Jia-Ming Liang

A Cross-Layer Framework for Overhead Reduction, Traffic Scheduling, and Burst Allocation in IEEE 802.16 OFDMA Networks

IEEE 802.16 orthogonal frequency-division multiple access (OFDMA) downlink subframes have a special 2-D channel-time structure. Allocation resources from such a 2-D structure incur extra control overheads that hurt network performance. Existing solutions try to improve network performance by designing either the scheduler in the medium access control layer or the burst allocator in the physical layer, but the efficiency of overhead reduction is limited. In this paper, we point out the necessity of “codesigning” both the scheduler and the burst allocator to efficiently reduce overheads and improve network performance. Under the partial-usage-of-subcarriers model, we propose a cross-layer framework that covers overhead reduction, real-time and non-real-time traffic scheduling, and burst allocation. The framework includes a two-tier priority-based scheduler and a bucket-based burst allocator, which is more complete and efficient than prior studies. Both the scheduler and the burst allocator are tightly coupled together to solve the problem of arranging resources to data traffic. Given available space and bucket design from the burst allocator, the scheduler can well utilize the frame resource, reduce real-time traffic delays, and maintain fairness. On the other hand, with priority knowledge and resource assignment from the scheduler, the burst allocator can efficiently arrange downlink bursts to satisfy traffic requirements with low complexity. Through analysis, the cross-layer framework is validated to give an upper bound to overheads and achieve high network performance. Extensive simulation results verify that the cross-layer framework significantly increases network throughput, maintains long-term fairness, alleviates real-time traffic delays, and enhances frame utilization.

An Energy Efficient Sleep Scheduling Considering QoS Diversity for IEEE 802.16e Wireless Networks

Power management is one of the most important issues in IEEE 802.16e wireless networks. In the standard, it defines three types of power saving classes (PSCs) for flows with different QoS characteristics. It allows a mobile device to turn off its wireless radio when all its PSCs are in sleep states. In this paper, we consider the scheduling of power saving classes of type II in an IEEE 802.16e network with a BS and multiple MSSs (mobile subscriber stations). Previous work proposes to enforce all MSSs to have the same sleep cycle, thus leading to higher energy cost for those MSSs with less strict delay bounds. We observe that if the sleep cycles of MSSs can be assigned according to their delay bounds, MSSs can significantly reduce their duty cycles. We propose an efficient tank-filling algorithm, which is standard-compliant and can allocate resources to MSSs according to their QoS characteristics with the least number of active frames. Simulation results verify that our algorithm incurs less power consumption and leads to higher bandwidth utilization than the previous schemes.

Energy-efficient uplink radio resource management in LTE-advanced relay networks for Internet of Things

For M2M (Machine-to-Machine) machines in cellular networks, employing high transmission rates or transmitting in large power actually cost them much energy. This is harmful to the machines, especially they are operated by batteries. The Relay Node (RN) in Long-Term Evolution-Advanced (LTE-A) networks is used to enhance the coverage of high data rate and solve the coverage hole problem. Considering the limited energy nature of machines, connecting to the RN instead of the BS is a better choice for cell-edge machines. In this paper, we consider an uplink resource and power allocation problem for energy conservation in LTE-A relay networks. The objective is to minimize the total energy consumption of machines while guarantee their quality of service (QoS). We prove this uplink resource and power allocation problem to be NP-complete and develop an energy-conserved resource and power allocation method to solve the problem. Simulation results show that our algorithm can effectively reduce the energy consumption of machines and guarantee their required service qualities.

Simple and Regular Mini-Slot Scheduling for IEEE 802.16d Grid-Based Mesh Networks

This work addresses the mini-slot scheduling problem in IEEE 802.16d wireless mesh networks (WMNs). A practical mini-slot scheduling needs to take into account following issues: the transmission overhead, the scheduling complexity, and the signaling overhead to notify the scheduling results to subscriber stations. We focus in a grid-based WMN, which is the most recommended topology due to its high capacity and connectivity. In this paper, we propose scheduling schemes featured by low complexity and low signaling overhead. The proposed schemes help find periodical and regular schedules, which can balance between transmission overhead and pipeline efficiency. They can achieve near-optimal transmission latencies. Simulation results show that our schemes outperform other schemes, especially when the network size is larger.

A web-based, real-time video surveillance system by leveraging PTZ cameras

Video surveillance systems are commonly used for environmental monitoring. Nevertheless, existing systems such as [1, 2] can only monitor scenes statically. When an accident or a fire event happens, we cannot get the critical pictures and check those situations immediately. Therefore, we propose to leverage pan-tilt-zoom (PTZ) cameras and develop a real-time surveillance system, where the PTZ cameras can rotate in a horizontal plane by panning and in a vertical plane by tilting, and adjust the focal length by zooming, so we can control these cameras dynamically for the emergent area. Especially for the accessibility, we implement this system as a web service to help users easily define the emergent area and preview the video of cameras remotely.

