• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.2 no.2
• /
• pp.82-102
• /
• 2008

Packet losses tend to occur during short error bursts separated by long periods of relatively error-free transmission. There is also a significant spatial correlation in loss among the receiver nodes in a multicast session. To recover packet transmission errors at the transport layer, tree-based protocols construct a logical tree for error recovery before data transmission is started. The current tree construction scheme does not scale well because it overloads the sender node. We propose a scalable recovery tree construction scheme considering these properties. Unlike the existing tree construction schemes, our scheme distributes some tasks normally handled by the sender node to specific nodes acting as repair node distributors. It also allows receiver nodes to adaptively re-select their repair node when they experience unacceptable error recovery delay. Simulation results show that our scheme constructs the logical tree with reduced message and time overhead. Our analysis also indicates that it provides fast error recovery, since it can reduce the number of additional retransmissions from its upstream repair nodes or sender node.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.39A no.12
• /
• pp.756-763
• /
• 2014

In this paper, we introduce a new sparse signal recovery algorithm referred to as the matching pursuit with greedy tree search (GTMP). The tree search in our proposed method is implemented to minimize the cost function to improve the recovery performance of sparse signals. In addition, a pruning strategy is employed to each node of the tree for efficient implementation. In our performance guarantee analysis, we provide the condition that ensures the exact identification of the nonzero locations. Through empirical simulations, we show that GTMP is effective for sparse signal reconstruction and outperforms conventional sparse recovery algorithms.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.22 no.9
• /
• pp.1867-1879
• /
• 1997

DREAM-S is a distributed main-memory database system for the real-time processing of shared operational datra in ATM switching systems. DREAM-S has a client-server architecture in which only the server has the diskstorage, and provides the T-Tree index structure for efficient accesses to the data. We propose a recovery technique for the T-Tree index structre in DREAM-S. Although main-memory database system offer efficient access performance, the database int he main-memory may be broken when system failure such as database transaction failure or power failure occurs. Therfore, a recovery technique that recovers the database (including index structures) is essential for fault tolerant ATM switching systems. Proposed recovery technique relieves the bottleneck of the server processors disk operations by maintaining the T-Tree index structure only in the main-memory. In addition, fast recovery is guaranteed even in large number of client systems since the T-Tree index structure(s) in each system can be recovered cncurrently.

• Journal of Communications and Networks
• /
• v.18 no.5
• /
• pp.699-712
• /
• 2016

Recently, greedy algorithm has received much attention as a cost-effective means to reconstruct the sparse signals from compressed measurements. Much of previous work has focused on the investigation of a single candidate to identify the support (index set of nonzero elements) of the sparse signals. Well-known drawback of the greedy approach is that the chosen candidate is often not the optimal solution due to the myopic decision in each iteration. In this paper, we propose a tree search based sparse signal recovery algorithm referred to as the tree search matching pursuit (TSMP). Two key ingredients of the proposed TSMP algorithm to control the computational complexity are the pre-selection to put a restriction on columns of the sensing matrix to be investigated and the tree pruning to eliminate unpromising paths from the search tree. In numerical simulations of Internet of Things (IoT) environments, it is shown that TSMP outperforms conventional schemes by a large margin.

• Proceedings of the Korean Society of Broadcast Engineers Conference
• /
• 2015.11a
• /
• pp.51-53
• /
• 2015

In this paper, we propose an efficient sparse signal recovery algorithm referred to as the matching pursuit with a tree pruning (TMP). Two key ingredients of TMP are the pre-selection to put a restriction on columns of the sensing matrix to be investigated and the tree pruning to eliminate unpromising paths from the search tree. In our analysis, we show that the sparse signal is accurately reconstructed when the sensing matrix satisfies the restricted isometry property. In our simulations, we confirm that TMP is effective in recovering sparse signals and outperforms conventional sparse recovery algorithms.

• Proceedings of the KSR Conference
• /
• 1998.11a
• /
• pp.280-287
• /
• 1998

In this paper, Dynamic Fault Tree algorithm(DFT algorithm) is presented. This new algorithm provides a concise representation of dynamic fault tolerance system structure with redundancy, dynamic redundancy management and complex fault ＆ error recovery techniques. And it allows the modeler to define a dynamic fault tree model with the relative advantages of both fault tree and Markov models that captures the system structure and dynamic behavior. This algorithm applies to TMR and Dual-Duplex systems with the dynamic behavior and show that this algorithm captured the dynamic behavior in these systems with fault ＆ error recovery technique, sequence-dependent failures and the use dynamic spare. The DFT algorithm for solving the problems of the systems is more effective than the Markov and Fault tree analysis model.

