Ratnabali Biswas

Energy aware routing for spatio-temporal queries in sensor networks

Wireless sensor networks form an emerging technology that can significantly improve the quality of spatio-temporal data monitoring because of their untethered operation and potential for large scale deployment. We define a communication architecture that supports distributed query processing to evaluate spatio-temporal queries within the network. We represent these queries by query trees and distribute query operators to appropriate sensor nodes. As operator execution demands high computation capability, we propose the use of a heterogenous sensor network where query operators are assigned to sparsely deployed resource-rich nodes within a dense network of low power sensor nodes. We design an adaptive, decentralized, low communication overhead algorithm to determine an operator placement on the resource-rich nodes in the network to minimize cost of transmitting data along a routing tree constructed to retrieve data continuously at the sink from a set of spatially distributed geographical regions. To the best of our knowledge, this is the first attempt to build an energy aware routing infrastructure to enable in-network processing of spatio-temporal queries.

On-demand reliable medium access in sensor networks

A wireless sensor network typically consists of a dense deployment of sensor nodes to achieve higher resolution and better network coverage. Having a dense network increases the fault-tolerance and robustness of the system. However, if not properly handled, it can lead to more collisions during transmission and also network congestion. Furthermore, wireless communication is inherently unpredictable and error-prone. Hence, it is imperative to design an efficient medium access control (MAC) protocol that facilitates guaranteed delivery of data over unreliable wireless links. In this paper, we have designed an on-demand reliable MAC (RMAC) protocol that enables timely delivery of data. We have demonstrated its superior performance over existing reliability-enforcing approaches in terms of reliability, latency, scalability and energy-efficiency

Energy-Efficient and Reliable Medium Access in Sensor Networks

Energy efficiency and reliable data delivery are the two most important parameters for designing wireless sensor network protocols. Wireless communication is inherently unpredictable and error-prone. Hence, reliability is required to ensure that a packet reaches its desired destination; otherwise the energy expended in forwarding the packet is wasted On the other hand, energy-saving mechanisms are required for battery-constrained sensor networks. In this paper, we have designed an on-demand energy-efficient and reliable medium access control (E2RM: AC) protocol that enables reliable data delivery and energy conservation without affecting packet latency. We have demonstrated the superior performance of E2RMAC over existing energy-efficient and reliability-enforcing approaches in terms of reliability, latency, scalability and energy-efficiency.

Attribute Allocation and Retrieval Scheme for Large-Scale Sensor Networks

Wireless sensor network is an emerging technology that enables remote monitoring of large geographical regions. In this paper, we address the problem of distributing attributes over such a large-scale sensor network so that the cost of data retrieval is minimized. The proposed scheme is a data-centric storage scheme where the attributes are distributed over the network depending on the correlations between them. The problem addressed here is similar to the Allocation Problem of distributed databases. In this paper, we have defined the Allocation Problem in the context of sensor networks and have proposed a scheme for finding a good distribution of attributes to the sensor network. We also propose an architecture for query processing given such a distribution of attributes. We analytically determine the conditions under which the proposed architecture is beneficial and present simulation results to demonstrate the same. To the best of our knowledge, this is the first attempt to determine an allocation of attributes over a sensor network based on the correlations between attributes.

Attribute allocation in large scale sensor networks

Wireless sensor network is an emerging technology that enables remote monitoring of large geographical regions. In this paper, we address the problem of distributing attributes over such a large-scale sensor network so that the cost of data retrieval is minimized. The proposed scheme is a data-centric storage scheme where the attributes are distributed over the network depending on the correlations between them. The problem addressed here is similar to the Allocation Problem of distributed databases. In this paper, we have defined the Allocation Problem in the context of sensor networks and have proposed a scheme for finding a good distribution of attributes to the sensor network. We also propose an architecture for query processing given such a distribution of attributes. Finally, we present simulations results to illustrate the conditions under which our proposed architecture is beneficial. To the best of our knowledge, this is the first attempt to study the attribute allocation problem of distributed databases in the context of sensor networks.

Communication architecture for processing spatio-temporal continuous queries in sensor networks

Wireless sensor networks have revolutionized distributed micro-sensing because of their ease of deployment, ad hoc connectivity and cost-effectiveness. They have also enabled collecting and monitoring data from a very large area or possibly several independent areas geographically separated from each other and such a process is known as spatio-temporal data monitoring. In this paper, we define an energy-aware routing infrastructure that enables distributed query processing and supports processing of spatio-temporal queries within the network. As operator execution demands high computation capability, we propose a possible use of a heterogeneous sensor network where query operators are assigned to sparsely-deployed resource-rich nodes within a dense network of low power sensor nodes. We have designed an adaptive, decentralized, low communication overhead algorithm to determine optimal operator placement on the resource-rich nodes such that data transfer cost in the network is minimized. To the best of our knowledge, this is the first attempt to build an energy-aware communication architecture to enable in-network processing of spatio-temporal queries.RésuméDe par leur facilité et leur souplesse de déploiement,mais aussi de par leur faible coût, les réseaux de capteurs sans fil ont bouleversé le domaine de la collecte d’informations. Il est maintenant possible de recueillir et de traiter des données provenant de plusieurs zones géo-graphiquement séparées et éventuellement très étendues : c’est ce qu’on appelle la gestion de données spatio-temporelles. Dans cet article, on définit une infrastructure de routage économe en énergie qui permet un traitement réparti des requêtes et une gestion des requêtes spatio-temporelles dans le réseau. L’exécution demandant une capacité de traitement élevée, on propose d’utiliser un réseau de capteurs hétérogène dans lequel les opérateurs de requêtes sont affectés à des nuds puissants mais relativement rares, l’essentiel du réseau étant composé de nuds à faibles capacités. On présente un algorithme adaptatif, décentralisé et à faible surcoût de communication pour déterminer le placement optimal des noeuds puissants dans le réseau de telle sorte que le coût de transmission des données zsoit minimal. A notre connaissance, cet article présente la première tentative de construire une architecture économe en énergie qui permette de traiter les requêtes spatio-temporelles.

Data-centric attribute allocation and retrieval (DCAAR) scheme for wireless sensor networks

Wireless sensor networks have enabled information gathering from a large geographical region and present unprecedented opportunities for a broad spectrum of monitoring applications. In this paper, we propose a data-centric storage scheme to determine a distribution of attributes over a large-scale sensor network such that the cost of retrieving data is minimized. We analytically determine the conditions under which the proposed architecture is beneficial and present simulation results to demonstrate the same. To the best of our knowledge, this is the first attempt to determine an allocation of attributes over a sensor network based on the correlations between attributes