We consider the problem of dynamically apportioning resources among a set of options in a worst-case online framework. The model we investigate is a generalization of the well studied online learning model. In particular, we allow the learner to see as additional information how high the risk of each option is. This assumption is natural in many applications like horse-race betting, where gamblers know odds for all options before placing bets. We apply Vovk's Aggregating Algorithm to this problem and give a tight performance bound. The results support our intuition that it is safe to bet more on low-risk options. Surprisingly, the loss bound of the algorithm does not depend on the values of relatively small risks.

To obtain large capacity, high quality mobile satellite communication systems in the future, we must use a multi-beam that can cope with extremely high levels of frequency reuse. This paper describes a novel resource allocation algorithm for multi-beam satellite communication systems that can dynamically adapt to maximum communication capacity without compromising quality. The algorithm combines two resource allocation schemes that enable it to contend with the ever-changing user distribution and inter-beam interference conditions. The first scheme optimizes the resources amongst beams. To minimize interference, the optimal constraint conditions are clarified when all clusters share and occupy the same bandwidth completely. These constraints are used in the optimization algorithm. The second scheme manages the various required resources and adapts them to the beam gain and interference levels at various user locations within a single beam. We propose a fixed power adaptive modulation scheme to obtain stable communications. This two-layered scheme can satisfactorily allocate multi-beam satellite resources to contend with the increasing communication capacity and still improve the quality.

The explosive growth of wireless network users and the existence of various wireless services have demanded high throughput as well as user's quality-of-service (QoS) guarantees. In accordance with, this paper proposes a novel resource allocation scheme improving both the capability of QoS-provisioning for multiple users and the overall data throughput. Towards this, the modified resource allocation technique combined with the modified largest weighted delay first (M-LWDF) scheme will be exploited upon considering statistical channel behavior as well as real time queuing analysis connected to resource allocation. In order to verify the validity of the proposed resource allocation scheme, the time division multiple access (TDMA) system will be considered as a target application. The simulation results confirm that the proposed scheme gives rise to superior performance in a way of showing results of several performance measures under time-varying wireless fading channel.

A power and spreading gain allocation strategy is considered for effectively providing data services for mobile users with different levels of priorities in a DS-CDMA system supporting real-time and non-real-time services. Specifically, the uplink in the DS-CDMA system is considered subject to a constraint on total power received at the base station caused by non-real-time data services. The constraint is imposed to meet QoS requirements of real-time services. The priority level of a data user is specified by the weighting factor assigned to the data throughput of the user. Our strategy implements a relative prioritization that affords a trade-off between spectral efficiency and strict prioritization.

An effective access control scheme in CDMA networks is proposed to provide multimedia services. The proposed scheme controls the access of multimedia traffic using the delay of data traffic and the transmission rate control of video traffic. Numerical results show that throughput and delay are improved by allowing delay of data traffic under low and medium traffic conditions, and by decreasing the transmission rate of video traffic under heavy traffic conditions.

In this paper, we propose an efficient rate and power allocation scheme for multiuser OFDM systems to minimize the total transmit power under the given QoS requirements. We deduce the optimal solution of transmit power minimization problem and develop a suboptimal algorithm with low complexity based on the theoretical analysis. Because of the avoidance of iterative procedure, it is less complex than the existing schemes. The simulation results show that our proposal outperforms the existing schemes and it is very close to the optimal solution.

We present an efficient method to optimize network resource allocations under nonlinear Quality of Service (QoS) constraints. We first propose a suite of generalized proportional allocation schemes that can be obtained by minimizing the information-theoretic function of relative entropy. We then optimize over the allocation parameters, which are usually design variables an engineer can directly vary, either for a particular user or for the worst-case user, under constraints that lower bound the allocated resources for all other users. Despite the nonlinearity in the objective and constraints, we show this suite of resource allocation optimization can be efficiently solved for global optimality through a convex optimization technique called geometric programming. This general method and its extensions are applicable to a wide array of resource allocation problems, including processor sharing, congestion control, admission control, and wireless network power control.

The resource allocation problem in multi-agent systems is one of the crucial problems hindering the development of multi-agent technologies. This study demonstrates that "time delay" functions as an effective factor in a resource allocation, contrasting to the conventional real-time oriented multi-agent paradigm by 1) introducing a "fickle" agent, whose own strategy fluctuates randomly, and 2) an agent repository mechanism. This study also demonstrates that in the resource allocation process, time delay induces dramatic changes in performance, the specific phenomenon is the so-called "phase transition phenomenon". This finding means emergence of the phase transition is cited as a major factor governing multi-agent system performance. This knowledge is of essential importance in the regulation in multi-agent performance.

