Research Of Incentive Mechanism And Efficient Data Access In Crowd Sensing Networks

With the rapid development of mobile communication and computing techniques,there is a proliferation of smart mobile terminals embedded with multiple sensors.Crowd sensing network has been a promising approach to collect and analyze distributed sensed data with the help of terminal users.Compared with traditional wireless networks,crowd sensing network is human-centric,namely that terminal users are both of “consumers” and “products” of sensed data.Enlarged sensed data coverage and efficient data access are important to the success of crowd sensing networks.In this paper,we analyze how to design incentive mechanism to provide enlarged sensed data coverage,and how to improve the performance of data access via D2 D communications.The success of crowd sensing network critically depends on the enlarged sensed data coverage.For example,the 3D modeling of a building requires complete angular coverage around the building's perimeter,and a noise pollution map of a city requires sensed data all over the city.However,most participants are clustered in some popular areas,and there is few participant in the unpopular areas,which creates the problem of coverage hole.None of the existing incentive mechanisms considers this problem.In this paper,we are the first to prose a movement-based incentive mechanism,where participants are stimulated to move under the instructions from the platform to benefit both participants and the platform.Compared with existing incentive mechanism,the movementbased incentive mechanism increases the task completion ratio by 135.75%,the participant winning ratio by 146.7%,and the social welfare by 85.71%.From the market perspective,we define that the supply for a sensing task is the number of participants bidding for this task,and the demand for a sensing task is the number of participants that this task requires to be completed by.Due to the uneven participant distribution,most of the sensing tasks in the popular areas are in supply surplus and most of the sensing tasks in the unpopular areas are in demand surplus.In this paper,we propose a market-based incentive mechanism,where the platform stimulates participants to complete the sensing tasks in the unpopular areas to achieve an enlarged sensed data coverage.Compared with existing incentive mechanism,the market-based incentive mechanism increases the task completion ratio by 294.9%,the participant winning ratio by294.9%,and the social welfare by 246.02%.With the development of crowd sensing-based applications,traffic demands explosive,while the capacity of the current cellular network is limited.In 5G,people analyze how to improve the performance of data access via device-todevice communications.Neighbor discovery is a crucial step in the initialization of device-to-device communication.Due to the long transmission range,low power,and high space utilization,there has been strong interest to utilize directional antennas.Compared with the synchronous neighbor discovery algorithm,the asynchronous one does not need GPS,which is easy to implement in practice.Most of existing algorithms are discussed in the synchronous scenarios.In this paper,we propose multiple asynchronous neighbor discovery algorithms in wireless networks with directional antennas,and validate the practicality of our proposed algorithms by various simulations.Caching is a promising way to improve the performance of data access.The key challenge is how to select relays.The existing algorithms select relays that contact other nodes with high probability from network structure perspective.Considering the “human-centric” of crowd sensing networks,we propose the relay selection algorithm from both of the network structure perspective and the social network perspective.Furthermore,we construct caching algorithms for multicasting and broadcasting,and discuss their differences.Our research results are easy to implement in crowd sensing networks,to improve the sensed data coverage and the performance of data access.Due to the diversity of the terminals' mobility,we will consider more practical mobile models and study how such mobile models affect the incentive mechanism design and relay selection algorithm.