Xiaolan Tang

A Multicast Routing Protocol with Pruning and Energy Balancing for Wireless Sensor Networks

This paper presents a novel multicast routing protocol for wireless sensor networks, named Multicast tree protocol with Pruning and Energy Balancing (MPEB) to disseminate data through a layered multicast tree with high-efficiency and low-power consumption. With pruning algorithm and energy balancing algorithm, MPEB can save energy and balance load. Pruning algorithm records and maintains backup parents for each child node, and thus it can detach possible nodes from the multicast tree and turn as many nodes as possible to sleep. Energy balancing algorithm protects nodes with low power from running out of energy and dying out, and thus it can balance total energy consumption of the whole network and prolong the network lifetime. The formal validations and simulations evaluate the performance of MPEB, which shows that MPEB has a distinct advantage over others in both reducing and balancing energy consumption.

Energy-efficient multicast routing scheme for wireless sensor networks

This paper presents a novel energy-efficient multicast routing scheme for wireless sensor networks, named extended multicast routing scheme with pruning and energy balancing E-MPEB to disseminate data through layered multicast trees with high efficiency and low power consumption. E-MPEB uses pruning and energy balancing algorithms to save energy and balance load. Especially, it supports multisource multicast and multiple multicast tasks. In multisource multicast, we propose dense tree construction and conjunctive pruning algorithms to minimise total transmission in the network. We increase the number of children having the same parent to improve transmission efficiency and turn more nodes into sleep. In multiple multicast tasks, we propose sharing node avoidance algorithm to separate trees for different multicast tasks. This separation reduces transmission congestion at sharing nodes and balances total energy consumption. Formal validations and simulations evaluate the performance of E-MPEB, which show that E-MPEB has a distinct advantage over others in both reducing and balancing energy consumption. Copyright

Knowledge-based replica deletion scheme using directional anti-packets for vehicular delay-tolerant networks

As stable end-to-end paths seldom exist in vehicular delay-tolerant networks, replication-based opportunistic routing protocols are often utilised to improve the data delivery ratio and decrease the transfer delay. However, the network load increases heavily because of numerous data replicas. In this paper, we propose a knowledge-based replica deletion Scheme using Directional Anti-packets SuDAs, in order to reduce the transmission of anti-packets by considering vehicle contact statistics. We firstly use the contact judgment algorithm to avoid invalid anti-packet transmissions and select better forwarder for the anti-packets to reach each relay node, which has redundant data replica. Then, in the directional anti-packet transmission algorithm, we set different anti-packet transmission thresholds according to different requirements for the quality of replica deletion in the network. Formal validations and extensive simulations evaluate the performance of our scheme, which show that SuDA has a distinct advantage over others in striking a balance between the replica deletion delay and the anti-packet overhead. Copyright

Data Acquisition Based on Stable Matching of Bipartite Graph in Cooperative Vehicle–Infrastructure Systems

Existing studies on data acquisition in vehicular networks often take the mobile vehicular nodes as data carriers. However, their autonomous movements, limited resources and security risks impact the quality of services. In this article, we propose a data acquisition model using stable matching of bipartite graph in cooperative vehicle-infrastructure systems, namely, DAS. Contents are distributed to roadside units, while vehicular nodes support supplementary storage. The original distribution problem is formulated as a stable matching problem of bipartite graph, where the data and the storage cells compose two sides of vertices. Regarding the factors relevant with the access ratio and delay, the preference rankings for contents and roadside units are calculated, respectively. With a multi-replica preprocessing algorithm to handle the potential one-to-many mapping, the matching problem is addressed in polynomial time. In addition, vehicular nodes carry and forward assistant contents to deliver the failed packets because of bandwidth competition. Furthermore, an incentive strategy is put forward to boost the vehicle cooperation and to achieve a fair bandwidth allocation at roadside units. Experiments show that DAS achieves a high access ratio and a small storage cost with an acceptable delay.

Cooperative transmission control scheme using erasure coding for vehicular delay-tolerant networks

Transmission control is a challenging problem in vehicular delay-tolerant networks because the network has a high vehicle mobility which leads to a dynamic and unreliable network connectivity. In this paper, we propose a COoperative Transmission control Scheme using erasure coding (COTS) to improve the transmission efficiency. In this scheme, the cooperative message distribution algorithm uses delivery capacities to decide the transmission direction and traffic. Besides, the cooperative task scheduling algorithm sets the transfer order for messages from both sides. This algorithm uses a comprehensive parameter, the number of data blocks to send, to simplify the computation of transmission priority. After analyzing the vehicle transmission behavior under different storage conditions, we apply local deleting and creating behaviors instead of sending and receiving behaviors in specific states to decrease communication overhead. Simulation results show that COTS, compared with other well-known schemes, not only increases the delivery ratio but also decreases the delivery latency and the transmission overhead.

Data Dissemination Based on Fuzzy Logic and Network Coding in Vehicular Networks

Vehicular networks, as a significant technology in intelligent transportation systems, improve the convenience, efficiency, and safety of driving in smart cities. However, because of the high velocity, the frequent topology change, and the limited bandwidth, it is difficult to efficiently propagate data in vehicular networks. This paper proposes a data dissemination scheme based on fuzzy logic and network coding for vehicular networks, named SFN. It uses fuzzy logic to compute a transmission ability for each vehicle by comprehensively considering the effects of three factors: the velocity change rate, the velocity optimization degree, and the channel quality. Then, two nodes with high abilities are selected as primary backbone and slave backbone in every road segment, which propagate data to other vehicles in this segment and forward them to the backbones in the next segment. The backbone network helps to increase the delivery ratio and avoid invalid transmissions. Additionally, network coding is utilized to reduce transmission overhead and accelerate data retransmission in interbackbone forwarding and intrasegment broadcasting. Experiments show that, compared with existing schemes, SFN has a high delivery ratio and a short dissemination delay, while the backbone network keeps high reliability.

Data Aggregation Based on Overlapping Rate of Sensing Area in Wireless Sensor Networks

Wireless sensor networks are required in smart applications to provide accurate control, where the high density of sensors brings in a large quantity of redundant data. In order to reduce the waste of limited network resources, data aggregation is utilized to avoid redundancy forwarding. However, most of aggregation schemes reduce information accuracy and prolong end-to-end delay when eliminating transmission overhead. In this paper, we propose a data aggregation scheme based on overlapping rate of sensing area, namely AggOR, aiming for energy-efficient data collection in wireless sensor networks with high information accuracy. According to aggregation rules, gathering nodes are selected from candidate parent nodes and appropriate neighbor nodes considering a preset threshold of overlapping rate of sensing area. Therefore, the collected data in a gathering area are highly correlated, and a large amount of redundant data could be cleaned. Meanwhile, AggOR keeps the original entropy by only deleting the duplicated data. Experiment results show that compared with others, AggOR has a high data accuracy and a short end-to-end delay with a similar network lifetime.

Correlation Feature of Big Data in Smart Cities

Smart cities are constantly faced with the generated data resources. To effectively manage and utilize the big city data, data vitalization technology is proposed. Considering the complex and diverse relationships among the big data, data correlation is very important for data vitalization. This paper presents a framework for data correlation and depicts the discovery, representation and growth of data correlation. In particular, this paper proposes an innovative representation of data correlation, namely the data correlation diagram. Based on the basic and the multi-stage data relations, we optimize the data correlation diagrams according to the transitive rules. We also design dynamic data diagrams to support data and relation changes, reducing the response time to data changes and enabling the autonomous growth of the vitalized data and the relations. Finally an instance of smart behaviors is introduced which verifies the feasibility and efficiency of the data relation diagram.