In this paper, we study the problem of efficient data recovery using the data mules approach, where a set of mobile sensors with advanced mobility capabilities re-acquire lost data by visiting the neighbors of failed sensors, thereby improving network resiliency. Our approach involves defining the optimal communication graph and mules' placements such that the overall traveling time and distance is minimized regardless to which sensors crashed. We explore this problem under different practical network topologies such as general graphs, grids and random linear networks and provide approximation algorithms based on multiple combinatorial techniques. Simulation experiments demonstrate that our algorithms outperform various competitive solutions for different network models, and that they are applicable for practical scenarios.

In this paper we consider the problem of efficient data gathering in sensor networks for arbitrary sensor node deployments. The efficiency of the solution is measured by a number of criteria: total energy consumption, total transport capacity, latency and quality of the transmissions. We present a number of different constructions with various tradeoffs between aforementioned parameters. We provide theoretical performance analysis for our approaches, present their distributed implementation and discuss the different aspects of using each. We show that in many cases our output-sensitive approximation solution performs better than the currently known best results for sensor networks. Our simulation results validate the theoretical findings.

One of the most challenging recommendation tasks is recommending to a new, previously unseen user. This is known as the user cold start problem. Assuming certain features or attributes of users are known, one approach for handling new users is to initially model them based on their features.

This paper studies the problem of interference-free broadcast in wireless ad hoc networks. In particular, we are interested in asymmetric power assignments so that the induced broadcast communication graph is both, energy efficient and has a short collision-free broadcast schedule. We consider both random and deterministic node layouts and develop four different broadcast schemes with provable performance guarantees on three optimization objectives simultaneously: total energy consumption, network lifetime and collision-free schedule length. We also show some numerical results which support our findings.