82 research outputs found
Decentralised Edge-Computing and IoT through Distributed Trust
The emerging Internet of Things needs edge-computing - this is an established fact. In turn, edge computing needs infrastructure decentralisation. What is not necessarily established yet is that infrastructure decentralisation needs a distributed model of Internet governance and decentralised trust schemes. We discuss the features of a decentralised IoT and edge-computing ecosystem and list the components that need to be designed, as well the challenges that need to be addressed
Differential Privacy-Based Online Allocations towards Integrating Blockchain and Edge Computing
In recent years, the blockchain-based Internet of Things (IoT) has been
researched and applied widely, where each IoT device can act as a node in the
blockchain. However, these lightweight nodes usually do not have enough
computing power to complete the consensus or other computing-required tasks.
Edge computing network gives a platform to provide computing power to IoT
devices. A fundamental problem is how to allocate limited edge servers to IoT
devices in a highly untrustworthy environment. In a fair competition
environment, the allocation mechanism should be online, truthful, and privacy
safe. To address these three challenges, we propose an online multi-item double
auction (MIDA) mechanism, where IoT devices are buyers and edge servers are
sellers. In order to achieve the truthfulness, the participants' private
information is at risk of being exposed by inference attack, which may lead to
malicious manipulation of the market by adversaries. Then, we improve our MIDA
mechanism based on differential privacy to protect sensitive information from
being leaked. It interferes with the auction results slightly but guarantees
privacy protection with high confidence. Besides, we upgrade our
privacy-preserving MIDA mechanism such that adapting to more complex and
realistic scenarios. In the end, the effectiveness and correctness of
algorithms are evaluated and verified by theoretical analysis and numerical
simulations
Multiattribute-Based Double Auction Toward Resource Allocation in Vehicular Fog Computing
Vehicular fog computing (VFC) could provide fast task processing services for vehicles. To make vehicles/fog nodes willing to buy/sell resources, a double auction mechanism considering the interests of all parties is needed. However, few works study the auction issue in VFC. Different from the existing edge-related auction which only considers the price, some nonprice attributes (location, reputation, and computing power) are also important for providing fair resource allocation in VFC. In this article, we propose a multiattribute-based double auction mechanism in VFC, which considers both the price and nonprice attributes for constructing reasonable matching. To the best of our knowledge, this is the first work to consider multiattribute-based auction in VFC. Our auction mechanism could satisfy computational efficiency, individual rationality, budget balance, and truthfulness. To verify the proposed mechanism, we simulate VFC using VISSIM and extract the driving data. The experimental results show the effectiveness and efficiency of this mechanism
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