Zhaoliang Zhang

A cyber physical networking system for monitoring and cleaning up blue-green algae blooms with agile sensor and actuator control mechanism on Lake Tai

Nowadays, the harmful blue-green algae blooms on lakes threaten the daily life of millions of people in China. We designed and developed a cyber physical networking system on Lake Tai for the monitoring and cleanup of the water blooms which is at work in Wuxi City, Jiangsu Province. We designed the sensor device and algorithm to monitor the order of severity of algae bloom. A GIS-based management website is built for the end user to monitor the whole system. In this paper, we focus on the agile sensor and actuator control (ASAC) mechanism to dispatch salvaging boats. The location area and the order of severity of a water bloom change rapidly with the climatic, the terrain and the sewage disposal system. The location and the capacity of salvaging boat are also in changing when the system is running. ASAC is designed to generate optimal dispatch plan in the changing environment. This mechanism also balances workloads among the boats and among the algae factories to achieve an overall high working efficiency. Through the tests in the real system, ASAC largely saved human resource and increased the work efficiency in the cleaning up process.

EasiPLED: Discriminating the causes of packet losses and errors in indoor WSNs

It is well known that there are two kinds of causes, namely channel-errors and collisions, which lead to high probability of packet losses and errors in wireless networks. The ability of discriminating the above two causes provides many opportunities for implementing high efficient networking protocols in wireless sensor networks (WSNs). This paper presents EasiPLED, a discriminator that can accurately and timely predict these two causes. EasiPLED has three salient features. First, it investigates F-BER patterns and statistic characteristics of RSSI in different indoor environments through extensive experimental studies. F-BER is the Frame-level Bit Error Rate measured at the receiver side by a coarse-grained method without incurring any overhead. An adaptive RSSI estimator based on error-based filter is proposed to mitigate effects of noise on RSSI readings for successfully received packets. Second, EasiPLED designs an off-line dominant-factor classifier using machine learning method. The classifier takes a combination of F-BER and RSSI features as input and outputs the probability of dominant causes of failed transmissions. Finally, it presents a lightweight on-line discriminator which diagnoses the root cause of a packet loss or error when it occurs at the receiver side. Experimental results show that EasiPLED achieves an accuracy by up to 95.4%. We evaluate the effectiveness of EasiPLED by applying it to link-layer retransmission scheme, which yields a reduction of single-hop transmission delay by up to 47%, and provides high packet delivery ratios as compared to the existing retransmission methods.

A Channel Allocation Scheme to Mitigate Wifi Interference for Wireless Sensor Networks: A Channel Allocation Scheme to Mitigate Wifi Interference for Wireless Sensor Networks

Wireless sensor networks will suffer severe performance degradation in communication reliability and throughput when interfered by co-located Wifi devices.When multiple sensor networks with different priority are interfered by Wifi devices,it is of great significance to allocate channels according to their priority as well as take into consideration the overall communication reliability and throughput.To address this problem,a channel allocation scheme to mitigate Wifi interference,called EasiCAP(Channel Allocation for wireless sensor networks with Priority),is presented.The scheme employs an external interference model,which is based on interference signal strength and activity ratio,to measure Wifi interference in each channel of sensor networks.In addition,a receiver-centric interference model is used to gauge internal interference amongst different sensor networks.Based on the measurements of external interference and internal interference,each sensor network independently selects its working channel in real time via a localized greedy algorithm in order to assign channels according to priority and also reduce the overall interference of all sensor networks as much as possible.Then,the sensor network performs one of the three operations,i.e.,channel keeping,channel swapping,and channel preempting,based on the channel selection decision.Testbed experiments and simulations are conducted to verify the effectiveness of the proposed scheme.The experimental results demonstrate that EasiCAP can provide differentiated communication reliability and throughput corresponding to the network priority.Also,it has higher average communication reliability and throughput than existing schemes.Furthermore,it does not introduce significant overhead.

