• 期刊
• OpenAccess

Sensor Scheduling Schemes and Network Coverage in Dense Wireless Sensor Networks

Energy optimization is a critical issue in randomly deployed dense wireless sensor networks (WSNs). In dense WSNs, the transmitted signal from a source sensor suffers by the interfering signals from surrounding sensors and unwanted events. In such network scenarios nodes are more likely to become non-functional because of noisy environment and residual battery energy depletion etc. This further arises the need for redundant sensor deployment and an energy efficient solution is to schedule sensors to go into sleep state periodically. In this present paper, we address a probabilistic coordinated sensor scheduling scheme to overcome the redundancy in sensor deployment and conserve energy thus extending the overall network lifetime. This scheme uses the concept of inhibition distance of hard-core point process (HCPP) for coordination among sensors with little communication overhead. We analyze the influence of various channel parameters and interferers on sensor activation probability. Further, we perform Monte Carlo simulation and show that the coverage fraction achieved by the coordinated scheduling outperforms random scheduling at same active sensor density. We also study the impact of node failure and K-coverage degree on the achievable coverage fraction in interference limited WSNs.

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• OpenAccess

Toward Pattern and Preference-Aware Travel Route Recommendation over Location-Based Social Networks

Travel route recommendation for Location-based Social Networks (LBSNs) has been received much attention to research people's activity patterns and personalized preferences. Existing travel route recommendation schemes in literature are confronted with three problems: (1) the location is limited in practical environment, and the data sparsity is always happened when they recommend travel route services based on the location information; (2) they fail to consider the order of mobile trajectory, which is valuable to reflect the interest and preference of users for travel route recommendation; (3) they can't be adapted to different kinds of POI category, which causes the extendibility is low. In this paper, we propose PP-TRR, a pattern and preference-aware travel route recommendation scheme to tackle the above problems. First, we construct the system architecture of our proposed travel route recommendation. Then, we model the movement pattern of each user. Finally, we present the travel route recommendation scheme to recommend personalized services for targeted users. The experimental results show that our method outperforms the existing method.

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• OpenAccess

Dimension based Localization Technique in Internet of Things: A Fuzzy Driven Approach for Mobile Target

The process of extracting the accurate geographical position of mobile target has a dominant efficacy on the performance of a wireless sensor network. The location information of moving node is a mandate requirement to process the data collected by the sensor nodes. The localization technique that finds the exact location of target node in a Internet of Things framework is applied for domain-specific applications. In this paper, a fuzzy driven approach embedded with Dimensionality based Particle Swarm Optimization algorithm is proposed. The Dimensionality based Particle Swarm Optimization (DPSO) is a variant of the traditional PSO and the particle deployment is done in each dimension of the co-ordinate of target node to obtain optimized values in the individual dimension. The anisotropic properties of propagation media (i.e., environmental factors) and the characteristics of devices (i.e., sending power) are considered to compute the Received Signal Strength (RSS). An Adaptive Neuro-Fuzzy Inference System (ANFIS) is developed to study these radio irregularities and a distinct set of rules are framed in the training phase to select the appropriate attenuation exponent value. The proposed algorithm can be applied in outdoor anisotropic environments. The DPSO model outperforms well in all localization instances for three test cases containing different trajectories, where the path of target node is randomly chosen. The results were compared with the existing algorithms such as PSO and HPSO in terms of average localization error and number of iterations required to attain convergence.

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• OpenAccess

Optimized Handover Mechanism in Heterogeneous Vehicular Communication Systems

In current years, vehicular communication systems are evolving for Intelligent Transportation System (ITS) by providing its wireless network services with increasing demand for high data rate. Vehicular communications supports for various applications that include safety, traffic efficiency and infotainment. However, the high mobility of vehicles and frequent topology changes in such communication systems pose challenges for the mobility management, including frequent, unnecessary and ping-pong handovers, with additional problems related to increased delay and packets loss rate, and failure of the handover process. In this article, we propose a solution to optimize the handover in vehicular networks. Our solution resides in creating a novel multi-criteria network selection mechanism. The objectives of the proposed solution are: to decrease handover failure, handover delay, and packet loss rates, also to distribute traffic load uniformly among available networks to improve the average system resource utilization. The proposed mechanism is based on Fuzzy Logic scheme to support the decision making process. Simulation results demonstrate that, compared to existing works, the proposed approach significantly reduces the handover failure, handover delay and packet loss rates. In addition, the proposed solution achieved an improvement in network resources utilization.

