679 research outputs found

    Resilient Wireless Sensor Networks Using Topology Control: A Review

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    Wireless sensor networks (WSNs) may be deployed in failure-prone environments, and WSNs nodes easily fail due to unreliable wireless connections, malicious attacks and resource-constrained features. Nevertheless, if WSNs can tolerate at most losing k − 1 nodes while the rest of nodes remain connected, the network is called k − connected. k is one of the most important indicators for WSNs’ self-healing capability. Following a WSN design flow, this paper surveys resilience issues from the topology control and multi-path routing point of view. This paper provides a discussion on transmission and failure models, which have an important impact on research results. Afterwards, this paper reviews theoretical results and representative topology control approaches to guarantee WSNs to be k − connected at three different network deployment stages: pre-deployment, post-deployment and re-deployment. Multi-path routing protocols are discussed, and many NP-complete or NP-hard problems regarding topology control are identified. The challenging open issues are discussed at the end. This paper can serve as a guideline to design resilient WSNs

    Self-* distributed query region covering in sensor networks

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    Wireless distributed sensor networks are used to monitor a multitude of environments for both civil and military applications. Sensors may be deployed to unreachable or inhospitable areas. Thus, they cannot be replaced easily. However, due to various factors, sensors\u27 internal memory, or the sensors themselves, can become corrupted. Hence, there is a need for more robust sensor networks. Sensors are most commonly densely deployed, but keeping all sensors continually active is not energy efficient. Our aim is to select the minimum number of sensors which can entirely cover a particular monitored area, while remaining strongly connected. This concept is called a Minimum Connected Cover of a query region in a sensor network. In this research, we have designed two fully distributed, robust, self-* solutions to the minimum connected cover of query regions that can cope with both transient faults and sensor crashes. We considered the most general case in which every sensor has a different sensing and communication radius. We have also designed extended versions of the algorithms that use multi-hop information to obtain better results utilizing small atomicity (i.e., each sensor reads only one of its neighbors\u27 variables at a time, instead of reading all neighbors\u27 variables). With this, we have proven self-* (self-configuration, self-stabilization, and self-healing) properties of our solutions, both analytically and experimentally. The simulation results show that our solutions provide better performance in terms of coverage than pre-existing self-stabilizing algorithms

    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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