ORIGINAL PAPER
RACOON: A Multiuser QoS Design for Mobile Wireless
Body Area Networks
ShihHeng Cheng&ChingYao Huang&Chun Chen Tu
Received: 1 November 2010 / Accepted: 25 February 2011 / Published online: 5 April 2011 # Springer Science+Business Media, LLC 2011
Abstract In this study, Random Contention-based Resource Allocation (RACOON) medium access control (MAC) protocol is proposed to support the quality of service (QoS) for multi-user mobile wireless body area networks (WBANs). Different from existing QoS designs that focus on a single WBAN, a multiuser WBAN QoS should further consider both inter-WBAN interference and inter-WBAN priorities. Similar problems have been studied in both overlapped wireless local area networks (WLANs) and Bluetooth piconets that need QoS supports. However, these solutions are designed for non-medical transmissions that do not consider any priority scheme for medical applications. Most importantly, these studies focus on only static or low mobility networks. Network mobility of WBANs will introduce unnecessary inter-network collisions and energy waste, which are not considered by these solutions. The proposed multiuser-QoS protocol, RACOON, simultaneously satisfies the inter WBAN QoS requirements and overcomes the performance degradation caused by WBAN mobility. Simulation results verify that RACOON provides better latency and energy control, as compared with WBAN QoS protocols without consider-ing the inter-WBAN requirements.
Keywords Wireless body area network . Multiuser quality of services . Mobility . Prioritized scheduling . Interference detection
Introduction
Quality of Service (QoS) for medical applications is an emerging issue for wireless body area networks (WBAN) [1, 2]. To reliably transmit data streams of medical applications (e.g. vital signals or diagnosis audio / video), WBAN QoS is asked to meet more harsh requirements than those of other wireless networks in terms of transmission latency, packet error rate (PER), and energy consumption, as mentioned in [3–9]. Furthermore, WBAN QoS is featured by considering different critical levels of vital signals. For instance, electrocardiograms (ECG) are deemed to have more important information than body temperature to indicate the health status of a person, hence ECG signals are supposed to have higher priority than that of body temperature. Many centralized scheduling technologies of medium access control (MAC) layer have been proposed to support QoS for a single WBAN (single user) [3–9]. In these works, a central processing node (CPN) of a WBAN centrally schedules radio resources of wireless sensor nodes (WSNs) illustrated in Fig.1. These centralized controls can effectively meet various QoS requirements of vital signals. They also save energy consumptions of WSNs due to their light control loading of WSN in the CPN-centralized controls [9]. Nevertheless, some WBAN scenarios involve co-existence of multiple users, e.g. a hospital waiting room or a crowded subway station. Co-channel and co-location interference happens when WBANs move close to each other. It causes packet collisions and energy waste, which hence impact WBAN QoS. Besides, multiuser scenarios S. Cheng (*)
:
C. Huang:
C. C. TuDepartment of Electronics Engineering, National Chiao Tung University, Hsinchu, Taiwan e-mail: scott.shcheng.ee95g@g2.nctu.edu.tw C. Huang e-mail: cyhuang@faculty.nctu.edu.tw C. C. Tu e-mail: ChunChenTu.ee99g@g2.nctu.edu.tw DOI 10.1007/s10916-011-9676-3
might need extra definitions of critical levels of medical data. The critical levels of vital signals might vary according to not only signal properties (like the ECGs v.s. Body temperature example in a single WBAN QoS) but also user status. For instance, vital signals of an injured person might need higher priority than that of a healthy one. Thus, inter-WBAN priority scheme would be neces-sary. As a result, a new challenge of multiuser QoS that considers above inter-WBAN issues is introduced. To the best of our knowledge, there is no existing works addressing on solutions of multiuser WBAN QoS so far. Comprehensive studies are still required.
