Modeling radio networks

We describe a modeling framework and collection of foundational composition results for the study of probabilistic distributed algorithms in synchronous radio networks. Though the radio setting has been studied extensively by the distributed algorithms community, their results rely on informal descriptions of the channel behavior and therefore lack easy comparability and are prone to error caused by definition subtleties. Our framework rectifies these issues by providing: (1) a method to precisely describe a radio channel as a probabilistic automaton; (2) a mathematical notion of implementing one channel using another channel, allowing for direct comparisons of channel strengths and a natural decomposition of problems into implementing a more powerful channel and solving the problem on the powerful channel; (3) a mathematical definition of a problem and solving a problem; (4) a pair of composition results that simplify the tasks of proving properties about channel implementation algorithms and combining problems with channel implementations. Our goal is to produce a model streamlined for the needs of the radio network algorithms community

Applying graph coloring in resource coordination for a high-density wireless environment

In a high density wireless environment, channel interference among users of many overlapped Basic Service Sets (OBSSs) is a serious problem. Our solution for the problem relies on a resource coordination scheme that utilizes the spatial distribution of the transceivers for channel reuse and time-slot division multiplexing for downlink transmission sharing among all participating BSSs. In this paper we show that an OBSS environment can be modeled by a planar graph and the OBSS group coordination assignment problem can be considered as a vertex coloring problem whose solution involves at most four colors. The graph coloring solution algorithm for the OBSS group coordination assignment is presented. The actual coloring is demonstrated, using a heuristics of Maximum Degree First. Performance simulation results of the coordination algorithm are also presented. © 2008 IEEE

New SEAMCAT Propagation Models: Irregular Terrain Model and ITU-R P. 1546-4, Journal of Telecommunications and Information Technology, 2011, nr 3

Implementation of the ITU-R P.1546-4 and ITM propagation models for SEAMCAT prepared and developed in the National Institute of Telecommunications Poland is presented. Results of our research encompasses methodology, implementation and verification of plug-ins into the SEAMCAT software are shown

Distributed computation on unreliable radio channels

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2009.Cataloged from PDF version of thesis.Includes bibliographical references (p. 169-175).An important topic in wireless networking is the development of reliable algorithms for environments suffering from adversarial interference. This term captures any type of channel disruption outside the control of the algorithm designer-from contention with unrelated devices to malicious jamming. In this thesis, we provide four contributions toward a comprehensive theoretical treatment of this topic. First, we detail a formal modeling framework. This framework is general enough to describe almost any radio network studied to date in the theory literature. It can also precisely capture the often subtle details of adversarial behavior. In addition, we prove a pair of composition results that allow a layered strategy for designing radio network algorithms The results can be used to combine an algorithm designed for a powerful channel with an implementation of this channel on a less powerful channel. Next, we formalize adversarial interference with the definition of the t-disrupted channel. We then define the more powerful (t, b, p)-feedback channel, and provide both a randomized and deterministic implementation of the latter using the former. To emphasize the utility of this layered approach, we provide solutions to the set agreement, gossip, and reliable broadcast problems using the powerful feedback channel. Combined with the implementation algorithms and composition results, this automatically generates solutions to these problems for the less powerful, but more realistic, t-disrupted channel. Finally, we define a variant of the modeling framework that captures the attributes of an ad hoc network, including asynchronous starts and the lack of advance knowledge of participating devices.(cont.) Within this new framework, we solve the wireless synchronization problem on a t-disrupted channel. This problem requires devices to agree on a common round numbering scheme. We conclude by discussing how to use such a solution to adapt algorithms designed for the original model to work in the ad hoc variant.by Calvin Newport.Ph.D

Journal of Telecommunications and Information Technology, 2011, nr 3

kwartalni

Modeling Radio Networks

We describe a modeling framework and collection of foundational composition results for the study of probabilistic distributed algorithms in synchronous radio networks. Existing results in this setting rely on informal descriptions of the channel behavior and therefore lack easy comparability and are prone to error caused by definition subtleties. Our framework rectifies these issues by providing: (1) a method to precisely describe a radio channel as a probabilistic automaton; (2) a mathematical notion of implementing one channel using another channel, allowing for direct comparisons of channel strengths and a natural decomposition of problems into implementing a more powerful channel and solving the problem on the powerful channel; (3) a mathematical definition of a problem and solving a problem; (4) a pair of composition results that simplify the tasks of proving properties about channel implementation algorithms and combining problems with channel implementations. Our goal is to produce a model streamlined for the needs of the radio network algorithms community

Modeling Radio Networks

Abstract. We describe a modeling framework and collection of foundational composition results for the study of probabilistic distributed algorithms in synchronous radio networks. Though the radio setting has been studied extensively by the distributed algorithms community, their results rely on informal descriptions of the channel behavior and therefore lack easy comparability and are prone to error caused by definition subtleties. Our framework rectifies these issues by providing: (1) a method to precisely describe a radio channel as a probabilistic automaton; (2) a mathematical notion of implementing one channel using another channel, allowing for direct comparisons of channel strengths and a natural decomposition of problems into implementing a more powerful channel and solving the problem on the powerful channel; (3) a mathematical definition of a problem and solving a problem; (4) a pair of composition results that simplify the tasks of proving properties about channel implementation algorithms and combining problems with channel implementations

Modeling radio networks

We describe a modeling framework and collection of foundational composition results for the study of probabilistic distributed algorithms in synchronous radio networks. Though the radio setting has been studied extensively by the distributed algorithms community, their results rely on informal descriptions of the channel behavior and therefore lack easy comparability and are prone to error caused by definition subtleties. Our framework rectifies these issues by providing: (1) a method to precisely describe a radio channel as a probabilistic automaton; (2) a mathematical notion of implementing one channel using another channel, allowing for direct comparisons of channel strengths and a natural decomposition of problems into implementing a more powerful channel and solving the problem on the powerful channel; (3) a mathematical definition of a problem and solving a problem; (4) a pair of composition results that simplify the tasks of proving properties about channel implementation algorithms and combining problems with channel implementations. Our goal is to produce a model streamlined for the needs of the radio network algorithms community