1.1. Paper Organization

This structured approach ensures a systematic and thorough examination of hybrid consensus mechanisms while addressing critical challenges and gaps in the existing literature.

2.1. Traditional Consensus Mechanisms

Consensus mechanisms are fundamental protocols in blockchain technology, ensuring that all nodes in a decentralized network reach agreement on the state of the ledger. These mechanisms validate transactions, maintain security, and safeguard network integrity by requiring consensus across all participants in the network [18].

Different consensus algorithms have distinct advantages and drawbacks, each offering unique trade-offs in terms of security, scalability, efficiency, and decentralization. For instance, PoW, widely used in systems like Bitcoin, is highly secure but requires vast computational resources, leading to significant energy consumption. PoS, on the other hand, provides better energy efficiency but raises concerns about network centralization, as participants with larger stakes exert greater influence [9].

These algorithms are further summarized in Table 2, which provides a comparative overview of their primary benefits and limitations. It sheds light on why certain consensus models are integrated into hybrid mechanisms. By combining the strengths of various models, hybrid consensus mechanisms aim to overcome the limitations of individual algorithms, optimizing performance and security across blockchain networks.

These traditional consensus algorithms, while effective, often face challenges in specific blockchain environments. Issues such as limited scalability, high energy consumption, and susceptibility to attacks hinder their suitability for all applications.

Hybrid consensus mechanisms address these challenges by combining the strengths of multiple algorithms. For example, integrating PoW with PoS reduces energy consumption while maintaining robust security. Similarly, DPoS is well-suited for resource-constrained environments, such as the IoT, as it achieves high scalability and efficiency by delegating transaction validation to a select group of nodes, thereby reducing computational overhead.

By adopting hybrid approaches, blockchain networks can achieve improved scalability, security, energy efficiency, and decentralization. These adaptable solutions cater to the diverse requirements of modern blockchain applications, enabling their deployment in scenarios that demand high performance and resilience.

2.2. Related Work

The development of consensus algorithms has been extensively documented in the literature, emphasizing their evolution and application across various blockchain environments. This paper reviews several pivotal studies to contextualize our research within the broader academic discourse, as summarized in Table 1.

Bouraga’s [4] taxonomy traces the evolution of consensus algorithms, from PoW to PoS, categorizing them based on origin, design, performance, and security. However, it mainly addresses general blockchain applications and does not discuss third-generation consensus algorithms or their specific use in IoT environments.

Another notable study by Salimitari and Chatterjee [16] provides a comprehensive analysis of consensus methods tailored for blockchain systems in resource-constrained IoT networks. Their work focuses on addressing key challenges specific to IoT environments, including limited computational power, intermittent network connectivity, and the need for energy-efficient solutions. The study explores various consensus algorithms, including PoW, PoS, PBFT, and DAGs, evaluating their suitability based on factors like computational requirements, energy efficiency, scalability, and fault tolerance. The paper also discusses optimization techniques and security considerations specific to IoT networks. The conclusion emphasizes the need for further research to develop efficient and secure consensus mechanisms tailored for resource-constrained IoT environments.

Elgountery et al. [5] focused on the application of consensus algorithms within resource-constrained IoT networks. It offers an extensive assessment of both traditional and third-generation methods, considering factors such as latency and throughput, and incorporates discussions on DAG consensus models. However, this study lacked a comparative analysis of these methods, particularly in terms of adaptability for IoT applications.

Guru et al. [6] evaluated consensus mechanisms suitable for both legacy and nonlinear algorithms but failed to extend their focus to resource-constrained IoT systems, which are critical for the practical deployment of blockchain technologies in such environments.

Bodkhe et al. [10] examined the intersection of IoT and blockchain, discussing not only the architectural and application aspects of IoT but also including examples of IoT applications that utilize DAG protocols. In contrast, Khobragade and Turuk [17] provide a comprehensive review of blockchain-based IoT, emphasizing security, robustness, and self-maintenance, thereby illustrating how blockchain technology could transform cloud-centered IoT environments.

