Chiu-Han Hsiao

A Near-Optimal Distributed QoS Constrained Routing Algorithm for Multichannel Wireless Sensor Networks

One of the important applications in Wireless Sensor Networks (WSNs) is video surveillance that includes the tasks of video data processing and transmission. Processing and transmission of image and video data in WSNs has attracted a lot of attention in recent years. This is known as Wireless Visual Sensor Networks (WVSNs). WVSNs are distributed intelligent systems for collecting image or video data with unique performance, complexity, and quality of service challenges. WVSNs consist of a large number of battery-powered and resource constrained camera nodes. End-to-end delay is a very important Quality of Service (QoS) metric for video surveillance application in WVSNs. How to meet the stringent delay QoS in resource constrained WVSNs is a challenging issue that requires novel distributed and collaborative routing strategies. This paper proposes a Near-Optimal Distributed QoS Constrained (NODQC) routing algorithm to achieve an end-to-end route with lower delay and higher throughput. A Lagrangian Relaxation (LR)-based routing metric that considers the “system perspective” and “user perspective” is proposed to determine the near-optimal routing paths that satisfy end-to-end delay constraints with high system throughput. The empirical results show that the NODQC routing algorithm outperforms others in terms of higher system throughput with lower average end-to-end delay and delay jitter. In this paper, for the first time, the algorithm shows how to meet the delay QoS and at the same time how to achieve higher system throughput in stringently resource constrained WVSNs.

Resource Allocation and Multisession Routing Algorithms in Coordinated Multipoint Wireless Communication Networks

In heterogeneous wireless networks, coordinated multipoint technology facilitates coordination and mutual cooperation among various types of networks and applications. The resource requirements of various applications differ considerably under the constraint of limited resources so that the allowable delay is considered. This study considered a centralized management scheme involving fourth-generation (4G) mobile networks Evolved Node B, access points, and back-end coordinated servers. The operator controls the flow and performs routing selection procedures through long-term evolution advanced and Wi-Fi in accordance with the 5G wireless networks. The problem was constructed as a mathematical programming model. A Lagrangian relaxation (LR) approach was adopted to maximize the revenue minus the penalty costs as objective to evaluate the resource allocation, tolerable delay, and multisession routing algorithm. The primal problem was decomposed into seven independent subproblems through LR procedures, and the combination of a subgradient method and a routing algorithm was used to obtain approximate solutions. A novel algorithm for flow control involving multisession routing is proposed for handling resource allocation. The algorithm involving a near-optimal approach was designed to solve the insufficient resource problem. The solution can be used by operators for improving resource utilization in next-generation wireless networks.

A testbed-based framework for performance evaluation of multicast broadcast systems in OFDMA networks

Multicast Broadcast Service MBS applications can efficiently reduce the usage of network resources, still providing mobile users with real-time high-quality content. MBS capabilities are usually implemented by using a single frequency network; moreover, new features, such as connection identifier for broadcast/multicast messages and other MBS-enabled descriptors, are added to cope with already existent entities and services. With the intention to optimize performances and verify the on-field feasibility, we propose an MBS approach to Orthogonal Frequency Division Multiple Access systems based on superposition coding SPC. Because MBS features have a large impact in the architectural design of the network protocols, an integrated framework is mandatory to speed up the system simulation, verification, and redesign steps. This paper shows the design of an experimental testbed for performance evaluation of SPC-enabled physical PHY and medium access control MAC layers over Mobile WiMAX systems. In addition, it proposes some architectural modifications of the WiMAX protocols, by exploiting its core network capabilities. The experimental results obtained from the testbed confirm that augmented throughput capabilities can be achieved by SPC-enabled PHY/MAC layers. However, to fully exploit the additional available throughput, an integrated framework must be adopted to evaluate the protocol modifications for the MBS-enabled entities. Copyright

Minimum-Cost QoS-Constrained Deployment and Routing Policies for Wireless Relay Networks

With the continued evolution of wireless communication technology, relaying is one of the features proposed for the 4G LTE Advanced (LTE-A) system. The aim of relaying is to enhance both coverage and capacity. The idea of relays is not new, but relaying is being considered to ensure that the optimum performance is achieved to enable the expectations or good quality of service (QoS) of the users to be met while still keeping capital expenditure (CAPEX) within the budgeted bounds of operators. In this paper, we try to stand for an operator to propose a solution that determines where and how many relays should be deployed in the planning stages to minimize the development cost. In the planning stages, we not only derive a multicast tree routing algorithm to both determine and fulfill the QoS requirements to enhance throughput, but we also utilize the Lagrangian relaxation (LR) method in conjunction with optimization-based heuristics and conduct computational experiments to evaluate the performance. Our contribution is utilizing the LR method to propose an optimal solution to minimize the CAPEX of operators to build up a relay network with more efficiency and effectiveness and the QoS can be guaranteed by service level agreement.