QoS designs for overlapped wireless local area networks (WLANs) or Bluetooth piconets might be the closest problems to multiuser QoS. Jiang and Howitt [10] analyze load-balancing between co-channel and co-location (overlapped) WLANs. Access points (APs) properly share bandwidth according to an optimized load-balancing through backhaul (wire-line) communications. On the other hand, for over-lapped piconets, the inter-piconet interference is overcome by interconnecting discrete piconets into a scatternet [11–16]. A scatternet (cross piconet) scheduling is thus applied to provide collision free transmissions among overlapped piconets. However, these approaches might not be suitable multiuser QoS solutions for several reasons. First, these approaches are originally designed for non-medical transmissions, which have less strict QoS requirements and lack priority schemes for medical data. Furthermore, the WLAN approach focuses on static or low mobility scenarios. Its backhaul optimization is only suitable for fixed wireless nodes, which is not possible to be applied for mobile WBANs. On the other hand, the scatternet approach introduces extra control/traffic loading and energy consumption of slave nodes (similar to WSNs in WBAN) when they serve as scatternet bridges. However, for many WBAN applications, WSNs are expected to be very low power and have a very long battery-life, e.g. an implanted pacemaker is requested to perform years heart-pacing without battery changes. Thus, neither the QoS solutions for over-lapped WLANs nor piconets can be directly applied to multiuser QoS.
In this study, proposed Random Contention-based Resource Allocation (RACOON), which is extended from
our previous work [17], provides a multiuser QoS scheme for mobile WBANs. RACOON is featured by:
& Simple inter-WBAN resource allocation, which simplifies the control overhead of inter-WBAN QoS control. Resource allocation between WBANs is decided through random-value comparisons between WBANs. In RA-COON, only one broadcasting packet that carries random values will be required to complete every inter-WBAN resource contention.
& Iterative inter/intra-WBAN QoS control, which supports a dynamic QoS adjustment in mobile WBAN scenarios. The adjustment will consider both critical-level differ-ences among (i) adjacent WBANs and (ii) Vital signals. & Hierarchy CPN/WSN resource allocation, which utilizes the asymmetric CPN/WSN structure and thus decrease control loadings and energy consumptions of WSNs. In the hierarchy CPN/WSN resource allocation, CPN is in charge of both inter/intra resource scheduling. WSN only wakes up while it is polled by its associated CPN. & Probing base inter-WBAN interference detection, which
detects potential inter-WBAN interferences before actual collisions happen in both downlink (CPN to WSN) and uplink (WSN to CPN) transmissions. The interference detection avoids packet collisions and energy waste caused by WBAN mobility and hence extends battery life of WSNs.
The rest of this paper is organized as follows:“WBAN quality of services (QoS)” section introduces requirements
of WBAN QoS. “Random contention-based resource allocation (RACOON)” section reveals the proposed
RACOON multiuser QoS protocol.“Computer simulation”
section presents the experimental results and“Conclusion”
section concludes this paper.
WBAN quality of services (QoS) Requirements of WBAN QoS
WBAN QoS controls that simultaneously support both intra and inter WBAN QoS are studied in this work. A WBAN consists of a single central processing node (CPN) and several wireless sensor nodes (WSNs). These WSNs collect various medical data (including vital signals from human body and diagnosis audio/video) and forward them to the CPN, which is depicted in Fig. 1. Intra WBAN QoS controls should make sure these medical data are timely transmitted by following their bound and delay-variation requirements [18]. However, when total band-width requirements of a WBAN overflow its capacity, transmissions should be scheduled in an order from the highest-priority data to that has the lowest priority, which Vital Signals WSN WBAN WBAN WBAN CPN
guarantees the QoS level of high priority data. Such priority settings are usually designed by medical experts according to their clinical experiences. For example, a heart failure could introduce much instant life risk than an abnormal body-temperature. Hence, ECG signals directly reflecting heart activity should have higher priority than that of temperature records. This kind of priority is called as intrinsic data priority. Furthermore, if abnormal vital signals are detected, the priorities of these signals should be dynamically increased to be higher than those of normal signals. Such priority is called as emergent data priority. Therefore, intra WBAN QoS controls should meet various latency requirements of difference medical data and follow proper intrinsic and emergent data priorities simultaneously. On the other hand, for inter-WBAN QoS designs, proper user priority should be further provided. In scenarios of multiple overlapped WBANs, WBANs need to share radio resource with each other. Once the overall capacity is not sufficient to support all transmission bandwidth of WBANs, radio resources should be allocated to WBANs that has higher user priority. Such priority should also be defined by medical experts. Usually, priority settings follow an order from the highest to the lowest life-critical WBAN users. High user-priority WBANs should be allowed to transmit all necessary medical data; low user-priority WBANs should transmit only partial medical data to maintain normal health monitoring. As a result, WBAN QoS controls should simultaneously satisfies (i) intrinsic data priority (ii) emergent data priority and (iii) user priority for both intra and inter WBAN QoS.
