# Sustainable Data-Driven Secured Optimization Using Dynamic Programming for Green Internet of Things
## 1 Introduction  
IoT is a network of \"things\" that share and collect data from the environment. These \"things\" could be sensors, portable electronics, wearable technology, or any networked item that can carry out certain tasks [1, 2, 3]. Similarly, a Wireless Sensor Network (WSN), as a component of IoT, transfers the obtained data after detecting any incident. However, there is limited security in the IoT environment due to its scale and heterogeneity, making it vulnerable to various assaults, including WSN-inherited attacks [4, 5, 6]. Sustainable computing has been extensively employed in social networks and IoT in the previous decade [7, 8, 9]. IoT has social, economic, and commercial consequences on human life. However, the open channel, i.e., the internet and IoT nodes used for data transmission channels, is vulnerable to a wide range of intrusions and routing processes. Several initiatives are underway in this area to cope with the developing security challenges in IoT systems and make them self-sufficient in harvesting energy for smooth operation [10, 11]. Cloud computing is essential in contemporary culture and allows various sustainable applications, ranging from infrastructure to social media [12, 13, 14]. Guarantees of Quality of Service (QoS) must be met by such a system, which must be able to handle variable loads and use patterns that reflect the interaction and reliance of societies on automatedcomputer systems [15; 16; 17]. These systems are enabled by a group of conceptual technologies that have been synthesized to fulfill the requirement of growing computer applications. However, with the increased proliferation of IoT devices, concerns such as security, privacy, efficiency, and environmentally friendly computing infrastructure are growing daily [18; 19]. Therefore, to develop a sustainable computing environment for future smart cities, it is necessary to consider their whole life cycle, from design to production for recycling and disposal, as well as their broader influence on people and places. Additionally, the system should consider the vulnerable attacks on IoT networks with strong privacy and authentication techniques [20; 21].  
The proposed SDS-GIoT model offers the following contributions.  
1. It provides a data-driven approach for sustainable smart cities using multistage graph-based structures and improves the system's response time.
2. Intelligent decisions are made based on dynamic programming, which allows for effective computing with minimum complexity on the IoT networks.
3. Edge computing and deterministic technique are combined to create and maintain system security. Using an offloading method lessens the burden of security measures on the devices.
4. The proposed SDS-GIoT model is verified in terms of green computing metrics against existing work.  
This research paper is structured in sections. Section 2 discusses the literature work. The SDS-GIoT model, with its developed components and states, is explained in Section 3. The network model and performance analysis are described in Section 4. Finally, Section 5 concludes with a summary.