This document proposes a cyclic sleep wake up scenario for wireless body area sensor networks to improve energy efficiency and extend network lifetime. The scenario involves having one sensor node in an active monitoring state while other nodes sleep, then cyclically switching the active node so all nodes can save power. Simulation results show this approach increases network lifetime compared to a normal setup without sleep cycling. The scenario is implemented using MATLAB and evaluated based on parameters like transmission range, sensor power consumption, data rate, and number of sensor nodes.

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Cyclic Sleep Wake Up Scenario for
Wireless Body Area Sensor Networks
Karthik.J1
, Dr.Rajesh.A2
1
Research Scholar, St Peters University, Avadi, Chennai
2
Professor, C.Abdul Hakeem College of Engineering and Technology, Vellore
ABSTRACT: Wireless Body Area Sensor Networks (WBASNs) are wireless monitoring systems, consisting of
wearable and implantable sensor nodes on or in the human body. In a WBASN, Lifetime of the network will be a
major key challenge due to the limited amount of energy supply in body nodes. Our paper proposed cyclic sleep wake
up scenario for the effective utilization of energy and to minimize the power consumption of the sensor node as well as
the network. This scenario will increase the life time of the node and network. In cyclic sleep wake up method one
sensor node will be in active state while other nodes are in sleep state, so all the nodes power can be saved by making
its state sleep. Cyclically other nodes will be selected for monitoring the human health. This scenario will help to
improve the energy efficiency.
KEYWORDS: cyclic sleep wake up scenario, WBASN, network life time
I. INTRODUCTION
As the ecosystem for consumer electronic devices continues to grow, a category of wirelessly-connected digital
‘accessories’ is becoming established. The wireless communications architecture of those accessories typically
consists of a short-range, low data rate and low-power sensor node that is used to periodically transmit data to a remote
hub (base station) such as a cell phone or application specific device.
The nature of communications between a sensor node and a hub has a great impact on the power consumed. For
instance, human body monitoring may be achieved by attaching sensors to the body’s surface as well as implanting
them into tissues for a more accurate clinical practice. Hence, some of these newly emerged challenges due to
healthcare requirements, range from low latency and high reliability, to low power consumption in order to protect
human tissue. One of the major concerns in BSNs is that of extremely energy efficiency, which is also the key to
extend the lifetime of battery-powered body sensors, reduce maintenance costs and avoid invasive procedures to
replace battery in the case of implantable devices.
As nodes consume their limited initial energy at a rate proportional to their activities in their respective cluster, it
transpires that to maximize the lifetime of the network, the control overhead due to routing information queries must
be minimized and the traffic should be evenly routed for balanced energy consumption amongst the nodes.
Wireless body area sensor networks (WBASNs) have become one of the most promising technologies for
enabling health monitoring at home. As a result, patients in noncritical condition may be released from a hospital or
clinic for at-home monitoring, once this technology is sufficiently mature. One major benefit introduced by WBASNs
is that the lack of wires enables people to move freely in their residence while they recover, which is otherwise
cumbersome to achieve with existing health monitoring technology
In this paper we have discussed about the introduction in Chapter I, and briefly explained about the challenges of
body area networks. We have taken the literature survey from various papers and details explained in Chapter II. We

