arXiv subjects

Sanjay Shakkottai

Publications and source records attributed to Sanjay Shakkottai.

95 records · Page 6Linked to original sources

arXiv2012

Greedy Learning of Markov Network Structure

We propose a new yet natural algorithm for learning the graph structure of general discrete graphical models (a.k.a. Markov random fields) from samples. Our algorithm finds the neighborhood of a node by sequentially adding nodes that produce the largest reduction in empirical conditional entropy; it is greedy in the sense that the choice of addition is based only on the reduction achieved at that iteration. Its sequential nature gives it a lower computational complexity as compared to other existing comparison-based techniques, all of which involve exhaustive searches over every node set of a certain size. Our main result characterizes the sample complexity of this procedure, as a function of node degrees, graph size and girth in factor-graph representation. We subsequently specialize this result to the case of Ising models, where we provide a simple transparent characterization of sample complexity as a function of model and graph parameters. For tree graphs, our algorithm is the same as the classical Chow-Liu algorithm, and in that sense can be considered the extension of the same to graphs with cycles.

stat.ML↗

arXiv2011

On Sharing Viral Video over an Ad Hoc Wireless Network

We consider the problem of broadcasting a viral video (a large file) over an ad hoc wireless network (e.g., students in a campus). Many smartphones are GPS enabled, and equipped with peer-to-peer (ad hoc) transmission mode, allowing them to wirelessly exchange files over short distances rather than use the carrier's WAN. The demand for the file however is transmitted through the social network (e.g., a YouTube link posted on Facebook). To address this coupled-network problem (demand on the social network; bandwidth on the wireless network) where the two networks have different topologies, we propose a file dissemination algorithm. In our scheme, users query their social network to find geographically nearby friends that have the desired file, and utilize the underlying ad hoc network to route the data via multi-hop transmissions. We show that for many popular models for social networks, the file dissemination time scales sublinearly with n; the number of users, compared to the linear scaling required if each user who wants the file must download it from the carrier's WAN.

cs.SI↗

arXiv2008

Communication Through Jamming over a Slotted ALOHA Channel

This work derives bounds on the jamming capacity of a slotted ALOHA system. A system with n legitimate users, each with a Bernoulli arrival process is considered. Packets are temporarily stored at the corresponding user queues, and a slotted ALOHA strategy is used for packet transmissions over the shared channel. The scenario considered is that of a pair of illegitimate users that jam legitimate transmissions in order to communicate over the slotted ALOHA channel. Jamming leads to binary signaling between the illegitimate users, with packet collisions due to legitimate users treated as (multiplicative) noise in this channel. Further, the queueing dynamics at the legitimate users stochastically couples the jamming strategy used by the illegitimate users and the channel evolution. By considering various i.i.d. jamming strategies, achievable jamming rates over the slotted ALOHA channel are derived. Further, an upper bound on the jamming capacity over the class of all ergodic jamming policies is derived. These bounds are shown to be tight in the limit where the offered system load approaches unity.

cs.IT↗

arXiv2007

Rethinking Information Theory for Mobile Ad Hoc Networks

The subject of this paper is the long-standing open problem of developing a general capacity theory for wireless networks, particularly a theory capable of describing the fundamental performance limits of mobile ad hoc networks (MANETs). A MANET is a peer-to-peer network with no pre-existing infrastructure. MANETs are the most general wireless networks, with single-hop, relay, interference, mesh, and star networks comprising special cases. The lack of a MANET capacity theory has stunted the development and commercialization of many types of wireless networks, including emergency, military, sensor, and community mesh networks. Information theory, which has been vital for links and centralized networks, has not been successfully applied to decentralized wireless networks. Even if this was accomplished, for such a theory to truly characterize the limits of deployed MANETs it must overcome three key roadblocks. First, most current capacity results rely on the allowance of unbounded delay and reliability. Second, spatial and timescale decompositions have not yet been developed for optimally modeling the spatial and temporal dynamics of wireless networks. Third, a useful network capacity theory must integrate rather than ignore the important role of overhead messaging and feedback. This paper describes some of the shifts in thinking that may be needed to overcome these roadblocks and develop a more general theory that we refer to as non-equilibrium information theory.

cs.IT↗

arXiv2004

Geographic Routing with Limited Information in Sensor Networks

Geographic routing with greedy relaying strategies have been widely studied as a routing scheme in sensor networks. These schemes assume that the nodes have perfect information about the location of the destination. When the distance between the source and destination is normalized to unity, the asymptotic routing delays in these schemes are $Θ(\frac{1}{M(n)}),$ where M(n) is the maximum distance traveled in a single hop (transmission range of a radio). In this paper, we consider routing scenarios where nodes have location errors (imprecise GPS), or where only coarse geographic information about the destination is available, and only a fraction of the nodes have routing information. We show that even with such imprecise or limited destination-location information, the routing delays are $Θ(\frac{1}{M(n)})$. We also consider the throughput-capacity of networks with progressive routing strategies that take packets closer to the destination in every step, but not necessarily along a straight-line. We show that the throughput-capacity with progressive routing is order-wise the same as the maximum achievable throughput-capacity.

cs.IT↗