The LCP aims to achieve agreement among participants by progressing through proposal rounds with different phases. It involves the preparation, promise, acceptance, and acknowledgment phases. Participants exchange their messages to gather information, make proposals, and reach a consensus on a value. The challenges of achieving consensus in distributed systems are captured by the famous CAP theorem [30], which states that if's impossible for a distributed system to simultaneously provide consistency (all nodes see the same data), availability (every request receives a response), and partition tolerance (the system continues to operate despite arbitrary message loss or failure of part of the system). The LCP ensures that all participants eventually agree on the same value, even in the presence of failures or delays. It provides security and availability while simplifying complexity. The LCP, rooted in L1 approximation, balanced asymmetry, absolute infinite flow, and unbounded interaction graphs, has been the most renowned approach for managing SDAs [31]. Nonetheless, the introduction of blockchain technology has exposed vulnerabilities in the LCP, particularly when confronted with soft attacks and hardware failures [32; 33]. Utilizing blockchain technology can effectively resolve challenges in managing Swarm Dynamic Agents (SDA), addressing issues such as miscommunications, Sybil, and adversarial attacks [34]. Therefore, we implemented blockchain for UAS management, and the outcomes provided evidence of its enhanced safety compared to the LCP approach [35]. A survey study on safe space allocation in transportation problems using blockchain was performed [36]. Another survey study (focusing on airspace allocation) investigated blockchain methodologies for UTM [37]. Ethereum blockchain was used for Automatic Dependent Surveillance-Broadcast (ADS-B) Air Traffic Management relying on satellite navigation [38]. This approach was able to provide situational awareness, allocate safe airspace, and eventually reduce potential conflicts while overcoming cyber threats. Each of these proposed methodologies used a smart contract, which was based on the Proof of Work (PoW) consensus protocol. In addition to the PoW consensus protocol, blockchain can be set up based on Proof of History (PoH), Proof of Stake (PoS), Proof of Authority (PoA), and Proof of Time (PoT) for appropriate decision making [39; 40]. Each of these techniques has its unique advantages. Indeed, PoW is a consensus algorithm employed in multi-agent systems, necessitating every agent node to validate the accurate completion of the undertaken task [41]. However, the PoW has two major drawbacks: its computational complexity and the lengthy confirmation time. To overcome these drawbacks, the Proof of Stake (PoS) consensus mechanism, which relies on validators that confirm blocks on the blockchain according to their credits, was suggested [42]. In this study, we utilized the blockchain sharding concept for partitioning UAVs. In our previous study, [43] the superiority of the blockchain over the partitioned running of UAVs was proven. We started this study regarding our previous proof and discussed it from different consensus mechanism aspects (PoW and PoS). The present study has two main objectives. The first objective is to design a reliable smart contract for airspace allocation, and the second is to reconfigure that smart contract with the aim of reducing energy consumption, computational complexity, and validation time. The reliable smart contract is initially designed using the PoW consensus method and is then reconfigured using the PoS consensus method to reduce its computational complexity. Some of the initial results obtained from error rate and validation time analysis were published as a conference paper in the AIAA Aviation Forum 2023 [44], where a consensus system was developed using Ethereum's blockchain for managing traffic in Unmanned Aircraft Systems (UASs), and to assign safe flying zones for UASs.