Aside from transmission qualities above, a WBAN QoS control should try to lower energy consumption of WSNs as well [1,18,19]. In a WBAN, a CPN will most likely be embedded in personal devices such as cellular phones or PDAs with larger and rechargeable batteries. In contrast, WSNs are expected to be light weight (small battery) and even un-rechargeable for certain implantable applications. Thus, WSNs are expected to keep their energy consump-tions as low as possible.
Performance metrics
To qualify a QoS control for WBAN, following performance metrics will be evaluated.
& Transmission Latency: transmission latency affects smoothness of real-time display of vital signals. A transmission latency of a medical packet is calculated from the time of a packet is generated in a WSN to the time of the packet is successively received by a CPN. To ensure a vital signal is timely displayed, every packet of the signal should be received before its delay bound expires. & Joule per bit of WSN: energy consumption of a WSN
affects its battery life. To evaluate energy consumptions
of WSNs with various traffic loading, an energy measurement is normalized by its transmission band-width with the unit, Joule per bit. An energy measure-ment of a WSN will count all its packet transmissions (successful/unsuccessful packet transmissions from WSN to CPN) and receptions (successful/unsuccessful polling message receptions from CPN to WSN). & User capacity: user capacity affects the density of
coexistence WBAN users, which is important for dense WBAN scenarios. User capacity is defined as the maximum number of coexistence WBANs that satisfy desired WBAN QoS requirements.
Related works
Significant contributions toward high quality WBAN QoS designs have been made in recent years [3–8,20,21]. These works adopt different framing, scheduling, and novel hard-ware techniques to optimize emergency transmission, packet latency, and power consumption of a single user WBAN. Huasong [5] creates a framing-structure-turning procedure to simultaneously improve throughput, queuing delay, and energy consumption of IEEE 802.15.4, a candidate protocol for WBAN. Yoon [3] further modifies the framing structure of 802.15.4 to remarkably reduce the packet delay of emergency alarm. He further introduces a preemptive scheduling to guarantee the transmission priorities of various medical data. There are also scheduling techniques utilizing TDMA-overhead-reduction [20], adaptive duty cycle [21], prioritized retransmission [6], delayed retransmission [4], fuzzy-logic controls [8], and wake-up radio [21] to enhance WBAN QoS. Su and Zhang further combine scheduling with realistic battery charging/discharging effect to significantly prolong battery life of WBAN sensors. More complete introductions and comparisons of existing WBAN QoS solutions are summarized by Ullah [19]. Different from above single WBAN solutions, proposed RACOON protocol puts more focus on multi-user WBAN QoS solution, which will be introduced in following sections.
Random contention-based resource allocation (RACOON) The proposed Random Contention-based Resource Alloca-tion (RACOON) is a bandwidth control system embedded in medium access control (MAC) layer for multi-WBAN QoS, which consists of two major designs: a CPN-based resource allocation and a random contention-based inter-CPN negotiation.
