You-Chiun Wang

Efficient deployment algorithms for ensuring coverage and connectivity of wireless sensor networks

Sensor deployment is a critical issue since it reflects the cost and detection capability of a wireless sensor network. Although lots of work has addressed this issue, most of them assume that the sensing field is an open space and there is a special relationship between the communication range and sensing range of sensors. In this work, we consider the sensing field as an arbitrary-shaped region possibly with obstacles. Besides, we allow an arbitrary relationship between the communication range and sensing range, thus eliminating the constraints of existing results. Our approach is to partition the sensing field into smaller sub-regions based on the shape of the field, and then to deploy sensors in these sub-regions. Simulation results show that our method requires fewer sensors compared to existing results.

Efficient Placement and Dispatch of Sensors in a Wireless Sensor Network

Sensor deployment is a critical issue because it affects the cost and detection capability of a wireless sensor network. In this work, we consider two related deployment problems: sensor placement and sensor dispatch. The former asks how to place the least number of sensors in a field to achieve sensing coverage and network connectivity, and the latter asks how to determine from a set of mobile sensors a subset of sensors to be moved to an area of interest with certain objective functions such that the coverage and connectivity properties are satisfied. This work is targeted toward planned deployment. Our solution to the placement problem allows an arbitrary-shaped sensing field possibly with arbitrary-shaped obstacles and an arbitrary relationship between the communication distance and sensing distance of sensors and, thus, significantly relaxes the limitations of existing results. Our solutions to the dispatch problem include a centralized one and a distributed one. The centralized one is based on adopting the former placement results and converting the problem to the maximum-weight maximum-matching problem with the objective of minimizing the total energy consumption to move sensors or maximizing the average remaining energy of sensors after movement. Designed in a similar way, the distributed one allows sensors to determine their moving directions in an autonomous manner.

Distributed Deployment Schemes for Mobile Wireless Sensor Networks to Ensure Multilevel Coverage

One of the research issues in wireless sensor networks (WSNs) is how to efficiently deploy sensors to cover an area. In this paper, we solve the k-coverage sensor deployment problem to achieve multi-level coverage of an area I. We consider two sub-problems: k-coverage placement and distributed dispatch problems. The placement problem asks how to determine the minimum number of sensors required and their locations in I to guarantee that I is k-covered and the network is connected; the dispatch problem asks how to schedule mobile sensors to move to the designated locations according to the result computed by the placement strategy such that the energy consumption due to movement is minimized. Our solutions to the placement problem consider both the binary and probabilistic sensing models, and allow an arbitrary relationship between the communication distance and sensing distance of sensors. For the dispatch problem, we propose a competition-based and a pattern-based schemes. The former allows mobile sensors to bid for their closest locations, while the latter allows sensors to derive the target locations on their own. Our proposed schemes are efficient in terms of the number of sensors required and are distributed in nature. Simulation results are presented to verify their effectiveness.

iMouse: An Integrated Mobile Surveillance and Wireless Sensor System

Incorporating the environment-sensing capability of wireless sensor networks into video- based surveillance systems can provide advanced services at a lower cost than traditional surveillance systems.The integrated mobile surveillance and wireless sensor system (iMouse) uses static and mobile wireless sensors to detect and then analyze unusual events in the environment.

Mobility management algorithms and applications for mobile sensor networks

Wireless sensor networks (WSNs) offer a convenient way to monitor physical environments. In the past, WSNs are all considered static to continuously collect information from the environment. Today, by introducing intentional mobility to WSNs, we can further improve the network capability on many aspects, such as automatic node deployment, flexible topology adjustment, and rapid event reaction. In this paper, we survey recent progress in mobile WSNs and compare works in this field in terms of their models and mobility management methodologies. The discussion includes three aspects. Firstly, we discuss mobility management of mobile sensors for the purposes of forming a better WSN, enhancing network coverage and connectivity, and relocating some sensors. Secondly, we introduce path-planning methods for data ferries to relay data between isolated sensors and to extend a WSNs lifetime. Finally, we review some existing platforms and discuss several interesting applications of mobile WSNs. Copyright

Exploring Load-Balance to Dispatch Mobile Sensors in Wireless Sensor Networks

In this paper, a hybrid sensor network consisting of static and mobile sensors is considered, where static sensors are used to detect events, and mobile sensors can move to event locations to conduct more advanced analysis. By exploring the load balance concept, we propose a CentralSD algorithm to efficiently dispatch mobile sensors. Our algorithm is general in that the numbers of mobile sensors and events can be arbitrary. When mobile sensors are more than event locations, we transform the dispatch problem to a maximum-matching problem in a weighted bipartite graph. When there are fewer mobile sensors than event locations, we propose an efficient clustering scheme to group event locations so that the maximum-matching approach can still be applied. To reduce message cost, we also develop a distributed GridSD algorithm. Simulation results are presented to verify the effectiveness of the proposed algorithms.

