Finding a framework that provides continuous, reliable, secure and sustainable diversified smart city services proves to be challenging in today’s traditional cloud centralized solutions. This article envisions a Mobile Edge Computing (MEC) solution that enables node collaboration among IoT devices to provide reliable and secure communication between devices and the fog layer on one hand, and the fog layer and the cloud layer on the other hand. The solution assumes that collaboration is determined based on nodes’ resource capabilities and cooperation willingness. Resource capabilities are defined using ontologies, while willingness to cooperate is described using a three-factor node criteria, namely: nature, attitude and awareness. A learning method is adopted to identify candidates for the service composition and delivery process. We show that the system does not require extensive training for services to be delivered correct and accurate. The proposed solution reduces the amount of unnecessary traffic flow to and from the edge, by relying on node-to-node communication protocols. Communication to the fog and cloud layers is used for more data and computing-extensive applications, hence, ensuring secure communication protocols to the cloud. Preliminary simulations are conducted to showcase the effectiveness of adapting the proposed framework to achieve smart city sustainability through service reliability and security. Results show that the proposed solution outperforms other semi-cooperative and non-cooperative service composition techniques in terms of efficient service delivery and composition delay, service hit ratio, and suspicious node identification.

在当今的传统云集中式解决方案中，寻找可提供持续，可靠，安全和可持续的多样化智能城市服务的框架被证明是一项挑战。本文设想了一种移动边缘计算（MEC）解决方案，该解决方案使IoT设备之间的节点协作能够在一方面与雾层之间，另一方面与雾层和云层之间提供可靠且安全的通信。该解决方案假定协作是根据节点的资源能力和协作意愿确定的。资源能力是使用本体定义的，而合作的意愿是使用三要素节点标准来描述的，即自然，态度和意识。采用一种学习方法来识别服务组合和交付过程的候选者。我们表明，该系统不需要为接受正确，准确的服务而进行的大量培训。所提出的解决方案通过依赖于节点到节点的通信协议来减少去往边缘的不必要流量。与雾层和云层的通信用于更多的数据和计算广泛的应用程序，因此，确保了与云的安全通信协议。进行了初步模拟，以展示调整建议的框架以通过服务可靠性和安全性实现智能城市可持续性的有效性。结果表明，在有效的服务交付和组合延迟，服务命中率以及可疑节点识别方面，所提出的解决方案优于其他半合作和非合作服务组合技术。