CPN-based resource allocation
The CPN-based resource allocation of RACOON is designed to minimize energy consumptions of WSNs and
early detect inter-WBAN interference to avoid unnecessary packet collisions. The proposed CPN-based protocol has a two-step resource allocation scheme, which is illustrated in Fig. 2. There are two distinct channels for inter and intra-WBAN communication, respectively. The inter-intra-WBAN channel is used to exchange the resource negotiation messages between WBANs. Only CPNs can access the inter-WBAN channel. On the other hand, the intra-WBAN channel is used to transmit polling messages from CPN to WSN and data packets from WSN to CPN. The superframe is divided into fixed number of slots. Each slot is sub-divided into a short polling slot and a data slot, which are illustrated in Fig. 2. WSN receive not only transmission schedule from polling messages but also framing structure information including the start of a superframe and number of slots in it. When multiple WBANs overlap with each other, a CPN first negotiates WBAN resources with adjacent CPNs through the inter-WBAN channel. The detailed procedure of inter-CPN negotiation will be introduced in “Random contention-based inter-CPN negotiation” section. The CPN then assigns reserved
resources to its WSNs by polling messages through the intra-WBAN channel. As a result, the WSNs wake up only when (1) receiving polling messages from the associated CPN in polling slots and (2) transmitting vital signals to that CPN if they are polled, hence energy consumptions of the WSNs can be reduced.
In the proposed CPN-based resource allocation, WSNs do not need to perform any interference detection. Instead, a probing-based interference detection, which utilizes a coverage difference between CPN and WSNs, is used and illustrated in Fig.3. A CPN has a larger transmission range than that of WSNs, which allow the CPN to detect potential interferences to its uplink (WSN to CPN) and downlink (CPN to WSN) transmissions. The detection is realized by periodic “probing” from the CPN to its adjacent CPNs. These probing messages are exactly the inter-CPN negoti-ation messages and the CPN is probed when it receives
negotiation messages from other CPNs. Therefore, the interference detection and inter-WBAN negotiation are finished at the same time. Figure 3 illustrates the proper range settings of a CPN and a WSN. For example, in an uplink (WSN to CPN) transmission with WSN’ as the source of interference (Soi), which is shown as case (a) in Fig. 3, CPN (CPN’) and WSN (WSN’) have the
transmis-sion ranges RCPNand RWSN, respectively. For simplicity, the
range of possible WSN position is assumed as a cylinder and shadowing effects of human body are ignored. CPN is located at the center of cylinder and WSNs are located within the cylinder. In case (a), a data packet is transmitted from WSN to CPN. In the mean time, WSN’ is transmitting data as well. To avoid a data collision happens at CPN, the distance from the interference edge of WSN’ (Soi) to CPN (Rx), that is, DEsoi2Rx¼ W!0C RWSN should be positive. Because the location of WSN’ is confined by the cylinder, the minimum W!0C lies on the C!0C connection. For this reason, the minimum RCPN that makes W0C
!
RWSN positive should be larger than RWSNþd
2 , where d is the diameter of the cylinder. CPN thus can detect the neighbor WBAN from radio activities of CPN’ before the interfer-ence of case (a) happens. Results of other combination of possible transmission directions and sources of interference are also presented in Fig.3. By considering all cases, RCPN
should be at least larger than RWSN+ d to ensure collision
free transmissions.
