Abstract Topological maps represent the world as a network of nodes and arcs: the nodes are distinctive places in the environment and the arcs represent paths between places. A significant issue in building topological maps is defining distinctive places. Most previous work in topological mapping

connectivity afterwards. To construct the minimum sensor cover, we present a principle for selecting sens-ing nodes based on the triangle lattice. In order to guarantee the relay connectivity of selected sensing nodes, we propose verification and reinforcement procedures. Extensive simulations show

Abstract—Due to non-homogeneous spread of sunlight, sens-ing nodes possess non-uniform energy budget in rechargeable Wireless Sensor Networks (WSNs). An energy-aware workload distribution strategy is therefore necessary to achieve good data accuracy subject to energy-neutral operation. Our previ

, memory and processing for primary embedded networked sensing applications. Using results obtained in real-time we show that for a large class of wireless sensor network nodes, there exist several interdependencies in energy con-sumption between different subsystems. Through the use of our measurement

on correlations of node locations and sensed phenomena. This metric enables the performance estimation of WSNs apply-ing DSC prior to the costly real deployment. Furthermore, we show that significant average energy savings and average lifetime extensions are possible using DSC under dif-ferent node deployment

Wireless sensor network (WSN) applications are used in many different scenarios ranging from indoor mote networks to participatory sensing applications using smartphones. As WSN systems operate in such diverse environments using different sensor node hardware, we have identified the need of a

This paper introduces a decentralized node selection algo-rithm, which we name autonomous node selection (ANS). The purpose of a node selection algorithm is to select the active nodes that sense, compute and communicate mea-surements for target tracking in a wireless sensor network. By selecting a

In this article, we present experimental investigations using energy harvesting and wireless energy transmission to power wireless structural health monitoring sensor nodes. The goal of this study is to develop sensing systems that can be permanently embedded within a host structure without

coopera-tive spectrum sensing scheme for mobile cognitive networks, based on a correlation-based, mobility-aware node selection algorithm is proposed. Correlation among sensing decisions is used to divide nodes into groups, and mobility is taken into account in the group leaders selection by means of a node

-messages and then couples a fine-grained random scheduling with random linear network coding for broadcast-ing the mini-messages. Theoretical analyses demonstrate that R2 performs optimally in order sense, no matter how fast network nodes move around, although different mobility has distinct effect on the speed of message