You are presented with multiple paper abstracts, alongside the associated literature review and chapter titles. Given the provided information, you are going to do a literature review. Please generate a coherent literature review that synthesizes the content, draws connections between different works, highlights major findings, and identifies any gaps in the existing research.

Literature Review Title: A Survey on Consensus Mechanisms and Mining Strategy Management in Blockchain Networks 
Chapter Title:  C. Consensus Provision and Computation Offloading under Nakamoto Protocols 
1. Abstract of Cited Paper (BIB001):  Blockchain, an emerging decentralized security system, has been applied in many applications, such as bitcoin, smart grid, and Internet-of-Things. However, running the mining process may cost too much energy consumption and computing resource usage on handheld devices, which restricts the use of blockchain in mobile environments. In this paper, we consider deploying edge computing service to support the mobile blockchain. We propose an auction-based edge computing resource market of the edge computing service provider. Since there is competition among miners, the allocative externalities (positive and negative) are taken into account in the model. In our auction mechanism, we maximize the social welfare while guaranteeing the truthfulness, individual rationality and computational efficiency. Based on blockchain mining experiment results, we define a hash power function that characterizes the probability of successfully mining a block. Through extensive simulations, we evaluate the performance of our auction mechanism which shows that our edge computing resources market model can efficiently solve the social welfare maximization problem for the edge computing service provider. 
2. Abstract of Cited Paper (BIB002):  Blockchain has recently been applied in many applications such as bitcoin, smart grid, and Internet of Things (IoT) as a public ledger of transactions. However, the use of blockchain in mobile environments is still limited because the mining process consumes too much computing and energy resources on mobile devices. Edge computing offered by the Edge Computing Service Provider can be adopted as a viable solution for offloading the mining tasks from the mobile devices, i.e., miners, in the mobile blockchain environment. However, a mechanism needs to be designed for edge resource allocation to maximize the revenue for the Edge Computing Service Provider and to ensure incentive compatibility and individual rationality is still open. In this paper, we develop an optimal auction based on deep learning for the edge resource allocation. Specifically, we construct a multi-layer neural network architecture based on an analytical solution of the optimal auction. The neural networks first perform monotone transformations of the miners' bids. Then, they calculate allocation and conditional payment rules for the miners. We use valuations of the miners as the data training to adjust parameters of the neural networks so as to optimize the loss function which is the expected, negated revenue of the Edge Computing Service Provider. We show the experimental results to confirm the benefits of using the deep learning for deriving the optimal auction for mobile blockchain with high revenue 
3. Abstract of Cited Paper (BIB003):  Mobile security has become more and more important due to the boom of mobile commerce (m-commerce). However, the development of m-commerce is facing many challenges regarding data security problems. Recently, blockchain has been introduced as an effective security solution deployed successfully in many applications in practice, such as, Bitcoin, cloud computing, and Internet-of-Things. However, the blockchain technology has not been adopted and implemented widely in m-commerce because its mining processes usually require to be performed on standard computing units, e.g., computers. Therefore, in this paper, we introduce a new m-commerce application using blockchain technology, namely, MobiChain, to secure transactions in the m-commerce. Especially, in the MobiChain application, the mining processes can be executed efficiently on mobile devices using our proposed Android core module. Through real experiments, we evaluate the performance of the proposed model and show that blockchain will be an efficient security solution for future m-commerce. 
4. Abstract of Cited Paper (BIB004):  Blockchain, as the backbone technology of the current popular Bitcoin digital currency, has become a promising decentralized data management framework. Although blockchain has been widely adopted in many applications, e.g., finance, healthcare, and logistics, its application in mobile services is still limited. This is due to the fact that blockchain users need to solve preset proof-of-work puzzles to add new data, i.e., a block, to the blockchain. Solving the proof-of-work, however, consumes substantial resources in terms of CPU time and energy, which is not suitable for resource-limited mobile devices. To facilitate blockchain applications in future mobile Internet of Things systems, multiple access mobile edge computing appears to be an auspicious solution to solve the proof-of-work puzzles for mobile users. We first introduce a novel concept of edge computing for mobile blockchain. Then, we introduce an economic approach for edge computing resource management. Moreover, a prototype of mobile edge computing enabled blockchain systems is presented with experimental results to justify the proposed concept. 
