Kui Huang

Data Gathering Protocols for Wireless Sensor Networks with Mobile Sinks

Wireless sensor networks with mobile sinks (mWSN) have attracted a lot of attention recently. In an mWSN, each mobile sink can move freely and unpredictably. In this paper, we design two efficient data gathering protocols for mWSNs. The first protocol (called AVRP) adopts Voronoi scoping plus dynamic anchor selection to handle the sink mobility issue. In the second protocol (called TRAIL), the trail of mobile sink is used for guiding packet forwarding as sinks move in the network. In TRAIL, to forward a data packet, integration of trail-based forwarding and random walk is used. Specifically, when no fresh trail of any sink is known, random walk is used; once a sensor on a fresh sink trail is reached, data packet will be forwarded along the trail. TRAIL is simple to implement and has small protocol overhead. Simulation results show the designed protocols have high performance and further AVRP is suitable for mWSNs with heavy traffic while TRAIL is suitable for mWSNs with light traffic.

D-ODMRP: a destination-driven on-demand multicast routing protocol for mobile ad hoc networks

This article proposes a destination-driven on-demand multicast routing protocol (D-ODMRP) to improve the multicast forwarding efficiency in mobile ad hoc networks (MANETs). In D-ODMRP, the path from the multicast source to a multicast destination tends to use those paths passing through another multicast destination. If such multiple paths are available, the one leading to the least extra cost is preferred. This destination-driven strategy is introduced into the on-demand construction process of a multicast forwarding structure in a popular multicast protocol ODMRP. Simulation results show that D-ODMRP can significantly improve the forwarding efficiency as compared with ODMRP. Moreover, the destination-driven strategy can also be introduced into other existing multicast routing protocols for MANETs.

An energy-efficient routing protocol with controllable expected delay in duty-cycled wireless sensor networks

Low duty cycled scheduling can largely prolong the lifetime of a wireless sensor network (WSN) but also brings longer end-to-end (E2E) delivery delay. In this paper, our design objective is to pursue the near minimum E2E energy consumption subject to a desired success ratio that the E2E delay is below a delay bound. Accordingly, we design a Markov decision process based geographic routing protocol such that each relay node currently holding a packet makes localized forwarding decision on continuing waiting or transmitting immediately to the so far best forwarder candidate based only on local network state information. Simulation results show that the designed protocol can achieve expected success ratio subject to given delay bound and also high energy use efficiency.

An Efficient Multi-Stage Data Routing Protocol for Wireless Sensor Networks with Mobile Sinks

In a wireless sensor network with mobile sinks, the maintenance of efficient data delivery structure often brings a large amount of control overhead, which may offset the benefit of introducing mobile sinks. In this paper, we propose a multi-stage data routing protocol (called MLRP) to address this problem. To reduce the protocol overhead, MLRP integrates layered Voronoi scoping and dynamic anchor selection. Such design is expected to greatly reduce the diffusion scope of sink movement updates and thus reduce the frequency at which the data delivery structure is refreshed. Simulation results show that MLRP can effectively reduce the protocol overhead while ensuring high packet delivery ratio as compared with existing work.

A gradient-based multiple-path routing protocol for low duty-cycled wireless sensor networks

Routing in a low duty-cycled wireless sensor network WSN has attracted much attention recently because of the challenge that low duty-cycled sleep scheduling brings to the design of efficient distributed routing protocols for such networks. In a low duty-cycled WSN, a big problem is how to design an efficient distributed routing protocol, which uses only local network state information while achieving low end-to-end E2E packet delivery delay and also high packet delivery efficiency. In this paper, we study low duty-cycled WSNs wherein sensor nodes adopt pseudorandom sleep scheduling for energy saving. The objective of this paper is to design an efficient distributed routing protocol with low overhead. For this purpose, we design a simple but efficient hop-by-hop routing protocol, which integrates the ideas of multipath routing and gradient-based routing for improved routing performance. We conduct extensive simulations, and the results demonstrate the high performance of the proposed protocol in terms of E2E packet delivery latency and packet delivery efficiency as compared with existing protocols. Copyright

MAX–MIN aggregation in wireless sensor networks: mechanism and modeling

In-network aggregation is crucial in the design of a wireless sensor network (WSN) due to the potential redundancy in the data collected by sensors. Based on the characteristics of sensor data and the requirements of WSN applications, data can be aggregated by using different functions. MAX—MIN aggregation is one such aggregation function that works to extract the maximum and minimum readings among all the sensors in the network or the sensors in a concerned region. MAX—MIN aggregation is a critical operation in many WSN applications. In this paper, we propose an effective mechanism for MAX—MIN aggregation in a WSN, which is called Sensor MAX—MIN Aggregation (SMMA). SMMA aggregates data in an energy-efficient manner and outputs the accurate aggregate result. We build an analytical model to analyze the performance of SMMA as well as to optimize its parameter settings. Simulation results are used to validate our models and also evaluate the performance of SMMA. Copyright

Measurement-Based Access Point Deployment Mechanism for Indoor Localization

In this paper, we study how to deploy new access points (AP) to achieve improved accuracy for WiFi- based indoor localization systems. Existing mechanisms in this aspect are typically simulation based and further they do not consider how to use pre-existing APs in target environment for achieving high localization performance. To overcome these issues, in this paper, we propose a measurement-based AP deployment mechanism (MAPD). MAPD takes advantage of those pre-existing APs to identify candidate positions with poor localization accuracy for deploying new APs. We then collect the fingerprints for all possible AP deployment layouts via over- deployment of APs, one at each candidate position. Finally, we present a greedy search algorithm to identify m positions out of the n candidate positions (mn) while minimizing the location error. Experimental results demonstrate that the localization errors can be largely reduced: Mean error distance can be reduced by 0.56 meter (26%) and 0.17 meter (10%) as compared with the case without deploying new APs and previous work, respectively; Moreover, the maximum location error can be reduced by 1.53 meter (27%) and 0.51 meter (11%), respectively.