List of Titles

Authors: Pervin, Shaila , Kamruzzaman, Joarder , Karmakar, Gour
Date: 2012
Type: Text , Conference paper
Full Text: false
Reviewed:
Description: Timeliness in query response is the major quality metric for query processing in the real-time applications of Wireless Sensor Networks (WSNs). The structure of the query routing tree directly affects the whole query processing delay as it provides the path to forward a query to the relevant nodes and return the response to the sink. In the current literature, query routing structure is designed irrespective of the variation in query loads among the sensors. As a consequence, current schemes do not guarantee for the routing tree to provide a faster path to the sensors with higher query load. This motivates the current work to consider query load in constructing and self-reconfiguring the routing tree. In this paper, we present a query load-based spanning tree construction method that reduces the query response delay as well as energy consumption in query execution and provides query response with the best possible accuracy. Simulation results illustrate the efficacy of the proposed framework.

Authors: Pervin, Shaila , Kamruzzaman, Joarder , Karmakar, Gour , Azad, Arman
Date: 2011
Type: Text , Conference paper
Relation: 2011 IEEE International Conference on Communications, ICC 2011; Kyoto, Japan; 5th-9th June 2011 p. 1-6
Full Text: false
Reviewed:
Description: Existing in-network query processing techniques are categorized as approximation and aggregation based approaches, where the former achieves lower network traffic at the expense of query response accuracy, whereas the later reduces query response inaccuracy by executing queries at the actual sensor nodes which necessitates the overhead of query specific sensor selection mechanism. In this paper, we propose a hybrid query processing framework that combines the advantages of both the approximation and aggregation based techniques and avoids their limitations. In our approach, we construct a hierarchical probabilistic data model representing the overall sensor data characteristics across the network, which is query independent and is later used for selecting sensor nodes to process user queries. Experimental results illustrate the efficacy of the proposed framework compared to contemporary approximation and aggregation based query processing techniques.

Authors: Pervin, Shaila , Kamruzzaman, Joarder , Karmakar, Gour
Date: 2011
Type: Text , Conference paper
Relation: 10th IEEE International Symposium on Network Computing and Applications, NCA 2011; Cambridge, United States; 25th-27th August 2011 p. 354-358
Full Text: false
Reviewed:
Description: Existing in-network query processing techniques are categorized as approximation and aggregation based approaches. The former achieves lower query response delay at the expense of accuracy, while the latter reduces query response inaccuracy by executing queries at the actual sensor nodes resulting in longer delay. In this paper, we propose a query processing framework which is delay as well as accuracy aware and capable of dynamic adjustment to meet user/application requirements. When query response is required within specific delay, it provides approximated sensor data meeting the delay requirement. On the other hand, when query response accuracy is vital, it tolerates longer delay in acquiring response with the desired accuracy. To achieve this, we propose a novel method of constructing a delay aware spanning tree (DAST) based on query load and organizing sensor data with varied accuracy. Experimental results illustrate superiority of the proposed framework against competing approaches.

Authors: Azad, Arman , Kamruzzaman, Joarder , Srinivasan, Bala , Alam, K. , Pervin, Shaila
Date: 2010
Type: Text , Conference paper
Relation: Second International Conference on Advances in Future Internet p. 75-81
Full Text: false
Reviewed:
Description: The wireless networked sensors embedded with everyday objects will become an integral part of Future Internet, where the interaction among people, computer and those objects will shift the current Internet to a new paradigm, namely the Internet of Things. The terabyte torrent of data generated by billions of sensors belonging to a large number of distributed heterogeneous sensor networks in Future Internet will only be valuable if they can be effectively used on purpose, which leads to the necessity of an Internet scale query processing framework. In this paper, firstly, we focus on the distinct challenges present in Internet scale query processing over distributed sensor networks. Then, we propose a flexible and scalable system architecture capable of handling the complex scenario that might arise from the integration of a large number of such networks in Future Internet. Finally, we discuss the overall query processing methodology over such system and present some directions on the possible solutions to a number of identified research challenges. The outcome of this paper would foster the sensor network research in Future Internet domain

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