Leveraging data fusion to improve barrier coverage in wireless sensor networks

Intruder detection and border surveillance are amongst the most promising applications of wireless sensor networks. Barrier coverage formulates these problems as constructing barriers in a long-thin region to detect intruders that cross the region. Existing studies on this topic are not only based on simplistic binary sensing model but also neglect the collaboration employed in many systems. In this paper, we propose a solution which exploits the collaboration of sensors to improve the performance of barrier coverage under probabilistic sensing model. First, the network width requirement, the sensor density and the number of barriers are derived under data fusion model when sensors are randomly distributed. Then, we present an efficient algorithm to construct barriers with a small number of sensors. The theoretical comparison shows that our solution can greatly improve barrier coverage via collaboration of sensors. We also conduct extensive simulations to demonstrate the effectiveness of our solution.

A comparative simulation study of rate adaptation algorithms in wireless LANs

Wireless channel condition varies quickly and unpredictably, which is the main reason leading to the low performance of 802.11 wireless local area networks. One effective way to overcome the above problem is rate adaptation, which adaptively selects an appropriate transmission rate according to current channel conditions. A number of rate adaptation algorithms have been proposed in the literatures. However, few of them have been thoroughly evaluated by simulations. It is necessary to conduct a comparative study of these rate adaptation mechanisms, to have a comprehensive view about their impacts on the performance of applications in different channel conditions. In this paper, we perform an extensive comparative simulation study on several well-known rate adaptation algorithms based on ns-3. We quantify their performance for aggregate network throughput in the following two environments: collision-concerned and mobility-concerned. This work is an important step to understand the behaviour of different rate adaptation algorithms.

EasiRA: A hybrid rate adaptation scheme for 802.11 mobile wireless access networks

Rate adaptation, which adapts transmission bit rate according to current wireless link conditions, is a fundamental mechanism used by link-layer protocols to improve the performance of 802.11 wireless access networks in terms of throughput. However, rate adaptation faces to severe challenges due to more and more congested and dynamic wireless links. In this paper, we design a hybrid rate adaptation scheme, called EasiRA, for 802.11 mobile wireless access networks. It has following three features. First, it combines the sensor-hints and protocol-hints information together to estimate current link status. Second, EasiRA exploits environmental signal strength information obtained by a 802.15.4-based radio to help distinguish the causes of packet losses and adjust the thresholds of the protocol-hints. Finally, EasiRA uses both random and deterministic rate increase or decrease schemes to combat the dynamic and unpredictable characteristics of wireless links. Simulation results show that EasiRA consistently outperforms the existing rate adaptation schemes, namely CARA, Minstrel and RapidSample, particularly in relatively high dynamic scenario.

The design and implementation of a surveillance and self-driven cleanup system for blue-green algae blooms on Lake Tai

Nowadays, the harmful blue-green algae blooms on lakes or streams threaten the daily life of millions of people in China. In this paper, we demonstrate the sensor network system we built on Lake Tai for the surveillance and cleanup of the algae blooms which is at work in Wuxi City, Jiangsu Province. We designed the sensor device and algorithm to monitor the algae bloom and estimate the bloom area. When the bloom area goes beyond the threshold, the salvaging boats are automatically dispatched to the scene to clean up the bloom for recycling utilization according to a mechanism in a scalable coordination fashion. The dispatching mechanism includes to consider the locations of salvaging boats, the number of available salvaging boats and the facility status in eight algae harvesting factories around the lake. The system also balances workloads of factories to achieve an overall high working efficiency. We develop a GIS-based management website for the end user to monitor the running of the whole system. All the sensing stations, the real time performance of the algae harvesting factory, the locations of salvaging boats and the automatically generated cleanup schedule are displayed in the map.

LogA: Concurrent Medium Access Control through Time Log Analysis in Sensor Networks

This paper focuses on the design of high-throughput MAC for data-intensive sensor networks with unpredictable traffic. We propose Log A, a reactive concurrent MAC protocol that increases transmission concurrency based on time log analysis. Each node reactively and passively learns the interference relationship by analyzing the start transmission time and the end transmission time of packet blocks. Then, the learned interference relationship is exploited to improve the probability of beneficial concurrent transmissions of nodes that are within the interference range of each other. Log A has two salient features. First, it is passive and does not need network downtime to build interference relationship. Second, it is reactive and works only when traffic are generated. Log A has been implemented in Tinyos-2.1 and extensively evaluated in TOSSIM, the simulator of sensor networks. Experimental result shows that Log A outperforms the traditional CSMA protocol and an existing reactive concurrent MAC in terms of throughput, delivery latency, and energy consumption.