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• OpenAccess

A Clustering Algorithm of Underwater Acoustic Sensor Networks based on Hierarchical 3D Mesh

Underwater acoustic sensor networks (UASNs) are important technical means to explore the ocean realm. As a strategic measure, clustering techniques balance the network energy and survival time obviously. This paper proposes a clustering algorithm for UASNs. First, an UASN structure of hierarchical 3D mesh is defined, and an energy consumption model is built. Second, the algorithm based on the designed framework is presented, including the basic clustering messages, the setup phase and the data transmission phase. Finally, experiment of the algorithm based on WOSS and MATLAB is implemented, and compared with DS-VBF, IAR, and GEDAR in terms of the average end-to-end delay, the survival rate, the number of survival nodes, the number of clusters, and the coverage ratio. Results demonstrate that a tradeoff between clustering performance and network survival is achieved and the algorithm is suitable for UASNs.

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• OpenAccess

Cooperative Jamming for Secrecy of Wireless Communications

This paper investigates cooperative jamming for security in wireless networks. No location information of eavesdropper is available and no constraint on the number of eavesdroppers is presupposed. A cooperative jamming strategy is proposed for jamming the eavesdroppers anywhere in the network, even if they are located quite close to the sender or the receiver. The basic ideas behind the strategy are to defeat eavesdroppers by a divide and conquer strategy, and exploit the helpful interference from the sender and the receiver to circumvent the nearby eavesdropper problem. Analysis and simulation results reveal that cooperative jamming can improve the secure performance and can be employed to establish initial connections in wireless networks.

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• OpenAccess

Efficient RSU Placement Schemes in Urban Vehicular Ad Hoc Networks

Roadside units play a vital role in vehicular ad hoc networks. Essential benefits of roadside units include providing information about traffic jams, accidents, and emergency messages to drivers in real-time. Because roadside units are expensive, developing a method to deploy them cost-effectively is pertinent. In this paper, we propose a roadside unit placement method using a limit number of roadside units to cover the intersections in an urban vehicular ad hoc network. Our strategy focuses on identifying potential candidate locations to place roadside units and minimizing the number of roadside units to deploy. Simulation results show that the proposed method outperforms existing methods in terms of the number of roadside units being used and the communication coverage.

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• OpenAccess

A QC-LDPC Code Based Digital Signature Algorithm

Courtois-Finiasz-Sendrier (CFS) digital signature algorithm, which proposed in 2001, is the most important code based digital signature algorithm and can resist the known attack of quantum algorithms such as Shor algorithm and Grover algorithm. But the efficiency of CFS is very low because of the extremely low signing speed and the large public key size. In this paper, a variation of CFS algorithm is presented. Instead of the Goppa code and the Patterson decoding algorithm, the new algorithm selects the Quasi-Cyclic Low Density Parity Check (QC-LDPC) code and the Belief Propagation (BP) decoding algorithm in the signing process. Compared with CFS algorithm, the new algorithm greatly reduces the storage space of public key and improves the efficiency of signature without compromising the security.

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• OpenAccess

A Cost-Efficient Virtual Sensor Management Scheme for Manufacturing Network in Smart Factory

The information comes from physical shop floor and manufacturing process is closely monitored and coordinated under the framework of cyber-physical system in Industry 4.0. Wireless sensor networks are deployed to collect the massive amounts of data generated in a smart factory. Researchers employ sensor cloud to facilitate the management of a large scale deployment of wireless sensor nodes. Facing with lots of concurrent sensing demands of users administrators of a manufacturing network need to deal with the mapping of physical sensors and virtual sensors. We propose a cost-efficient virtual sensor management scheme which is able to accord an overall virtual sensor instantiation result for the whole manufacturing network. Both the architecture of the manufacturing network and the application scenario are modeled by entities, actions, and messages. The key component of the proposed model is called k resource scheduler. Different resource scheduling algorithms could be applied to the k resource scheduler, and thus make our model flexible. Three resource scheduling algorithms are devised to tackle the problem of virtual sensor management. The effectiveness of the proposed model is verified by simulation experiments and a comprehensive analysis of the experimental results is provided.

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• OpenAccess

Frequency Estimation by the Method of Minimum Mean Squared Error and P-value Distributed in the Wireless Sensor Network

The development of electronic equipment technology, followed by the advancement of electronic systems, has increased the sensitivity of signal identification. Control and monitoring is a matter that forces existing engineers to make decisions and protect systems. In this paper, the distributed least mean p-norm method (dLMP) has been evaluated and evaluated to estimate the distributed frequency of the signal in three incremental, consensus, and scattering strategies. In the proposed method, based on the definition of appropriate cost functions, a distributed method is used to estimate the frequency of common sinusoidal signals with a common frequency in a wireless sensor network. The results of simulation with MATLAB software showed that the proposed algorithm has better and more favorable performance compared to other methods such as single-sensor and distributed methods. In the proposed method simultaneously with the distributed frequency estimation, the domain and phase estimation with a suitable and fast convergence is possible locally. Due to this advantage compared to the distributed filter method, the proposed method is less complicated and the convergence rate is appropriate and better.