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Institute
Dynamic Real-Time Range Queries (DRRQ) are a common means to handle mobile clients in high-density areas where both, clients requested by the query and the inquirers, are mobile. In contrast to the very well-known continuous range queries, only a few approaches, such as Adaptive Quad Streaming (AQS), address the mandatory scalability and real-time requirements of these so-called ad-hoc mobility challenges. In this paper we present the highly decentralized solution Adaptive Quad Streaming Flexible (AQSflex) as an extension of the already existing more theoretical AQS approach. Beside a highly distributed cell structure without data structures and a lightweight streaming communication, we use a multi-cell-assignment on limited pool resources instead of an idealistic unlimited cell-per-server assignment. The described experimental results show the potential of our local capacity balancing scheme for cell handover in a strongly decentralized setting. Leafs of a cell hierarchy define a kind of self-optimizing fuzzy edge for the processing resources in high-density systems without any centralized controlling or cloud component.
Im März 2008 führte die Fakultät Bauingenieurwesen der HTWG Konstanz eine studentische Exkursion nach China durch. Auf dem Programm standen interessante Baustellen Shanghai, Nanjing, Zhenjiang und Beijing sowie der Besuch von Hochschulen. Der Exkursionsbericht beschreibt die besuchten Bauvorhaben und gibt persönliche Eindrücke der Exkursionsteilnehmer wieder.
Location-aware mobile devices are becoming increasingly popular and GPS sensors are built into nearly every portable unit with computational capabilities. At the same time, the emergence of location-aware virtual services and ideas calls for new efficient spatial real-time queries. Communication latency in mobile environments interacting with high decentralization and the need of scalability in high-density systems with immense client counts leads to major challenges. In this paper we describe a decentralized architecture for continuous range queries in settings in which both, the requested and the requesting clients, are mobile. While prior works commonly use a request-response approach we provide a stream-based adaptive grid solution dealing with arbitrary high client counts and improving communication latency that meets given hard real-time constraints.
Continuous range queries are a common means to handle mobile clients in high-density areas. Most existing approaches focus on settings in which the range queries for location-based services are mostly static whereas the mobile clients in the ranges move. We focus on a category called Dynamic Real-Time Range Queries (DRRQ) assuming that both, clients requested by the query and the inquirers, are mobile. In consequence, the query parameters results continuously change. This leads to two requirements: the ability to deal with an arbitrary high number of mobile nodes (scalability) and the real-time delivery of range query results. In this paper we present the highly decentralized solution Adaptive Quad Streaming (AQS) for the requirements of DRRQs. AQS approximates the query results in favor of a controlled real-time delivery and guaranteed scalability. While prior works commonly optimizes data structures on servers, we use AQS to focus on a highly distributed cell structure without data structures automatically adapting to changing client distributions. Instead of the commonly used request-response approach, we apply a lightweight streaming method in which no bidirectional communication and no storage or maintenance of queries are required at all.
Dynamic Real-Time Range Queries (DRRQ) are widely used to discover local context between mobile clients in high-density areas where both clients requested by the query and inquirers are mobile. Unlike the very well-known continuous range queries only a few approaches such as Adaptive Quad Streaming (AQS) address scalability and real-time requirements that are important for ad-hoc mobility challenges in fully distributed client networks. In this paper we address fundamental limitations of AQS presenting the new lightweight AQSdynamic which supports arbitrary, individual, and time-dependent range query shapes instead of fixed circular ones, thus covering much more realistic scenarios. More important, AQSdynamic combines the decentralized streaming approach of AQS with "subscriptions"guaranteeing a real-time behavior with constant complexity with to the number of clients.
