A local average consensus algorithm for wireless sensor networks

—In many application scenarios sensors need to calculate the average of some local values, e.g. of local measurements. A possible solution is to rely on consensus algorithms. In this case each sensor maintains a local estimate of the global average, and keeps improving it by performing a weighted sum of the estimates of all its neighbors. The number of iterations needed to reach an accurate estimate depends on the weights used at each sensor. Speeding up the convergence rate is important also to reduce the number of messages exchanged among neighbors and then the energetic cost of these algorithms. While it is possible in principle to calculate the optimal weights, the known algorithm requires a single sensor to discover the topology of the whole network and perform the calculations. This may be unfeasible for large and dynamic sensor networks, because of sensor computational constraints and of the communication overhead due to the need to acquire the new topology after each change. ...

• Type: Journal
• Year: 2011
• Where: DCOSS
• Authors: Konstantin Avrachenkov, Mahmoud El Chamie, Giovanni Neglia
• Keywords: Consensus Algorithms, DCOSS 2011, Distributed And Parallel Computing, Dynamic Sensor Networks, Wireless Sensor Networks