Tripathi et al. [22] provided critical insights into cases where blockchain technology may not be suitable. They highlight several limitations, including performance challenges in applications requiring high throughput and low latency, such as real-time systems. Additionally, blockchain is less efficient in centralized environments with established trust, where traditional databases are more cost-effective. Resource constraints are another significant issue, as lightweight systems like IoT devices with limited power and storage struggle to meet blockchain’s resource demands. Environmental concerns also complicate its adoption, with energy-intensive consensus mechanisms like PoW being impractical for low-value or environmentally sensitive applications. Lastly, blockchain’s immutability, while a strength in many contexts, becomes a drawback for use cases requiring frequent data updates or deletions. The authors conclude by emphasizing the need for a careful evaluation of application requirements and suggest exploring alternative or hybrid approaches to address blockchain’s inherent limitations.

Recent works, such as Alsunaidi and Alhaidari [25] and Ferdous et al. [23], delve into hybrid consensus mechanisms and their applications in IoT environments. Alsunaidi and Alhaidari [25] provide a comprehensive review of consensus algorithms, with particular emphasis on their technical and operational aspects. They evaluate the adaptability of hybrid mechanisms to IoT networks, focusing on their ability to address resource constraints and maintain energy efficiency. The study also discusses the integration of DAGs as a potential solution for improving scalability and reducing latency in IoT-specific use cases.

Ferdous et al. [23] systematically analyzed blockchain consensus mechanisms, highlighting trade-offs between performance, security, and scalability. Their work examines various consensus protocols, such as PoW, PoS, and PBFT, in the context of hybrid designs. The authors emphasize the importance of balancing computational efficiency with network decentralization, particularly in IoT environments where devices are resource-constrained. Additionally, the study outlines future directions for developing lightweight consensus mechanisms capable of meeting the demands of real-time applications.

These studies underscore the critical need for further research into hybrid consensus mechanisms that can address performance and scalability challenges in IoT and other resource-constrained environments. By exploring the integration of existing algorithms with novel approaches, these works lay the groundwork for more efficient and adaptable blockchain solutions.

This study underscores the importance of recognizing blockchain’s limitations and conducting a thorough evaluation of application requirements. The authors advocate for exploring alternative or hybrid approaches in cases where the drawbacks of blockchain outweigh its benefits, ensuring more suitable and efficient solutions for diverse use cases.

While these contributions are valuable, they often overlook detailed comparisons of third-generation consensus methods or the applicability of DAG systems for IoT-specific challenges. It is also observed that current literature tends to rely on intuitive categorization of domain knowledge, which might obscure the inherent logical connections between concepts within the field.

Table 1 provides a comparative analysis of various review papers on consensus algorithms within blockchain technology, with the objective of shedding light on the current landscape of literature in this crucial domain. The selection of these papers was meticulously curated to encompass a diverse range of contributions, survey methodologies, and coverage areas, allowing for a comprehensive exploration of the nuances and gaps within the existing literature.

Through this analysis, our aim is to identify and elucidate the gaps in the literature, particularly in the exploration of hybrid consensus mechanisms. The table categorizes these papers based on several key aspects, including their contribution to the field, the type of survey conducted, the tools used in the analysis, and the coverage of consensus algorithms.

The analysis of consensus algorithms in blockchain technology, as outlined in Table 1, highlights the diverse approaches taken by various review studies, providing a clearer understanding of how these studies interpret and discuss the development of consensus mechanisms in different blockchain environments. Some reviews focus on traditional consensus algorithms, primarily emphasizing cryptographic principles, while others delve into the complexities of hybrid blockchains that integrate both public and private architecture elements. Despite these valuable contributions, a significant gap remains in the literature, particularly regarding the application of hybrid consensus mechanisms tailored for specialized use cases like the IoT.

Several studies, such as those by Alkhateeb et al. [8], examine the platforms commonly utilized to integrate blockchain with IoT. These studies highlight platforms like Ethereum, known for its robust smart contract capabilities, alongside other blockchain networks such as EOS, Bitcoin, Litecoin, and Ripple. These platforms are primarily discussed in terms of storing IoT data, facilitating private communications, and supporting decentralized applications. However, most reviews focus on the general applications of these platforms, rather than investigating how hybrid consensus mechanisms can optimize these platforms for improved IoT performance. This represents a key underexplored area in the literature.

Our study fills this gap by providing the first comprehensive evaluation of hybrid consensus algorithms specifically in the context of IoT, a critical area where existing literature tends to focus on traditional consensus models or generalized blockchain applications. This contribution is significant in shifting the focus from a generalized view of blockchain platforms to a more detailed exploration of how hybrid consensus mechanisms can provide tailored solutions for IoT integration.

