exploration data aggregation distributed di nandy indranil (9 risultati)

Condizione: New. pp. 156.

Condizione: New.

Taschenbuch. Condizione: Neu. Exploration and Data Aggregation in Distributed Sensor Networks | - A Geometric Approach | Indranil Nandy | Taschenbuch | 156 S. | Englisch | 2011 | LAP LAMBERT Academic Publishing | EAN 9783846554456 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu.

Paperback. Condizione: Like New. Like New. book.

Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Coverage is an important issue in WSN. The problem is to ensure full coverage of a region whose geometrical details are not available. A set of mobile sensors is to be deployed in the unexplored region to form a mobile sensor network. In the first part, our work is on the field of Exploration in sensor networks. We have proposed an incremental algorithm to explore the region. First a general algorithm is given for a completely unknown region. Next with a little modification it is applied to the case of partially known region. Later we have discussed about some more special cases and related algorithms. In the second part, we have worked on another important field of sensor networks - Data Aggregation. Here we have discussed about the k-selection algorithm. Given a general connected network of diameter D, consisting of n nodes, each node containing m number of numeric elements, we are to find the kth smallest element among the elements across the network. In our work, there is no imposed assumption or constraint on the magnitude of the elements or the size of the network or the range of element-values. We have proposed a deterministic algorithm with much improved complexity. 156 pp. Englisch.

Condizione: New. Print on Demand pp. 156 2:B&W 6 x 9 in or 229 x 152 mm Perfect Bound on Creme w/Gloss Lam.

Condizione: New. PRINT ON DEMAND pp. 156.

Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Coverage is an important issue in WSN. The problem is to ensure full coverage of a region whose geometrical details are not available. A set of mobile sensors is to be deployed in the unexplored region to form a mobile sensor network. In the first part, our work is on the field of Exploration in sensor networks. We have proposed an incremental algorithm to explore the region. First a general algorithm is given for a completely unknown region. Next with a little modification it is applied to the case of partially known region. Later we have discussed about some more special cases and related algorithms. In the second part, we have worked on another important field of sensor networks - Data Aggregation. Here we have discussed about the k-selection algorithm. Given a general connected network of diameter D, consisting of n nodes, each node containing m number of numeric elements, we are to find the kth smallest element among the elements across the network. In our work, there is no imposed assumption or constraint on the magnitude of the elements or the size of the network or the range of element-values. We have proposed a deterministic algorithm with much improved complexity.Books on Demand GmbH, Überseering 33, 22297 Hamburg 156 pp. Englisch.

Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Coverage is an important issue in WSN. The problem is to ensure full coverage of a region whose geometrical details are not available. A set of mobile sensors is to be deployed in the unexplored region to form a mobile sensor network. In the first part, our work is on the field of Exploration in sensor networks. We have proposed an incremental algorithm to explore the region. First a general algorithm is given for a completely unknown region. Next with a little modification it is applied to the case of partially known region. Later we have discussed about some more special cases and related algorithms. In the second part, we have worked on another important field of sensor networks - Data Aggregation. Here we have discussed about the k-selection algorithm. Given a general connected network of diameter D, consisting of n nodes, each node containing m number of numeric elements, we are to find the kth smallest element among the elements across the network. In our work, there is no imposed assumption or constraint on the magnitude of the elements or the size of the network or the range of element-values. We have proposed a deterministic algorithm with much improved complexity.