In this work, we investigate the problem of lifetime optimization for partial coverage in heterogeneous sensor networks. This problem which is NP-Hard in its general form is known under the name of α-coverage, where α refers to a prescribed level of coverage threshold that we need to maintain. Sleep-Awake scheduling which turns sensors to On and Off, is the common and the well known technique that has been heavily studied in the literature to deal with energy management under coverage constraint. The question is how to orchestrate the clustering of the sensor nodes into disjoint or non-disjoint covers, and to schedule these covers, so that the total network’s lifetime is maximized. Unlike earlier works, we consider both global (whole targets) resp. local (individual target) monitoring thresholds to improve the coverage quality rather than dealing with a single global leveling threshold as in the literature. In addition, instead of employing a default covers’ activation which may lead to the starvation phenomenon, where targets may remain uncovered for a long time period, we provide a clairvoyant scheduling for the obtained covers to ensure fair smoothing for the cumulated target’s uncovered time periods during the network’s service. First, a novel mathematical Binary Integer Linear Programming (BILP) is proposed to solve the α-coverage problem to optimality. Then, provable guarantees of the upper bound for the number of partial cover sets are given. Next, we formulate the covers’ planning as a p-dispersion problem and due to the NP-Completeness of the former, an efficient Genetic Algorithm (GA) based approach is designed to achieve efficient covers’ scheduling with minimal execution time complexity. Finally, a series of experiments are conducted and several QoS metrics are evaluated to show the usefulness of our proposals.

在这项工作中，我们调查了异构传感器网络中部分覆盖的生命周期优化问题。这个一般意义上的NP-Hard问题以α-coverage的名称已知，其中α指我们需要保持的规定水平的覆盖阈值。将传感器打开和关闭的“睡眠唤醒”调度是常见且众所周知的技术，已在文献中进行了大量研究以处理覆盖范围约束下的能源管理。问题是如何将传感器节点的群集编排成不相交或不相交的覆盖范围，并安排这些覆盖范围，以使整个网络的寿命最大化。与早期的作品不同，我们考虑了全球（整个目标）的响应。本地（单个目标）监视阈值以提高覆盖质量，而不是像文献中那样处理单个全局级别阈值。此外，与其采用可能导致饥饿现象的默认封面激活，如果目标可能会长期处于未发现状态，则我们会为获取的覆盖范围提供透视计划，以确保在网络服务期间对累积目标的未发现时间段进行公平的平滑处理。首先，提出了一种新颖的数学二进制整数线性规划（BILP）来解决α覆盖问题达到最优。然后，给出了部分封面集数量上限的可证明的保证。接下来，我们将封面的计划表述为p离散问题，并且由于前者的NP完整性，因此设计了一种基于有效遗传算法（GA）的有效方法，可以以最小的执行时间复杂性来实现有效的封面计划。最后，进行了一系列实验，并对几个QoS指标进行了评估，以显示我们建议的有效性。