## 1 Introduction
### Background  
In the 21 st century, the healthcare industry has seen the drastic improvements due to the involvement of wireless medical sensor networks (WMSNs) in healthcare applications. A few decades ago WSNs were a topic of science/movie fiction for healthcare industries, and now they have become a reality and provide much quality-of-care. As the world's aging population is increasing at an unprecedented rate in the developed and developing countries. According to the \"An Aging World: 2008\" report [2], in 2008 the number of aging people worldwide (_i.e._, 65 years and older) was estimated at 506 million, and by 2040, that number will touch 1.3 billion. Thus, in just over three decades, the percentage of older age people will increase two times from 7% to 14% of the total world population [2]. Although the aging population signifies, a human success story of increased longevity, the steady, sustained growth of the older population also poses health challenges. As more and more people will be entering an elder age, the risk of developing certain chronic and debilitating diseases is significantly higher. For example, Alzheimer disease symptoms typically first appear after age 60 [3], Heart disease and stroke rates rise after age 65 [4], diabetes, like those of many other conditions (e.g., blood pressure, blood glucose levels _etc._). Further, if aged populations prefer to live alone they do however require long-term monitoring for better independent life [5]. Thus the aging population desperately demands independent life and good quality-of-care without disturbing their comfort, while reducing their care costs. In this context, wireless sensor technology could provide highly useful tools for elderly people health monitoring and patients who need continuous monitoring. Consequently healthcare using wireless sensor networks constitutes an exciting and growing field for scientific investigation. In fact the future of modern healthcare in an aging world will need ubiquitous monitoring of health with least actual interaction of doctor and patients [6]. Recently, a term wireless medical sensor network (WMSN) has coined to bring many researchers together from interdisciplinary areas (bioengineering, electronics, computer, medicine), as shown in Figure 1.  
Wireless medical sensors may be wearable, implantable or portable, and integrated on various kinds of wireless communication motes (such as, Mica2, MicaZ, Telos, _etc._). A typical Mica2 mote has a 7.3 MHz Atmel ATmega128L CPU with 128 KB of ROM, and 4 KB of RAM for data [7]. The radio operates at 76.8 Kbps bandwidth at a range of a few meters. Moreover, a sensor node typically has a limited battery power (e.g., AA-batteries), which is just enough for communication (e.g., unicast, multicast and broadcast) and computation [7]. Furthermore, WMSNs are different from generic WSNs. The main differences are summarized in Table 1.  
As we can see from the Table 1, generic WSNs are automatic and standalone, deployed at a large scale in either a fixed or distributed manner, and their data rates depend specifically on the applications, whereas WMSNs have direct human involvement (_i.e._, patient, doctor, nurse, _etc._), are deployed at a small scale (_i.e._, depending on usability), must support mobility (a patient can carry the devices), and WMSNs requires high data rates (e.g., ECG data is normally sampled at a rate of 250 Hz and blood pressure at 100 Hz [8]), with reliable communication and multiple recipients [9]. Wireless medical sensor motes are deployed on a patient's body, and are used to closely monitor the physiological condition of patients. These medical sensors sense the patient's vital body signs and transmit the sensed data in a timely fashion to some remote location without human intervention. A doctor can use these medical sensor readings and gain a broader assessment of a patient's health status.