Abstract
Advances in microelectromechanical systems (MEMS) and nanotechnology have enabled design of low power wireless sensor nodes capable of sensing different vital signs in our body. These nodes can communicate with each other to aggregate data and transmit vital parameters to a base station (BS). The data collected in the base station can be used to monitor health in real time. The patient wearing sensors may be mobile leading to aggregation of data from different BS for processing. Processing real time data is compute-intensive and telemedicine facilities may not have appropriate hardware to process the real time data effectively. To overcome this, sensor grid has been proposed in literature wherein sensor data is integrated to the grid for processing. This work proposes a scheduling algorithm to efficiently process telemedicine data in the grid. The proposed algorithm uses the popular swarm intelligence algorithm for scheduling to overcome the NP complete problem of grid scheduling. Results compared with other heuristic scheduling algorithms show the effectiveness of the proposed algorithm.
Highlights
Telemedicine plays a very important role in patient management and has been effectively used for intrahospital transport of patients
This paper proposes artificial bee colony (ABC) algorithm that can be used in scheduling of resource for the middleware discussed in [8] to provide a scheduling solution which optimizes the makespan of the submitted task
A sensor grid middleware has been designed to receive vital sign from the patients and monitor them continuously to check for abnormality
Summary
Telemedicine plays a very important role in patient management and has been effectively used for intrahospital transport of patients. (i) Large amount of real time data generated by sensors can be processed and stored in the grid. Grid monitoring [10] collects the status and performance details of a large-scale distribution system The parameters such as load on the system, number of jobs in the running state, and the performance of each job in running state are gathered to notify the behavior of the grid environment to the consumers. The information about the jobs and resources are available at the time of scheduling. This paper proposes ABC algorithm that can be used in scheduling of resource for the middleware discussed in [8] to provide a scheduling solution which optimizes the makespan of the submitted task
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