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Mukundan Sridharan

Publications and source records attributed to Mukundan Sridharan.

4 recordsLinked to original sources

Achieving Throughput via Fine-Grained Path Planning in Small World DTNs

We explore the benefits of using fine-grained statistics in small world DTNs to achieve high throughput without the aid of external infrastructure. We first design an empirical node-pair inter-contacts model that predicts meetings within a time frame of suitable length, typically of the order of days, with a probability above some threshold, and can be readily computed with low overhead. This temporal knowledge enables effective time-dependent path planning that can be respond to even per-packet deadline variabilities. We describe one such routing framework, REAPER (for Reliable, Efficient and Predictive Routing), that is fully distributed and self-stabilizing. Its key objective is to provide probabilistic bounds on path length (cost) and delay in a temporally fine-grained way, while exploiting the small world structure to entail only polylogarithmic storage and control overhead. A simulation-based evaluation confirms that REAPER achieves high throughput and energy efficiency across the spectrum of ultra-light to heavy network traffic, and substantially outperforms state-of-the-art single copy protocols as well as sociability-based protocols that rely on essentially coarse-grained metrics.

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Census: Fast, scalable and robust data aggregation in MANETs

This paper describes Census, a protocol for data aggregation and statistical counting in MANETs. 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.

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On the repair time scaling wall for 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, this paper 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.

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A Little Prediction Goes a Long Way: Routing in Semi-Deterministic Delay Tolerant Networks

Realizing delay-capacity in intermittently connected mobile networks remains a largely open question, with state-of-the-art routing schemes typically focusing either on delay or on capacity. We show the feasibility of routing with both high goodput and desired delay constraints, with REAPER (for Reliable, Efficient, and Predictive Routing), a fully distributed convergecast routing framework that jointly optimizes both path length and path delay. A key idea for efficient instantiation of REAPER is to exploit predictability of mobility patterns, in terms of a semi-deterministic model which appropriately captures several vehicular and human inter-contact patterns. Packets are thus routed using paths that are jointly optimal at their time of arrival, in contrast to extant DTN protocols which use time-average metrics for routing. REAPER is also self-stabilizing to changes in the mobility pattern. A simulation-based evaluation confirms that, across the spectrum of ultra-light to heavy traffics, REAPER achieves up to 135% and 200% higher throughput and up to 250% and 1666% higher energy efficiency than state-of-the-art single-copy protocols MEED-DVR and PROPHET, which optimize a single metric only, specifically, expected delay and path probability respectively.

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