Incorporating insights from recent works, including Bouraga’s [4] taxonomy and Gedam and Karmore’s review [21], we explore how the evolution of consensus algorithms—from PoW to PoS and beyond—has paved the way for more scalable and efficient blockchain architectures. Bouraga’s taxonomy traces this evolution, while Gedam and Karmore’s comprehensive review on blockchain–IoT integration emphasizes challenges around security and scalability. Both studies reinforce the importance of addressing scalability and security in IoT environments, where blockchain plays a crucial role in ensuring data integrity and providing secure, scalable solutions. Our study is innovative in its exclusive focus on hybrid consensus mechanisms, exploring how they uniquely contribute to improving IoT integration. By offering a deeper understanding of how these mechanisms function in real-world IoT applications, we provide valuable insights into deploying more efficient and scalable blockchain solutions in an increasingly interconnected world.

3.1. Examples of Hybrid Consensus Mechanisms in Blockchain

3.2. Hybrid Consensus Overview

3.3. Comparison Hybrid Consensus Algorithms

Hybrid consensus mechanisms are increasingly utilized within blockchain networks due to their ability to synergize different algorithms, thereby optimizing performance across various dimensions. This section presents Table 3, which outlines the combination of algorithms, their distinctive characteristics, and probable applications for each hybrid consensus model. These hybrid models are specifically designed to address unique challenges and enhance specific aspects of blockchain consensus, offering tailored solutions to meet the diverse requirements of blockchain applications. Table 3 provides an in-depth comparison of different hybrid consensus algorithms, highlighting their unique attributes and the critical factors to consider for each.

Table 3 illustrates how each hybrid model combines the strengths of different consensus mechanisms to optimize blockchain functionality. For instance, the Honesty-Based Distributed Proof-of-Authority hybrid leverages a scalable work consensus protocol tailored for IoT applications. By combining the Honesty-Based Distributed Proof-of-Authority with scalability features, this model addresses the specific needs of IoT systems, such as lightweight operation, high security, and efficient resource utilization, making it suitable for environments with constrained devices and real-time requirements.

3.4. Classification of Hybrid Consensus Mechanisms

Hybrid consensus mechanisms can be categorized based on three primary criteria: combination type, performance focus, and application domain. This multidimensional approach ensures a thorough understanding of their functional and operational attributes.

4.1. Validation in Hybrid Consensus

Mechanisms validation is crucial for maintaining the blockchain’s integrity, involving multiple steps tailored to each consensus mechanism. Below is a comprehensive table “Table 5” that combines the strengths and weaknesses of various hybrid consensus mechanisms across multi-step aspects of validation.

Understanding the trade-offs in each hybrid consensus mechanism is essential for selecting the most appropriate one for maintaining blockchain integrity. Each mechanism has unique strengths and weaknesses across transaction verification, consensus verification, block verification, and network-wide verification. By evaluating these factors, one can choose the optimal consensus mechanism based on the specific requirements of the blockchain application.

4.2. IoT Applications

Hybrid consensus mechanisms enhance IoT applications by providing scalable, efficient, and secure transaction validations suitable for resource-constrained environments. Below is a detailed comparison of various mechanisms tailored for IoT applications, as shown in Table 6.

4.3. Real-Time Processing

Real-time processing is essential for applications requiring immediate data validation and consensus. This part compares various hybrid consensus mechanisms based on their real-time processing capabilities. Table 7 presents a comparative analysis of each mechanism’s efficiency, outlining the advantages that support rapid processing and the limitations that may hinder performance under time-sensitive conditions.

4.4. Application Suitability

Ultimately, the selection of a hybrid consensus mechanism should align with the specific requirements, goals, and characteristics of the intended decentralized application. By matching the mechanism to the use case, blockchain networks can achieve optimal performance, scalability, and security.

4.5. Security in Hybrid Consensus Mechanisms

Security is a critical concern in the design of hybrid consensus mechanisms, especially in the face of increasingly sophisticated attacks. While traditional surveys have explored individual vulnerabilities and defense mechanisms, they often fail to account for the interplay between consensus mechanisms and real-world network dynamics. This subsection aims to address this gap by integrating both perspectives into a comprehensive evaluation of hybrid mechanisms.

