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Coverage is a significant performance indicator of wireless sensor networks. Data redundancy in k-coverage raises a set of issues including network congestion, coverage reduction, energy inefficiency, among others. To address these issues, this paper proposes a novel algorithm called complex alliance strategy with multi-objective optimization of coverage (CASMOC) which could improve node coverage effectively. This paper also gives the proportional relationship of the energy conversion function between the working node and its neighbors, and applies this relationship in scheduling low energy mobile nodes, thus achieving energy balance of the whole network, and optimizing network resources. The extensive simulation results demonstrate that CASMOC could not only improve the quality of network coverage, but also mitigate rapid node energy consumption effectively, thereby extending the life cycle of the network significantly. [ABSTRACT FROM AUTHOR]

The target nodes are k-covered by the sensor nodes; there will be a lot of redundant data forcing the phenomenon of congestion which lowers the network communication capability and coverage and accelerates network energy consumption. Therefore, this paper proposes an energy-efficient coverage control with multinodes redundancy verification (ECMRV). The algorithm constructs the coverage network model by using the positional relationship among the sensor nodes, and the proof procedure of the sector coverage expected value of the monitoring area also has been provided. On the aspect of the energy consumption, this paper gives the proportion of energy conversion functions between the working sensor nodes and the neighboring sensor nodes. And by using the function proportional to schedule the sensor nodes with low energy, we achieve the energy balance of the whole network and the optimization of the network resources. Finally, the simulation experiments indicate that this algorithm can not only improve the quality of network coverage, but completely inhibit the rapid energy consumption of the sensor nodes as well; as a result, the network lifetime extends, which has verified availability and stability of the algorithm in the paper. [ABSTRACT FROM AUTHOR]

Due to the existence of a large number of redundant data in the process of covering multiple targets, the effective coverage of monitored region decreases, causing the network to consume more energy. To solve this problem, this paper proposes a multitarget k-degree coverage preservation protocol. Firstly, the affiliation between the sensor nodes and target nodes is established in the network model; meanwhile the method used to calculate the coverage expectation value of the monitored region is put forward; secondly, in the aspect of the network energy conversion, use scheduling mechanisms on the sensor nodes to balance the network energy and achieve different network coverage quality with energy conversion between different nodes. Finally, simulation results show that NMCP can improve the network lifetime by effectively reducing the number of active nodes to meet certain coverage requirements. [ABSTRACT FROM AUTHOR]

Coverage problem is an important research topic in the field of wireless sensor network (WSN). The coverage algorithm based on event probability driven mechanism (EPDM) is put forward in this paper. First of all, the network probability model is established and the subordinate relation between sensor nodes and the target nodes is presented. Secondly, a series of probability is computed and the related theorems and reasoning are also proven. Thirdly, effective coverage for the monitoring region is achieved through scheduling mechanism of nodes themselves, thus the purpose of increasing network lifetime can be realized. Finally, experimental results show that the proposed algorithm could achieve complete coverage for networks of different scale and increase the network lifetime. It possesses the good quality of effectiveness and stability. [ABSTRACT FROM AUTHOR]

The non-consecutive coverage problem for the target nodes in Sensor Networks could lead to the coverage blind area and a large amount of redundant data, which causes the bottleneck phenomenon for the communication link. A novel Coverage Control Algorithm for Moving Target Nodes Based on Sensing Probability Model (CMTN-SP) is proposed in this work. Firstly, according to the probability theory, we derive the calculation method for the expectation of the coverage quality with multiple joint nodes, which aims to reduce the coverage blind area and improving network coverage rate. Secondly, we employ the dynamic transferring mechanism of the nodes to re-optimize the deployment of the nodes, which alleviates the rapid exhaustion of the proper network energy. Finally, it is verified via the results of the simulation that the network coverage quality could not only be improved by the proposed algorithm, but the proposed algorithm could also effectively curb the rapid exhaustion of the node energy. [ABSTRACT FROM AUTHOR]

When the nodes in the network are deployed in the target area with an appropriate density, the effective aggregation and transmission of the data gathered in the monitoring area remain to be solved. The existing Compressed Sensing (CS) based on data aggregation schemes are accomplished in a centralized manner and the Sink node achieves the task of data aggregation. However, these existing schemes may suffer from load imbalance and coverage void issues. In order to address these problems, we propose a Compressed Sensing based on Fault-tolerant Correcting Data Aggregation (CS-FCDA) scheme to accurately reconstruct the compressed data. Therefore, the network communication overhead can be greatly reduced while maintaining the quality of the reconstructed data. Meanwhile, we adopt the node clustering mechanism to optimize and balance the network load. It is shown via simulation results, compared with other data aggregation schemes, that the proposed scheme shows obvious improvement in terms of the Fault-tolerant correcting capability and the network energy efficiency of the data reconstruction. [ABSTRACT FROM AUTHOR]

In the process of the wireless sensor network research, the issue on the energy consumption and coverage is an essential and critical one. According to the characteristic of the sensor nodes, it is homogeneous, and we proposed the k-degree coverage algorithm based on optimization nodes deployment. First, the algorithm gives the solving procedure of the maximum seamless coverage ratio, when the three-node joint coverage has been provided. Second, when the sensor nodes are covering the monitoring area, the algorithm gives the solving procedure of the expected coverage quality and the judgment methods of the coverage ratio, when the nodes are compared with the nearby ones. And when there is redundancy coverage in the given monitoring area, we have given the solving procedure of any sensor nodes that exist in the redundant nodes coverage. Finally, using the simulation experiment, the results of the coverage algorithm based on optimization nodes deployment are compared with other algorithms in terms of the coverage quality and the network lifetime, the performance indexes have enhanced to 13.36% and 12.92% on average. Thus, the effectiveness and viability of the coverage algorithm based on optimization nodes deployment have been proved. [ABSTRACT FROM AUTHOR]

The problem of using lesser wireless sensor network nodes to achieve coverage and connection of certain areas under given coverage conditions is a priority and hotspot issue of WSN. For this reason, in this paper, an optimized strategy coverage control (OSCC) algorithm is proposed. First of all, a relation mapping model of sensor nodes and target nodes is established by OSCC which is based on geometric figure and related theories, probability theory, converge property, and so forth to complete effective reasoning and calculate certain network models. Secondly, OSCC makes efficient analysis of the calculating results figure out the least number of sensor nodes to cover specific monitoring area. Thirdly, OSCC picks out the optimal routing solution while conducting combinatorial optimization of routing path using ant colony optimization (ACO) algorithm, thus reducing the energy spending of whole network. In the end, this paper verifies OSCC algorithm by simulation experiment and proves it can use least sensor nodes to effectively cover target area. Also, OSCC helps greatly reduce network energy consuming, minimize network resources layout costs, and enhance network life cycle, simultaneously. [ABSTRACT FROM AUTHOR]