Connectivity, Coverage and Placement in Wireless Sensor Networks

Wireless communication between sensors allows the formation of flexible sensor networks, which can be deployed rapidly over wide or inaccessible areas. However, the need to gather data from all sensors in the network imposes constraints on the distances between sensors. This survey describes the state of the art in techniques for determining the minimum density and optimal locations of relay nodes and ordinary sensors to ensure connectivity, subject to various degrees of uncertainty in the locations of the nodes

Proximity-driven social interactions and their impact on the throughput scaling of wireless networks

We present an analytical framework to investigate the interplay between a communication graph and an overlay of social  relationships.  We focus on geographical distance as the key element that interrelates the concept of routing in a communication network with the dynamics of interpersonal relations on the corresponding social graph. We identify  classes of social relationships that let the ensuing system  scale---i.e., accommodate a large number of users given only finite amount of resources. We establish that geographically concentrated communication patterns are indispensable to network scalability. We  further examine the impact of such proximity-driven interaction patterns on the throughput scaling of wireless networks, and show that, when social communications are geographically localized, the maximum per-node throughput scales approximately as $1/\log n$, which is significantly better than the well-known bound of $1/\sqrt{n \log n}$ for the uniform communication model