A Blockchain-Based Reward Mechanism for Mobile Crowdsensing

Abstract

Mobile CrowdSensing (MCS) is a novel sensing scenario of Cyber-Physical-Social Systems. MCS has been widely adopted in smart cities, personal health care, and environment monitor areas. MCS applications recruit participants to obtain sensory data from the target area by allocating reward to them. Reward mechanisms are crucial in stimulating participants to join and provide sensory data. However, while the MCS applications execute the reward mechanisms, sensory data and personal private information can be in great danger, because of malicious task initiators/participants and hackers. This work proposes a novel blockchain-based MCS framework that preserves privacy and which secures both the sensing process and the incentive mechanism by leveraging the emergent blockchain technology. Moreover, to provide a fair incentive mechanism, this paper has considered an MCS scenario as a sensory data market, where the market separates the participants into two categories: monthlypay participants and instant-pay participants. By analysing two different kinds of participants and the task initiator, this paper proposes an incentive mechanism aided by a three-stage Stackelberg game. Through theoretical analysis and simulation, the evaluation addresses two aspects: the reward mechanism and the performance of the blockchain-based MCS. The proposed reward mechanism achieves up to a ten percent improvement of the task initiator's utility compared with a traditional Stackelberg game. It can also maintain the required market share for monthly-pay participants whilst achieving sustainable sensory data provision. The evaluation of the blockchain-based MCS shows that the latency increases in a tolerable manner as the number of participants grows. Finally, the paper discusses the future challenges of blockchain-based MCS. Index Terms-Mobile crowdsensing, blockchain, reward mechanism, Stackelberg game, sensory data market I. INTRODUCTION T HE development of network technology, sensing devices, and social networks has increased the deployment of the next generation of Internet of Things (IoT)-Mobile CrowdSensing (MCS). MCS is a novel sensing framework, which is assisted by smartphone sensors and with the inclusion of human intelligence in the loop. MCS has become a typical application in Cyber-Physical-Social Systems (CPSS) [1], [2] because it adopts the multidisciplinary approach where knowledge from communication, computer science, computer network, economic, psychology, and social research unite to provide a solution of a sensing task.

Blockchain-Aided Flow Insertion and Verification in Software Defined Networks

“…Verifier i ∈ V = {1, ..., n} who participates in verification can select the blocksize from a set S = {s 1 , ..., s n }, n ≥ 1. We define verifier i select blocksize s i ∈ S Similarly to [4], the execution cost of a verifier is defined in quadratic form, which is thus convex and provides a straightforward evaluation of the derivative.…”

“…The use of an independent confirmation is important as it can be separate from the underlying SDN application, which may be vulnerable. This is performed through a flow conformance test implemented within a smart contract of a blockchain (BC) [4]. BC technology, a sub-concept of distributed ledger technology, is essentially an append-only data structure maintained by a group of not-fully-trusted nodes, that nevertheless provide a trusted data structure through a suitable consensus algorithm [5].…”

SMCP: a Secure Mobile Crowdsensing Protocol for fog-based applications

“…Distributed consensus in the context of the Internet of Vehicles is achieved in [24] through permissionless blockchains in order to guarantee reliability of information collected from individual vehicles. Similarly, blockchain technology is adopted in [25] both to ensure privacy during the mobile crowdsensing process, and to protect the reward mechanism for participants.…”

Hybrid Blockchain for IoT—Energy Analysis and Reward Plan

“…While a number of blockchain systems exist, two common approaches are—proof of work (PoW) based consensus mechanisms and Practical Byzantine Fault Tolerance (PBFT) consensus mechanisms [ 3 ]. Blockchains based on a PoW consensus mechanism are computationally-intensive and hence energy-expensive [ 4 ], however, they provide excellent trustworthiness in a system that spans organizational boundaries.…”

“…Blockchains based on a PoW consensus mechanism are computationally-intensive and hence energy-expensive [ 4 ], however, they provide excellent trustworthiness in a system that spans organizational boundaries. On the other hand, a PBFT based consensus mechanism is communication-intensive [ 3 ] but has been widely used as a permissioned private blockchain system. Thus, there is a motivation for a combination of these systems to achieve a balance between verification performance and energy cost.…”