We investigate distributed algorithms for mobile ad hoc networks for moving radio stations with adjustable transmission power in a worst case scenario. We consider two models to find a reasonable restriction on the worst-case mobility. In the pedestrian model we assume a maximum speed v_max of the radio stations, while in the vehicular model we assume a maximum acceleration a_max of the points. Our goal is to maintain...

Abstract. This article surveys mobility patterns and mobility models for wirelss networks. Mobility patterns are classified into the following types: pedestrians, vehicles, aerial, dynamic medium, robot, and outer space motion. We present the characteristics of each and shortly mention the specific problems. We shortly present the specifics of cellular networks, mobile ad hoc networks, and sensor networks regarding mobility. Then, we present the most important mobility models from the literature. At last we give a brief discussion about the state of research regarding mobility in wireless networks. 1

The ability to represent and query continuously moving objects is important in many applications of spatio-temporal database systems. In this paper we develop data structures for answering various queries on moving objects, including range and proximity queries, and study tradeoffs between various performance measures—query time, data structure size, and accuracy of results. 1

Abstract The ability to represent and query continuously moving objects is important in many applica-tions of spatio-temporal database systems. In this paper we develop data structures for answering various queries on moving objects, including range and proximity queries, and study tradeoffsbetween various performance measures--query time, data structure size, and accuracy of results.

This papers proposes techniques for writing self-adjusting programs that can adjust to any change to their data (e.g., inputs, decisions made during the computation) etc. We show that the techniques are e#cient by considering a number of applications including several sorting algorithms, and the Graham Scan, and the quick hull algorithm for computing convex hulls. We show that the techniques are flexible by showing that self-adjusting programs can be trivially transformed into a kinetic programs that maintain their property as their input move continuously. We show that the techniques are practical by implementing a Standard ML library for kinetic data structures and applying the library to kinetic convex hulls. We show that the kinetic programs written with the library are more than an order of magnitude faster than recomputing from scratch. These results rely on a combination of memoization and dynamic dependence graphs. We show that the combination is sound by presenting a semantics based on abstraction of memoization via an oracle.