Abstract:Moving the path of the beacon has an important impact on the localization performance in a wireless sensor network with mobile beacons; however, without full consideration of the influences of the distribution and density unknown nodes’ when planning beacon’s moving path, most of existing localization methods have lower efficiency. In this paper, the beacon model is first presented according to the theory of equal distance 3-optimal-coverage. Next, a heuristic path planning method is proposed for the ROI in which unknown nodes are distributed randomly, and the node density is limited by using the location mechanism of RSSI to locate range-free, unknown nodes. Simulation results show that the given method is effective.

Abstract:Due to the declining accuracy caused by noise in wireless sensor networks, a data fusion method called normal score test, based on sliding window, is proposed. With this method, a measured data sample in a cycle is taken as a sliding window, and a double sample normal score test is employed into samples. Furthermore, a relationship matrix is created to maximize the adjacent subgraph. An estimated fusion value is achieved in terms of weighting and averaging its vertices. To some extent, this method makes good use of the character of a normal score test and restrains the impact noise on fusion. Simulation results demonstrate the effectiveness of proposed method.

Abstract:A multi-hop routing protocol, based on double cluster head alternation and compressed sensing (DCHACS), is proposed to improve network’s performance in wireless sensor networks. In DCHACS, a distributed algorithm is adopted to select temporary cluster heads, and the temporary cluster heads use a neighbor cluster optimization algorithm to dynamically adjust the size of the cluster through local information. After optimization, temporary cluster heads re-selects better cluster heads by residual energy and location information of member nodes. In the data transmission phase, the double cluster head alternation mechanism is adopted to reduce the burden of cluster head, and cluster heads use compressed sensing theory to aggregate data and route the packets to the next hop. The cluster head replacement mechanism is adopted to replace old cluster head with the new one under certain conditions. The simulation results show that the proposed protocol is able to enhance the clustering performance, make the distribution of cluster’s size more uniform, and significantly reduces the number of lost packets that are due to the death of cluster head to balance the energy consumption of the network and extend the network’s lifetime.

Abstract:With mobile cloud computing system architecture gradually replacing the traditional Client-Server model, one of the most critical issues that needs to be addressed is the resource allocation deciding problem to resolve how a cloud could efficiently handle the cloud resources to satisfy the requirements of mobile device for cloud services. Simoultaneously, this is in effort to obtain the maximal utilization rate of cloud resources and system rewards of cloud. The study first proposes a novel cloud computing resource allocation model based on semi-Markov decision process (SMDP) to achieve the optimal resource allocation scheme in terms of maximal system reward, cloud resource utilization, and the QoS of mobile device while capturing the dynamics of resource request arrivals and departures. Finally, the performance of the proposed model is evaluated by the simulation results, which show that the obtained theoretic results are consistent with this simulation results.

Abstract:With the development of small scale unmanned aerial vehicles, researchers are paying more and more attention to airborne mobile sensor networks (MSNs) which are potentially used in various application areas. However, existing deployment strategies are not suitable to this new style of networks. On one hand, aerial nodes are free of movement in the three-dimensional space. Collision prevention has to be implemented, while flocking together as a whole also needs to be done first. On the other hand, against concrete coverage objectives, a key area should be multiply treated and an average region should be generally served. Therefore, the research first looks for new algorithms and models for specific airborne characteristics. Based on the idea of charged particle swarms, this paper chooses the fitness function as the breakthrough and uses fuzzy measure as the performance evaluation index of candidate solutions. Simulation results witness the effectiveness of charged swarm strategy to traditional particle swarm and virtual forces strategies.

Abstract:Although socially aware opportunistic communication paradigms are considered to have broad potential applications, very little is known about how the dynamic networks evolve and which nodes are more important both in sustaining the network topology and in forwarding or disseminating messages. Through the concept of walk and the adjacent matrix product of static graph theory, this paper extends a measurement, Katz Centrality (KC) that originated from Social Networks Analysis (SNA), to dynamic evolving opportunistic mobile networks. This is done in effort to examine the dissemination capabilities of different mobile nodes. The cornerstone of this method is the dynamics of an opportunistic contact network can be expressed through time-split observations, which result in a sequence of snapshots. By simply multiplying the adjacent matrix of each snapshot along the direction of time, the resulting matrix, in which the spatial and temporal dependency of the network are fully captured, can be obtained, so as to evaluate the relative information dissemination capability of each mobile node. The research uses two typical contact trace datasets for validation and the results show that several mobile nodes with the highest communicability identified by this method are more efficient in information dissemination than others in the whole network and can be chosen as good candidates when some interventions, such as accelerating or suppressing the speed of message dissemination in network, are required to be made on network.

