Group communication is a useful abstraction in the development of highly available distributed and communication-oriented applications in wide area networks (WANs). The most important aspects of this abstraction are the dynamic maintenance of group membership and its diverse semantics for interleaving membership change noti cations within the ow of regular messages. In this paper we propose a new architecture for a scalable group membership service for wide area environments. Our architecture provides two di erent service levels and their semantics, each geared to di erent applications with di erent needs: The congress membership service which provides simple semantics of membership approximation, and the moshe service, which extends congress, provides full virtual synchrony semantics. The novelty of our design is in its client-server approach, which allows lightweight clients to bene t from advanced membership services. Furthermore, our design supports the coexistence of full-edged clients along with thin clients.

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In recent years, the demand for high-precision tracking systems has significantly increased in the field of Wireless Sensor Network (WSN). A new tracking system based on exploitation of Received Signal Strength Indicator (RSSI) measurements in WSN is proposed. The proposed system is designed in particular for WSNs that are deployed in close proximity and can transmit data at a high transmission rate. The close proximity and an optimized transmit power level enable accurate conversion of RSSI measurements to range estimates. Having an adequate transmission rate enables spatial-temporal correlation between consecutive RSSI measurements. In addition, advanced statistical and signal processing methods are used to mitigate channel distortion and to compensate for packet loss. The system is evaluated in indoor conditions and achieves tracking resolution of a few centimeters which is compatible with theoretical bounds.

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Intrusion Detection systems (IDS) were developed to identify and report attacks in the late 1990s, as hacker attacks and network worms began to affect the internet. Traditional IDS technologies detect hostile traffic and send alerts but do nothing to stop the attacks. Network Intrusion Prevention Systems (NIPS) are deployed in-line with the network segment being protected. As the traffic passes through the NIPS, it is inspected for the presence of an attack. Like viruses, most intruder activities have some sort of signatures. Therefore, a pattern-matching algorithm resides at the heart of the NIPS. When an attack is identified, the NIPS blocks the offending data. There is an alleged trade-off between the accuracy of detection and algorithmic efficiency. Both are paramount in ensuring that legitimate traffic is not delayed or disrupted as it flows through the device. For this reason, the pattern-matching algorithm must be able to operate at wire speed, while simultaneously detecting the main bulk of intrusions. With networking speeds doubling every year, it is becoming increasingly difficult for software based solutions to keep up with the line rates. This paper presents a novel pattern-matching algorithm. The algorithm uses a Ternary Content Addressable Memory (TCAM) and is capable of matching multiple patterns in a single operation. The algorithm achieves line-rate speed of several orders of magnitude faster than current works, while attaining similar accuracy of detection. Furthermore, our system is fully compatible with Snort's rules syntax, which is the de facto standard for intrusion prevention systems.

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Abstract-In this paper we develop a continuous high-precision tracking system based on Received Signal Strength Indicator (RSSI) measurements for small ranges. The proposed system uses minimal number of sensor nodes with RSSI capabilities to track a moving object in close-proximity and high transmission rate. The close-proximity enables conversion of RSSI measurements to range estimates and the high transmission rate enables continuous tracking of the moving object. The RSSI-based tracking system includes calibration, range estimation, location estimation and refinement. We use advanced statistical and signal processing methods to mitigate channel distortion and packet loss. The system is evaluated in indoor settings and achieves tracking resolution of few centimeters. Therefore, it becomes the motion trackers of notice in many applications.

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