Shukui Zhang

A Routing Algorithm Based on Dynamic Forecast of Vehicle Speed and Position in VANET

Considering city road environment as the background, by researching GPSR greedy algorithm and the movement characteristics of vehicle nodes in VANET, this paper proposes the concept of circle changing trends angle in vehicle speed fluctuation curve and the movement domain and designs an SWF routing algorithm based on the vehicle speed point forecasted and the changing trends time computation. Simulation experiments are carried out through using a combination of NS-2 and VanetMobiSim software. Compared with the performance of the SWF-GPSR protocol with general GPSR, 2-hop C-GEDIR, and the GRA and AODV protocols, we find that the SWF algorithm has a certain degree of improvement in routing hops, the packet delivery ratio, delay performance, and link stability.

Cooperative Data Processing Algorithm Based on Mobile Agent in Wireless Sensor Networks

Mobile agent (MA) systems provide new capabilities for energy-efficient data processing by flexibly planning its itinerary for facilitating agent-based data collection and aggregation. In this paper, we present a cooperative data processing algorithm based on mobile agent (MA-CDP), and considers MA in multihop environments and can autonomously clone and migrate themselves in response to environmental changes. MA accounts for performing data processing and making data aggregation decisions at nodes rather than bringing data back to a central processor, and redundant sensory data will be eliminated. The results of our simulation show that MA-based cooperative data processing provides better performance than directed diffusion in terms of end-to-end delivery latency, packet delivery ratio, and energy consumption.

An Efficient Reliable Communication Scheme in Wireless Sensor Networks Using Linear Network Coding

We address the modeling and design of linear network coding (LNC) for reliable communication against multiple failures in wireless sensor networks (WSNs). To fulfill the objective, we design a deterministic LNC scheme RDLC based on the average number of path failures simultaneously happening in the network other than the maximum number of path failures. The scheme can significantly improve the network throughput comparing with the traditional approaches. In our study, we also investigate the potential of random linear code RRLC for providing reliable communication in WSNs and prove the low bound of the probability that the RRLC can provide the reliable communication. Finally, extensive simulation experiments have been conducted, and the results demonstrate the effectiveness of the proposed LNC schemes.

A Diagnosis-Based Clustering and Multipath Routing Protocol for Wireless Sensor Networks

In wireless sensor networks, it is of great importance for fault diagnosis to ensure the gathering information accuracy and reduce energy additionally consumed by faulty nodes, for the deployment of a large number of sensor nodes in hostile environment. In this paper, we propose an energy-efficient data collection protocol which consists of clustering and multipath routing. Clustering based on fault diagnosis eliminates the possibility of cluster heads (CHs) acting by faulty nodes which reduce energy consumption and fault information transmission. Multipath routing provided by directed acyclic graph (DAG) increases system fault tolerance. Furthermore, clustering and multihop routing consider residual energy and routing cost, respectively; thus balanced energy consumption is achieved. Performance analysis shows that the message complexity disseminated in clustering and fault diagnosis is acceptable. Simulations demonstrate that the protocol has better energy efficiency compared with other related protocols.

An Efficient Clustering Algorithm in Wireless Sensor Networks Using Cooperative Communication

Processing the gathered information efficiently is a key functionality for wireless sensor networks. In generally, the sensor networks often use in-network data aggregation and clustering to optimize network communication. The set of aggregating nodes forms a dominating set of the network graph. Finding the weakly connected dominating set (WCDS) is a promising approach for clustering the WSN. However, finding a minimum WCDS is NP-hard problem for most graphs, and a host of approximation algorithm has been proposed. The aim of the paper is to construct a minimum WCDS as a clustering scheme for WSN. Our clustering schemes construction algorithm includes two phases. First of all, we construct a maximal data aggregation tree (DAT) of the network. The second phase of the algorithm is to choose the nodes (called connectors) to make the WCDS connected. The correctness and performance of our algorithms are confirmed through theoretical analysis and comprehensive simulations.

