# Classification between Failed Nodes and Left Nodes in Mobile Asset Tracking Systems +
## 2 Related Work  
Several works on node failure detection in WSNs are briefly reviewed in this section. [PERSON] _et al._ [20] and [PERSON] [21] proposed a distributed node monitoring tool (DiMo) and Memento, respectively. DiMo and Memento are network management tools for WSNs. These methods divide all nodes into two categories: observer nodes and remote nodes. Each remote node transmits heartbeat messages to its observer node periodically. If the observer node does not hear any heartbeat message for a certain threshold from the remote node, the observer considers the remote node as a faulty node. However, they do not consider a situation in which a mobile node can leave a WSN without failures. [PERSON] _et al._ [22] proposed a node failure detector that distinguishes between a node failure and a node movement. This method uses two types of nodes: observer nodes and target nodes. When a target node leaves the communication range of an observer node, the observer cannot distinguish between the target's movement and the target's failure. In order to handle this situation, the observer uses additional information obtained from one of the initiated nodes in the network. Initiated nodes are a few designated nodes that collect neighbor information from all nodes by propagating a message periodically. When an initiate node receives a message including \"the target is alive\" from one of the neighbors of the target, the initiator relays the response to the observer. The observer then recognizes that the target has moved. However, the method also does not consider a situation in which the target can leave the network. [PERSON] _et al._ [23] proposed Sympathy, a tool to debug and detect failures occurring in WSNs. Sympathy runs at individual node, and failure detection occurs at a sink node. There are two types of packets in WSNs: monitored traffic and metric traffic. Each sensor node produces the former, and Sympathy produces the latter. Sympathy monitors the traffic to identify failure nodes and to decide the sources of failures. If a node produces monitored traffic less than a given threshold, Sympathy considers the node to be failed. However, Sympathy is not applicable to mobile nodes that leave the monitoring area without failures. As the sink node cannot hear any messages from all mobile nodes that normally leave the WSN, Sympathy incorrectly considers them to be failed. [PERSON] and [PERSON] [24] proposed a failure detection method based on the connection state of a mobile node and its battery lifetime. It is used to detect faulty mobile nodes in mobile asset tracking systems. This method runs on a central server. A mobile node is attached to a mobile object, which is mobile within a monitoring region, leaves it freely and then returns to the area repeatedly. Therefore, the status of a mobile node is either in or out. This failure detection method using the connection state is primarily intended for detecting failed nodes with the in status; on the other hand, the method using the battery lifetime considers the out status. Although a battery lifetime estimator can detect failed nodes that have the out status and the low battery power at the same time, it cannot detect failed nodes that have sufficient battery power. On the other hand, the proposed method in this paper detects failed nodes with the out status regardless of the battery level. [PERSON] and [PERSON] [25] proposed a node failure detection method using the the round-trip delay time occurring in both directions along a routing path in WSNs. This method detects failure nodes by measuring the latency in a round-trip path and comparing it to a certain threshold. The round-trip delay time of a failed node will be higher than the threshold value or infinite. However, this method cannot detect the failure of a mobile node that can leave the network without failure. In summary, previous methods can efficiently detect node failures in certain ways.