For wireless sensor networks in which resources are limited and network topology dynamically changes, we propose the one-hop neighbor based broadcast scheduling (ONBS) algorithm to provide reliable delivery service of broadcast packets. The proposed algorithm reduces the scheduling overhead by allowing each joining node to decide its broadcast schedule based on only its one-hop neighbor information in an on-line and distributed manner. Also, once the broadcast schedule is decided, it is not changed to accommodate a newly joining node in order to prevent the consecutive changes of existing schedules. The network simulation results show that the proposed algorithm provides low latency and high reachability despite low overhead and on-line algorithm design.

Next generation wired/wireless networks will be based on IP technology. In the IP based networks, it is crucially required to support seamless mobility especially for proving real-time services in the mobile environment. The conventional Mobile IP protocols cannot satisfy such seamless mobility requirements for real-time services. Therefore various extensions of Mobile IP are being proposed. In this paper, we propose a new handover scheme to enhance the existing tunnel-based fast handover method, which is a typical Mobile IP extension to support seamless mobility. It is shown that the proposed method reduces the traffic overhead in the networks. It is expected that the proposed method will be particularly useful in the IP-based networks in which there are a number of users simultaneously using the long-lived real-time services, or in the condition that the traffic overhead is considered as a critical performance measure.

This paper proposes T-CROM (Time-delayed Collaborative ROuting and MAC) protocol, that allows collaboration between network and MAC layers in order to extend the lifetime of MANETs in a resources-limited environment. T-CROM increases the probability of preventing energy-poor nodes from joining routes by using a time delay function that is inversely proportional to the residual battery capacity of intermediate nodes, making a delay in the route request (RREQ) packets transmission. The route along which the first-arrived RREQ packet traveled has the smallest time delay, and thus the destination node identifies the route with the maximum residual battery capacity. This protocol leads to a high probability of avoiding energy-poor nodes and promotes energy-rich nodes to join routes in the route establishment phase. In addition, T-CROM controls the congestion between neighbors and reduces the energy dissipation by providing an energy-efficient backoff time by considering both the residual battery capacity of the host itself and the total number of neighbor nodes. The energy-rich node with few neighbors has a short backoff time, and the energy-poor node with many neighbors gets assigned a large backoff time. Thus, T-CROM controls the channel access priority of each node in order to prohibit the energy-poor nodes from contending with the energy-rich nodes. T-CROM fairly distributes the energy consumption of each node, and thus extends the network lifetime collaboratively. Simulation results show that T-CROM reduces the number of total collisions, extends the network lifetime, decreases the energy consumption, and increases the packet delivery ratio, compared with AOMDV with IEEE 802.11 DCF and BLAM, a battery-aware energy efficient MAC protocol.

In this paper, an efficient node-level target classification scheme in wireless sensor networks (WSNs) is proposed. It uses acoustic and seismic information, and its performance is verified by the classification accuracy of vehicles in a WSN. Because of the hard limitation in resources, parametric classifiers should be more preferable than non-parametric ones in WSN systems. As a parametric classifier, the Gaussian mixture model (GMM) algorithm not only shows good performances to classify targets in WSNs, but it also requires very few resources suitable to a sensor node. In addition, our sensor fusion method uses a decision tree, generated by the classification and regression tree (CART) algorithm, to improve the accuracy, so that the algorithm drives a considerable increase of the classification rate using less resources. Experimental results using a real dataset of WSN show that the proposed scheme shows a 94.10% classification rate and outperforms the k-nearest neighbors and the support vector machine.

Existing query tree protocols deal with RFID tags in a blind manner. They query tags in a fixed bit order based on the assumption that the tag ID numbers are uniformly distributed throughout the range of the entire ID space because readers have no prior knowledge of the tags. This paper attempts to distinguish RFID applications where readers are already aware of all tags used by the application. We propose a heuristic query tree (H-QT) protocol that uses heuristic to select effective bits from known tags for the best queries in a divide and conquer approach. The performance evaluation shows that the proposed protocol is superior to original query tree protocols because it significantly reduces the number of tag collisions and no tag response.