Adaptive Medium Access Control for Internet-of-Things Enabled Mobile Ad Hoc Networks

An Internet-of-Things (IoT) enabled mobile ad hoc network (MANET) is a self organized distributed wireless network, in which nodes can randomly move making the network traffic load vary with time. A medium access control (MAC) protocol, as a most important mechanism of radio resource management, is required in MANETs to coordinate nodes’ access to the wireless channel in a distributed way to satisfy their quality of service (QoS) requirements. However, the distinctive characteristics of IoT-enabled MANETs, i.e., distributed network operation, varying network traffic load, heterogeneous QoS demands, and increased interference level with a large number of nodes and extended communication distances, pose technical challenges on MAC. An efficient MAC solution should achieve consistently maximal QoS performance by adapting to the network traffic load variations, and be scalable to an increasing number of nodes in a multi-hop communication environment. In this thesis, we develop comprehensive adaptive MAC solutions for an IoT-enabled MANET with the consideration of different network characteristics. First, an adaptive MAC solution is proposed for a fully-connected network, supporting homogeneous best-effort data traffic. Based on the detection of current network traffic load condition, nodes can make a switching decision between IEEE 802.11 distributed coordination function (DCF) and dynamic time division multiple access (D-TDMA), when the network traffic load reaches a threshold, referred to as MAC switching point. The adaptive MAC solution determines the MAC switching point in an analytically tractable way to achieve consistently high network performance by adapting to the varying network traffic load. Second, when heterogeneous services are supported in the network, we propose an adaptive hybrid MAC scheme, in which a hybrid superframe structure is designed to accommodate the channel access from delay-sensitive voice traffic using time division multiple access (TDMA) and from best-effort data traffic using truncated carrier sense multiple access with collision avoidance (T-CSMA/CA). According to instantaneous voice and data traffic load conditions, the MAC exploits voice traffic multiplexing to increase the voice capacity by adaptively allocating TDMA time slots to active voice nodes, and maximizes the aggregate data throughput by adjusting the optimal contention window size for each data node. Lastly, we develop a scalable token-based adaptive MAC scheme for a two-hop MANET with an increasing number of nodes. In the network, nodes are partitioned into different one-hop node groups, and a TDMA-based superframe structure is proposed to allocate different TDMA time durations to different node groups to overcome the hidden terminal problem. A probabilistic token passing scheme is adopted for packet transmissions within different node groups, forming different token rings. An average end-to-end delay optimization framework is established to derive the set of optimal MAC parameters for a varying network load condition. With the optimal MAC design, the proposed adaptive MAC scheme achieves consistently minimal average end-to-end delay in an IoT-based two-hop environment with a high network traffic load. This research on adaptive MAC provides some insights in MAC design for performance improvement in different IoT-based network environments with different QoS requirements

Resource Management in E-health Systems

E-health systems are the information and communication systems deployed to improve quality and efficiency of public health services. Within E-health systems, wearable sensors are deployed to monitor physiology information not only in hospitals, but also in our daily lives under all types of activities; wireless body area networks (WBANs) are adopted to transmit physiology information to smartphones; and cloud servers are utilized for timely diagnose and disease treatment. The integrated services provided by E-health systems could be more convenient, reliable, patient centric and bring more economic healthcare services. Despite of many benefits, e-health systems face challenges among which resource management is the most important one as wearable sensors are energy and computing capability limited, and medical information has stringent quality of service (QoS) requirements in terms of delay and reliability. This thesis presents resource management mechanisms, including transmission power allocation schemes for wearable sensors, Medium Access Control (MAC) for WBANs, and resource sharing schemes among cloud networks, that can efficiently exploit the limited resources to achieve satisfactory QoS. First, we address how wearable sensors could energy efficiently transmit medical information with stringent QoS requirements to a smart phone. We first investigate how to provide worst-case delay provisioning for vital physiology information. Sleep scheduling and opportunistic channel access are exploited to reduce energy consumption in idle listening and increase energy efficiency. Considering dynamic programming suffers from curse of dimensionality, Lyapunov optimization formulation is established to derive a low complexity two-step transmission power allocation algorithm. We analyze the conditions under which the proposed algorithm could guarantee worst-case delay. We then investigate the impacts of peak power constraint and statistical QoS provisioning. An optimal transmission power allocation scheme under a peak power constraint is derived, and followed by an efficient calculation method. Applying duality gap analysis, we characterize the upper bound of the extra average transmission power incurred due a peak power constraint. We demonstrate that when the peak power constraint is stringent, the proposed constant power scheme is suitable for wearable sensors for its performance is close to optimal. Further, we show that the peak power constraint is the bottleneck for wearable sensors to provide stringent statistical QoS provisioning. Second, WBANs can provide low-cost and timely healthcare services and are expected to be widely adopted in hospitals. We develop a centralized MAC layer resource management scheme for WBANs, with a focus on inter-WBAN interference mitigation and sensor power consumption reduction. Based on the channel state and buffer state information reported by smart phones deployed in each WBAN, channel access allocation is performed by a central controller to maximize the network throughput. Note that sensors have insufficient energy and computing capability to timely provide all the necessary information for channel resource management, which deteriorates the network performance. We exploit the temporal correlation of body area channel such that channel state reports from sensors are minimized. We then formulate the MAC design problem as a partially observable optimization problem and develop a myopic policy accordingly. Third, cloud computing is expected to meet the rising computing demands. Both private clouds, which aim at patients in their regions, and public clouds, which serve general public, are adopted. Reliability control and QoS provisioning are the core issues of private clouds and public clouds, respectively. A framework, which exploits the abundant resource of private clouds in time domain, to enable cooperation among private clouds and public clouds, is proposed. Considering the cost of service failure in e-health system, the first time failure probability is adopted as reliability measures for private clouds. An algorithm is proposed to minimize the failure probability, and is proven to be optimal. Then, we propose an e-health monitoring system with minimum service delay and privacy preservation by exploiting geo-distributed clouds. In the system, the resource management scheme enables the distributed cloud servers to cooperatively assign the servers to the requested users under a load balance condition. Thus, the service delay for users is minimized. In addition, a traffic shaping algorithm is proposed, which converts the user health data traffic to the non-health data traffic such that the capability of traffic analysis attacks is largely reduced. In summary, we believe the research results developed in this dissertation can provide insights for efficient transmission power allocation for wearable sensor, can offer practical MAC layer solutions for WBANs in hospital environment, and can improve the QoS provisioning provided by cloud networks in e-health systems