Random contention-based inter-CPN negotiation
The inter-CPN negotiation of RACOON is an iterative bandwidth control scheme adjusted by two parameters: Bandwidth Requirement and User Priority Index. These two parameters are calculated by each CPN according to the status of it associated WSNs. From Fig.4, each WBAN iteratively contends wireless resources to achieve a pre-defined bandwidth target. Besides, to reflect the emergency level (user priority index) of WBAN, two trends of
WBAN 2 WBAN 1 CPN 1 CPN 2 Negotiation between CPN 1 and CPN 2 Slots reserved by CPN 2 Slots reserved by CPN 1
t
WBAN 1 WBAN 2 Poll Datat
Superframe Slott
t
Slot reservation Intra-WBAN Channel Inter-WBAN
Channel Inter-CPN negotiation
Fig. 2 CPN-based resource allocation of RACOON
bandwidth control scheme are provided for high and low priority WBANs, respectively. High priority WBANs aggressively contend resources to achieve a high bandwidth target, BWDesire. Bandwidth requirements of a low priority
WBANs are relaxed to be in between BWDesireand a lower
target BWRequire. Thus, when high and low priority WBANs
contend to each other, high priority WBANs are expected to achieve better bandwidth targets than those of low priority WBANs can achieve.
The calculation of the bandwidth target, BWDesire,
BWRequire, and User Priority Index depends on proposed
priority system for WSN. Each WSN has two kinds of priority indexes: static priority (SP) and dynamic priority (DP). Both SP and DP are set to either 0 (low) or 1 (high) depending on its intrinsic and emergent data priorities mentioned in “WBAN quality of services (QoS)” section.
SP represents the importance of monitored signal. DP denotes the emergency level when a value of a monitored signal is out of its normal range.
BWRequire is defined as the minimum resource that a
WBAN requires to transmit its emergency data, that is, BWRequire¼PiBWi; ð8i 2 WÞ \ ðDPi¼ 1Þ, where W is Fig. 3 Probing-based
interfer-ence detection
Priority (SP/DP) Traffic Rate Data of WSNs
User Priority Index (High / Low) Bandwidth (Require / Desire)
Trend of BW control for Low Priority WBAN
RACOON
BWDesire
BWRequire
High Priority Low Priority
Trend of BW control for High Priority WBAN RACOON
Input
Iterative BW control of inter-CPN negotiation
BWW
Fig. 4 Random contention-based Inter-CPN negotiation of RACOON
the set of WSNs in a WBAN; DPiis the dynamic priority of
WSNi. On the other hand, BWDesire is defined as the
bandwidth that a WBAN needs to transmit both emergency and non-emergency data, that is, BWDesire¼PiBWi; 8i 2 W . As for the User Priority Index, it is decided by comparing the ratio of the number of emergency WSNs over all WSNs with a pre-defined threshold of User Priority Index, which are j jj jWE ; E ¼ 8i W \ DPif ¼ 1g and UPIth
respectively. Whenj jj jWE > UPIth, it is a high priority WBAN, otherwise, it is a low priority WBAN. Usually, UPIthis a
personal configuration and is expected to be defined by medical experts by considering syndromes and associated sensors of a WBAN user.
In RACOON, with the inputs of BWDesire, BWRequire,
and User Priority Index, each CPN generates a weighted random value to contend resources with its neighbor CPNs. The scheme of weighted random value is inspired by Neighborhood-aware Contention Resolution (NCR) algorithm [22], which provides collision free scheduling. The skill of NCR is a random value comparison scheme. Each wireless node first generates a random value. The wireless node that has the largest random value wins the transmission slot. As for the weighted random value contention in our case, it can be realized by a pseudo contention. A CPN first generates its Nrnduniform random
values and picks the largest one for a slot contention. The average probability Pi that CPN i can obtain a slot is
proportional to the number of random values, Nrndi, used
in the pseudo contention. That is Pi¼P Nrndi
j;j2NðiÞ[iNrndj
ð1Þ where N(i) is the set of neighbors of CPN i. With this skill, each CPN iteratively controls its Nrnd to achieve their
bandwidth targets according to the control flow illustrated in Fig.5. At the start of each contention iteration, the available bandwidth BWAvb, which is defined as the bandwidth that a
WBAN has in its previous iteration, is compared with its two bandwidth targets, BWDesireand BWRequire. Then a three-case
decision is decided basing on that: Case 1 : BWAvb< BWRequire
Case 2 : BWRequire BWAvb BWDesire Case 3 : BWDesire< BWAvb
The value of Nrnd will be changed based on the priority
setting of a WBAN. As shown in Fig. 5, high-priority WBANs are designed to increase their Nrndmore aggressively
than those of low-priority WBANs. Thus, the high priority WBANs are more possible to achieve their bandwidth requirements than the low priority WBANs. In the proposed
design, an iteration of contention is performed in a super-frame. A CPN first generates random values for all slots according to Nrnd respectively and broadcasts only one
negotiation message carrying these values through the inter-WBAN channel to its adjacent CPNs. Thus, contentions can be performed by value comparisons between CPNs. To avoid collisions between negotiation-messages, these messages are broadcasted at random time slots within a superframe.
