A Survey on Mobile Anchor Node Assisted Localization in Wireless Sensor Networks

Localization is one of the key technologies in Wireless Sensor Networks (WSNs), since it provides fundamental support for many location-aware protocols and applications. Constraints on cost and power consumption make it infeasible to equip each sensor node in the network with a Global Position System (GPS) unit, especially for large-scale WSNs. A promising method to localize unknown nodes is to use mobile anchor nodes (MANs), which are equipped with GPS units moving among unknown nodes and periodically broadcasting their current locations to help nearby unknown nodes with localization. A considerable body of research has addressed the Mobile Anchor Node Assisted Localization (MANAL) problem. However to the best of our knowledge, no updated surveys on MAAL reflecting recent advances in the field have been presented in the past few years. This survey presents a review of the most successful MANAL algorithms, focusing on the achievements made in the past decade, and aims to become a starting point for researchers who are initiating their endeavors in MANAL research field. In addition, we seek to present a comprehensive review of the recent breakthroughs in the field, providing links to the most interesting and successful advances in this research field.

The Coxian Phase-type distribution with a Hidden Node

Healthcare providers are under increased pressure to ensure that the quality
of care delivered to patients are off the highest standard. Modelling quality of
care is difficult due to the many ways of defining it. This paper introduces a potential
model which could be used to take quality of care into account when modelling
length of stay. The Coxian phase-type distribution is used to model length of stay
and quality of care incorporated into this using a Hidden Markov model. This model
is then applied to

Network Connectivity under Node Failure

We examine a non-cooperative model of network formation where players may stop functioning with a given probability. When this happens all the links associated with this player are no longer available in the network. In the model, players receive benefits from connecting directly and indirectly to other agents in the network through costly links. We identify conditions under which a Nash network will remain connected after the loss of k nodes by introducing the notion of k-Node Super Connectivity network. We identify similar conditions for efficient networks as well.