Abstract:For irregular sensing range of sensor nodes, the paper proposes a randomly deployment wireless sensor network algorithm based on the Delaunay triangulation and grid. In the deployment algorithm, sensor nodes that have already been started are grouped by Delaunay triangulation, which then calculates the target point TP by the TPM algorithm and chooses the TP as a reference point to start a new node. This algorithm adjusts TP in accordance with grid coverage around nodes and the distance between nodes. The paper also proposes a “border reinforcement mechanism” and “obtuse triangle TP-point optimization strategy” to improve coverage effectively. Experimental results show that the proposed deployment algorithm can effectively use randomly deployed sensor nodes. It can quickly raise coverage to 90% or more and has the feature that makes the redundant cover region less, the coverage rate growing fast, and small amount of nodes can achieve high coverage.

Abstract:The MAC (medium access contro1) protocol of traditional wireless sensor network has a problem with the high energy consumption of nodes. This paper proposes a CLEE-MAC (cross layer based energy-efficient MAC) protocol using the thought of cross-layer design, based on adaptive S-MAC (sensor MAC) protocol. The CLEEMAC protocol changes the format of control packets of S-MAC protocol with the information coming from a routing layer. It makes the most and reduces the overhearing listening, and at the same time, simplifies the control overhead of multi-hop transmission, improves the utilization of nodes energy, and reduces the delay of data transmission.

Abstract:For the applications of wireless sensor networks in typical industrial environments, the wireless link quality of IEEE 802.15.4 has a certain degree of fluctuation and packets loss appear bursty. In this paper, a data-trace-driven modeling method and statistical inference is adopted for the statistical analysis of the loss interval in link-layer packet transmission traces. The study finds that the loss interval follows Pareto distribution and the distribution parameter reflects the distribution characteristics of loss interval under a different packet loss rate. Take the D_α, namely correlation distance, which is the difference between the sample distribution parameter and that of the independent identical distribution under the same packet loss rate, as the indicator to characterize burstiness of packet loss. Through analysis and experiments, it is indicated that the retransmission independence distance (RID) in the link-layer has an approximate linear relation to the correlation distance. The study designs an optimal data retransmission mechanism using the indicator D_α in single-hop links, which can improve data retransmission reliability. Finally, it is verified by experiments that the average of reliability improvement is 6.3% with the maximum 14.5%, which is relative to the fixed time-slot retransmission mechanism that does not consider the packets loss burstiness.

Abstract:Currently, bus arrival time prediction studies have not yielded the best results under complex road conditions. A bus arrival time prediction mechanism based on the similarity of road conditions is proposed in this paper. By analyzing the past trip records of the bus, the historical traffic condition of each road section was estimated. The road condition for each trip records was extracted. In the operational phase, each road section’s traffic condition was estimated by gathering bus locations continually. The mechanism predicted bus arrival time for the rest bus station by the most similar historical which was searched by the time, distance, and real-time road conditions. The evaluation result using historical data of real bus trips shows that the arrival time prediction of the mechanism is accurate—with an absolute percentage error around 5%.

Abstract:The rapid movement of vehicles which result in frequent changes in the position and speed of the vehicle usually leads to the wrong packet forwarding decisions in VANET. Combining V2V (vehicle to vehicle) and V2I (vehicle to infrastructure), a routing protocol named TGPSR-WI (traffic information aware algorithm based on GPSR with infrastructure) algorithm is proposed. This algorithm works on the principle that when static infrastructural nodes exist in a neighboring list, the neighbor which is closest to the destination will be selected as the next hop; otherwise, the moving direction and “lifetime” are used to filter hopeless candidates. Next, incorporate speed, vehicular density, etc. to select the optimal next hop node. Key data structures are designed and MOVE (mobility model generator for vehicular network) is used to construct typical Grid map urban simulation scenario. The protocol is simulated in NS-2 under the urban scenario and compared with GPSR-L and GPSR routing protocols. Experimental results indicate that the improved GPSR routing protocol performs better when packet delivery rate, average end-to-end delay are used as the performance metrics, and is better for VANET (vehicular ad hoc network) under urban scenarios.

