In this paper, we ask whether it is possible to build an IP address to geographic location mapping service for Internet hosts. Such a service would enable a large and interesting class of location-aware applications. This is a challenging problem because an IP address does not inherently contain an indication of location.We present and evaluate three distinct techniques, collectively referred to as IP2Geo , for determining the geographic location of Internet hosts. The first technique, Geo Track , infers location based on the DNS names of the target host or other nearby network nodes. The second technique, GeoPing , uses network delay measurements from geographically distributed locations to deduce the coordinates of the target host. The third technique, GeoCluster , combines partial (and possibly inaccurate) host-to-location mapping information and BGP prefix information to infer the location of the target host. Using extensive and varied data sets, we evaluate the performance of these techniques and identify fundamental challenges in deducing geographic location from the IP address of an Internet host.

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Developing wireless sensor networks can enable information gathering, information processing and reliable monitoring of a variety of environments for both civil and military applications. It is however necessary to agree upon a basic architecture for building sensor network applications. This paper presents a general classification of sensor network applications based on their network configurations and discusses some of their architectural requirements. We propose a generic architecture for a specific subclass of sensor applications which we define as self-configurable systems where a large number of sensors coordinate amongst themselves to achieve a large sensing task. Throughout this paper we assume a certain subset of the sensors to be immobile. This paper lists the general architectural and infra-structural components necessary for building this class of sensor applications. Given the various architectural components, we present an algorithm that self-organizes the sensors into a network in a transparent manner. Some of the basic goals of our algorithm include minimizing power utilization, localizing operations and tolerating node and link failures.

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