Xiaoyu Tong and Edith C.-H. Ngai Dept. of Information Technology, Uppsala University, Sweden

A UBIQUITOUS PUBLISH/SUBSCRIBE PLATFORM FOR WIRELESS SENSOR NETWORKS WITH MOBILE MULES

• Stationary sensors are more likely to be sparsely deployed in most scenarios.

• But it is cost prohibitive to connect each of them to the Internet at every site.

• As a result, their deployments and usages are heavily limited.

Problems of Ubiquitous Sensing

Sparsely Deployed Temperature Sensors in a Forest

• On the other hand, applications of mobile sensors become incredibly popular.

• But they are constrained by sensor types and abilities.

• Our goal: – Easier and more flexible

deployments of stationary sensors.– Enable ubiquitous sensing services

from both stationary sensors and mobile sensors.

Problems of Ubiquitous Sensing

• Publish/subscribe paradigm is employed to support asynchronous communications.

• Smart phones are utilized as both mobile sensors and data mules.– Built-in sensors: GPS, Camera, etc.– Short range communication with wireless sensors,

IEEE802.15.4, Bluetooth, or ANT.– Encounter and communicate with wireless

sensors opportunistically.

• Stationary sensors are sparsely deployed.

System Model

• Deployments of both stationary sensors and mobile sensors are dynamic.

• Communication overhead will draw power quickly from both mobile phones and stationary sensors.

• Mobile users who carry the smart phones have individual and uncontrollable mobility.

Key Challenges

• MQTT-S has been proposed to enable topic-based publish/subscribe in WSNs.

• Huang et al. described how to distribute the system across multiple computers or mobile devices to distribute load and cope with failures, message loss and disconnections.

• The above works focus on adoption of publish/subscribe in WSNs and publish/subscribe system with mobile environments, while the sensing context, heterogeneity of sensing devices, mobility of nodes and limited connectivity of wireless sensors remain to be further explored.

Related Work

Network Model

• Stationary Sensor: SSensor.• Mobile Sensor: MSensor.• Platform Server: Broker.• Mobile Phone: Mobile Broker.• Sparse Sensor Networks: SSNs.

Publish/Subscribe Platform Design • Area-based Subscriptions

Publish/Subscribe Platform Design • Adaptive Location

Updates– How often should a MB

update its locations?– Default: periodically with

constant time interval– Reduce unnecessary

location updates–

Publish/Subscribe Platform Design • Full Installation• Best-effort Subscription

Delivery– Number of MSensors in a

target area is higher dynamic.– Installations of subscriptions

to SSensors are opportunistic.– Keep deployments of sensors

transparent to platform.

Publish/Subscribe Platform Design • Event Data Collection– ECF: flag avoiding

unnecessary collection.– Push-based event collection

for MSensors.– Pull-based event collection

for Ssensors.

Implementation

• Broker:– Restful Http Server.

• Mobile Broker: – Android + Usb cable + IEEE 802.15.4.– ANT or Bluetooth 4 in the future

• Stationary Sensor: – Contiki + Rime + Coffee + IEEE802.15.4.

Experimentation

• Scenario and Settings

Experimentation

• Installation of Stationary Sensors along Hiking Trail.

Experimentation

• Sensing Data from Stationary Sensors

Experimentation

• Sensing Data from Mobile Sensors

Experimentation

• Sensing Data from Mobile Sensors

Experimentation

• Data Delivery Delay

Experimentation

• Number of Received Data

Experimentation

• Communication Overhead

Summary

• We proposed and implemented a novel publish/subscribe platform for ubiquitous data access from both wireless sensors and mobile phones without relying on any network infrastructure.

• Mobile phones are utilized as mobile mules to relay subscriptions and published data between the Internet users and the remote sensors.

• We implemented our platform on real hardwares and experimented it in a hiking trail application.

• In the future, we plan to study the coordination among heterogeneous mobile and sensing devices to further reduce the energy consumption and communication overhead.