Abstract:In wireless sensor networks, a weighted aggregation is an important method for the users to obtain the information when monitoring the environment. This method enforces the objectivity of the aggregation result by assigning different weights to different nodes or sensed data. On the other hand, the WSNs are both energy constraint and unstable, so it is better to do the approximate data aggregation if one can ensure the error-bound is tolerable for the users. A group-based sampling algorithm for approximate weighted aggregation is proposed. The theoretical analysis demonstrates that the proposed algorithm can reach arbitrary precision. Furthermore, the proposed algorithm is scalable, and it can adapt to large-scale dynamic sensor networks, and support the modification of the precision during the processing of a query. Experimental results show the correctness of the proposed algorithm and demonstrates the high performance of the proposed algorithm by comparing it with previous algorithms.

Abstract:In event-driven wireless sensor networks, many redundant packets flow from monitored sites through the network and to the sink, resulting in a typical funnel effect which affects event reliability, negatively. Taking this transport property into account, a differentiated priority queue management scheme is presented, in which the packets with same event identification are prioritized according to their arrival sequence, and scheduled differentially. The queue model, packet prioritization strategy and event table maintaining methods are examined in detail. Simulation results show that the queue management scheme can improve event reliability of event-driven sensor networks in terms of event detection ratio, accuracy ratio, and event delay efficiently.

Abstract:Time synchronization protocol is an important part of wireless sensor networks. Many applications and communication protocols of wireless sensor networks are built on the basis of an accurate synchronized timing. The previous time synchronization protocol for wireless sensor networks focuses on how to improve the accuracy and reduce related energy consumption, but now the security problem of time synchronization protocol in wireless sensor networks is catching people’s attention. This paper designs a new fault-tolerant time synchronization protocol (FTTSP) for wireless sensor networks with random weighting estimation, based on the analysis for the attack to time synchronization protocol for wireless sensor networks. Simulation results show that the protocol has good intrusion detection capability and fault tolerance to malicious synchronization information.

Abstract:By focusing on the multi-sensors’ measurement on the same characteristic index from different directions, a multi-sensor data fusion algorithm based on optimal fusion set is proposed. The optimal fusion set is defined to obtain the valid observation data, in which the consistent fusion degree and the distribution degree of sensors are measured by using an optimal fusion degree matrix set. Next, the weights of the valid observation data in the fusion process are reasonably assigned. The final expression of data fusion and estimation is obtained. The data fusion results show that this method demonstrates higher fusion precision, and also excellent.

Abstract:Based on the analysis of proposed routing protocols in vehicular ad hoc networks (VANETs), this paper gives a new algorithm PCAR(position-based and connectivity aware routing) by combining the position information and the network connectivity. The algorithm also takes advantage of the vehicle density information to estimate the network connectivity and selects anchor nodes and the routing based on the weight of the road. Next it gives the extended greedy forwarding strategy based on the velocity and direction of vehicles. Compared to the GPSR and GSR, the simulations show that PCAR is good for VANETs in the city scenario and has a more efficitn delivery rate and transmission delay.

Abstract:To help resolve the deficiency of existing target tracking algorithm in sensor networks, a GM(1,1) based target tracking algorithm (GMTT) is proposed in this paper. GMTT treats the target tracking issue in sensor networks as a state prediction problem of inadequate-information system and applies the gray theory to deal with this issue. It makes use of the GM(1,1) model to predict the region where the target may arrive in the next moment, and forwards tracking messages to this predicted region to detect and track the target with dense nodes. Simulations demonstrate that GMTT processes good merits in tracking probability, tracking precision and tracking delay.

Abstract:Human itineraries are often initiated by some general intentions and will be optimized after considering all kinds of constraints and available information. This paper proposes a category-based itinerary recommendation framework to help the user transfer from intentions to itinerary planning, which join physical trajectories and information of location based social networks. The main contributions are: (1) Build the category based activity scheduling model; (2) Design and implement the category tree based POI (point or interest) query strategy and algorithm; (3) Propose the Voronoi graph based GPS trajectory analysis method to build traffic information networks; (4) Combine social networks with traffic information networks to implement category based recommendation by ant colony algorithm. The study conducts experiments on datasets from FourSquare and GeoLife project. A test on satisfaction of recommended items is also performed. Results show that the satisfaction reaches 80% in average.