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.
[Show abstract][Hide abstract] 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. DOI:10.1109/TMC.2007.70770 · 2.54 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Data replication has been well adopted in data intensive scientific applications to reduce data file transfer time and bandwidth consumption. However, the problem of data replication in Data Grids, an enabling technology for data intensive applications, has proven to be NP-hard and even non approximable, making this problem difficult to solve. Meanwhile, most of the previous research in this field is either theoretical investigation without practical consideration, or heuristics-based with little or no theoretical performance guarantee. In this paper, we propose a data replication algorithm that not only has a provable theoretical performance guarantee, but also can be implemented in a distributed and practical manner. Specifically, we design a polynomial time centralized replication algorithm that reduces the total data file access delay by at least half of that reduced by the optimal replication solution. Based on this centralized algorithm, we also design a distributed caching algorithm, which can be easily adopted in a distributed environment such as Data Grids. Extensive simulations are performed to validate the efficiency of our proposed algorithms. Using our own simulator, we show that our centralized replication algorithm performs comparably to the optimal algorithm and other intuitive heuristics under different network parameters. Using GridSim, a popular distributed Grid simulator, we demonstrate that the distributed caching technique significantly outperforms an existing popular file caching technique in Data Grids, and it is more scalable and adaptive to the dynamic change of file access patterns in Data Grids.
IEEE Transactions on Parallel and Distributed Systems 09/2011; 22(8-22):1299 - 1306. DOI:10.1109/TPDS.2010.207 · 2.17 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Data replication is an effective way to improve data accessibility in ad hoc networks because of the movement of hosts and the changing of network topology. A new data replication method called Hierarchical Replication Model (HRM) is proposed in this paper. This method selects mobile hosts as data replicas holders taking into account not only data access frequencies and network topology, but also link bandwidth and remaining amount of batteries of hosts. This method groups the network into three hierarchies to improve the data accessibility, and it speeds up the data transmission and increase the data accessing efficiency at the same time. Furthermore, simulation results verify the effectiveness of this method.
Data provided are for informational purposes only. Although carefully collected, accuracy cannot be guaranteed. The impact factor represents a rough estimation of the journal's impact factor and does not reflect the actual current impact factor. Publisher conditions are provided by RoMEO. Differing provisions from the publisher's actual policy or licence agreement may be applicable.