## 1 Introduction  
With recent advances in intelligent (bio-) medical sensors, low-power integrated circuits and wireless networking technologies, Body Sensor Networks (BSNs) have been applied in many areas, especially in human health monitoring [1-5]. By outfitting patients with wireless wearable or implantedvital sign sensors, detailed real-time data on physiological status can be continuously sampled [6,7]. Although BSN shares many of the same challenges with general wireless sensor networks (WSNs), a number of BSN-specific challenges could be specified.  
BSNs often demand high degrees of reliability and specific message latency requirements for real-time health monitoring [8]. However, BSNs have fewer and smaller nodes compared with conventional WSNs. Smaller nodes imply smaller batteries, creating stricter constrains on the energy consumed by processing, storage, and communication resources [9]. Usually, BSNs are vulnerable to channel impairments due to body fading effects and/or RF interference [10]. The radio channel assigned to the BSN services is not always clean and sometimes, even the efficient coding schemes used to combat interference may fail. Channel impairments can cause unreliable data transmission and high Bit Error Rate (BER). Hence in some cases the critical data can't be sent to control nodes in time. Consequently, the doctor may make wrong diagnosis and the patient may be delayed to be cured and even die. In addition, the packet loss results in data retransmission. Because the buffer of a biosensor is often very limited, data retransmissions will consume much energy, thus impelling the node to fail. Therefore, it has become crucially important to provide a fault-tolerant communication scheme for BSNs to guarantee reliable data transmission.  
In BSNs, biosensors gathering different types of physiological data may have different reliability requirements [11]. For example, heart rate sensors are often considered more important than blood pressure sensors, and hence should be served first under the condition of lack of shared resources (e.g., bandwidth). At the same time, the level of reliability requirements may change dynamically at runtime. For instance, the reliability requirement of the blood pressure sensor might be low when blood pressure readings are in normal range, but the reliability requirement will become much more rigorous when the readings indicate hypotension or hypertension. As a consequence, the system needs to dynamically maintain the reliability requirements of sensors to provide reliability assurance for the sensor nodes with high demand of reliability.  
In this paper we present an adaptive and flexible fault-tolerant communication scheme for BSNs, namely AFTCS. When channel impairments occur, AFTCS can provide reliable data transmission for critical sensors by reserving channel bandwidth according to the perceived information about human physiological status, external environment, and the system itself. Fault-tolerant priority and queue are employed to adaptively adjust the channel resource allocation. Simulations have been conducted to evaluate the performance of the proposed scheme. Results are presented and analyzed.  
The rest of the paper is organized as follows. In Section 2, we summarize the related work. Section 3 presents the related variables used in the AFTCS scheme and its application scenario. The detailed description of AFTCS is given in Section 4. In Section 5, the performance of AFTCS is evaluated. Finally, we conclude the paper and outline some future work in Section 6.