This paper presents a distributed task assignment algorithm in a logical unidirectional ring, which guarantees that almost all tasks are assigned to servers with the first come first served (FCFS) policy without a global clock. A task assignment for a process is obtained in the time period needed for a message to circle the ring. This time period is almost optimal for a unidirectional ring. The FCFS policy is very important in terms of task fairness and can also avoid starvation and provide an efficient response time. Simulation results show that the algorithm generally works better than conventional task assignment or load balancing schemes with respect to both mean response time and task fairness.

In wide-area wireless access systems such as satellite communications systems and stratospheric platform systems, electric power supplies for radio communications are realized using solar photovoltaic cells and/or fuel cells. However, the on-board weight limits restrict the number of cells that can be equipped. In addition, the transmission power of such systems is limited taking account of issues and regulations on sharing the same frequency band with other systems. Hence, both the frequency band and electric power is limited, which are crucial radio resources for those systems. Although radio channel allocation methods taking account of the frequency constraint only or the power constraint only have been proposed, radio channel allocation methods taking account of both constraints simultaneously have been insufficiently studied. This paper proposes a radio channel allocation method that provides global optimum allocation results by utilizing the linear programming method. The proposed method has features such that the method first allocates radio channels in proportion to the traffic demand distributed over the service coverage area and then maximizes the total radio channels allocated to systems. Numerical results are presented for a stratospheric platform system that covers an area of Japan, as an example, to demonstrate that the proposed method optimally allocates radio channels taking account of both constraints while efficiently allocating excess resources. In addition, whether a system reaches either the frequency or power limit can be estimated, by investigating the radio channel allocation results. Furthermore, enhanced linear programming models based on a method aiming at practical use of the radio channel allocation results in operation are also introduced. The enhanced model is demonstrated to work effectively to avoid unbalanced radio channel allocations over geographical areas. The proposed method and linear programming models are useful not only for making pre-plans but also for determining the amount of necessary frequency and power resources in designing systems.

In mobile cellular networks it is crucial to be able to use the available radio spectrum as efficiently as possible while providing a certain level of Quality of Service (QoS) for the users. Emergence of miscellaneous services has dramatically increased the complexity of this problem by creating a heterogeneous traffic environment. In this paper an efficient resource allocation scheme between two real-time services with different bandwidth requirements has been proposed for cellular networks with multimedia offered traffic and highly mobile users, which combines classical intera-cell resource borrowing concept with a novel inter-cell resource-sharing scheme between diverse classes of traffic. By assuming the heterogeneous offered traffic to be a combination of audio and video traffic types, through extensive simulations it will be shown that HCBA-UCB is capable of significantly improving audio teletraffic performance of the system while preserving fairness in service provision, i.e. without imposing additional expenses upon video QoS performance.

In this letter, a resource allocation scheme is proposed to efficiently utilize the resource of CDMA systems with respect to the throughput. When we let the throughput be a function of various data rates for multimedia traffics, the scheme is to find the optimum set of data rates for concurrent user groups with which we can achieve the maximum throughput. It is also shown that the optimum data rate set always includes one non-trivial rate while all the others keep the minimum required data rate.

This paper addresses the utility-based radio resource allocation problem in DS-CDMA systems carrying multimedia traffic. The proposed scheme, aiming at achieving optimal resource allocation, considers the joint power and data rate allocation. To avoid high computational complexity of nonlinear optimization, we reformulate the radio resource allocation problem as a market model, where resource is regarded as a commodity. Since the market model satisfies the incentive-compatible constraint, the optimal resource allocation can be obtained at the market equilibrium in a distributed manner. According to whether to allocate a minimal transmission data rate to each user, two algorithms, UCA and FCA, are proposed. UCA emphasize on maximizing system overall utilities, while FCA guarantees fairness to users. Simulation results show that the proposed radio resource allocation scheme and algorithms are flexible and efficient for multimedia DS-CDMA systems.

A power and spreading gain allocation strategy is considered to effectively provide data services for mobile users with different levels of priorities in a DS-CDMA system. The priority level of a user is specified by a factor that is a weighting on the data throughput of the user. Our strategy implements a relative prioritization that affords a trade-off between spectral efficiency and strict prioritization.

