scholarly journals Random Walk Based Key Nodes Discovery in Opportunistic Networks

2016 ◽  
Vol 12 (03) ◽  
pp. 28
Author(s):  
Qin Qin ◽  
Yong-qiang He
Keyword(s):  
Random Walk ◽  
Binary Tree ◽  
Opportunistic Networks ◽  
Communication Cost ◽  
Simulation Experiments ◽  
Efficiency And Effectiveness ◽  
Iteration Number ◽  
Key Nodes

In opportunistic networks, temporary nodes choose neighbor nodes to forward messages while communicating. However, traditional forward mechanisms don’t take the importance of nodes into consideration while forwarding. In this paper, we assume that each node has a status indicating its importance, and temporary nodes choose the most important neighbors to forward messages. While discovering important neighbors, we propose a binary tree random walk based algorithm. We analyze the iteration number and communication cost of the proposed algorithm, and they are much less than related works. The simulation experiments validate the efficiency and effectiveness of the proposed algorithm.

scholarly journals Fault-tolerant communication topology management based on minimum cost arborescence for leader–follower UAV formation under communication faults

2017 ◽  
Vol 14 (2) ◽  
pp. 172988141769396 ◽  
Author(s):  
Guoqiang Wang ◽  
He Luo ◽  
Xiaoxuan Hu ◽  
Huawei Ma ◽  
Shanlin Yang
Keyword(s):  
Graph Theory ◽  
Fault Tolerant ◽  
Minimum Cost ◽  
Formation Flight ◽  
Communication Cost ◽  
Topology Management ◽  
Simulation Experiments ◽  
Communication Topology ◽  
Aerial Vehicle ◽  
Management Method

A novel fault-tolerant communication topology management method for the leader–follower unmanned aerial vehicle (UAV) formation is proposed to minimize the formation communication cost while keeping the formation shape, even in the case of communication faults during the formation flight. This method is based on Edmonds’ algorithm for the minimum cost arborescence problem in graph theory. When a formation shape is given before the formation flight, this method can get the optimal initial communication topology with the minimum formation communication cost for keeping the formation shape. When some communication faults occur during the formation flight, which will cause the formation shape cannot be kept, this method can reconfigure the communication topology in time to guarantee the safety of all UAVs and recover the formation shape, and then it can reoptimize the communication topology by UAV position reconfiguration in the formation shape to minimize the formation communication cost for continuously keeping the formation shape. The effectiveness of this method is demonstrated through several simulation experiments.

Asymptotic distribution theory for Hoare's selection algorithm

1996 ◽  
Vol 28 (1) ◽  
pp. 252-269 ◽  
Author(s):  
Rudolf Grübel ◽  
Uwe Rösler
Keyword(s):  
Stochastic Process ◽  
Random Walk ◽  
Asymptotic Behaviour ◽  
Asymptotic Distribution ◽  
Random Environment ◽  
Binary Tree ◽  
Selection Algorithm ◽  
Real Numbers ◽  
Asymptotic Distribution Theory ◽  
Path Lengths

We investigate the asymptotic behaviour of the distribution of the number of comparisons needed by a quicksort-style selection algorithm that finds the lth smallest in a set of n numbers. Letting n tend to infinity and considering the values l = 1, ···,n simultaneously we obtain a limiting stochastic process. This process admits various interpretations: it arises in connection with a representation of real numbers induced by nested random partitions and also in connection with expected path lengths of a random walk in a random environment on a binary tree.

