Distributed Storage Schemes for Controlling Data Availability in Wireless Sensor Networks.
ABSTRACT The high unreliability of sensor nodes decreases the data availability. The replica management systems can provide very high data availability in the distributed systems. Due to energy limitations, the biggest challenge is the placement and management of replicas in the sensor networks. This paper addresses the problem of introducing sufficient redundancy with minimal communication cost to a network such that the entire network data can be retrieved after a failure. We formalize the replica placement problem and using failure models, give the optimal placement equation. Because the optimal placement equation is the 0-1 integer program problem which generally is very difficult to solve, we simplify the optimization equation by implicit enumeration method. The proposed data distribute scheme reduces the communication cost and ensure data availability in wireless sensor networks.
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Conference Paper: A replication strategy based on swarm intelligence in spatial data grid[Show abstract] [Hide abstract]
ABSTRACT: In the spatial data grid, the distribution of query and the data is unevenly some resource become hotspot and the hotspots are changing over time, which may cause the global load unbalanced, this dynamic problem becomes a key challenge in Data Grid. Data replication is a way to deal with this problem, which improves data availability, reduces latency and increases throughput. In this paper, we present a new replication approach which is adaptive, completely decentralized, and based on swarm intelligence which is intrinsically a bottom-up approach. Every site in the grid system has a single agent, which is serving as containers for data, following simple rules of behavior and without knowing any global information. The strategy that agents follow includes which data to create replica and where the replica is locating. The local interactions and simple action between agents give a fairly optimal replication location solution globally. We carried the experiments using OptorSim for the EU Data Grid Testbed 1. Experimental results show that our approach performs better than No replication and when the scale of jobs is big, our method will outperform the Economic Model, but the space consumption is proportional.Geoinformatics, 2010 18th International Conference on; 07/2010
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ABSTRACT: Storage of sensed data in wireless sensor networks is essential when the sink node is unavailable due to failure and/or disconnections, but it can also provide efficient access to sensed data to multiple sink nodes. Recent approaches to data storage rely on Geographic Hash Tables for efficient data storage and retrieval. These approaches however do not support different QoS levels for different classes of data as the programmer has no control on the level of redundancy of data. They result in a great unbalance in the storage usage in each sensor, even when sensors are uniformly distributed. This may cause serious data losses, waste energy and shorten the overall lifetime of the sensornet. In this paper, we propose a novel protocol, Q- NiGHT, which (1) provides a direct control on the level of QoS in the data dependability, and (2) uses a strategy similar to the rejection method to build a hash function which scatters data approximately with the same distribution of sensors. The benefits of Q-NiGHT are assessed through a detailed simulation experiment, also discussed in the paper. Results show its good performance on different sensors distributions on terms of both protocol costs and load balance between sensors.8th International Conference on Mobile Data Management (MDM 2007), Mannheim, Germany, May 7-11, 2007; 01/2007
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ABSTRACT: Data caching can significantly improve the efficiency of information access in a wireless ad hoc network by reducing the access latency and bandwidth usage. However, designing efficient distributed caching algorithms is nontrivial when network nodes have limited memory. In this article, we consider the cache placement problem of minimizing total data access cost in ad hoc networks with multiple data items and nodes with limited memory capacity. The above optimization problem is known to be NP-hard. Defining benefit as the reduction in total access cost, we present a polynomial-time centralized approximation algorithm that provably delivers a solution whose benefit is at least 1/4 (1/2 for uniform-size data items) of the optimal benefit. The approximation algorithm is amenable to localized distributed implementation, which is shown via simulations to perform close to the approximation algorithm. Our distributed algorithm naturally extends to networks with mobile nodes. We simulate our distributed algorithm using a network simulator (ns2) and demonstrate that it significantly outperforms another existing caching technique (by Yin and Cao ) in all important performance metrics. The performance differential is particularly large in more challenging scenarios such as higher access frequency and smaller memory.IEEE Transactions on Mobile Computing 04/2008; 7(3):289-304. · 2.40 Impact Factor