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Location discovery, especially in mobile environments, has recently become the key component of many applications. Accurate location discovery, particularly in safety critical applications using autonomous robots or unmanned vehicles, however, is still an open problem. Existing popular methods either heavily rely on the use of global positioning systems (GPS) which do not readily lend themselves for use for the majority of applications where precision is of primary concern or are not suitable for ad-hoc deployments. In this paper, we propose a novel directional localization algorithm, called Dual Wireless Radio Localization (DWRL), which performs accurate node localizations in the plane using only distances between nodes, without the use of a GPS or nodes with known positions (anchors). The main novelty of DWRL is the use of an additional radio per node to support directional localization in static networks. To the best of our knowledge, this is the first time dual radios are employed in a localization setting. Existence of the dual radios on board enables DWRL algorithm to perform directional localization, which is not possible with existing single radio systems in static networks. We present the practical and theoretical benefits of the use of an additional radio per node in detail, test our algorithm under excessive synthetic and real-world noise scenarios, and show that DWRL algorithm is robust enough to perform directional localization even in high noise environments.

Many applications in wireless networks depend on accurate localization services to operate properly. Trilateration is a widely used range-based localization method that can operate in polynomial time, given that the distance measurements are precise. However in real-world, range measurements tend to have errors due to internal and external factors. Flip ambiguities that occur during trilateration as a consequence of imprecise range measurements turn localization via trilateration into an intractable problem. In this paper, we analyze flip ambiguities due to range measurement errors and propose a heuristic solution that tries to minimize the number of flips in trilateration even in highly noisy environments. We simulate our algorithms under various noise scenarios and observe that the use of our heuristic based solution e↵ectively decreases the number of flips in trilateration and increases the accuracy of the localization.

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METU INteroperable Database System (MIND) is a multidatabase system that aims at achieving interoperability among heterogeneous, federated DBMSs. MIND architecture is based on OMG distributed o b j e ct management model. It is implemented on top of a CORBA compliant ORB, namely, ObjectBroker. MIND provides users a single ODMG-93 compliant common data model, and a single global query language based on SQL. This makes it possible to incorporate both relational and object oriented databases into the system. Currently Oracle7, Sybase and METU OODBMS (MOOD) have been incorporated into MIND. The main components of MIND are a global query processor, a global transaction manager, a schema integrator, interfaces to supported database systems and a user graphical interface.In MIND all local databases are encapsulated in a generic database object with a well de ned single interface. This approach hides the di erences between local databases from the rest of the system. The integration of export schemas is currently performed manually by using an object de nition language (ODL) which is based on OMG's interface de nition language. The DBA builds the integrated schema as a view over export schemas. The functionalities of ODL allow selection and restructuring of schema elements from existing local schemas.MIND global query optimizer aims at maximizing the parallel execution of the intersite joins of the global subqueries. Through MIND global transaction manager, the serializable execution of the global transactions a r e p r ovided.