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briefly discussed about our proposed Sleep Wake Up Scenario and its algorithm in Chapter III. Then our findings are
narrated in Chapter IV. Finally we conclude our concept and also direct the future work in Chapter V.
II. RELATED WORKS
Ubiquitous healthcare promises continuous gathering and analysis of physiological, behavioral and other such
health-related information and either acting on it, providing feedback, or delivering it to health professionals. The aim
is to provide better healthcare to people via continuous monitoring of small autonomous wireless body-worn sensors,
often outside of typical healthcare settings such as hospitals [1].
To deliver the levels of comfort and unobtrusiveness required for widespread adoption, BAN sensor nodes must
be small and have batteries that last on the order of days to years, depending on the application. The size requirement
obviously limits the size of the batteries that will power the nodes (energy scavenging is another option, but the
amount of power available from such techniques is relatively small), so BAN nodes must be extremely frugal in their
energy usage[2].
The development of wireless body area networks (WBANs) brings a number of research challenges such as
interoperability, scalability, reliability, QoS, and energy efficiency to the design of communication protocols. Utilizing
energy efficient communication protocols to maximize the network lifetime is important for WBAN applications.
Reducing transmit power can be a potential approach. Note that, to avoid negative impact of electromagnetic radiation
on human body, it is critical to keep a low transmit power in WBAN[3]. However, the path loss in WBAN is usually
larger than 50 dB [4], causing severe attenuation on wireless signals, and thus, without sufficient transmit power the
link quality is very likely to be deteriorated.
it is observed that, with 1 mW transmit power at 2:4 GHz, the on-body (off-body) links of WBAN are
intermittently disconnected up to 14.8% (14.9%) of the time when people sleep on bed [5].
A handoff protocol that can be readily implemented by WBASN coordinators and APs when the RSS of the
former falls below acceptable levels. For this, we promote employing multiple radio channels in order to leverage the
system’s capacity, which allows monitoring multiple users in a deployment setting with several rooms[6].
In [7] Many different studies have been done that involve nodes switching between an active and sleep mode. The
variables include how to determine the active/sleep schedule, the duration of the active/sleep period, and whether or
not the nodes are aware of the schedules of the other nodes in the network.
III. SLEEP WAKE UP SCENARIO
The schedule between the sleeping and awakening of sensors: achieves the effectiveness of saving power by
sleeping mechanism. The proposed sleeping control mechanism takes the dynamic scheduling method. We calculate
the sleep probability for each level by the density. The nodes away from the sink will increase the sleep probability to
decrease the forward frequency of the nodes near to the sink. In this way, the nodes near to the sink could share the
energy consumption and preserve the energy. For the wireless sensor networks, the sleeping scheduling is very
important. If the nodes set into the active status for long duration, it will waste a lot of energy. On the contrary, the
transmission will delay if the nodes be with long sleep duration.
Algorithm
Step1 : Consider all the nodes which are present in WBASN.
Step2 : Select the node for monitoring the human body and keep the node in active state.
Step3 : Make all other nodes to sleep to reduce the wastage of energy
Step4 : Alternatively select the other node for monitoring the human body

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Step5 : Energy level will be maintained equally in all nodes of the network
The time of sleeping and awakening of sensor nodes is fixed. In sleeping control mechanism, there are two parts
for each duty cycle which are active status and sleep status. For active status, sensor nodes could communicate with
neighbor nodes. For sleep status, sensor nodes will suspend all communication to save energy.
Fig 1 : Cyclic Sleep Wake Up Scenario
Our cyclic Sleep wakeup scheme allows for a node to be active during a randomly chosen fixed interval in each
time frame. This removes the necessity of time synchronization and makes the protocol implementation very simple.
The idea is to have each node wake up once in every slot, be awake for a predetermined time, and then sleep again.
IV. RESULTS AND DISCUSSIONS
The proposed Cyclic Wake Up Scenario is implemented with MATLAB. We have considered the following
parameters for the simulation. Transmission Range will be maximum of 10 meters, Sensing Power of Sensor node is
30 mA, Initial power of node 2000mAh, Data Transfer rate will be less than 1mbps, and number of nodes placed in
human body is between 2 to 14.
Fig 2 : Comparison of Sleep Wakeup Setup and Normal Setup
From the above Simulation results it is clear that the sleep wakeup scenario will increase the lifetime of the node
and also increase the network life time. The above graph shows that the best case scenario (ie) the number of time the
sleep wake up method used will be minimum.
Similarly we also consider the average and worst case algorithms for this sleep wakeup scenario, for all situation
our proposed scenario increase the lifetime of the node and network when compared with normal set up.
V. CONCLUSION AND FUTURE WORK
Minimizing the power wastage in Wireless Body Area Sensor Networks will be major issue in recent years. We
discussed about the challenges that are faced in WBASN, and also we proposed a sleep wakeup scenario to avoid the
wastage of energy of sensor node and also increase the network life time. Here we implemented the cyclic sleep
0
2
4
6
8
10
2 4 6 8 10 12 14
Sleep Wakeup
Normal
NetworkLifetime(Days)
No of Nodes

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wakeup method; we further can take this into an advanced sleep awake mechanism for the effective utilization of the
energy of nodes. We further concentrated on on-demand sleep awake concept(ie) awake the node only when there is
demand. Until that the nodes can be in sleep state. Future work can be concentrated on the above on-demand sleep
awake method.
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