Cooperative Transmission in Cognitive Radio Ad Hoc Networks

Cognitive radio technology is the key to realize dynamic spectrum access system and promote the spectrum utilization through exploiting the spectrum holes left by primary users. However, the spatial heterogeneity of spectrum availability imposes special challenges for efficient utilization of the spectrum resources for cognitive radio ad hoc networks (CRAHNs). The cross-layer cooperative transmission scheme is a promising approach to improve the efficiency of spectrum utilization and improve the performance of cognitive radio networks. Such an approach leverages relay-assisted discontiguous OFDM (DOFDM) for data transmission at physical and MAC layers in a basic three-node configuration. With this scheme, a relay node will be selected that can bridge the source and the destination using its common channels between those two nodes. In this paper, we investigate the application of such a cooperative transmission scheme to address the spectrum heterogeneity issue in CRAHNs. In particular, we describe several types of cooperative transmission and formulate a new resource allocation problem with joint relay selection and channel allocation. We propose a heuristic algorithm to solve the resource allocation problem, which is based on the metric of utility-spectrum ratio of transmission groups. Simulations demonstrate the performance improvement of the cooperative transmission over the direct transmission.

Data Dissemination in Mobile Wireless Sensor Network Using Trajectory-Based Network Coding

With GPS devices spreading, more mobile nodes are guided by the navigation systems to select better paths. The performance of mobile networks can be improved with the navigation information in nodes. In this paper, we propose a trajectory-based network coding (TBNC) method to disseminate data in mobile wireless sensor network (MWSN). It is designed according to the characteristics of MWSN and is appropriate for the mobile nodes that share anonymously its GPS pretrajectory for the higher bandwidth. Data are disseminated in the topology that is predicted on the basis of the trajectory information. Network coding is used to adapt for the dynamics velocity of mobile nodes. Simulation results show that TBNC is able to cut down 1/2 overhead messages of PRoPHET when mobile nodes share GPS trajectory. It improves the reliability and scalability of MWSN.

Uncertainty-Aware Sensor Deployment Strategy in Mixed Wireless Sensor Networks

Deployment is a fundamental issue in wireless sensor networks (WSNs), which affects the performance and lifetime of the networks. Usually the sensor locations are precomputed based on “perfect” sensor detection model, whereas sensors may not always provide reliable information, either due to operational tolerance levels or environmental factors. Therefore, it is very important to take into account this uncertainty in the deployment process. In this paper, we address the problem of sensor deployment in a mixed sensor network where the mobile and static nodes work collaboratively to perform deployment optimization task. We consider the Gaussian white noise in the environment and present a centralized algorithm (FABGM for short) which discoveres vacancies by using detection model based on false alarm and moves the mobile nodes according to the method based on bipartite graph matching in this study. In this algorithm, the management node of the WSNs collects the geographical information of all of the static and mobile sensors. Then, the management node executes the algorithm to get the best matches between mobile sensors and coverage holes. Simulation results are presented to demonstrate the effectiveness of the proposed approach.

Research on Vehicle Automatically Tracking Mechanism in VANET

The intelligent vehicle is a complex system equipped with advanced technologies such as the artificial intelligence, automatic control, and computer, communication. It is a combination of multiple academic subjects and the latest technologies representing the developing tendency of future automobile technology and attracts more and more attention. In this paper, we made some useful explorations in the fields of intelligent vehicle control technology and obstacle avoidance, and a deep research is carried out about the distance of vehicle, vehicle tracking, vehicle lane changing and intersections obstacle avoidance and communication protocols, and some innovative ideas are proposed during the research. By using VANET, some predictable status of tracing and tracking of intelligent vehicle technology was researched, and the communication protocols between two vehicles, the safe spacing algorithm, the method of computing the actual distance at corners and straights, and the trajectory of lane change were designed. In addition, a series of vehicle tracing and tracking technologies, such as without knowing the road conditions, homeostatic mechanism, keeping a safe spacing to the target vehicle, and adjusting its own speed to track the target vehicle smoothly to the destination by comparing the actual distance and safe spacing between vehicles, were discussed here.

A Path Planning Algorithm with a Guaranteed Distance Cost in Wireless Sensor Networks

Navigation with wireless sensor networks (WSNs) is the key to provide an effective path for the mobile node. Without any location information, the path planning algorithm generates a big challenge. Many algorithms provided efficient paths based on tracking sensor nodes which forms a competitive method. However, most previous works have overlooked the distance cost of the path. In this paper, the problem is how to obtain a path with minimum distance cost and effectively organize the network to ensure the availability of this path. We first present a distributed algorithm to construct a path planning infrastructure by uniting the neighbors’ information of each sensor node into an improved connected dominating set. Then, a path planning algorithm is proposed which could produce a path with its length at most c times the shortest Euclidean length from initial position to destination. We prove that the distributed algorithm has low time and message complexity and c is no more than a constant. Under different deployed environments, extensive simulations evaluate the effectiveness of our work. The results show that factor c is within the upper bound proved in this paper and our distributed algorithm achieves a smaller infrastructure size.