Efficient Crowd Sensing Task Distribution Through Context-Aware NDN-Based Geocast

Abstract

To realize a crowd sensing campaign, sensing tasks with spatio-temporal requirements are distributed to the devices that can provide the requested information. Typically, this distribution relies on a centralized communication infrastructure such as cloud servers, which is unsuitable when access to such infrastructure is restricted, for example in disaster relief scenarios. This paper proposes a decentralized approach to task distribution using Named Data Networking (NDN) with context-aware geocasting to efficiently reach devices matching the spatio-temporal requirements of a sensing task.

Publication
Proceedings of the 42nd IEEE Conference on Local Computer Networks (LCN)

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