Smart Surveillance with Context and Location Sensitivity and Quality Control

Smart video surveillance systems are essentials in modern environments to ensure safety and security for lives and property. In order to capture critical clues of reconnaissance, it is important to automatically and dynamically control the surveillance sensitivity and quality for detecting abnormal/suspicious events to perform high quality monitoring. In this work, we design a smart video surveillance system, which fully utilizes pan-tilt-zoom (PTZ) cameras and well integrates with environment sensors (such as fire/motion/door sensors) while cooperating with wearable devices that can adaptively monitor events and ensure the surveillance quality in terms of pixel-per-foot (PPF), viewing-angles, timeliness, and accuracy. In addition, this system also supports to define the special monitoring tasks and surveillance requirements, such as the surveillance timeliness and duty cycle for particular moving objects to be tracked per time unit. Then, a smart camera dispatch algorithm will calculate and determine the best cameras set with the corresponding configurations to accomplish the surveillance tasks effectively and precisely. We will show how our system realizes smart detecting and monitoring in this demonstration by leveraging PTZ cameras, environmental sensors and wearable devices.

Sleep scheduling in IEEE 802.16j relay networks

Power saving for mobile stations (MSs) is one of the most critical issues in IEEE 802.16j relay networks. To reduce power consumption of MSs, IEEE 802.16j borrows the sleep mode of 802.16e, but new parameters are introduced. Up to now, no previous work has addressed the sleep scheduling problem in IEEE 802.16j networks. Therefore, this paper proposes an energy-efficient, standard-compliant sleep scheduling scheme which involves relay stations (RSs) and realizes spatial reuse on RS transmissions to minimize energy consumption of MSs while guaranteeing their QoS. The main idea of the proposed scheme is to interleave the sleep patterns of MSs and exploit spatial reuse on MS-RS transmissions to reduce resource consumption while enlarging the available frame space. Comprehensive simulation has been conducted to verify the effeteness of our scheduling scheme. It shows that our scheme can serve more requests of MSs while increasing their sleep ratios.

Energy-Efficient Uplink Resource Units Scheduling for Ultra-Reliable Communications in NB-IoT Networks

For 5G wireless communications, the 3GPP Narrowband Internet of Things (NB-IoT) is one of the most promising technologies, which provides multiple types of resource unit (RU) with a special repetition mechanism to improve the scheduling flexibility and enhance the coverage and transmission reliability. Besides, NB-IoT supports different operation modes to reuse the spectrum of LTE and GSM, which can make use of bandwidth more efficiently. The IoT application grows rapidly; however, those massive IoT devices need to operate for a very long time. Thus, the energy consumption becomes a critical issue. Therefore, NB-IoT provides discontinuous reception operation to save devices’ energy. But, how to further reduce the transmission energy while ensuring the required ultra-reliability is still an open issue. In this paper, we study how to guarantee the reliable communication and satisfy the quality of service (QoS) while minimizing the energy consumption for IoT devices. We first model the problem as an optimization problem and prove it to be NP-complete. Then, we propose an energy-efficient, ultra-reliable, and low-complexity scheme, which consists of two phases. The first phase tries to optimize the default transmit configurations of devices which incur the lowest energy consumption and satisfy the QoS requirement. The second phase leverages a weighting strategy to balance the emergency and inflexibility for determining the scheduling order to ensure the delay constraint while maintaining energy efficiency. Extensive simulation results show that our scheme can serve more devices with guaranteed QoS while saving their energy effectively.

Spatial and Temporal Aggregation for Small and Massive Transmissions in LTE-M Networks

Machine-to-machine (M2M) communication is one of the key technologies to realize Internet of Things (IoT). Since IoT applications are mainly for smart sensing, such as metering, home surveillance, disaster detection, and e-health, their special sensing#x002F;uploading behaviors will result in periodic and#x002F;or event-driven small data transmissions, which may potentially decrease the radio resource efficiency. On the other hand, the widespread deployment of IoT raises the concurrent massive connectivity of IoT devices. How to solve these two problems is a critical issue. In this paper, we investigate an uplink resource allocation problem which considers the periodic, event-driven, and query-based IoT traffic behaviors over LTE-M. The proposed approach takes advantage of data aggregation and both spatial and temporal reuse. Our solution exploits long-term static scheduling for periodic data to ensure the latency and data rate, and employs short-term dynamic scheduling for event-driven, query-based data to improve transmission efficiency. Therefore, both small data and massive connectivity problems are relieved. Extensive simulation results show that the proposed scheme can improve resource efficiency and enlarge network capacity effectively.

A Dynamic Reservation Scheme in Online Charging System for Family Shared Plan

For simplifying billing and limiting data usage, Family Shared Plan (FSP) is now a popular plan provided by telecommunications operators. Based on the 3rd Generation Partnership Project (3GPP) specifications, Online Charging System (OCS) has to determine the Granted Unit (GU) and create reservations per session before a service is delivered by the serving network to a User Equipment (UE). However, fixed GUs cannot adapt to dynamic consumer behaviors, which usually require dynamic GUs. Clearly, giving small GUs will incur too many signaling messages for making reservations, but giving excessive GUs will cause unbalanced distribution of resources, especially in FSP cases. How to determine GUs is an open issue that can be self-defined by telecommunications operators. In this paper, we propose a new scheme for dynamically assigning GUs to UEs belonging to the same FSP, based on their historical data usage and total monthly data allowance. Simulation results show that our scheme can substantially save signalings by at least 22% compared to fixed scheme under unpredictable behaviors.