1 APPLICATION PARAMETERS OPTIMIZATION TO GUARANTEE QoS IN E-HEALTH SERVICES I.Martínez J. García E. Viruete J.Fernández Communications Technologies Group (GTC) - Aragon Institute of Engineering Research (I3A) imr_at_unizar.es University of Zaragoza. Ada Byron Building. Campus Río Ebro - c/María de Luna 3 50018. Zaragoza (Spain)
Description of the evaluation scenario
The implementation of a new e-Health service requires a QoS technical evaluation to study its behaviour under different conditions. The main characteristics of this evaluation (see Fig. 1) are
Evaluation scenario communications among health professionals of different specialties.
e-Health services cooperative work shared medical applications remote diagnosis etc.
Type of information multimedia applications based on TCP (biomedical information transfers and medical files retrieval) and UDP (videoconference on-line biosignals transmission).
Evaluation parameters (see Fig. 2) TCP data (SMSS) UDP data (S) UDP packet size (s) burst size (MBS) data rate (1/Dt) delay (EED) loss rate (PLR) capacity (C) bandwidth (BW).
Use Cases (UCs)
UC1. The health professional sends biomedical data to the hospital in Store-and-Forward (SF) mode. This SF.Data service includes medical tests and patient-related information.
UC2. Including UC1 the health professional also queries the hospital database to manage the Electronic Patient Report (EPR) through a real-time (RT) web connection (RT.EPR).
UC3. Including UC2 the health professional establishes a RT multimedia conference (including audio and video) with other specialist to support the diagnosis (RT.Media).
UC4. The health professional often requires acquiring and sending specific biomedical signals (ECG ECO BP Sp02) to complete the patient diagnosis (RT.Bio).
Fig.1 Evaluation scheme and use cases (Ucs) of a rural e-Health service Fig.2 Specific RT and SF parameters considered in this study
Results. UC1 and UC2 (TCP services)
SMSS analysis. Using results previously obtained UC1 and UC2 were evaluated with the QoS network conditions recommended by ITU PLRlt0.20 EEDlt180s. The evaluation includes specific test sizes (S) for the main medical practices computing radiography electrocardiography ecography etc (see Fig.3).
The results show that T decreases when SMSS rises and in a nonlinear way with the loss variability T remains constant with a low PLR level (PLRlt0.05) but T notably increases (31) when PLR rises. Since large packets fit the link capacity better T decreases with higher SMSS values (but the retransmission percentage increases due to the reactivation algorithm regardless of packet size).
EED analysis keeps this compromise (see Fig. 4) it is almost constant without PLR (independently of SMSS) but rises when SMSS does (due to SS algorithm reactivations with lower SMSS values that empty the buffer and reduce EED).
BW analysis. The available BW (ABW) depends on PLR level (see Fig. 5) with low SMSS values BW decreases down to ABW1.4Mb/s in the worst case (with SMSS512B and PLR0.20).
In summary all these tendencies recommend the use of low SMSS values in order to avoid using specific priority allocation methods and allow sharing network resources with UDP services as it is evaluated in the next section.
(a) PLR lt 0.10 (b) PLR lt 0.03 Fig. 3 Transmission time regarding SMSS with constant PLR Fig. 4 EED regarding SMSS with variable PLR Fig. 5 ABW regarding SMSS with variable PLR Results. UC3 and UC4 (UDP services) The UC3 and UC4 specific evaluation parameters are data size S4k 2k 1k 500 (B) a variable number (N) of simultaneous user connections (with user rate r64 32 (kb/s)) buffer size range of Q515 and two groups of sizes large packets sHi1472 1380 (B) and small packets sLi512 240 (B). Table I. Evolution of PLR as a function of Q with different S N combinations and two groups of packet sizes (a) large packets (b) small packets
PLR analysis. The combinations that fulfill the PLR threshold (see Table I for sH11472B (left) and sL2240B (right) and r164kb/s) are
- Large packets Q10 (with N4) and Q6 (with N2).
- Small packets Q15 (with N4) and Q15 (with N2).
EED analysis. The variation of C shows (see Fig.6a)-(b) with S14kB and N4) when the QoS thresholds are guaranteed
- Large packets if C128kb/s Q5 if C192kb/s Q7
if C256kb/s Q9 if C384kb/s Q12.
- Small packets if C128kb/s Q8 if C192kb/s Q10
if C256kb/s Q11 if C384kb/s Q15.
This analysis is completed with r232kb/s for the same Si variation range. Fig. 6(a)-(c) shows a example with S14kB and sH11472B. The new EED (r232kb/s N8) is lower than the previous (r164kb/s N4) even with the same information amount. Moreover it changes the QoS thresholds C192kb/s is now useful with Q9 (previously Q7) and C384kb/s is useful with 12Q15 (previously only Q12). Thus low burst sizes fulfill better QoS.
(a) sHi altos r164kb/s (b) sLi bajos r164kb/s (c) sHi altos r232kb/s Fig. 6 EED with variable si y rk regarding Q focusing on the most critical areas closer to the QoS thresholds (EEDlt200ms) Conclusions The results obtained show the best performance range with small TCP packets and buffer sizes lower than 15 packets for the UDP services. These values are recommended in further designs of e-Health services to guarantee the specific QoS requirements. Figure at right shows an example of how the adaptive selection of the buffer size would be (buffer is initially sized with Q15 10 or 6 depending on small packets and N4/N2 (step 1a) large packets and N4 (step 1b) or N2 (step 1c) with C256kb/s. If C192kb/s it can be reconfigured to Q12 8 or 5 (steps 2a 2b or 2c).
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