Instituto ITACA, Universitat Politècnica de València, Valencia, España.
PLoS One. 2023 May 23;18(5):e0285924. doi: 10.1371/journal.pone.0285924. eCollection 2023.
Nowadays, Wireless Sensor Networks (WSNs) are widely used for collecting, communicating, and sharing information in various applications. Due to its limited resources in terms of computation, power, battery lifetime, and memory storage for sensor nodes, it is difficult to add confidentiality and integrity security features. It is worth noting that blockchain (BC) technology is one of the most promising technologies, because it provides security, avoids centralization, and a trusted third party. However, to apply BCs in WSNs is not an easy task because BC is typically resource-hungry for energy, computation, and memory. In this paper, the additional complication of adding BC in WSNs is compensated by an energy minimization strategy, which basically depends on minimizing the processing load of generating the blockchain hash value, and encrypting and compressing the data that travel from the cluster-heads to the base station to reduce the overall traffic, leading to reduced energy per node. A specific (dedicated) circuit is designed to implement the compression technique, generate the blockchain hash values and data encryption. The compression algorithm is based on chaotic theory. A comparison of the power consumed by a WSN using a blockchain implementation with and without the dedicated circuit, illustrates that the hardware design contributes considerably to reduce the consumption of power. When simulating both approaches, the energy consumed when replacing functions by hardware decreases up to 63%.
如今,无线传感器网络(WSN)广泛应用于各种应用中,用于收集、通信和共享信息。由于传感器节点在计算、功率、电池寿命和内存存储方面的资源有限,因此很难添加保密性和完整性安全功能。值得注意的是,区块链(BC)技术是最有前途的技术之一,因为它提供了安全性、避免了中心化和可信的第三方。然而,将 BC 应用于 WSN 并非易事,因为 BC 通常对能源、计算和内存的要求很高。在本文中,通过一种节能策略来弥补在 WSN 中添加 BC 的额外复杂性,该策略主要依赖于最小化生成区块链哈希值的处理负载,以及加密和压缩从群头传输到基站的数据,以减少整体流量,从而降低每个节点的能耗。设计了一个特定(专用)电路来实现压缩技术、生成区块链哈希值和数据加密。压缩算法基于混沌理论。通过比较使用区块链实现和不使用专用电路的 WSN 消耗的功率,说明了硬件设计有助于显著降低功耗。在模拟这两种方法时,用硬件替换功能所消耗的能量减少了 63%。