition actually describes a bidding game, where clients bid for the service time from the AP. We prove that although all clients behave selfishly in this game, the resulting equilibrium point of the game maximizes the total utility. In addition, we also establish an efficient scheduling policy for the AP to reach the optimal point of the ACCESS-POINT problem. We prove that the policy not only approaches the optimal point but also achieves some forms of fairness among clients. Finally, simulation results show that our proposed policy does achieve higher utility than all other compared policies.

Utility Maximization for Delay Constrained QoS in Wireless

This paper studies the problem of utility maximization for clients with delay based QoS requirements in wireless networks. We adopt a model used in a previous work that characterizes the QoS requirements of clients by their delay constraints, channel reliabilities, and timely throughput requirements. In this work, we assume that the utility of a client is a function of the timely throughput it obtains. We treat the timely throughput for a client as a tunable parameter by the access point (AP), instead of a given value as in the previous work. We then study how the AP should assign timely throughputs to clients so that the total utility of all clients is maximized. We apply the techniques introduced in two previous papers to decompose the utility maximization problem into two simpler problems, a $CLIENT$ problem and an $ACCESS$-$POINT$ problem. We show that this decomposition actually describes a bidding game, where clients bid for the service time from the AP. We prove that although all clients behave selfishly in this game, the resulting equilibrium point of the game maximizes the total utility. In addition, we also establish an efficient scheduling policy for the AP to reach the optimal point of the $ACCESS$-$POINT$ problem. We prove that the policy not only approaches the optimal point but also achieves some forms of fairness among clients. Finally, simulation results show that our proposed policy does achieve higher utility than all other compared policies.

http://cesg.tamu.edu/wp-content/uploads/2012/02/PID999274.pdf

Over the past few years, there has been a growing interest for research in wireless adaptive networking and resource management to efficiently handle wireless communications between mobile hosts and base stations. Moreover, in wireless environments, the bandwidth of an ongoing multimedia flow can dynamically be adjusted, so there must be an efficient bandwidth allocation scheme to ensure quality-of-service (QoS) guarantees and high system utilization. In this paper, the attention is focused on the management of mobile services. In particular, two classes of service, i.e., mobility independent predictive (MIP) and mobility dependent predictive (MDP), have been considered, as defined in integrated service packet networks. A utility-based rate adaptation algorithm has been considered, and an admission control has been proposed, taking into account channel conditions, through a slow-fading channel model for wireless LAN 802.11b. The valued algorithm is based on a user utility function, and the admission control can use the prereservation phase among potentially visited cells from MIP hosts while only considering the bandwidth availability on current cells for MDP services. We analyzed the MIP users' mobility along coverage areas to reduce passive resource reservations on cells that users will probably never visit through the knowledge of some mobility parameters. A prediction technique is also proposed. The performances of the wireless system have been evaluated in terms of total bandwidth utilization for MIP services, average user perceived utility, and system outage probability.

http://peppinofazio.com/wp-content/uploads/2014/04/R06-Utility-Based-Predictive-Services-for-Adaptive-Wireless-Networks-with-Mobile-Hosts-TVT.pdf

Utility-Based Predictive Services for Adaptive Wireless Networks With Mobile Hosts

In this paper we propose a general utility-oriented adaptive quality of service (QoS) model for wireless networks and establish a framework for formulating the bandwidth allocation problem for users with time-varying links. For slow link variations, it is inadequate to only employ low-level adaptive mechanisms at the symbol or packet level, such as error correction coding or swapping packet transmission opportunities. To improve bandwidth utilization and satisfy users' QoS requirements, high-level adaptive mechanisms working at larger time scale are needed. We propose an adaptive bandwidth allocation scheme, which is capable of providing QoS guarantees, ensuring long-term fairness, and achieving high bandwidth utilization. A finite-state Markov channel model (FSMC) is used to model wireless links.

/pdf/utility-oriented-adaptive-qos-and-bandwidth-allocation-in-3ntzc91svn.pdf

V.O.K. Li

Papers

Utility-oriented adaptive QoS and bandwidth allocation in wireless networks