The rise of grid modernization has been prompted by the escalating demand for power, the deteriorating state of infrastructure, and the growing concern regarding the reliability of electric utilities. The smart grid encompasses recent advancements in electronics, technology, telecommunications, and computer capabilities. Smart grid telecommunication frameworks provide bidirectional communication to facilitate grid operations. Software-defined networking (SDN) is a proposed approach for monitoring and regulating telecommunication networks, which allows for enhanced visibility, control, and security in smart grid systems. Nevertheless, the integration of telecommunications infrastructure exposes smart grid networks to potential cyberattacks. Unauthorized individuals may exploit unauthorized access to intercept communications, introduce fabricated data into system measurements, overwhelm communication channels with false data packets, or attack centralized controllers to disable network control. An ongoing, thorough examination of cyber attacks and protection strategies for smart grid networks is essential due to the ever-changing nature of these threats. Previous surveys on smart grid security lack modern methodologies and, to the best of our knowledge, most, if not all, focus on only one sort of attack or protection. This survey examines the most recent security techniques, simultaneous multi-pronged cyber attacks, and defense utilities in order to address the challenges of future SDN smart grid research. The objective is to identify future research requirements, describe the existing security challenges, and highlight emerging threats and their potential impact on the deployment of software-defined smart grid (SD-SG).

Communication networks in power systems are a major part of the smart grid paradigm. It enables and facilitates the automation of power grid operation as well as self-healing in contingencies. Such dependencies on communication networks, though, create a roam for cyber-threats. An adversary can launch an attack on the communication network, which in turn reflects on power grid operation. Attacks could be in the form of false data injection into system measurements, flooding the communication channels with unnecessary data, or intercepting messages. Using machine learning-based processing on data gathered from communication networks and the power grid is a promising solution for detecting cyber threats. In this paper, a co-simulation of cyber-security for cross-layer strategy is presented. The advantage of such a framework is the augmentation of valuable data that enhances the detection as well as identification of anomalies in the operation of the power grid. The framework is implemented on the IEEE 118-bus system. The system is constructed in Mininet to simulate a communication network and obtain data for analysis. A distributed three controller software-defined networking (SDN) framework is proposed that utilizes the Open Network Operating System (ONOS) cluster. According to the findings of our suggested architecture, it outperforms a single SDN controller framework by a factor of more than ten times the throughput. This provides for a higher flow of data throughout the network while decreasing congestion caused by a single controller’s processing restrictions. Furthermore, our CECD-AS approach outperforms state-of-the-art physics and machine learning-based techniques in terms of attack classification. The performance of the framework is investigated under various types of communication attacks.

As more people and devices come online with the rapid growth of the internet, the need for secure and efficient network resource management becomes increasingly important. The boom of these connections on Next Generation Wireless Networks through the advent of technologies like the Internet of Things has changed the landscape of traditional edge networks. This necessitates a drastic change in the existing edge network infrastructure. As these devices come online, make requests, and go offline, the allocation and management of edge network resources become paramount. Blockchain, with its growing popularity, presents itself as a potential solution. The inherent features of blockchain such as decentralization, transparency, security, and immutability, make it possible for network providers to manage network resources efficiently. This survey paper delves into the diverse applications of blockchain in edge network resource management, offering a comprehensive discussion of its potential to revolutionize network infrastructure. Unlike other surveys, we focus this work on three specific contexts of blockchain integration for network resource management: Cloud and Edge Computing, Radio Access Networks in Next Generation Wireless Networks, Reinforcement Learning, and Federated Learning. We provide an extensive analysis of recent research advances in these areas, and the main findings are highlighted. Understanding the current use of blockchain and network resource management opens the door to new research and more efficient and secure networks. The open research issues that arise from the combination of blockchain with the management of edge network resources are identified. Finally, the future directions to fuel innovative research are presented in this survey.