After a CPN finish an inter-WBAN resource contention, it performs an intra-WBAN scheduling to allocate its reserved transmission slots to its WSNs. A multi-queue scheduler is adopted to schedule resource by following order from the WSN that has the highest value of SP + DP to that has the lowest value, which is depicted in Fig.6. A data in a queue is scheduled only when there is no data in other queues that has higher SP + DP value.
Computer simulation
Benchmarking WBAN QoS protocol
BodyQoS [9] is a MAC layer scheduling scheme chosen to benchmark the proposed WBAN QoS protocol. BodyQoS is a CPN-centralized single-WBAN-QoS control that is capable of overcoming performance impacts from co-channel inter-ference. The design strategy of BodyQoS is to increase transmission opportunities of a WSN when it suffers a bad channel condition. The transmission opportunity is inversely proportional to its available bandwidth, hence a vital signal can be timely transmitted without extra delay. The band-width control of BodyQoS can be expressed as:
TxOpportunitiesðtÞ
TxOpportunitiesideal ¼
BWideal
BWAvbðt1Þ
BWAvbðt 1Þ ¼ a BWMeasuredðt 1Þ þ ð1 aÞ BWAvbðt 2Þ
ð2Þ where BWideal is the ideal bandwidth with perfect channel;
BWAvbis calculated by a moving average of previous measured
bandwidth BWMeasured. To fairly compare the BodyQoS with
the proposed RACOON protocol, bandwidth measurement of the BodyQoS is performed every superframe. Besides, to avoid unpredictable interference, transmission opportunities are randomly scheduled within every superframe.1
Experimental settings
A MATLAB simulation platform is built to evaluate the proposed RACOON protocol. Detail settings of topology,
1
The original interference-avoidance scheme of BodyQoS is a Carrier Sense Multiple Access with Collision Avoidance (CSMA/CA) protocol. A random scheduling is used to simulate the random backoff skill of CSMA/CA.
PHY radio, MAC framing, and traffic loads, are listed in Table1. Besides, to simulate WBAN mobility, the location change of WBANs follows the Gauss-Markov mobility model [23]. We use [23] to simulate the smooth movement path of a human, while avoiding the sudden stops and sharp turns that happen in the random walk mobility model [24]. The Gauss-Markov mobility model has a tuning factorα to control the randomness of WBAN movement. α is set as 0.5 in this study (α=0 and α=1 direct to a Brownian motion and linear movement respectively).
Experimental results
Packet latency of different vital signals in Fig.7 illustrate how intra and inter WBAN priorities are realized in RACOON. For either high or low priority, latency of vital
signals are ranked in order of SP + DP. Signal with higher SD + DP value should have lower latency. Note that SP and DP reflect the intrinsic and emergent data priorities, respectively. Furthermore, due to that the high-priority WBAN contends resources more aggressively than the low-priority WBAN does, same signal with same low-priority setting in the high-priority WBAN has shorter latency than that in the low-priority WBAN. This meets the QoS requirements of the user priority.