Exploiting Spectral Reuse in Routing, Resource Allocation, and Scheduling for IEEE 802.16 Mesh Networks

The IEEE 802.16 standard for wireless metropolitan area networks (WMANs) is defined to meet the need for wide-range broadband wireless access at low cost. The objective of this paper is to study how to exploit spectral reuse in resource allocation in an IEEE 802.16 mesh network, which includes routing tree construction (RTC), bandwidth allocation, time-slot assignment, and bandwidth guarantee of real-time flows. The proposed spectral reuse framework covers bandwidth allocation at the application layer, RTC and resource sharing at the medium access control (MAC) layer, and channel reuse at the physical layer. To the best of our knowledge, this is the first paper that formally quantifies spectral reuse in IEEE 802.16 mesh networks and exploits spectral efficiency under an integrated framework. Simulation results show that the proposed schemes significantly improve the throughput of IEEE 802.16 mesh networks.

Efficient eNB deployment strategy for heterogeneous cells in 4G LTE systems

Base station deployment is an important issue in cellular communication systems because it determines the cost to construct and maintain a system and also the service quality to users. Conventional 2G and 3G systems assume that base stations are identical in the sense that they have the similar coverage range. For 4G systems, LTE introduces the concept of heterogeneous base stations (also called eNBs), which supports different sizes of coverage range. Given the user distribution and demands in a service area, the problem of deploying heterogeneous eNBs is NP-hard. Therefore, we propose a four-stage eNB deployment strategy to efficiently solve the problem. Our strategy first employs a geometric approach to provide the basic coverage to the service area. Then, it adaptively adjusts the cell range to satisfy the user demands under the power and bandwidth constraints on each eNB. Simulation results verify that the proposed strategy not only significantly saves the system cost, but also reduces the power consumption while balances the traffic loads of eNBs.

A jamming-based MAC protocol to improve the performance of wireless multihop ad-hoc networks

Summary One critical issue in multihop ad-hoc networks is the medium access control (MAC). The IEEE 802.11 MAC protocol is originally designed for fully connected, one-hop ad-hoc networks but not for multihop ad-hoc networks. In addition to the well known hidden-terminal problem, we found that IEEE 802.11 also suffers from an erroneous reservation problem which occurs when RTS-CTS exchange fails but the channel is incorrectly reserved. In this paper, we propose a jamming-based MAC (JMAC) protocol that is not only free from both the hiddenterminal and the erroneous reservation problems but also allows more concurrent transmission/receipt activities for stations within each other’s transmission range. The idea behind the JMAC is to separate source stations’ traffic from destination stations’ traffic into different channels (i.e. dividing the shared medium into two channels), and explicitly signal the channel status by jamming the channels. Simulation results show that although the channel division incurs some cost, the advantages of being free from the erroneous reservation and the hidden-terminal problems, and the benefits of more concurrent transmissions will compensate the cost and provide higher channel utilization when data frame size is median or large. Copyright # 2004 John Wiley & Sons, Ltd.

A Two-Phase Dispatch Heuristic to Schedulethe Movement of Multi-Attribute MobileSensors in a Hybrid Wireless Sensor Network

The paper considers a hybrid wireless sensor network with static and mobile sensors, where each static sensor can detect only one attribute of event while a mobile sensor can analyze multiple attributes of events. Static sensors monitor the environment and report where events appear. Mobile sensors then move to these event locations to conduct more in-depth analysis. A critical issue is how to schedule the traveling paths of mobile sensors so as to extend their lifetime. We formulate this issue as a multi-round multi-attribute sensor dispatch problem and prove it to be NP-complete. Then, we develop a two-phase dispatch heuristic that adopts the concepts of Pareto optimality and spanning-tree construction. Our heuristic allows arbitrary numbers of mobile sensors and event locations and tries to reduce and balance the energy consumption of mobile sensors in each round. Through simulations, we verify the effectiveness of our heuristic. The paper contributes in defining a new sensor dispatch problem and developing an energy-efficient solution to the problem.