Samer Samarah

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In this paper, we propose a comprehensive framework for mining wireless ad hoc sensor networks (WASNs), which is able to extract patterns regarding the sensors' behaviors. The main goal of determining behavioral patterns is to use them to generate rules that will improve the WASN's quality of service by participating in the resource management process or(More)
In recent years, we have witnessed an increasing interest in deploying wireless sensor networks (WSNs) for real-life applications. However, before WSNs become a commodity, several challenging issues remain to be resolved. Object-tracking sensor network (OTSN)-based applications are widely viewed as being among the most interesting applications of WSNs. OTSN(More)
With the advances of wireless sensor networks and their ability to generate a large amount of data, data mining techniques to extract useful knowledge regarding the underlying network have recently received a great deal of attention. However, the stream nature of the data, the limited resources, and the distributed nature of sensor networks bring new(More)
Recently, association rules for sensors have received a great deal of attention due to their importance in capturing the temporal relations between sensor nodes in wireless sensor networks (WSNs). Because of this capability, these rules can be used to improve the Quality of Service (QoS) of wireless sensor networks by participating in the resource(More)
With the advances in wireless sensor networks and their ability to generate a large amount of data, data mining techniques used to extract useful knowledge regarding the underlying network have recently received a great deal of attention. In this paper the authors use a new formulation for association rules, a well known data mining technique. This(More)
Recently, Knowledge Discovery Process has proven to be a promising tool for extracting behavioral patterns regarding sensor nodes from wireless vehicular ad hoc and sensor networks. In this paper, we propose a new type of behavioral patterns, which we refer to as Coverage-based Rules, to discovers the correlation among the set of locations monitored by the(More)
Wireless Sensor Networks (WSNs) have proven their success in a variety of applications for monitoring physical and critical environments. However, the streaming nature, limited resources, and the unreliability of wireless communication are among the factors that affect the Quality of Service (QoS) of WSNs. In this paper, we propose a data mining technique(More)