Neighbourhood watch is a concept that allows a community to distribute a complex security task in between all members. Members of the community carry out individual security tasks to contribute to the overall security of it. It reduces the workload of a particular individual while securing all members and allowing them to carry out a multitude of security tasks. Wireless sensor networks (WSNs) are composed of resource-constraint independent battery driven computers as nodes communicating wirelessly. Security in WSNs is essential. Without sufficient security, an attacker is able to eavesdrop the communication, tamper monitoring results or deny critical nodes providing their service in a way to cut off larger network parts. The resource-constraint nature of sensor nodes prevents them from running full-fledged security protocols. Instead, it is necessary to assess the most significant security threats and implement specialised protocols. A neighbourhood-watch inspired distributed security scheme for WSNs has been introduced by Langend\"orfer. Its goal is to increase the variety of attacks a WSN can fend off. A framework of such complexity has to be designed in multiple steps. Here, we introduce an approach to determine distributions of security means on large-scale static homogeneous WSNs. Therefore, we model WSNs as undirected graphs in which two nodes connected iff they are in transmission range. The framework aims to partition the graph into $n$ distinct security means resulting in the targeted distribution. The underlying problems turn out to be NP hard and we attempt to solve them using linear programs (LPs). To evaluate the computability of the LPs, we generate large numbers of random {\lambda}-precision unit disk graphs (UDGs) as representation of WSNs. For this purpose, we introduce a novel {\lambda}-precision UDG generator to model WSNs with a minimal distance in between nodes.

翻译：邻里守望是一种概念，它允许社区将复杂的安全任务分配给所有成员。社区成员执行各自的安全任务，以促进整体安全。这种方法减轻了特定个体的工作负担，同时保护所有成员，并使他们能够执行多种安全任务。无线传感器网络（WSN）由资源受限的独立电池驱动计算机节点组成，这些节点通过无线方式通信。WSN的安全性至关重要。如果没有足够的安全性，攻击者能够窃听通信、篡改监测结果，或拒绝关键节点提供服务，从而切断更大范围的网络部分。传感器节点的资源受限特性使其无法运行完善的安全协议。相反，有必要评估最重大的安全威胁并实现专门的协议。Langendörfer提出了一种受邻里守望启发的WSN分布式安全方案。其目标是增加WSN能够抵御的攻击种类。这种复杂框架需要分多个步骤设计。在此，我们介绍一种在大规模静态同构WSN上确定安全手段分布的方法。为此，我们将WSN建模为无向图，其中两个节点连接当且仅当它们在传输范围内。该框架旨在将图划分为n种不同的安全手段，从而得到目标分布。底层问题被证明是NP难的，我们尝试使用线性规划（LP）来解决。为了评估LP的可计算性，我们生成大量随机λ-精度单位圆盘图（UDG）作为WSN的表示。为此，我们引入了一种新颖的λ-精度UDG生成器，以建模节点间具有最小距离的WSN。