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One-slot link scheduling is important for enhancing the throughput capacity of wireless sensor networks. It includes two aspects: maximum links scheduling (MLS) and maximum weighted links scheduling (MWLS). In this paper we propose two heuristic algorithms for the two NP-hard problems with obvious power assignments under the SINR (signal-to-interference-plus-noise-ratio) model. For MLS, we propose an algorithm MTMA (maximum tolerance and minimum affectance), which improves the currently best approximation algorithm by 28%–62% on average. For MWLS, we give an effective heuristic algorithm MWMA (maximum weighted and minimum affectance), which performs better on improving the throughput and reducing the running time. The correctness and performance of our algorithms are confirmed through theoretical analysis and comprehensive simulations. [ABSTRACT FROM AUTHOR]

Person reidentification (ReID) is a challenging computer vision task for identifying or verifying one or more persons when the faces are not available. In ReID, the indistinguishable background usually affects the model's perception of the foreground, which reduces the performance of ReID. Generally, the background of the same camera is similar, whereas that of different cameras is quite different. Based on this finding, we propose a template-aware transformer (TAT) method which can learn intersample indistinguishable features by introducing a learnable template for the transformer structure to cut down the model's attention to regions of the image with low discrimination, including backgrounds and occlusions. In the multiheaded attention module of the encoder, this template directs template-aware attention to indistinguishable features of the image and gradually increases the attention to distinguishable features as the encoder block deepens. We also increase the number of templates using side information considering the characteristics of ReID tasks to adapt the model to backgrounds that vary significantly with different camera IDs. Finally, we demonstrate the validity of our theories using various public data sets and achieve competitive results via a quantitative evaluation. [ABSTRACT FROM AUTHOR]

Due to the imbalanced energy consumption among nodes in wireless sensor networks, some nodes die prematurely, which decreases the network lifetime. To solve this problem, existing clustering protocols usually construct unequal clusters by exploiting uneven competition radius. Taking their imperfection on designing the uneven competition radius and intercluster communication into consideration, this paper proposes an improved distributed unequal clustering protocol (IDUC) for wireless sensor networks, where nodes are energy heterogeneous and scattered unevenly. The cores of IDUC are the formation of unequal cluster topology and the construction of intercluster communication routing tree. Compared with previous protocols, IDUC is suitable for various network scenarios, and it can balance the energy consumption more efficiently and extend the lifetime of networks significantly. [ABSTRACT FROM AUTHOR]

Coverage is one of the key issues to achieve energy efficiency of a wireless sensor network. Sensor scheduling is one of the most important methods to solve coverage problems. It can ensure the coverage degree of a region and prolong the network lifetime. In this paper, we focus on the k -coverage scheduling problem to guarantee k -coverage sensing and network connectivity. We consider both deterministic and stochastic sensing models of the sensors and adapt the results of deterministic sensing model to solve the sensor scheduling problem under the stochastic sensing model. We use regular pentagons to divide the sensing disks to solve the k -coverage problem. Each sensor node runs a stochastic k -coverage-preserving scheduling algorithm to determine its work modes, and redundant nodes can enter into sleep mode, while active nodes ensure the coverage of the network. Theoretical analysis and simulation results show that our algorithm can reduce the number of active nodes and extend the network lifetime significantly while maintaining a given coverage degree. [ABSTRACT FROM AUTHOR]