Towards Proactive Context-Aware Service Selection in the Geographically Distributed Remote Patient M...
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Towards Proactive Context-Aware Service Selection in the Geographically Distributed Remote Patient Monitoring System. P. Pawar, B. J. F. van Beijnum, H. Mei, H. Hermens. Outline. Introduction Remote patient monitoring system (RPMS) Proactive and reactive context-aware service selection

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P. Pawar, B. J. F. van Beijnum, H. Mei, H. Hermens

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Towards Proactive Context-Aware Service Selection in the Geographically Distributed Remote Patient Monitoring System

P. Pawar, B. J. F. van Beijnum, H. Mei, H. Hermens



Remote patient monitoring system (RPMS)

Proactive and reactive context-aware service selection

Problem description

Need for distributed RPMS solution in the large scale geographic environment

Clever solution is required for proactive service selection


Hierarchical architecture for distributed RPMS

Services, data and context flow

Proactive service selection approach

Simulation methodology

Conclusion and future work


AWARENESS Project: Remote Patient Monitoring System

Architecture of the Centralized Remote Patient Monitoring System

  • Based on the SOA concept

  • Fixed and mobile services

  • Services have associated context sources

  • Emergency response services: doctor, ambulance/paramedic, hospital

  • SSIM uses context information of the patient and ERSs to select appropriate ERSs

  • Useful context information

    • Location of patient, ambulance, hospital

    • Availability of ERSs

    • Patient emergency status

Reactive and Proactive ERSs Selection Approaches

  • Reactive approach

    • Select ERSs on occurrence of emergency

  • Proactive approach

    • Select ERSs before emergency occurs

  • Persistent context-aware service discovery is enabler for proactive approach

  • Context changes need updating ERSs selection

  • Proactive approach may need higher amount of resources

Problem Description

Proactive ERSs Selection in Large Scale Distributed Remote Patient Monitoring System

  • For targeting larger geographic region, we need to move from centralized solution to the distributed solution

  • The distributed solution could have components such as context server, service directory distributed according to the geographic zones

  • Reactive approach in the distributed RPMS could be a bottleneck due to distributed nature of services and other components

  • Hence a clever solution for proactive ERSSs selection is required


SSI Module

Mobile Services

Service Directory

Surrogate Host

Fixed Services

Context Source

Context Server

OID Server

POS Server

Logical Hierarchical Architecture for Distributed RMPS

OID Index Space


POS Server

POS Server

Service Selection &

Invocation Module

POS Server

Service Selection &

Invocation Module


Service Selection &

Invocation Module






Context Server

Context Server

Context Server





Other ctx.

Other ctx.

Other ctx.


Fixed OID

Mobile OID

Service Directory

Service Directory

Service Directory




Other attr.

Other attr.

Other attr.

Basic Components and Interactions in Distributed RPMS

  • Object Index (OID) server: keep track of servers storing object data for queries like which context server stores the context information of caregiver object with OID CG12?

  • Position (POS) server: Stores X-Y coordinates of the location of fixed and mobile objects

OID Server record

Services, Data and Context Flow

  • Each level 1 OID-index server subscribes to the service directory (1) and context server (2).

  • POS server subscribes to the context server (3) to receive object location changes events.

  • When a service is activated, it first contacts the central data server (4) to obtain service dir., context server and SH info.

  • Service (5-7-8) and context source registration (6-9).

  • Service directory (context server) sends notification to the OID-index server (10 (11)).

  • Context server sends notification to the POS-server (12).

  • OID index server updates its records and this update is propagated to the root level OID index server (13-14).

  • For proactive ERSs selection approach, the surrogate host sends ERSs selection request to the level 1 SSIM (15).

  • SSIM contacts the POS server (16) to obtain the zone adjacency list, determines the least common SSIM to the current zone and adjacent zones.

  • ERSs selection request is forwarded to the least common SSIM (17) which could eventually reach root level SSIM (18) in case required ERSs are not found in these zones.

Handling Mobile Object’s Geographic Mobility

  • Results in the handover from old SH to new SH

  • Old SH monitors object location and determines need for handover and new SH - Use dwell timer to prevent ping-pong effect

  • Old SH sends the new SH info of the mobile object (1)

  • Mobile object sends further service and context data to the new SH (3-4).

  • New SH confirms data reception to old SH (5)

  • Old SH sends the service (context source) removal due to handover message to the old service directory (old context server) (6 (7)).

  • New SH registers service (context source) in the new service directory (new context server) (9 (10))

  • Removal of state of mobile object from old service directory, context server and POS Server (11-12-13)

  • Registration of state of mobile object to the new POS Server, OID server and further propagations (15-16-17-18)

Proactive Context-Aware ERSs Selection & Invocation Mechanism

  • Determine initial SSIM

  • Perform context-aware ERSs selection, if not found, propagate selection request upwards

  • After ERSs found, send ERSs selection to the maintaining SSIM

  • Wait for context changes for updating ERSs selection

    • Caregiver status changes to busy.

    • Doctor’s status changes to busy.

    • Hospital is full and can not accommodate further number of patients.

    • The relative distance between of the patient and caregiver (or between the patient and ambulance) exceeds certain value.

    • Any of the ERSs (caregiver, ambulance and hospital) goes offline.

    • The caregiver (or ambulance) moves out of the current geographic zone.

Simulation Methodology and Approach

  • Event based simulation

    • Order and process the events according to their timestamp (temporal ordering)

    • Process events one by one and queue the possible resulting events in the temporal order for further processing

  • We are working with the medical professionals in Singapore

  • The simulation will specifically analyze

    • Resource utilization (e.g. computational and communication requirements, time spent for the service selection and invocation operations);

    • Emergency response time savings of the proactive vs. reactive ERSs selection approaches.

Conclusion and Future Work

Conclusion and Future Work

  • Proactive context-aware ERSs selection approach could be beneficial in the distributed RPMS

  • A logical architecture for the distributed RPMS where the RPMS components are distributed geographically

  • Details on the ERSs data and context flow, mobility handling mechanisms and proactive ERSs selection approach in such architecture

  • Simulation methodology for the performance evaluation for analyzing tradeoff for the resource utilization and emergency response time

  • Working on the event based simulation of the distributed RPMS modeled according to the geographical zones and patient population distribution in the Singapore region


  • Freeband Awareness project (Funded by Dutch BSIK program BSIK5902390)

  • IST-Amigo project (Partially funded by EC)

  • Institute for Infocomm Research, Singapore


Towards Proactive Context-Aware Service Selection

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