4,277 research outputs found
Heterogeneous attachment strategies optimize the topology of dynamic wireless networks
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
Resilient Wireless Sensor Networks Using Topology Control: A Review
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
Overlapping Multi-hop Clustering for Wireless Sensor Networks
Clustering is a standard approach for achieving efficient and scalable
performance in wireless sensor networks. Traditionally, clustering algorithms
aim at generating a number of disjoint clusters that satisfy some criteria. In
this paper, we formulate a novel clustering problem that aims at generating
overlapping multi-hop clusters. Overlapping clusters are useful in many sensor
network applications, including inter-cluster routing, node localization, and
time synchronization protocols. We also propose a randomized, distributed
multi-hop clustering algorithm (KOCA) for solving the overlapping clustering
problem. KOCA aims at generating connected overlapping clusters that cover the
entire sensor network with a specific average overlapping degree. Through
analysis and simulation experiments we show how to select the different values
of the parameters to achieve the clustering process objectives. Moreover, the
results show that KOCA produces approximately equal-sized clusters, which
allows distributing the load evenly over different clusters. In addition, KOCA
is scalable; the clustering formation terminates in a constant time regardless
of the network size
Performance Characterization of Random Proximity Sensor Networks
In this paper, we characterize the localization performance
and connectivity of sensors networks consisting of
binary proximity sensors using a random sensor management
strategy. The sensors are deployed uniformly at random over
an area, and to limit the energy dissipation, each sensor node
switches between an active and idle state according to random
mechanisms regulated by a birth-and-death stochastic process.
We first develop an upper bound for the minimum transmitting
range which guarantees connectivity of the active nodes in the
network with a desired probability. Then, we derive an analytical
formula for predicting the mean-squared localization error of
the active nodes when assuming a centroid localization scheme.
Simulations are used to verify the theoretical claims for various
localization schemes that operate only over connected active
nodes
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