{'fraction_non_alphanumeric': 0.02912087912087912, 'fraction_numerical': 0.0, 'mean_word_length': 5.215017064846417, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
An Energy-Delay Trade-Off in Wireless Visual Sensor Networks Based on Two-Sided Matching

Wireless visual sensor networks (WVSNs) comprise a large number of battery-powered visual sensors with limited processing and transmission capacity in the field of interest. Hence, energy conservation is an important issue in resource-constrained WVSNs. In-network data fusion, clustering networks has been proved to be an effective scheme in reducing energy consumption. However, in most clustering algorithms, clustering may introduce bottlenecks to WVSNs which bring extra delay in the processes of data collection and forwarding. Such delay can be reduced by the design of routing schemes. In this paper, we propose an approach of energy-delay trade-off (EDT) based on two-sided matching theory. First, we determine a balance clustering structure which can balance energy consumption and delay in random-densely-deployed WVSNs. Then, the problem formulation of EDT problem in the balance clustering structure is provided. Moreover, the transformation strategy based on two-sided matching (TS-TSM) is proposed. After the TS-TSM, the EDT problem is transformed into a stable two-sided matching (STSM) problem with single objective function and the computational complexity is reduced. Furthermore, most of floating-point operations in original EDT problem are converted into integer operations which are easy to parallel compute. Finally, an improved deferred-acceptance algorithm (IDAA) is provided to generate a stable matching solution as the EDT scheme. Evaluation results demonstrate that the EDT approach can reduce delay in data aggregation processes and keep the total energy consumption at low levels. Further simulations show that the EDT approach is a fast approach, and it is not inferior to the existing algorithms.