Distributed Medium Access Control for QoS Support in Wireless Networks

With the rapid growth of multimedia applications and the advances of wireless communication technologies, quality-of-service (QoS) provisioning for multimedia services in heterogeneous wireless networks has been an important issue and drawn much attention from both academia and industry. Due to the hostile transmission environment and limited radio resources, QoS provisioning in wireless networks is much more complex and difficult than in its wired counterpart. Moreover, due to the lack of central controller in the networks, distributed network control is required, adding complexity to QoS provisioning. In this thesis, medium access control (MAC) with QoS provisioning is investigated for both single- and multi-hop wireless networks including wireless local area networks (WLANs), wireless ad hoc networks, and wireless mesh networks. Originally designed for high-rate data traffic, a WLAN has limited capability to support delay-sensitive voice traffic, and the service for voice traffic may be impacted by data traffic load, resulting in delay violation or large delay variance. Aiming at addressing these limitations, we propose an efficient MAC scheme and a call admission control algorithm to provide guaranteed QoS for voice traffic and, at the same time, increase the voice capacity significantly compared with the current WLAN standard. In addition to supporting voice traffic, providing better services for data traffic in WLANs is another focus of our research. In the current WLANs, all the data traffic receives the same best-effort service, and it is difficult to provide further service differentiation for data traffic based on some specific requirements of customers or network service providers. In order to address this problem, we propose a novel token-based scheduling scheme, which provides great flexibility and facility to the network service provider for service class management. As a WLAN has small coverage and cannot meet the growing demand for wireless service requiring communications ``at anywhere and at anytime", a large scale multi-hop wireless network (e.g., wireless ad hoc networks and wireless mesh networks) becomes a necessity. Due to the location-dependent contentions, a number of problems (e.g., hidden/exposed terminal problem, unfairness, and priority reversal problem) appear in a multi-hop wireless environment, posing more challenges for QoS provisioning. To address these challenges, we propose a novel busy-tone based distributed MAC scheme for wireless ad hoc networks, and a collision-free MAC scheme for wireless mesh networks, respectively, taking the different network characteristics into consideration. The proposed schemes enhance the QoS provisioning capability to real-time traffic and, at the same time, significantly improve the system throughput and fairness performance for data traffic, as compared with the most popular IEEE 802.11 MAC scheme

Cooperative Strategies for Management of Power Quality Problems in Voltage-Source Converter-based Microgrids

The development of cooperative control strategies for microgrids has become an area of increasing research interest in recent years, often a result of advances in other areas of control theory such as multi-agent systems and enabled by emerging wireless communications technology, machine learning techniques, and power electronics. While some possible applications of the cooperative control theory to microgrids have been described in the research literature, a comprehensive survey of this approach with respect to its limitations and wide-ranging potential applications has not yet been provided. In this regard, an important area of research into microgrids is developing intelligent cooperative operating strategies within and between microgrids which implement and allocate tasks at the local level, and do not rely on centralized command and control structures. Multi-agent techniques are one focus of this research, but have not been applied to the full range of power quality problems in microgrids. The ability for microgrid control systems to manage harmonics, unbalance, flicker, and black start capability are some examples of applications yet to be fully exploited. During islanded operation, the normal buffer against disturbances and power imbalances provided by the main grid coupling is removed, this together with the reduced inertia of the microgrid (MG), makes power quality (PQ) management a critical control function. This research will investigate new cooperative control techniques for solving power quality problems in voltage source converter (VSC)-based AC microgrids. A set of specific power quality problems have been selected for the application focus, based on a survey of relevant published literature, international standards, and electricity utility regulations. The control problems which will be addressed are voltage regulation, unbalance load sharing, and flicker mitigation. The thesis introduces novel approaches based on multi-agent consensus problems and differential games. It was decided to exclude the management of harmonics, which is a more challenging issue, and is the focus of future research. Rather than using model-based engineering design for optimization of controller parameters, the thesis describes a novel technique for controller synthesis using off-policy reinforcement learning. The thesis also addresses the topic of communication and control system co-design. In this regard, stability of secondary voltage control considering communication time-delays will be addressed, while a performance-oriented approach to rate allocation using a novel solution method is described based on convex optimization