The latency comparison between RACOON and Body-QoS [9] in mobile WBAN scenarios is shown in Fig. 8. RACOON has much lower packet latency than BodyQoS has when WBANs move at either 2 m/s or 6 m/s. The reason is that RACOON makes WBANs cooperatively share the radio resource when they overlap to each other. On the contrary, BodyQoS does not consider interference Fig. 5 Bandwidth control flow
of inter-CPN negotiation in RACOON
Fig. 6 Multi-queue scheduler of intra-WBAN scheduling
interactions between WBANs, which makes improper decisions of bandwidth control and thus induces high transmission delay. In the original ideas of BodyQoS, interference is assumed to be generated by regular co-channel communications or path-loss due to limb move-ments. These sources of interference have “passive” interference patterns, which means it does not increase or decrease its interference level following the bandwidth control of BodyQoS. Therefore, BodyQoS reasonably increases transmission opportunities to overcome bad
channel conditions. However, in multi-WBAN scenarios, the increasing transmission opportunities cause serious inter-WBAN interference. It than increases the transmission opportunities again and causes more serious interference, which enters a vicious circle. Collision measurements with RACOON and BodyQoS in Fig.9 echo this observation.
The collision measurements also show that collision of WBAN with RACOON is less sensitive to the number of co-existence WBANs, as compared with BodyQoS. Interference between WBANs is overcome by RACOON’s cooperative Table 1 Experimental settings
Item Value
Framing structure 10 slots per superframe / each slot is 50 ms long
Packet size 240bytes
Transmission rate 48 kbps
RX Power 27.3 mW
TX Power 31.2 mW
Topology 1 to 10 WBANs randomly deployed in a 6×6 m2square. When number of WBANs is more than one, the ratio between high and low priority WBANs is 1:1.
Transmission range Distance between CPN and WSN: 0.5 m. Referring to the range settings of probing-base interference detection in section“Random Contention-Based Resource Allocation (RACOON)”, CPN: 3 m / WSN: 2 m.
Data Type Data Rate Data Priority (SP, DP) Delay Bound
ECG ch1 4 kbps 1, 1 1 s ECG ch2 4 kbps 1, 1 1 s SpO2 3 kbps 1, 0 1 s Blood pressure 3 kbps 0, 1 10 s Temperature 2 kbps 0, 0 10 s Heart rate 2 kbps 0, 0 10 s 2 3 4 5 6 7 8 9 10 0 5 10 15 20 25 30 35 40 45 50 WBAN number Packet Latency(slots)
High priority ECG ch1 High priority ECG ch2 High priority SpO2 High priority Blood pressure High priority Temperature High priority Heart rate Low priority ECG ch1 Low priority ECG ch2 Low priority SpO2 Low priority Blood pressure Low priority Temperature Low priority Heart rate
Fig. 7 Packet latency of vital signals in high and low priority WBANs
inter-WBAN resource sharing scheme and proposed probing-based interference detection. Collisions of RACOON are created by out-of-date scheduling. A WBAN moves and encounters other un-negotiated WBANs with out-of-date inter-WBAN scheduling and thus packet collisions happen. However, besides of collisions created by WBAN mobility, BodyQoS creates extra collision by its problem of the inter-WBAN-interference enhancement. This problem gets worse when number of co-existence WBANs increases and hence introduces more collisions. The difference reasons of colli-sions of RACOON and BodyQoS are also reflected in their energy consumptions, which is depicted in Fig.10. Note that the energy consumption is normalized to transmission throughput. The energy consumption considers both TX and RX according to the definition in performance metrics, “Performance metrics” section.
