The Influence of Communication Range on Connectivity for Resilient Wireless Sensor Networks Using a Probabilistic Approach.

Wireless sensor networks (WSNs) consist of thousands of nodes that need to communicate with each other. However, it is possible that some nodes are isolated from other nodes due to limited communication range. This paper focuses on the influence of communication range on the probability that all nodes are connected under two conditions, respectively: (1) all nodes have the same communication range, and (2) communication range of each node is a random variable. In the former case, this work proves that, for 0menor queepsmenor quee^(-1) , if the probability of the network being connected is 0.36eps , by means of increasing communication range by constant C(eps) , the probability of network being connected is at least 1-eps. Explicit function C(eps) is given. It turns out that, once the network is connected, it also makes the WSNs resilient against nodes failure. In the latter case, this paper proposes that the network connection probability is modeled as Cox process. The change of network connection probability with respect to distribution parameters and resilience performance is presented. Finally, a method to decide the distribution parameters of node communication range in order to satisfy a given network connection probability is developed

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

Partial Connectivity in Wireless Sensor Networks

Given a bounded region of the 2-dimensional plane, a discrete set of nodes is distributed throughout according to a Poisson point process. Given some fixed, finite, real number, two nodes are said to connect and form an edge if their mutual distance is less than this number. Let G be the graph of all such edges over the set of generated nodes and let C be any set of mutually connected nodes. It is shown that there is a critical mutual distance such that at least half of all generated nodes are mutually connected to form a connected cluster. Now, suppose that the 2-dimensional plane is partitioned into hexagons chosen such that each can be inscribed into a circle of radius which is half the size of the mutual distance. Define another notion of connectivity on the generated nodes by saying that two nodes connect if each lies in the same hexagon or each lies in a hexagon which shares a common face with the hexagon containing the other node. It is shown that the original graph of edges contains the new graph of edges and that there is an inequality relationship among the critical mutual distances. Finally, using results mentioned above, upper and lower bounds on the probability of connecting slightly more or slight less than half of all generated nodes are obtained and used to estimate the length of the interval of radii such that the probability of connecting at least half of all generated nodes will increase from some small positive value to a value near 1. This interval of connectivity radii is called a sharp threshold interval