Ramanuja Vedantham

A scalable approach for reliable downstream data delivery in wireless sensor networks

There exist several applications of sensor networks wherere liability of data delivery can be critical. While the redundancy inherent in a sensor network might increase the degree of reliability, it by no means can provide any guaranteed reliability semantics. In this paper, we consider the problem of reliable sink-to-sensors data delivery. We first identify several fundamental challenges that need to be addressed, and are unique to a wireless sensor network environment. We then propose a scalable framework for reliable downstream data delivery that is specifically designed to both address and leverage the characteristics of a wireless sensor network, while achieving the reliability in an efficient manner. Through ns2 based simulations, we evaluate the proposed framework.

Component based channel assignment in single radio, multi-channel ad hoc networks

In this paper, we consider the channel assignment problem in single radio multi-channel mobile ad-hoc networks. Specifically, we investigate the granularity of channel assignment decisions that gives the best trade-off in terms of performance and complexity. We present a new granularity for channel assignment that we refer to as component level channel assignment. The strategy is relatively simple, and is characterized by several impressive practical advantages. We also show that the theoretical performance of the component based channel assignment strategy does not lag significantly behind the optimal possible performance, and perhaps more importantly we show that when coupled with its several practical advantages, it significantly outperforms other strategies under most network conditions.

GARUDA: Achieving Effective Reliability for Downstream Communication in Wireless Sensor Networks

There exist several applications of sensor networks where the reliability of data delivery can be critical. Although the redundancy inherent in a sensor network might increase the degree of reliability, it by no means can provide any guaranteed reliability semantics. In this paper, we consider the problem of reliable sink-to-sensors data delivery. We first identify several fundamental challenges that need to be addressed and are unique to the environment of wireless sensor networks. We then propose a scalable framework for reliable downstream data delivery that is specifically designed to both address and leverage the characteristics of the wireless sensor networks while achieving the reliability in an efficient manner. Through ns2-based simulations, we evaluate the proposed framework.

A scalable correlation aware aggregation strategy for wireless sensor networks

Sensors-to-sink data in wireless sensor networks (WSNs) are typically correlated with each other. Exploiting such correlation when performing data aggregation can result in considerable improvements in the bandwidth and energy performance of WSNs. In order to exploit such correlation, we present a scalable and distributed correlation-aware aggregation structure that addresses the practical challenges in the context of aggregation in WSNs. Through simulations and analysis, we evaluate the performance of the proposed approach with centralized and distributed correlation aware and unaware structures.

Mutual Exclusion in Wireless Sensor and Actor Networks

A typical wireless sensor network (WSN) performs only one action: sensing the environment. The need for smart interaction with the environment has led to the emergence of wireless sensor and actor networks (WSANs). The evolution from WSNs, which can be thought of to perform only read operations, to WSANs, which can perform both read and write operations, introduces unique and new challenges that need to be addressed. In this context, we identify the problem of mutual exclusion, which is the requirement to act only to the desired level for any particular location and command. We define the different types of mutual exclusion and the associated challenges in the context of WSANs, and show the undesirable consequences of not providing mutual exclusion with example applications. To address this problem efficiently, we propose a greedy centralized approach, and a distributed and fully localized approach based on the centralized approach. Through simulations, we study the performance of the proposed solution with the centralized approach and a baseline strategy, and show that the proposed solution is efficient for a variety of network conditions

Sink-to-sensors congestion control

The problem of congestion in sensor networks is significantly different from conventional ad-hoc networks and has not been studied to any great extent thus far. In this paper, we focus on providing congestion control from the sink to the sensors in a sensor field. We identify the different reasons for congestion from the sink to the sensors and show the uniqueness of the problem in sensor network environments. We propose a scalable, distributed approach that addresses congestion from the sink to the sensors in a sensor network. Through ns2 based simulations, we evaluate the proposed framework, and show that it performs significantly better over a basic approach which does not provide any congestion control.