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Event Details

  • Wednesday, November 8, 2017
  • 16:00 - 16:30

QoS for Internet of Things Crowdsourced Environmental Monitoring

Traditional wireless sensor networks and computer vision techniques were utilized to acquire real-time data of the world conditions. Such data collection is vital for the decision-making of many domains like dynamic urban planning, traffic management, public safety, and environmental monitoring. The emerging domain of Mobile Crowd Sensing proposes a new framework for data collection based on the power of sensors installed in smartphones, wearable devices, and sensor-equipped vehicles. Taking advantage of such sensor-enabled devices which reside at the edge of the Internet in more real-life disciplines will cause an evolution in the concept of Internet of Things (IoT). Soon up to several billions of IoT devices will push their sensing data across the Internet. The amount of data IoT promises to generate will challenge the existing networks that were initially built for human-centric interactions. Due to the dynamic and real-time nature of IoT, traditional network architectures become inadequate to provide this type of Quality of Service (QoS).In this talk, I will propose making the network intelligent enough to take some early on decisions to provide certain QoS for IoT crowdsourced environmental applications. Thus, I leverage the new paradigm of Software Defined Networks (SDN), along with the Hierarchical Token Bucket (HTB) queuing discipline to provide dynamic and within application QoS. We employed the well-known weather signal application as a use case for our experimental design. We implement our design through well-known open source SDN components and evaluate its effectiveness using real IoT sensor traces. Our results show that the proposed framework can provide higher QoS for IoT applications under the exact network resources and conditions.