Adaptive power ranges and associations for self-healing in multiple types of Wi-Fi networks

Wi-Fi wireless communication has become a basic service in public areas. However, the quality of service (QoS) might be inadequate in some areas because of the following influential factors: 1) the limited number of non-overlapping channels, 2) the interference caused by unplanned deployment and mobility, 3) the rapidly changing distribution of customers, and 4) access point (AP) failures. These factors result in non-uniform network traffic distribution and unavailability of service in some areas. Hence, this study focused on addressing the problems of AP failure and interference. We propose a self-healing algorithm to provide seamless and reliable service despite AP failures. The proposed water ripple algorithm maximizes the minimum delay difference, which is defined as the difference between transmission delay and tolerable delay, to satisfy requirements of multiple users simultaneously. Variable transmission power ranges (which involve cell breathing method types) and association management are adjusted to minimize the number of out-of-service mobile devices (MDs). Thus, fair allocation of resources to users and adequate QoS are satisfied.

Dynamical cloud hosts assignment to achieve cost-effectiveness in cloud radio access networks

Cloud radio access network (C-RAN) has been proposed as a core network in the fifth-gene rati on mobile communications system. The computing resources are clustered as a pool that is centralised management as a cloud. The pool provides flexible capabilities to satisfy variant demands with large scale processing. This work stands on an operator perspective to analyse a centralised management mechanism. The research problem is a type of knapsack and bin packing problems that is formulated as a mathematical formulation. The objective is to increase the revenue with minimal server operations cost. Two-phase approximation method is proposed. In phase I, a dynamic programming method is utilized for finding a set of tasks with maximum revenue. In Phase II, three modified Next-Fit, First-Fit, and Best-Fit schemes are developed for solving and evaluating the resource allocations to reduce the number of power-on servers. It presents a way to support operators determine how to allocate the cloud hosts by leveraging cloud technology. The finding can be used to improve resource utilization and achieve cost-effectiveness in C-RANs.

A Precision Operation Optimization for Detection-Based Sensor Networks

Wireless Sensor Networks (WSNs), which are connected by sensor nodes with wireless communication techniques, are used to collect, process, and transmit the various types of environmental data, such as temperature, fire and smoke detectors, CO gas, humidity, pressure, and video-based data. The network lifetime is limited due to sensors are equipped with batteries. The measurement uncertainties and detection faults lead higher power consumption by retransmissions due to event detection error. These two factors influence with each other. In this study, there are two indicators are introduced for detection errors, false positive (FP) and false negative (FN) to evaluate a detection-based sensor network. For operation perspectives, three models are addressed to near-optimize the network lifetime and detection errors. Linear-and non-linear mathematical planning problems are formulated as (1) to minimize event FP rate subject to FN constraints, (2) to minimize the network energy consumption subject to detection accuracy requirements, turning sensor ON/OFF decisions, the required number of voting nodes, and given FP/FN constraints, and (3) to extend from the previous model as a planning problem for various types of sensor nodes deployed with diverse FP/FN characteristics and costs. An integer programming (IP) tool, LINGO, is adopted to solve the problems with computational experiments on several situations. The experimental results show that the objectives can be achieved, lots of useful hints or configurations can be applied for system implementations to improve system performance efficiently and effectively.

Explore and Analyze the Performance Factors on Wi-Fi Sensing Starvation Problems

Wi-Fi wireless communication has become a basic service in public areas. But the quality is not stable due to the factors that are influenced by 1) a limited number of channels results in access interference, 2) various transmission ranges, carrier sensing and hidden terminal starvation problems, and 3) the barriers reduce the quality of transmissions. This work aims to explore and analyze the factors to show the level of performance effect on various transmission ranges of access points. Accordingly, this study designs several simulation cases to evaluate whether a small cell size can provide high performance co-existing with a large cell size by controlling the effect of the sensing ranges, transmission ranges, traffic types, data rates, and packet sizes. Network Simulation 3 (NS3) tool is used to implement the simulation cases and compare the results. We discussed our findings on these factors that affect the levels of starvation caused by the various signal ranges.

Utilizing Joint Routing and Capacity Assignment Algorithms to Achieve Inter- and Intra-Group Delay Fairness in Multi-Rate Multicast Wireless Sensor Networks

Recent advance in wireless sensor network (WSN) applications such as the Internet of Things (IoT) have attracted a lot of attention. Sensor nodes have to monitor and cooperatively pass their data, such as temperature, sound, pressure, etc. through the network under constrained physical or environmental conditions. The Quality of Service (QoS) is very sensitive to network delays. When resources are constrained and when the number of receivers increases rapidly, how the sensor network can provide good QoS (measured as end-to-end delay) becomes a very critical problem. In this paper; a solution to the wireless sensor network multicasting problem is proposed in which a mathematical model that provides services to accommodate delay fairness for each subscriber is constructed. Granting equal consideration to both network link capacity assignment and routing strategies for each multicast group guarantees the intra-group and inter-group delay fairness of end-to-end delay. Minimizing delay and achieving fairness is ultimately achieved through the Lagrangean Relaxation method and Subgradient Optimization Technique. Test results indicate that the new system runs with greater effectiveness and efficiency.