There is an interesting result in Figs.8,9, and10. While mobility of WBAN user is increased, BodyQoS and proposed RACOON have opposite reactions. For Body-QoS, the latency, collision, and energy consumption of a WBAN are decreased. On the contrary, for RACOON, those of a WBAN are increased, which are shown in Figs.8,9, and10. The reason comes from the different anti-interference strategies of them. As for BodyQoS, a WBAN increases its transmission opportunities when it suffers inter-WBAN interference. If a collision history of a WBAN is separated into collision and non-collision, it will form an iterative collision / non-collision / collision / non-collision… pattern. Thus, for BodyQoS, a WBAN first senses collision and tries to increase its TX times. When the TX times are increased and the WBAN moves into a non-collision area, the latency, non-collision, and energy
consump-1 2 3 4 5 6 7 8 9 10 0 100 200 300 400 500 600 700 800 900 1000 Number of WBANs
Packet Collisions (times)
BodyQoS 2m/s BodyQoS 6m/s Racoon 2m/s Racoon 6m/s
Fig. 9 Packet collisions with RACOON and BodyQoS controls
1 2 3 4 5 6 7 8 9 10 100 101 102 103 104 Number of WBANs Packet Latency(slots) BodyQos ECG 2m/s BodyQoS ECG 6m/s Racoon ECG 2m/s Racoon ECG 6m/s
Fig. 8 Packet Latency with RACOON and BodyQoS
BodyQoS-All Traffic BodyQoS-ECG only Racoon-All Traffic Racoon-ECG only 0 2 4 6 8 10 12 14 User Capacity 1 4 10 1
Fig. 11 User Capacity with RACOON and BodyQoS
1 2 3 4 5 6 7 8 9 10 2 2.2 2.4 2.6 2.8 3 3.2 3.4 3.6 3.8 4x 10 -3 Number of WBANs
Power Consumption (Joule per bit)
BodyQoS ECG 2m/s BodyQoS ECG 6m/s Racoon ECG 2m/s Racoon ECG 6m/s
tion of a WBAN are decreased. And then this WBAN starts to decrease the TX times because it senses no interference in the non-collision area. While the TX times are decreased and the WBAN happens to move into a collision area, some collisions are avoided. As a result, for BodyQoS, mobility helps a WBAN to decrease its latency, collision, and energy consumption. RACOON has an opposite strategy in TX-times control. For RACOON, a WBAN tries to decrease its TX times (through inter-WBAN resource negotiation) to resolve inter-WBAN collision and increase the TX times when there is no collision. RACOON thus has an opposite collision result during the iterative collision / non-collision pattern. As a result, RACOON introduces more collision to a WBAN when its mobility is increased. Although mobility helps the performance of BodyQoS and decreases that of RACOON’s, RACOON still guarantee a WBAN to have lower latency, collision rate, and energy consumption than what BodyQoS does due to RACOON’s cooperative inter-WBAN resource allocation.
User capacity is calculated by counting number of co-existence WBANs that provide delay-bound-satisfied transmissions of corresponding vital signals, which is illustrated in Fig. 11. The proposed QoS protocol, RACOON, provides up to four co-existence WBANs that guarantee delay-bound requirements of all traffics. Its user capacity can be increased to ten co-existence WBANs when only the delay-bound of ECG traffics are satisfied. On the contrary, BodyQoS can support only single WBAN QoS due to its problem of inter-WBAN-interference enhancement.
Conclusion
This work proposes Random Contention-based Resource Allocation (RACOON) protocol to provide multiuser QoS for wireless body area networks (WBANs). By considering QoS requirements of practical medical applications, the inter-WBAN scheduling should have QoS controls that simultaneously consider three different priorities: (i) intrin-sic data priority, (ii) emergent data priority, and (iii) user priority. The proposed RACOON protocol uses a dynamic weighted-random-value-comparison scheme to meet these priority requirements. Furthermore, RACOON utilizes a centralized control and a probing-based inter-WBAN interference detection to simplify QoS controls of wireless sensor nodes (WSNs), which decreases unnecessary energy waste of WSN. Simulation results shows that RACOON has better QoS performance in terms of transmission latency, energy consumption, and user capacity, as com-pared with other WBAN QoS controls that do not consider inter-WBAN interference and priority.
Acknowledgement Work supported by MOEA of Taiwan, ROC,
under Grant 99-EC-17-A-03-S1-0005.
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