activity
20092011
most citedFundamentals of Large Sensor Networks: Connectivity, Capacity, Clocks and Computation

111 citations · 119 across the 6 of their papers we have counts for

collaborators

6 papers

cs.IT2011

Optimal Computation of Symmetric Boolean Functions in Collocated Networks

Hemant Kowshik, P. R. Kumar

We consider collocated wireless sensor networks, where each node has a Boolean measurement and the goal is to compute a given Boolean function of these measurements. We first consi…

cs.IT2011

Optimal Function Computation in Directed and Undirected Graphs

Hemant Kowshik, P. R. Kumar

We consider the problem of information aggregation in sensor networks, where one is interested in computing a function of the sensor measurements. We allow for block processing and…

cs.IT2010★ 6 cited

Optimal ordering of transmissions for computing Boolean threhold functions

Hemant Kowshik, P. R. Kumar

We address a sequential decision problem that arises in the computation of symmetric Boolean functions of distributed data. We consider a collocated network, where each node's tran…

cs.IT2010★ 2 cited

Optimal computation of symmetric Boolean functions in Tree networks

Hemant Kowshik, P. R. Kumar

In this paper, we address the scenario where nodes with sensor data are connected in a tree network, and every node wants to compute a given symmetric Boolean function of the senso…

cs.NI2009★ 111 cited

Fundamentals of Large Sensor Networks: Connectivity, Capacity, Clocks and Computation

Nikolaos M. Freris, Hemant Kowshik, P. R. Kumar

Sensor networks potentially feature large numbers of nodes that can sense their environment over time, communicate with each other over a wireless network, and process information.…

cs.IT2009

Optimal strategies for computing symmetric Boolean functions in collocated networks

Hemant Kowshik, P. R. Kumar

We address the problem of finding optimal strategies for computing Boolean symmetric functions. We consider a collocated network, where each node's transmissions can be heard by ev…