This paper describes how to selleckchem recognize and correct the incorrect in/out status of a mobile node on an application server that is located outside the WSN. We detect two failures that cause incorrect in/out status of the selleck chem Gefitinib mobile node: abnormal connection state and exhausted battery. We use connection state and battery lifetime of the mobile node to detect the failures. When the mobile node moves, its connection state changes and can be classified into a state of joined, left, or transitive. We detect the abnormal connection state of the mobile node if it stays in the transitive state for Inhibitors,Modulators,Libraries more than a certain amount of time. Each mobile node has a battery that has a limited lifetime. Mobile nodes consume different amounts of energy according to their in/out statuses.

We Inhibitors,Modulators,Libraries estimate the energy consumption of the battery and Inhibitors,Modulators,Libraries detect abnormal nodes from the exhausted battery. Detecting the incorrect in/out status is very important in the mobile asset tracking system. False Inhibitors,Modulators,Libraries in/out status determination turns users away from the system because they feel they cannot trust its reliability. Incorrect status should be identified and corrected to Inhibitors,Modulators,Libraries increase system reliability as well as customer satisfaction. In summary, the contributions of this paper are as follows:? We develop a framework to detect and correct the incorrect in/out status of a mobile node in a mobile asset tracking system based on the properties of mobile nodes. This method is applicable to many mobile asset tracking applications.

To our knowledge, this is the first incorrect in/out status detection technique for mobile asset tracking systems.

? Inhibitors,Modulators,Libraries We propose two state classifiers to control the incorrect in status of a mobile node. These are network based and frequency based classifiers that categorize mobile nodes as either a normal node with a normal connection state or an abnormal node with an abnormal connection Inhibitors,Modulators,Libraries state.? We propose a battery Anacetrapib lifetime estimator to control the incorrect out status of a mobile node. This method estimates battery lifetime and categorizes nodes as either a normal node with a good battery level or an abnormal Inhibitors,Modulators,Libraries node with an exhausted battery.

? We perform experiments with real data sets using both state Site URL List 1|]# classifiers and battery lifetime estimation. The experiments show that our approach not only detects incorrect in/out status but also corrects it accurately.The rest of the paper is organized as follows. Section 2 presents the related work and background. Section 3 presents the system architecture of the mobile asset tracking system and describes its components. Section 4 explains our methods for tackling the problem. Section 5 describes our experimental environment and compares the proposed method with an existing method. Finally, Vandetanib VEGFR Section 6 concludes the paper.2.