• Korean Journal of Soil Science and Fertilizer
• /
• v.32 no.2
• /
• pp.132-139
• /
• 1999

A field experiment was conducted at Cheju from early March 1998 to early March 1999 to evaluate the effects of foliar applied urea on leaf N content and N recovery in satsuma mandarins (Citrus unshiu Marc.). Seven years old 'Okitsu Wase' trees received foliar spray of urea (22 or 43 g N $tree^{-1}yr^{-1}$) or soil application of urea (86 g N $tree^{-1}yr^{-1}$). 56% of N was applied in spring, 11% in summer and 33% in fall. There were seven trees per N treatment and two trees per N treatment received $^{15}N$-labeled urea in spring and summer to determine N recovery. There were no differences between the treatments for fruit yield and its quality. Nitrogen content of spring flush leaf blades up to early September was greater for trees received foliar spray comparing with soil application but was not greatly affected by any treatment after mid-November. The recovery of fertilizer N in various parts of trees receiving foliar spray of 22 g N $tree^{-1}yr^{-1}$ was greatest, followed by receiving foliar spray of 43 g N and soil application of 86 g N. The recovery of fertilizer N in tree was 29.2 and 17.7% for foliar spray of 22 and 43 g N $tree^{-1}yr^{-1}$, respectively and 8.0% for soil application of 86 g N $tree^{-1}yr^{-1}$. The recovery of fertilizer N in the upper 40 cm of soil was 50.3, 45.6, and 51.8% for foliar spray of 22 and 43 g N $tree^{-1}yr^{-1}$, and soil application of 86 g N $tree^{-1}yr^{-1}$ respectively. The total (tree, fallen leaves, winter weeds, and soil) recovery of fertilizer N was 81.8, 65.1, and 60.6% for foliar spray of 22 and 43 g N $tree^{-1}yr^{-1}$, and soil application of 86 g N $tree^{-1}yr^{-1}$, respectively.

• Proceedings of the Korean Society of Broadcast Engineers Conference
• /
• 2015.11a
• /
• pp.1-3
• /
• 2015

In this paper, we propose a sparse signal reconstruction method referred to as the matching pursuit with a pruning-based tree search (PTS-MP). Two key ingredients of PTS-MP are the pre-selection to put a restriction on columns of the sensing matrix to be investigated and the tree pruning to eliminate unpromising paths from the search tree. In our simulations, we confirm that PTS-MP is effective in recovering sparse signals and outperforms conventional sparse recovery algorithms.

• Journal of KIISE
• /
• v.43 no.11
• /
• pp.1233-1244
• /
• 2016

In the IoT network environments for LLNs(Low power and Lossy networks), IPv6 Routing Protocol for Low Power and Lossy networks(RPL) has been proposed by IETF(Internet Engineering Task Force). The goal of RPL is to create a directed acyclic graph, without loops. As recommended by the IETF standard, RPL route recovery mechanisms in the event of a failure of a node should avoid loop, loop detection, DIO Poisoning. In this process, route recovery time and control message might be increased in the sub-tree because of the repeated route search. In this paper, we suggested RPL route recovery method to solve the routing overhead problem in the sub-tree during a loss of a link in the RPL routing protocol based on IoT wireless networks. The proposed method improved local repair process by utilizing a route that could not be selected as the preferred existing parents. This reduced the traffic control packet, especially in the disconnected node's sub tree. It also resulted in a quick recovery. Our simulation results showed that the proposed RPL local repair reduced the recovery time and the traffic of control packets of RPL. According to our experiment results, the proposed method improved the recovery performance of RPL.

• Journal of KIISE:Databases
• /
• v.27 no.2
• /
• pp.216-226
• /
• 2000

This paper suggests a new access path, hashed B-tree which is an efficient access method for integrity checking. Hashed B-tree is based on the observation that most query patterns in enforcing integrity constraints are point queries. Hashed B-tree compresses the key by hashing procedure, which reduces the height of tree and results in fast node search. This method has the advantages such as it can be implemented easily and use the B-tree concurrency control and recovery algorithm with minor modifications.