## 1 Introduction  
Forest fires are one of the main disasters that have multi-dimensional negative effects in ecological, economic, and social areas throughout the world. It is reported that there are on average more than 100,000 wildfires every year in the US, which destroy about 9 million acres of forest [1]. Due to the spread features of forest fires (forest fires move at speeds of up to 23 km per hour), the firefighter should be aware of this threat within 6 min once the fire starts. Hence, early detection is significantly important in firefighting, especially for regions which have a high frequency of forest fire such as North Africa, China, and the US. Estimating the spread direction and the speed of fires is also critical in extinguishing fires. To ensure firefighters are aware of the forest fires as early as possible, some important technologies have been developed to monitor and detect forest fires. For instance, there are charge-coupled device (CCD) cameras [2] and infrared (IR) detectors [3], satellite systems and images [4], wireless sensor networks (WSNs) [5] and UAV-based forest fire detection and tracking technology [6]. In CCD cameras and IR detectors-based systems, CCD cameras and IR detectors are installed on the top of towers to sense any abnormal events such as fire and smoke and report to a control center [7]. However, the accuracy of such a system is highly dependent on the effects of terrain, time of day and other environmental conditions. For satellite systems and images, it takes 1-2 days to retrieve a complete earth's image, which is infeasible for early fire detection. As a promising alternative,WSNs could be deployed for forest fire detection effectively [8]. WSNs are the networks characterized by being self-organizing and infrastructure-less, and consisting of several small, energy-limited, and low-cost sensor nodes. Several wireless sensor nodes can be pre-deployed in a forest to collect different types of data such as temperature, humidity, pressure, and solar radiation, and deliver these raw or processed data wirelessly in an ad hoc fashion to a sink station, where the collected data can be further analyzed and be used to make a decision if fires happen. However, the deployment of WSNs is restricted by some major issues and challenges owing to the nature of this type of network. For example, energy consumption of power-limited WSNs becomes a major concern when targeting a long-term continuous surveillance of the entire forest area.  
In this paper, we propose a novel framework for the use of WSNs in forest fire monitoring and detection with the following modules. First, we propose hierarchical network architecture coupled with intra-cluster and inter-cluster protocols to enable early detection with reasonable energy consumption. Second, the operating modes of WSNs are based on the level of fire risk, which is derived from changing climate conditions such as high temperatures, strong winds and a lack of rainfall. Third, we propose a distributed protocol which runs in each sensor node. In this way, the information regarding possible detected fire events can be disseminated to a sink station rapidly.  
The remainder of this paper is organized as follows. Section 2 gives a detailed literature survey on the most relevant related works. Section 3 provides a high-level description of the proposed framework that includes deployment scheme, clustered hierarchy network architecture and environment-aware protocols. Performance evaluation using ns-2 and results analysis is presented in Section 4. Finally, Section 5 concludes this paper and provides a discussion on future work.