Differentiated Services architecture provides a framework that enables relative differentiation of Assured Forwarding (AF) service. The differentiation is quantified by QoS parameters in terms of loss probability and maximum delay. We develop herein an efficient model to compute resource allocation in terms of buffer and service rate that satisfies the QoS differentiation between classes of service. To evaluate the performance of the proposed model, we conducted extensive simulation on both single-node and multi-node cases. The simulation studies show that the model can provide an efficient method to allocate network resources for aggregated traffic.

In this paper, we analyzed the performance of dynamic resource allocation with channel de-allocation and buffering in cellular networks. Buffers are applied for data traffic to reduce the packet loss probability while channel de-allocation is exploited to reduce the voice blocking probability. The results show that while buffering data traffic can reduce the packet loss probability, it has negative impact on the voice performance even if channel de-allocation is exploited. Although the voice blocking probability can be reduced with large slot capacity, the improvement decreases as the slot capacity increases. On the contrary, the packet loss probability increases as the slot capacity increases. In addition to the mean value analysis, the delay distribution and the 95% delay of data packets are provided.

Band Division MC-CDM (BD-MC-CDM) has been proposed for high quality wireless communications and has been investigated in terms of link level performance. In this paper, we investigate frequency band and time slot selection technique from the viewpoint of system level performance in order to realize the efficient BD-MC-CDM system under cellular environments. Then a downlink frequency band and time slot selection scheme is proposed for cellular BD-MC-CDM systems. The proposed scheme selects transmission frequency band according to the signal-to-interference ratio (SIR) estimated by using the pilot signal at mobile stations and also selects transmission time slot by using the SIR threshold. Simulation results show that the proposed scheme improves the downlink throughput but degrades delay performance and it has a trade off between throughput and delay performance. By selecting suitable control parameters, the proposed scheme achieves the throughput improvement without sacrificing the delay performance.

Multiuser diversity, identified by recent information theoretic results, is a form of diversity inherent in a wireless network. The diversity gain is obtained from independent time-varying fading channels across different users. The main practical issue in multiuser diversity is lack of Quality of Service (QoS) guarantees. This study proposes a wireless scheduling algorithm named MUDSEQ for downlink channels exploiting multiuser diversity under explicit QoS constraints. The numerical results demonstrate that the novel algorithm can yield non-negligible diversity gain even under tight QoS constraints and little scattering or slow fading environments. Additionally, a system framework for dynamic resource allocation based on the proposed algorithm is developed.

Service differentiation has been a subject of research for the past few years in the IETF; and in the current Internet, IP flows are mostly treated in a best-effort approach. However, for next generation networks it is expected that users would like to obtain service differentiation based on their preferences or profiles as well as the different types of multimedia they opt to receive or send. In addition, current Quality of Service (QoS) provisioning architectures have been designed mostly for the fixed networks without taking into consideration the wireless or radio links special requirements, such as low bandwidth availability, error prone communications, etc. In this paper we propose a QoS provisioning architecture for next generation networks that uses a hybrid approach to deal with both the wireless and wired (fixed) part of the network. For administering the scarce resource of the radio environment, we have developed a resource allocation algorithm based on micro-economic principles that uses associated piecewise linear utility functions which describe the benefit a user receives from the allocation of various amounts of resource. For the wired part of the network we have also developed a Core-Stateless Utility based Rate allocation Framework (SURF) for performing traffic policing where the flow's requirements are expressed using utility functions. The core routers maintain no per-flow state and implement a simple packet level admission control algorithm that is based on a threshold utility value that is computed dynamically. To tie in these two mechanisms, we developed a signaling mechanism that collect network statistics when a user starts a call and a QoS administrator entity (or Broker) perform the computations for allocating resources based on the information of available resources in the fixed and the wireless sections of the network. A comparison between the hybrid approach and the SURF approach to show the performance of the proposed architecture is presented later in the paper.

Flexible Resource Allocation (FRA) strategies selectively control the transmission rates of users allowing them to specify maximum and minimum bandwidth requirements for the service type requested ensuring a minimum quality of service (QoS) is met. Complete, Partial, and Non Resource Sharing are the three types of resource sharing policies that can be used in systems with integrated services (voice, video and data) with different QoS and elasticities requirements. In this paper, an FRA strategy with Partial Resource Sharing, called Primary Unavailable Secondary Minimum (PUSMin), is presented. An analytical method is developed to assess its performance in an environment where several service types (with different bandwidth and elasticities requirements) exist. Results show that PUSMin decreases the resource reassignment rate as the offered traffic increases. This decreases the signalling overhead and computational complexity in the Base Station Controller (BSC) or Base Transceiver Station (BTS).