216 research outputs found

    FLOC-SPANNER: An O(1) time, locally self-stabilizing algorithm for geometric spanner construction in a wireless sensor network

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    Geometric spanners are a popular form of topology control in wireless networks because they yield an efficient, reduced interference subgraph for both unicast and broadcast routing.;In this thesis work a distributed algorithm for creation of geometric spanners in a wireless sensor network is presented. Given any connected network, we show that the algorithm terminates in O(1) time, irrespective of network size. Our algorithm uses an underlying clustering algorithm as a foundation for creating spanners, and only relies on the periodic heartbeat messages associated with cluster maintenance for the creation of the spanners. The algorithm is also shown to stabilize locally in the presence of node additions and deletions. The performance of our algorithm is verified using large scale simulations. The average path length ratio for routing along the spanner for large networks is shown to be less than 2.;Geometric Spanners is a well-researched topic. The algorithm presented in this thesis differs from other spanner algorithms in the following ways: 1. It is a distributed locally self-stabilizing algorithm. 2. It does not require location information for its operation. 3. Creates spanner network in constant time irrespective of network size and network density

    MAP: Medial Axis Based Geometric Routing in Sensor Networks

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    One of the challenging tasks in the deployment of dense wireless networks (like sensor networks) is in devising a routing scheme for node to node communication. Important consideration includes scalability, routing complexity, the length of the communication paths and the load sharing of the routes. In this paper, we show that a compact and expressive abstraction of network connectivity by the medial axis enables efficient and localized routing. We propose MAP, a Medial Axis based naming and routing Protocol that does not require locations, makes routing decisions locally, and achieves good load balancing. In its preprocessing phase, MAP constructs the medial axis of the sensor field, defined as the set of nodes with at least two closest boundary nodes. The medial axis of the network captures both the complex geometry and non-trivial topology of the sensor field. It can be represented compactly by a graph whose size is comparable with the complexity of the geometric features (e.g., the number of holes). Each node is then given a name related to its position with respect to the medial axis. The routing scheme is derived through local decisions based on the names of the source and destination nodes and guarantees delivery with reasonable and natural routes. We show by both theoretical analysis and simulations that our medial axis based geometric routing scheme is scalable, produces short routes, achieves excellent load balancing, and is very robust to variations in the network model

    Localized and Configurable Topology Control in Lossy Wireless Sensor Networks

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    Recent empirical studies revealed that multi-hop wireless networks like wireless sensor networks and 802.11 mesh networks are inherently lossy. This finding introduces important new challenges for topology control. Existing topology control schemes often aim at maintaining network connectivity that cannot guarantee satisfactory path quality and communication performance when underlying links are lossy. In this paper, we present a localized algorithm, called Configurable Topology Control (CTC), that can configure a network topology to different provable quality levels (quantified by worst-case dilation bounds in terms of expected total number of transmisssions) required by applications. Each node running CTC computes its transmission power solely based on the link quality information collected within its local neighborhood and does not assume that the neighbor locations or communication ranges are known. Our simulations based on a realistic radio model of Mica2 motes show that CTC yields configurable communication performance and outperforms existing topology control algorithms that do not account for lossy links

    07151 Abstracts Collection -- Geometry in Sensor Networks

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    From 9.4.2007 to 13.4.07, the Dagstuhl Seminar 07151 ``Geometry in Sensor Networks\u27\u27 was held in the International Conference and Research Center (IBFI), Schloss Dagstuhl. During the seminar, several participants presented their current research, and ongoing work and open problems were discussed. Abstracts of the presentations given during the seminar as well as abstracts of seminar results and ideas are put together in this paper. The first section describes the seminar topics and goals in general. Links to extended abstracts or full papers are provided, if available

    A clustered back-bone for routing in ad-hoc networks

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    In the recent years, a lot of research work has been undertaken in the area of ad-hoc networks due to the increasing potential of putting them to commercial use in various types of mobile computing devices. Topology control in ad-hoc networks is a widely researched topic; with a number of algorithms being proposed for the construction of a power-efficient topology that optimizes the battery usage of the mobile nodes. This research proposes a novel technique of partitioning the ad-hoc network into virtually-disjoint clusters. The ultimate aim of forming a routing graph over which power-efficient routing can be implemented in a simple and effective manner is realized by partitioning the network into disjoint clusters and thereafter joining them through gateways to form a connected, planar back-bone which is also a t-spanner of the original Unit Disk Graph (UDG). Some of the previously proposed algorithms require the nodes to construct local variations of the Delaunay Triangulation and undertake several complicated steps for ensuring the planarity of the back-bone graph. The construction of the Delaunay Triangulation is very complex and time-consuming. This work achieves the objective of constructing a routing graph which is a planar spanner, without requiring the expensive construction of the Delaunay Triangulation, thus saving the node power, an important resource in the ad-hoc network. Moreover, the algorithm guarantees that the total number of messages required to be sent by each node is O(n). This makes the topology easily reconfigurable in case of node motion

    Heterogeneous attachment strategies optimize the topology of dynamic wireless networks

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    In optimizing the topology of wireless networks built of a dynamic set of spatially embedded agents, there are many trade-offs to be dealt with. The network should preferably be as small (in the sense that the average, or maximal, pathlength is short) as possible, it should be robust to failures, not consume too much power, and so on. In this paper, we investigate simple models of how agents can choose their neighbors in such an environment. In our model of attachment, we can tune from one situation where agents prefer to attach to others in closest proximity, to a situation where distance is ignored (and thus attachments can be made to agents further away). We evaluate this scenario with several performance measures and find that the optimal topologies, for most of the quantities, is obtained for strategies resulting in a mix of most local and a few random connections

    Topology design for time-varying networks

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    Traditional wireless networks seek to support end-to-end communication through either a single-hop wireless link to infrastructure or multi-hop wireless path to some destination. However, in some wireless networks (such as delay tolerant networks, or mobile social networks), due to sparse node distribution, node mobility, and time-varying network topology, end-to-end paths between the source and destination are not always available. In such networks, the lack of continuous connectivity, network partitioning, and long delays make design of network protocols very challenging. Previous DTN or time-varying network research mainly focuses on routing and information propagation. However, with large number of wireless devices' participation, and a lot of network functionality depends on the topology, how to maintain efficient and dynamic topology of a time-varying network becomes crucial. In this dissertation, I model a time-evolving network as a directed time-space graph which includes both spacial and temporal information of the network, then I study various topology control problems with such time-space graphs. First, I study the basic topology design problem where the links of the network are reliable. It aims to build a sparse structure from the original time-space graph such that (1) the network is still connected over time and/or supports efficient routing between any two nodes; (2) the total cost of the structure is minimized. I first prove that this problem is NP-hard, and then propose several greedy-based methods as solutions. Second, I further study a cost-efficient topology design problem, which not only requires the above two objective, but also guarantees that the spanning ratio of the topology is bounded by a given threshold. This problem is also NP-hard, and I give several greedy algorithms to solve it. Last, I consider a new topology design problem by relaxing the assumption of reliable links. Notice that in wireless networks the topologies are not quit predictable and the links are often unreliable. In this new model, each link has a probability to reflect its reliability. The new reliable topology design problem aims to build a sparse structure from the original space-time graph such that (1) for any pair of devices, there is a space-time path connecting them with the reliability larger than a required threshold; (2) the total cost of the structure is minimized. Several heuristics are proposed, which can significantly reduce the total cost of the topology while maintain the connectivity or reliability over time. Extensive simulations on both random networks and real-life tracing data have been conducted, and results demonstrate the efficiency of the proposed methods
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