Ke Bao

Spectrum handoffs with mixed-priority queueing model over Cognitive Radio Networks

In this paper, we propose a mixed preemptive and non-preemptive resume priority (PRP/NPRP) M/G/1 queueing model for the modeling of the traffic in Cognitive Radio (CR) Networks with prioritized transmissions. A traffic-adaptive spectrum handoff scheme is then developed based on the proposed queueing model for delay sensitive applications. This spectrum handoff scheme reduces the delivery time of the delay-sensitive applications for secondary users (SUs) while ensuring the overall performance of the network by avoiding overly frequent spectrum handoff between SUs. In the experiment section, we compare with two recently proposed queueing models using the traffic-adaptive spectrum handoff scheme and show the superior performance of the proposed approach.

Diamond-Shaped Mesh Network Routing with Cross-Layer Design to Explore the Benefits of Multi-Beam Smart Antennas

Conventional wireless mesh network (WMN)routing protocols are designed for the nodes that use the omni-directional or single-beam directional antennas. This research presents a throughput-efficient routing scheme for WMN, by taking advantage of the nodes equipped with the multi-beam directional antennas (MBDAs). Our routing design has the following two novel features: First, it is a cross-layer design by integrating the routing scheme with multi-beam oriented medium access control (MAC) scheme. Second, the routing topology has a diamond-like shape and uses the multi-path routes (i.e., one main path and a few side paths). The diamond shape makes the traffic converge and diverge periodically in the routing paths, which exploits the simultaneous data delivery capability of multi-beam antennas, and enhances the network throughput. Our simulation results demonstrate the high throughput efficiency of the proposed multi-beam routing scheme.

Low-Cost Pyroelectric Sensor Networks for Bayesian Crowded Scene Analysis

In this paper, we present a framework for complex scenarios recognition with crowded walkers. This study aims to develop an alternative surveillance system to traditional video camera and visual sensor based systems. Instead of utilizing visual devices in traditional surveillance systems, our crowded scene analysis is based on PIR (Pyroelectric Infrared) sensor networks with intelligent algorithms for context pattern extraction and analysis. Specifically, we will propose two new ideas to handle the crowded scenes: (1) Use hierarchical Bayesian NMF (Non-negative Matrix Factorization) algorithm to automatically identify the basic pattern basis, which will be used for accurate scenario recognition, (2) Use a tree-based structure to organize all basic features for fast object recognition. The experimental results valid the efficiency of the proposed two schemes on crowded scenario recognition with low-cost, non-visual system. The results also demonstrate that our framework is appropriate to be implemented in a wireless sensor based monitoring system under severe circumstances.

Measuring activities and counting steps with the SmartSocks - An unobtrusive and accurate method

Physical inactivity is an important contributor to non-communicable diseases in countries of high income, and increasingly so in those of low and middle income. Physical inactivity is the leading cause of many diseases. It has been estimated that as many as 250,000 deaths per year in the United States, approximately 12% of the total, are attributable to a lack of regular physical activity. Measuring physical activities and counting steps is an effective method to diagnose some diseases. It can also serve as an effective method to encourage people to increase their physical activity. Pedometers have been invented as a convenient way of counting steps. However most of them lack the functionality of differentiating activities. Pressure sensor pads can measure steps and gait, but as the pad has a limited size, it can not meet the need of anytime and anywhere usage. In this study, we made the Sensor Socks for measuring physical activities and counting steps. It is unobtrusive and convenient for everyday usage. Our experimental results show that the system has a high accuracy of the classification of physical activities and counting steps in a home or community environment.

A Fast Raptor Codes Decoding Strategy for Real-Time Communication Systems

We propose an efficient algorithm for Raptor decoding, which reduces the computational complexity of the most time-consuming steps in systematic decoding. Our proposed algorithm includes two aspects: First, to handle the decoding failure of the Raptor decoding, we propose a scheme, which is called the No-Wrapup Failure Handling scheme. It can resume the decoding process from where it fails after receiving a pre-defined number of additional encoded symbols, and thus avoids the repetition of time-consuming steps in the decoding process. Second, in order to reduce the time of finding the row with the minimum degree in the precode, we propose a Fast Min-Degree Seeking (FMDS) scheme. FMDS automatically maintains and updates the row degrees of the precode when converting the precode into an identity matrix through Gaussian elimination and Belief-propagation. Experimental results show that, compared to other Raptor decoding schemes, the proposed scheme achieves a much shorter decoding time, and can greatly speed up the data recovery in real-time applications.

Intelligent Software-Defined Mesh Networks With Link-Failure Adaptive Traffic Balancing

In the software defined networking (SDN)-based wireless mesh network (WMN) architecture (SD-WMN), the network is monitored and managed in a centralized manner. Although the use of SDN simplifies the WMN management, it is still not clear whether the SDN architecture, which was originally designed for wired links, can effectively handle the dynamic topology of WMNs. This paper addresses the traffic balancing issue introduced by node mobility. To reduce the response time of SDN controller for dynamic network topology, a two-layer supervised learning model is proposed that helps the controller to predict the node mobility and link failure probability. Then, an alternative route selection scheme is proposed, which achieves optimal traffic balancing while minimizing the control plane overhead. Efficiency of the proposed SD-WMN architecture is validated in the widely used network simulator—ns-3. Our results demonstrate the network throughput enhancement achieved by the proposed SD-WMN architecture with link-failure adaptive traffic control.

Adaptive Batch Coding: A High-Throughput Congestion Control for Wireless Big Data Transmissions

Multi-Beam Smart Antennas (MBSAs) achieve concurrent communications in multiple beams, thereby providing higher throughput compared to regular directional antennas. Most of the transport control schemes used today are based on TCP, which is too conservative since it indiscriminately reduces the window size upon any packet loss. The other extremity is the de-congestion control strategy, which abandons both window size control and retransmission, aggressively saturates the network, and compensates packet loss via network coding. To adapt to the features of the MBSA-based networks, this paper proposes a balanced transport control strategy between the above two categories, which is based on the idea of Adaptive Batch Coding (ABC). The proposed ABC scheme resists random loss through redundant coding and copes with congestion via window shrink and retransmission. Using a cross-layer design (between transport and routing layer), both the coding scheme and the traffic allocation are adaptively adjusted according to network conditions. A customized simulation system has been developed to comprehensively evaluate the performance of the proposed ABC protocol. Experimental results show that the proposed scheme overcomes the drawbacks of those two extremities. It achieves both high throughput and high throughput (under packet loss) in MBSA-based networks.

A Control-Message Quenching Algorithm in Openflow-Based Wireless Mesh Networks with Dynamic Spectrum Access

In recent years, Open Flow [1] is becoming a popular network architecture. As more and more users starts to join the conventional Internet, the drawbacks of the conventional networks are now gradually appearing. OpenFlow network provides us a brand new sight to the development of networks. This architecture separates the control plane and data plane from the hardware level(physically). OpenFlow has plenty of benefit compare to other network structures. Firstly, the control plane and data plane are decoupled, this means more flexible networks can be figure out with customized rules in the network. Secondly, OpenFlow provides us a new platform to design and test network protocols. Researchers could test new protocols in a real network environment. Thirdly, in OpenFlow architecture networks we could monitor flow traffic statistics. This fine-grained monitoring of flows enables us to better understanding the network protocols and scheme we applied.