Smart grids are replacing conventional power grids due to rising electricity use, failing infrastructure, and reliability problems. Two-way communication, demand-side administration, and real-time pricing make smart grids (SGs) dependent on its communication system. Manual network administration slows down SG communication. SG networks additionally utilize hardware and software from several vendors, allowing devices to communicate. Software-defined SGs (SD-SG) use software-defined networking (SDN) to monitor and regulate SG global communication networks to address these concerns. SDN separates the data plane (routers and switches) from the control plane (routing logic) and centralizes control into the SDN controller. This helps network operators manage visibility, control, and security. These benefits have made SDN popular in SG architectural and security studies. But because SD-SGs are vulnerable to cyberattacks, there are concerns about the security of these SD-SG networks. Cybercriminals can attack software-defined communication networks, affecting the power grid. Unauthorized access can be used to intercept messages and introduce false data into system measurements, flood communication channels with fraudulent data packets, or target controllers, a potential single point of failure, to cripple SDN networks. Current research reflects this paradigm as defense and security against such attacks have developed and evolved. There is a need for a current study that provides a more detailed analysis and description of SD-SG network security dangers and countermeasures, as well as future research needs and developing threats for the sector. To fill this void, this survey is presented.

The evolution of wireless networks and radio access technologies (RATs) has transformed communication from user-driven traffic into a dynamic ecosystem of autonomous systems, including IoT devices, edge nodes, autonomous vehicles, AR/XR clients, and AI-powered agents. These systems exhibit diverse traffic patterns, latency requirements, and mobility behaviors, increasingly operating across overlapping heterogeneous RATs such as 5G, WiFi, satellite, NB-IoT, LoRaWAN, Zigbee, etc. This multi-RAT coexistence creates opportunities for intelligent access, mobility, and routing strategies. However, most mobility decisions still rely heavily on RSSI, which neglects RAT-specific features, congestion, queuing delays, and application needs, favoring high-power links over optimal ones. To address this gap, we propose chrome (Congestion-aware Offloading and Handover via Empirical RAT Evaluation), a multi criteria framework for dense multi-RAT networks. chrome enhances RSSI with multiple criteria and applies the Technique for Order of Preference by Similarity to the Ideal Solution (TOPSIS) to rank available RATs. Criteria weights are determined using both subjective (operator-driven) and objective (measurement-based) approaches. Based on this ranking, chrome performs intelligent cross-RAT offloading to reduce congestion on over-utilized links. We evaluate chrome in a dense SDN-controlled 5G/WiFi Multi-RAT environment using Mininet WiFi. Compared to RSSI-only handover, COHERE reduces the load on the congested RAT by up to 32%, reduces total handovers by 25%, lowers handovers to the congested RAT by 55%, and improves link delay by up to 166%, while maintaining comparable or up to 11% higher throughput. These results demonstrate that guarded, multi-criteria decision-making can exploit RAT coexistence to deliver robust, congestion-aware performance across heterogeneous deployments.

Grid modernization has been ushered in by rising electricity consumption, deteriorating infrastructure, and increasing reliability concerns for electric utilities. New advances, collectively referred to as the smart grid, include modern electronics, technology, telecommunications, and computing capabilities. Smart grid telecommunication frameworks provide two-way communication to support grid operations. Software-defined networking (SDN) has been proposed as a method of monitoring and controlling telecommunication networks, enabling increased smart grid visibility, control, and security. However, being connected to telecommunications infrastructure means that smart grid networks are exposed to cyber-attacks. Attackers may use unauthorized access to intercept messages, inject false data into system measurements, flood communication channels with false data packets, or target centralized controllers to cripple network control. Defense and security techniques against these threats are constantly evolving, necessitating an up-to-date, comprehensive study analyzing cyber attacks and defense methods for smart grid networks. Previous smart grid security surveys do not contain recent techniques and to our knowledge most, if not all, address only one type of attack type and/or one type of defense. This survey considers the latest security techniques, simultaneous multi-pronged cyber attacks and defensutilityes to meet the challenges of the next-generation SDN smart grid research with the goal of identifying future research needs, describing the open security challenges, and exposing both emerging threats and their potential impact on SD-SG deployment.