Repair time scaling wall in MANETs

The inability of practical MANET deployments to scale beyond about 100 nodes has traditionally been blamed on insufficient network capacity for supporting routing related control traffic. However, our research points out that network capacity is significantly under-utilized by standard MANET routing algorithms at observed scaling limits. Therefore, as opposed to identifying the scaling limit for MANET routing from a capacity stand-point, it is instead characterized as a function of the interaction between dynamics of path failure (caused due to mobility) and path repair. This leads to the discovery of the repair time scaling wall, which is used to explain observed scaling limits in MANETs. The factors behind the repair time scaling wall are identified and techniques to extend the scaling limits are described. One of the key observations here is that fast neighbor discovery is critical for ensuring scalability of MANET routing protocols.

Technical report can be found here. (Under submission)

Unstructured protocols for scalable and robust data aggregation in MANETs using biased random walks

Our findings in repair time scaling wall, point out that route maintenance is a hard problem in MANETs, incurs significant overhead, and is vulnerable to failures. Therefore, we explore unstructured approaches for problems such as routing and data aggregation in MANETs. Recently, we have used biased random walks for this purpose. Our protocol, Census, operates by circulating a set of tokens in the network using biased random walks such that each node is visited by at least one token. The protocol is structure-free so as to avoid high messaging overhead for maintaining structure in the presence of node mobility. It biases the random walks of tokens so as to achieve fast cover time; the bias involves short albeit multi-hop gradients that guide the tokens towards hitherto unvisited nodes. Census thus achieves a cover time of O(N/k) and message overhead of O(Nlog(N)/k) where N is the number of nodes and k the number of tokens in the network. Notably, it enjoys scalability and robustness, which we demonstrate via simulations in networks ranging from 100 to 4000 nodes under different network densities and mobility models.

Technical report can be found here. (Under submission)

Distance-sensitive Common Operating Picture

Supplying system-wide state information at high rates is a fundamental problem in several large scale networked systems. Examples include location tracking in mobile ad-hoc and sensor networks, decentralized control of spatially distributed systems, and safety and navigation control in vehicular networks. While all of these applications would benefit from network wide state information supplied at high rates and low latency, achieving all-all broadcast using a contention-prone wireless network is challenging. Instead we use distance-sensitive ideas for compressing state information from nodes that are farther away, resulting in a distance-sensitive Common Operating Picture.

TuscArora framework for MANETs

TuscArora is an agile networking framework that is designed to decouple networking patterns from waveforms (radio), so that both networking patterns and waveforms can be added or removed during normal operation and so that both can be automatically tested in isolation. The framework is aimed at making it easier to integrate adaptive routing services that handle critical communication across multiple hardware platforms.

All of the above research was initiated as part of two DARPA funded projects on which we were subcontractors through The Samraksh Company, Dublin, OH.

DARPA Fixed Wireless At a Distance [Aug 2012 – Feb 2015]

DARPA Communication in Congested Environments [Aug 2014 – Oct 2015]