Search

Mobile edge computing (MEC), as a promising technology, provides proximate and prompt computing service for mobile users on various applications. With appropriate incentives, profit-driven users can offload multi-task requests across heterogeneous edge servers. However, such incentive trade lacks a trustworthy platform. Due to the decentralized nature of MEC, trading information from players is easily tampered with by edge servers, which poses a threat to cross-server resource allocation. In this paper, we jointly consider incentives and cross-server resource allocation in blockchain-driven MEC, where the blockchain prevents malicious edge servers from tampering with player information by maintaining a continuous tamper-proof ledger database. Particularly, we propose two double auction mechanisms, namely a double auction mechanism based on breakeven (DAMB) and a more efficient breakeven-free double auction mechanism (BFDA), in which users request multi-task service with claimed bids and edge servers cooperate with each other to serve users. A delegated proof of stake (DPoS) based blockchain technology is leveraged to realize decentralized, untampered, safe and fair resource allocation consensus mechanism. The simulation results show that the proposed DAMB and BFDA can significantly improve the system efficiency of MEC.

Recently, wireless streaming of on-demand videos of mobile users (MUs) has become the major form of data traffic over cellular networks. As a response, caching popular videos in the storage of small base stations (SBSs) has been regarded as an efficient approach to reduce the transmission latency and alleviate the data traffic loaded over backhaul channels. This paper considers a small-cell based caching market composed of one mobile network operator (MNO) and multiple video service providers (VSPs). In this system, the MNO manages and operates its SBSs, and assigns these SBSs’ storage to different VSPs, who have caching requirements. However, videos have different popularities and MUs present different preferences to these VSPs when they request videos. In addition, the caching service brings different utilities to different VSPs as well as that providing caching service to different VSPs causes distinct costs to the MNO. Such privacy information cannot be aware of among VSPs and the MNO. Therefore, to elicit this hidden information, this paper designs a double auction-based caching mechanism, which ensures the efficient operation of the market by maximizing the social welfare, i.e., the gap between VSPs’ caching utilities and MNO’s caching costs. Moreover, this paper demonstrates the economic properties of the designed caching mechanism, which are also validated by the simulation results.

The explosively growing demands for mobile traffic services bring both challenges and opportunities to wireless networks. Wireless network virtualization is proposed as the main evolution path toward the forthcoming fifth generation (5G) cellular networks. In this paper, we propose a software defined and virtualized (SDV) wireless network architecture for enabling multi-flow transmission with multiple infrastructure providers (InPs) and multiple mobile virtual network operators (MVNOs). In order to ensure the heterogeneity, we formulate the virtual resource allocation problem with diverse QoS requirements as a social welfare maximization problem with distance-related transaction cost. Due to hidden information of InPs and MVNOs for the auctioneer, we introduce a shadow price for ensuring desirable economic properties and total welfare for the system. Simulations are conducted with different system configurations to show the effectiveness and the energy efficiency performance of the proposed SDV wireless network framework and iterative double auction mechanism.

Cooperative communication effectively enhances the channel capacity of wireless networks by allowing some single-antenna nodes to relay data for other nodes. In such a communication scheme, choosing appropriate relay nodes is critical to maximize the overall network performance. In this paper, we consider the assignment problem of relay nodes in a cooperative wireless network, where physical relay infrastructures and relay supporting services (relay assignment) are independently operated by different selfish entities, each of which is driven by its own benefit. We first formulate the problem as a repeated double auction by taking into account the benefits of all entities in the system. That is, we consider a system consisting of a set of source-to-destination pairs, relay nodes, group agents, and the auctioneer, where source nodes are grouped into different groups and each group is represented by a group agent. The source nodes and group agents seek opportunities to maximize their own benefits through untruthful bidding, colluding with each other, and so on. We then show that these behaviors will jeopardize the social benefit of all entities in the system. To mitigate the effect of such behaviors, we devise a truthful repeated double auction that is able to bound the collusion probability of each entity. We finally conduct experiments by simulations to evaluate the performance of the proposed auction mechanism. Empirical results show that the proposed auction is effective in collusion-resistance with bounded collusion probabilities. To our best knowledge, this is the first auction mechanism for relay assignment in wireless networks that is truthful, collusion-resistant, budget-balance and individual-rational.

Spectrum auctions motivate existing spectrum owners (as sellers) to lease their selected idle channels to new spectrum users (as buyers) who need the spectrum desperately. The most significant requirement is how to make the auctions economic-robust (truthful in particular) while enabling spectrum reuse. Furthermore, in practice, both sellers and buyers would require to trade multiple channels at one time, while guaranteeing their individual profitability. Unfortunately, existing designs can not meet all these requirements simultaneously. We address these requirements by proposing True-MCSA, a framework for truthful double multi-channel spectrum auctions. True-MCSA introduces novel virtual buyer group (VBG) splitting and bidding algorithms, and applies a proper winner determination and pricing mechanism to achieve truthfulness and other economic properties, meanwhile successfully dealing with multi-channel requests from both buyers and sellers and improving spectrum utilization. Our experiments show that the auction efficiency is impacted by the economic factors with efficiency degradations within 30%, under different settings. Furthermore, the experimental results indicate that we can improve the auction efficiency by choosing a proper bidding algorithm and using a positive base bid. True-MCSA makes an important contribution on enabling spectrum reuse to improve auction efficiency in multi-channel cases.

Auction is widely applied in wireless communication for spectrum allocation. Most of prior works have assumed that all spectrums are identical. In reality, however, spectrums provided by different owners have distinctive characteristics in both spacial and frequency domains. Spectrum availability also varies in different geo-locations. Furthermore, frequency diversity may cause non-identical conflict relationships among spectrum buyers since different frequencies have distinct communication ranges. Under such a scenario, existing spectrum auction schemes cannot provide truthfulness or efficiency. In this paper, we propose a Truthful double Auction mechanism for HEterogeneous Spectrum, called TAHES, which allows buyers to explicitly express their personalized preferences for heterogeneous spectrums and also addresses the problem of interference graph variation. We prove that TAHES has nice economic properties including truthfulness, individual rationality and budget balance. Results from extensive simulation studies demonstrate the truthfulness, effectiveness and efficiency of TAHES.