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Node location is of great significance as a supporting technology of wireless sensor network (WSN). The information without position would be greatly devalued. So this paper is about location algorithm for nodes of ship-borne WSN based on research on structure of ship and work environment of ship-borne WSN. The whole location process consists of two steps: one is location algorithm among cabins (LAAC), and the other one is location algorithm in the cabin (LAIC). LAAC refers to location with the topology of ship-borne WSN. We can learn which cabin the node lies in. LAIC refers to location based on received signal strength indication (RSSI), we can get distance relationship between nodes by RSSI, and then obtain the specific location by solving this distance relationship. In the last part, this paper verifies the designed location algorithm by experimenting on "A" ship. Experiments show that the location algorithm designed by this paper is feasible. [ABSTRACT FROM AUTHOR]

In vehicular networks, the multihop message delivery from information source to moving vehicles presents a challenging task due to many factors, including high mobility, frequent disconnection, and real-time requirement for applications. In this paper, we propose a moving target oriented opportunistic routing algorithm in vehicular networks for message delivery from information source to a moving target vehicle. In order to adapt the constantly changing topology of networks, the forwarding decisions are made locally by each intermediate vehicle based on the trajectory information of the target vehicle. The simulation and real trace experiment show that our design provides an efficient message delivery with a higher success ratio, shorter success time, and lower transmission overhead compared with other reference approaches. [ABSTRACT FROM AUTHOR]

Dynamic service composition provides us with a promising approach to cooperate different sensor nodes in WSN to build complex applications based on their basic functions. Usually multiple nodes located in different regions provide data with different security levels, and it is critical to ensure the security of the information flow in the composite services. However, the energy-limited nature of sensor nodes in WSN poses a significant challenge for the centralized information flow verification with which the verification node needs to consume lots of computation and network resources. In this paper, we specify the security constraints for each service participant to secure the information flow in a service chain based in the lattice model and then present a distributed verification framework that cooperates different service participants to verify their information flow policies distributively The evaluation results show a significant decrease on the verification cost of the single verification node, which provides a better load balance in each sensor node. [ABSTRACT FROM AUTHOR]

With the development of wireless sensor network (WSN) technologies, WSNs have been applied in many areas. In all WSN technologies, localization is a crucial problem. Traditional localization approaches in WSNs mainly focus on calculating the current location of sensor nodes or mobile objects. In this paper, we study the problem of future location prediction in WSNs. We assume the location histories of mobile objects as a rating matrix and then use a random walk based social recommender algorithm to predict the future locations of mobile objects. Experiments show that the proposed algorithm has better prediction accuracy and can solve the rating matrix sparsity problem more effectively than related works. [ABSTRACT FROM AUTHOR]

In designing wireless sensor networks, it is important to reduce energy dissipation and prolong network lifetime. This paper presents research on the existing clustering algorithm applied in heterogeneous sensor networks and then puts forward an energy-efficient prediction clustering algorithm, which is adaptive to sensor networks with energy and objects heterogeneous. This algorithm enables the nodes to select the cluster head according to factors such as energy and communication cost, thus the nodes with higher residual energy have higher probability to become a cluster head than those with lower residual energy, so that the network energy can be dissipated uniformly. In order to reduce energy consumption when broadcasting in clustering phase and prolong network lifetime, an energy consumption prediction model is established for regular data acquisition nodes. Simulation results show that compared with current clustering algorithms, this algorithm can achieve longer sensor network lifetime, higher energy efficiency, and superior network monitoring quality. [ABSTRACT FROM AUTHOR]

In wireless sensor networks, secure data aggregation is very important for reducing the quantity of data transmitted and prolonging the lifetime of wireless sensor networks. When wireless sensor networks are deployed in untrusted and hostile environments, their nodes are often compromised, which reduces the security and reliability of the transmitted data. Compromised nodes can inject erroneous data, selectively forward data to an adversary, impersonate legal nodes to join routing paths, and disrupt data transmission during the data-aggregation operation. Previous researchers have relied on reputation system to find compromised nodes and prevent attacks during the data-aggregation operation. In this paper, we propose an improved reliable, trust-based, and energy-efficient data-aggregation protocol for wireless sensor networks. We call the protocol the iRTEDA protocol, and it combines the reputation system, residual energy, link availability, and a recovery mechanism to improve secure data aggregation and ensure that the network is secure, reliable, and energy-efficient. Simulations have shown that the iRTEDA protocol exceeds the performances of other protocols from the perspectives of the accuracy of the data, the reliability of the routing path, the consumption of energy, and the lifetime of secure data aggregation. [ABSTRACT FROM AUTHOR]

Opportunistic activity recognition as research discipline is characterized by the fact that human activities (and more generally the context) shall be recognized with sensors that are initially unknown to the system. In contrast to "traditional" applications -- where sensors, their modalities, locations, and working characteristics have to be defined at design time-opportunistic systems do not rely on an initially defined and fixed sensing infrastructure. Sensors have to be utilized upon their spontaneous availability and activity recognition capabilities and dynamic sensor ensembles have to be configured at runtime with respect to maximized recognition accuracy and minimized energy consumption. This requirement contains two research challenges that this paper tackles: (i) estimating the accuracy of an ensemble without being able to compare the output in the form of recognized activity classes to a (labeled) ground truth and (ii) optimizing the accuracy/energy trade-off by applying exact and heuristic methods adapted for cooperative sensor ensembles. [ABSTRACT FROM AUTHOR]

Many existing routing protocols in Mobile Ad hoc Networks (MANETs) focus on finding paths in dynamic networks without considering security. In this paper, we propose a trust model which evaluates neighbours' direct trust by factors of encounter time, mobility, and successful cooperation frequency.The revised D-S evidence theory is used to combinemultiple recommended pieces of evidence and obtain the recommended trust value. Then based on the novel trust mechanism, we propose a trusted routingprotocol named TDS-AODVprotocol by extending the AOD Vprotocol. In this protocol, a nodemakes a routing decision according to the trust values of its neighbour nodes. Finally, two routes are built: themain route with highest route trust value in the candidate routes and a backup route. Simulation results reveal that TDS-AODV can eliminate malicious nodes effectively when building the route; furthermore, it also achieves better performance than TAODV and AODV in terms of throughput, packet delivery ratio, and average end to end delay. [ABSTRACT FROM AUTHOR]