Wen-Hsing Kuo

Utility-based resource allocation in wireless networks

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, i.e., 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 radio resource allocation for QoS traffic 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 Resource Allocation for Layer-Encoded IPTV Multicast in IEEE 802.16 (WiMAX) Wireless Networks

In this paper, we propose a utility-based resource allocation scheme for layer-encoded IPTV multicast streaming service over IEEE 802.16 WiMAX networks. Unlike existing utility-based schemes, this mechanism is designed for wireless networks which support adaptive modulation and coding. Each video stream (or program) is encoded into different layers. Then, our mechanism adjusts the number of each users received layers dynamically according to its channel condition and the available network bandwidth, so as to maximize total utility. We prove that this problem is NP-hard, and show that our scheme is bounded in performance to the optimal solution and can run in polynomial time. The simulation results show that this scheme can allocate resource flexibly according to the utility function of each program, the popularity of each program (i.e., the number of users receiving each program), and the amount of total available resource in the network. The result also shows that the fairness of the system can be guaranteed.

Multicast Recipient Maximization in IEEE 802.16j WiMAX Relay Networks

In this paper, we propose a resource-allocation scheme for multicast service in downlink transmission for IEEE 802.16j WiMax relay networks. Most existing algorithms try to minimize the total energy of a multicast tree. In contrast, we address the multicast recipient maximization (MRM) problem, which maximizes the total number of recipients with the given budget by adjusting the distribution of the allocated resource between the base station and the relay nodes. We prove that MRM is NP-complete and propose a polynomial-time scheme called dynamic station selection (DSS) to solve the problem based on the proposed auxiliary graph. Based on the provided lemmas, which serve as important guidelines for solving similar problems, we show that our heuristic algorithm has polynomial-time complexity and prove that its performance is bound to the optimum. The results of simulations demonstrate that, given different amounts of resource and variable channel conditions, the performance of DSS is always close to the optimum. Moreover, DSS more efficiently utilizes resources as the node density increases, resulting in more efficient resource allocation.

Dynamic Fingerprinting Combination for Improved Mobile Localization

This paper proposes a dynamic fingerprinting combination (DFC) algorithm that improves mobile localization by dynamically weighting the spatial correlation from multiple location fingerprinting systems. This DFC algorithm first extracts the complementary advantages of fingerprinting functions to construct a fusion profile, and then dynamically combines individual outputs based on the fusion profile surrounding the test sample. The proposed algorithm generates more accurate location estimates and reduces the risk of selecting a poorly-performing fingerprinting approach. This study applies DFC to an actual GSM network with realistic measurements. Experimental results show that DFC improves the positioning accuracy of base fingerprinting algorithms, including the Bayesian approach and a neural network model.

Utility-based optimal resource allocation in wireless networks

In this paper, we study utility-based optimal resource allocation in wireless networks. Utility here refers to a function which describes the degree of user satisfaction with a certain amount of allocated resource. We introduce utility function maximization in a centralized wireless environment and consider two types of traffic, i.e., best effort and QoS, the characteristics of which can be described by two existing utility functions. An allocation for the mixture of QoS and best effort traffics is proposed and its performance is evaluated via simulations. From this study, we show that optimal wireless resource allocation depends on the traffic types, the total available resource, and the channel quality, rather than solely dependent on the channel quality or traffic types as assumed in most existing work

Multicast Routing Scheme for Recipient Maximization in Wireless Relay Networks

In this paper, we study the multicast routing problem in wireless relay networks. Our objective is to maximize the number of recipients of a multicast stream by deciding the topology of the wireless relay network based on the given resource budget and the channel quality of the nodes. To the best of our knowledge, this important maximization problem has not been previously addressed. Since existing approaches cannot effectively solve the problem, we propose a scheme called multicast subscriber selection (MSS). Through analysis, we prove that the path-construction problem is NP-hard. Our heuristic MSS has polynomial-time complexity, and its performance is bound to the optimal solution. We also evaluate the performance of MSS via simulations. The results demonstrate that the existing unicast routing approach is inefficient under different budgets and channel conditions. In contrast, the proposed MSS scheme achieves better performance, because it can effectively utilize relay stations.

The impact of GPS positioning errors on the hop distance in Vehicular Adhoc Networks (VANETs)

In this paper, we study the impact of GPS positioning errors on the operation of Vehicular Adhoc Networks. To the best of our knowledge, this important issue has not been investigated before. First, we formulate a straight-road model. Then, to reduce the computational complexity of finding the expected degradation, we propose an approximate formula. The results of the simulations show that GPS errors do indeed degrade the hop-distance in VANETs. Moreover, the proposed approximation method yields good accuracy under sparse density conditions. Our study provides a good starting point for further research into this issue.

Recipient Maximization Multicast Scheme in IEEE 802.16j WiMAX Relay Networks

In this paper, we tackle an important problem in WiMAX relay networks called Multicast Recipient Maximization (MRM), which maximizes the number of multicast recipients with given budget. To deal with this problem, a novel resource allocation scheme called Dynamic Station Selection (DSS) is proposed. We prove that MRM is NP-hard, while our DSS has polynomial-time computational complexity. The simulation results show that under different situations, the performance of DSS always approximates the optimal solution. With this scheme, multimedia streams can be efficiently multicast over IEEE 802.16j WiMAX Relay Networks.

A node management scheme for R2V connections in RSU-supported Vehicular Adhoc Networks

Vehicular Adhoc Networks (VANETs) have become a popular research topic in recent years. In VANETs, RSU-to-Vehicle (R2V) unicast has a great deal of potential because it enables a Road-Side Unit (RSU) to contact a specific car and provide customized pushing services. However, to date, R2V has only been considered by a few works as it is difficult for the RSU to gather information about cars that are several hops way. To overcome this difficulty, we propose a scheme called RSU-Based Node Tracking (RBNT). Given on a predetermined road framework, RBNT chooses vehicles as Relay Nodes that connect with each other distributedly and form a hierarchical structure. Then, the RSU can connect to cars in its management area through the Relay Nodes. The results of simulations conducted to evaluate RBNTs performance demonstrate that the schemes connection delay is significantly lower than that of existing approaches, and its coverage range is stable under different traffic densities. To the best of our knowledge, this is the first work that focuses on the R2V unicast issue and provides all the above advantages.