## 2 Background  
Generally a WSN node can be put into one of the following five states: Transmit, Receive, Idle, Sleep and Sense. Each state corresponds to a specific power consumption level. Energy consumption in Sense state is relevant to a specific application, while energy consumptions in other states are related tothe work process of a node. In addition, energy consumption for the radio component in a node is much greater than that of other components in the majority of WSN applications [6]. Therefore, the energy consumption in the Sense state is ignored in this paper. In terms of energy consumption per time unit, the Transmit state usually consumes the most energy, Receive consumes second to Transmission, then is Idle and Sleep state consumes the least among these four states. Therefore a common technical solution to prolong network lifetime is to schedule nodes to pending most working time in the states with lower energy consumption, and research on scheduling mechanisms has become and increasingly hot topic in the field of WSNs. Reference [7] summarized a lot of distributed scheduling mechanisms designed for WSNs. However, more and more distributed scheduling approaches to improve energy efficiency have been proposed in recent years. The main objective of scheduling mechanism is to reduce energy consumption and prolong the lifetime of WSNs, which is the fundamental function of power management plane related to every layer in the protocol architecture [8]. Many papers study issues on scheduling mechanisms in MAC layer to minimize energy consumption [9-16]. Some of them have focused on the conflict-free networks like TDMA network or CDMA network [9-13] to save energy by scheduling nodes to work in their own time slot and change to sleep state when nodes are out of their own time slot. Others focused on the contention-based networks [14-16]. Normally, TDMA-based MAC scheduling mechanisms can guarantee delay bounds due to collision elimination, while contention-based MAC scheduling mechanisms may result in non-deterministic packet delays due to the collisions and the packet retransmissions. However, the contention-based MAC protocols are not only robust to the network topology and network load, but also are scalable to network size and node density. There are many other scheduling approaches to study energy saving above MAC layer [17-21]. Reference [18] presented an energy-efficient organization method, which schedules the nodes to sleep by sensing the object location collaboratively, and to perform probability awakening in a distributed manner. Reference [19] proposed a sensor scheduling approach, jointing sensing coverage and network connectivity, to save energy in the absence of accurate location information. The authors of [20] presented a scheduling algorithm which allows nodes to learn the shape of the traffic through observing upstream neighboring nodes independently, and then shape the transmission traffic and determine its sleep time for saving energy. The authors in [21] proposed a wake-up scheduling algorithm that determines the wake-up frequency of the nodes. Because scheduling approaches above the MAC layer are not designed for a specific MAC protocol, they can be easily used in many applications. Most scheduling approaches reduce energy consumption by increasing the sleep time of nodes. Moreover, in a contention-based network, some energy wastes on the packets transmission. Therefore some papers, like [14] and [20], also took packet transmission scheduling into consideration. In a WSN, which is based on a contention channel and samples environmental information simultaneously and periodically, nodes normally initiate data packet transmission simultaneously, which leads to energy waste due to the serious collision and idle listening. For example, a structural health monitoring system should correctly collect raw data information on structural behavior in a continuous and periodical way.