For instance, Saad et al. [97] provided an in-depth analysis of the Nakamoto consensus in asynchronous networks, yet their study does not extensively address how network-level factors, such as partitioning attacks or delays in block propagation, directly affect consensus security. Similarly, Heo et al. [2] discussed partitioning attacks in Ethereum, while Saad et al. [98] highlighted the SyncAttack, where double-spending can occur in Bitcoin without requiring significant mining power. These studies underscore critical vulnerabilities in traditional mechanisms but do not explore how hybrid consensus models could offer more robust defenses by combining complementary protocols.

Despite these contributions, there remains a gap in understanding how different hybrid consensus mechanisms can provide tailored security solutions against a range of attacks in diverse network settings. Specifically, the combination of PoS and BFT in hybrid mechanisms is often analyzed in isolation from the broader network behavior, leading to an incomplete understanding of their resilience in more adversarial scenarios [98].

Table 8 provides a comprehensive comparison of hybrid consensus mechanisms, evaluating their protection against key attacks and risks based on a synthesis of theoretical, experimental, and empirical studies. The ratings in Table 8 are supported by three types of evidence: theoretical analysis, experimental studies, and empirical data. Theoretical analysis includes formal proofs and analyses from the literature, while experimental studies consist of results from controlled laboratory experiments or simulations. Empirical data are derived from real-world deployments, such as Hedera’s operational data. Each hybrid consensus mechanism was evaluated based on a thorough review of existing studies, with references provided in the Ref column. For instance, [77] offers theoretical and experimental evidence for Casper’s security, while [98] analyzes the scalability and security of PoS + PBFT through simulations.

Table 8 highlights that while mechanisms like Hedera offer comprehensive protection across a range of risks, others, such as Microchain, provide only basic protection, emphasizing the need for tailored approaches depending on specific application requirements.

As seen in Table 8, hybrid mechanisms leverage the strengths of multiple protocols to address a range of attacks and risks. However, their effectiveness varies significantly depending on the network context and adversarial conditions. For example, Hedera demonstrates comprehensive protection, benefiting from its asynchronous Byzantine Fault Tolerance (aBFT) design and carefully balanced validator network [101], whereas PoS + PBFT mechanisms rely heavily on controlled simulations to validate security under ideal conditions [98]. In contrast, existing works like Khan et al. [13] focus on reward/punishment schemes for consensus mechanisms but fail to explore their integration into hybrid structures for evaluating overall system security.

Furthermore, hybrid mechanisms are specifically designed to mitigate certain vulnerabilities, yet many existing surveys overlook the critical impact of network dynamics on consensus security. The findings in Table 8 align with insights from Saad et al. [98], who emphasize the importance of scalability and security in hybrid mechanisms under controlled conditions. However, as Tran et al. [12] suggest, these mechanisms still face challenges in addressing real-world network fluctuations.

This nuanced approach provides a more comprehensive understanding of how hybrid consensus mechanisms can be tailored to secure decentralized networks under varying adversarial conditions—a consideration that has been insufficiently addressed in existing surveys.

4.6. Implementation of Hybrid Consensus Mechanisms

Hybrid consensus mechanisms represent a sophisticated blend of technologies designed to address traditional blockchain challenges such as scalability, energy consumption, and resource constraints. By optimizing performance and security through innovative combinations of consensus protocols, these mechanisms have the potential to revolutionize blockchain applications across IoT, finance, and real-time processing [72, 96].

5.1. Future Work

5.2. Proposed New Hybrid Consensus Algorithm

The adaptive hybrid consensus mechanism (AHCM) is a conceptual framework designed to address current challenges in blockchain scalability, security, and energy efficiency. This algorithm is part of ongoing research and aims to provide a flexible solution tailored to diverse network conditions and application requirements.

The AHCM is a conceptual framework proposed for further exploration in our ongoing research. Implementation details will be disclosed in future publications.

5.3. Summary and Outlook

Research into hybrid consensus algorithms represents a promising frontier in blockchain technology. By addressing current challenges and exploring new applications, future advancements in this area hold the potential to significantly enhance the scalability, security, and efficiency of blockchain systems, making them more adaptable and suitable for a broader range of applications.

The AHCM framework represents ongoing research by the authors. This conceptual design is intended for academic discussion, with implementation details to be shared in future works. Unauthorized use or replication is prohibited.

This survey lays the groundwork for continued innovation in the field, offering a comprehensive framework that can guide future research and development efforts.