Multiobjective Communication Optimization for Cloud-Integrated Body Sensor Networks

Cluster, Cloud and Grid Computing(2014)

引用 25|浏览8
暂无评分
摘要
This paper focuses on push-pull hybrid communication in a cloud-integrated sensor networking architecture, called Sensor-Cloud Integration Platform as a Service (SC-iPaaS). SC-iPaaS consists of three layers: sensor, edge and cloud layers. The sensor layer consists of wireless body sensor networks, each of which operates several sensors for a homebound patient for a remote physiological and activity monitoring. The edge layer consists of sink nodes that collect sensor data from sensor nodes in the sensor layer. The cloud layer hosts cloud applications that obtain sensor data through sink nodes in the edge layer. This paper formulates an optimization problem for SC-iPaaS to seek the optimal data transmission rates for individual sensor and edge nodes and solves the problem with respect to multiple objectives (e.g., data yield, bandwidth consumption and energy consumption) subject to given constraints. This paper sets up a simulation environment that performs remote multi-patient monitoring with five on-body sensors including ECG, pulse oximeter and accelerometer per a patient. Simulation results demonstrate that the proposed optimizer successfully seeks Pareto-optimal data transmission rates for sensor/sink nodes against data request patterns placed by cloud applications. The results also confirm that the proposed optimizer outperforms an existing well-known optimization algorithm.
更多
查看译文
关键词
body sensor networks,optimisation,patient monitoring,ECG,accelerometer,activity monitoring,cloud integrated body sensor networks,cloud layer,edge layer,multiobjective communication optimization,pulse oximeter,push pull hybrid communication,remote physiological monitoring,sensor cloud integration platform as a service,sensor data,sensor layer,sink nodes,wireless body sensor networks,Body sensor networks,cloud-integrated sensor networking,evolutionary algorithms,multiobjective optimization
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要