5. Abstract of Cited Paper (BIB005):  Blockchain technology has been applied in a variety of fields due to its capability of establishing trust in a decentralized fashion. However, the application of blockchain in wireless mobile networks is hindered by a major challenge brought by the proof-of-work puzzle during the mining process, which sets a high demand for the computational capability and storage availability in mobile devices. To address this problem, we propose a novel mobile edge computing (MEC) enabled wireless blockchain framework where the computation-intensive mining tasks can be offloaded to nearby edge computing nodes and the cryptographic hashes of blocks can be cached in the MEC server. Particularly, two offloading modes are considered, i.e., offloaded to the nearby access point or a group of nearby users. First, we conduct the performance analysis of each mode with stochastic geometry methods. Then, the joint offloading decision and caching strategy is formulated as an optimization problem. Furthermore, an alternating direction method of multipliers based algorithm is utilized to solve the problem in a distributed manner. Finally, simulation results demonstrate the effectiveness of our proposed scheme. 
6. Abstract of Cited Paper (BIB006):  Public blockchain networks using proof of work (PoW)-based consensus protocols are considered as a promising platform for decentralized resource management with financial incentive mechanisms. In order to maintain a secured, universal state of the blockchain, PoW-based consensus protocols financially incentivize the nodes in the network to compete for the privilege of block generation through cryptographic puzzle solving. For rational consensus nodes, i.e., miners with limited local computational resources, offloading the computation load for PoW to the cloud/fog providers (CFPs) becomes a viable option. In this paper, we study the interaction between the CFPs and the miners in a PoW-based blockchain network using a game theoretic approach. In particular, we propose a lightweight infrastructure of the PoW-based blockchains, where the computation-intensive part of the consensus process is offloaded to the cloud/fog. We formulate the computation resource management in the blockchain consensus process as a two-stage Stackelberg game, where the profit of the CFP and the utilities of the individual miners are jointly optimized. In the first stage of the game, the CFP sets the price of offered computing resource. In the second stage, the miners decide on the amount of service to purchase accordingly. We apply backward induction to analyze the subgame perfect equilibria in each stage for both uniform and discriminatory pricing schemes. For uniform pricing where the same price applies to all miners, the uniqueness of the Stackelberg equilibrium is validated by identifying the best response strategies of the miners. For discriminatory pricing where the different prices are applied, the uniqueness of the Stackelberg equilibrium is proved by capitalizing on the variational inequality theory. Further, the real experimental results are employed to justify our proposed model.

Literature Review:
In contrast to the studies that we review in Sections VII-A and VII-B, another line of works focus on (decentralized) resource allocation for consensus provision in the Nakamotobased blockchain networks. In other words, these studies view the consensus in blockchain networks of a given protocol as the goal to be achieved instead of a ready-to-use service. Recall that the Nakamoto protocols require consumption of certain resources in the PoW-like puzzle solution competition for new block proposing (see also Section III). With this property in mind, a plethora of works, e.g., BIB007 , BIB002 , BIB003 - BIB004 , are devoted to the studies of resource allocation in the block mining process in exchange for monetary rewards (i.e., mining reward in tokens) offered by the blockchain. In BIB007 , BIB005 , BIB006 , a scenario of deploying blockchains on the mobile edge devices is considered. Due to the intensive resource consumption for PoW solution, it is difficult to directly migrate blockchain networks to the mobile environment BIB005 . Therefore, the computation offloading schemes are proposed in these studies by either formulating the problems in a nonlinear/binary programming framework BIB006 or as a hierarchical (i.e., Stackelberg) game BIB007 , BIB005 . We use BIB007 as an example to explain how the PoWwork offloading process can be formulated as a conventional optimization or game theoretic problem. To offload the tasks of PoW-solution searching from mobile devices to the edge/fog/cloud, a series of factors including transaction transmission delay and blockchain-forking probability need to be considered when constructing the utility model of the mobile node at the edge. Considering that the computation providers at the edge/fog are able to control the price of the offered computational resource, the offloading process is modeled in BIB007 as a two-stage Stackelberg game. In brief, the cloud/fog providers act as the leader to set the resource price, and the edge devices acts as the follower to determine the share of resource to purchase for offloading the mining tasks. According to the various assumptions about the offloading scenarios (e.g., multi-leader vs. single leaders), different approaches such as nonlinear optimization formulation or best responsebased equilibrium searching are applied to each layer's subproblem in the manner of backward induction BIB001 Chapter 3.4.2] . Extending from the basic scenarios in BIB007 , BIB006 , various tools of mechanism design, e.g., auctions BIB002 , BIB003 , can be further applied into the similar offloading problems for resource allocation in the blockchain consensus process.