THE BIRTH AND DEATH PROCESSES OF HYPERCYCLE SPIRALS

2003 ◽  
Vol 06 (04) ◽  
pp. 515-535
Author(s):  
KAZUMASA OIDA
Keyword(s):  
Brownian Motion ◽  
Random Walk ◽  
Phase Synchronization ◽  
Occurrence Rate ◽  
Two Dimensional ◽  
Archimedean Spiral ◽  
Simulation Experiments ◽  
Birth And Death Processes ◽  
Long Time ◽  
Random Walk Simulation

The behavior of hypercycle spirals in a two-dimensional cellular automaton model is analyzed. Each spiral can be approximated by an Archimedean spiral with center, width, and phase change according to Brownian motion. A barrier exists between two spirals if the phase synchronization hypothesis is taken into account, and the occurrence rate of pair decay (simultaneous disappearance of two spirals) can be explained through a random walk simulation with the barrier. Simulation experiments show that adjacent species violation is necessary to create new spirals. A hypercycle system can live for a long time if spirals in the system are somewhat unstable, since new spirals cannot emerge when existing spirals are too stable.

LOC algorithm

2014 ◽  
Vol 10 (4) ◽  
pp. 481-496 ◽  
Author(s):  
Sardar Kashif Ashraf Khan ◽  
Jonathan Loo ◽  
Aboubaker Lasebae ◽  
Muhammad Awais Azam ◽  
Muhammad Adeel ◽  
...  
Keyword(s):  
Ad Hoc ◽  
Opportunistic Networks ◽  
Communication Cost ◽  
Destination Node ◽  
Data Sets ◽  
Message Delivery ◽  
Movement Model ◽  
Content Type ◽  
Mobility Data ◽  
Working Day

Purpose – This paper aims to propose an algorithm, location-aware opportunistic content forwarding (LOC), to improve message directivity using direction vectors in opportunistic networks. The LOC is based on the assumption that if approximate location of the destination node is known, then overall message delivery and cost can be improved. Efficient message delivery with low communication cost is a major challenge in current opportunistic networks. In these networks, nodes do not have prior knowledge of their recipients, and message forwarding can be achieved by selecting suitable forwarder based on some forwarding criteria, as compared to its ancestor mobile ad hoc networks. Design/methodology/approach – In this paper, the authors tested LOC in two sets of mobility models, synthetic movement model and real mobility data sets. In the first set, working day movement is used as synthetic movement model, where proposed algorithm is compared against Lobby Influence (LI) and Epidemic algorithms. In the second set of experiments, the new algorithm is tested in three mobility data sets, namely, Cambridge, Reality and Sassy, and results compared against LI algorithm. The reason of using various movement models is to establish strengths and weaknesses of the proposed algorithm in different scenarios. Findings – The experimental results show that the new algorithm performed extremely well in different scenarios, not only in terms of overall message delivery but also successfully managed to reduce the communication cost. Originality/value – The new contribution increases the overall energy and storage efficiency of nodes by targeting relevant forwarding nodes in the network.

scholarly journals Energy-Efficientβ-Approximate Skylines Processing in Wireless Sensor Networks

2015 ◽  
Vol 2015 ◽  
pp. 1-11 ◽  
Author(s):  
Junchang Xin ◽  
Zhiqiong Wang ◽  
Mei Bai ◽  
Linlin Ding ◽  
Guoren Wang
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Energy Efficient ◽  
Synthetic Data ◽  
Communication Cost ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Skyline Query ◽  
Sensing Applications ◽  
Efficiency And Effectiveness

As the first priority of query processing in wireless sensor networks is to save the limited energy of sensor nodes and in many sensing applications a part of skyline result is enough for the user’s requirement, calculating the exact skyline is not energy-efficient relatively. Therefore, a new approximate skyline query,β-approximate skyline query which is limited by a guaranteed error bound, is proposed in this paper. With an objective to reduce the communication cost in evaluatingβ-approximate skyline queries, we also propose an energy-efficient processing algorithm using mapping and filtering strategies, named Actual Approximate Skyline (AAS). And more than that, an extended algorithm named Hypothetical Approximate Skyline (HAS) which replaces the real tuples with the hypothetical ones is proposed to further reduce the communication cost. Extensive experiments on synthetic data have demonstrated the efficiency and effectiveness of our proposed approaches with various experimental settings.

scholarly journals SCR-CC: A Novel Sensing Clustering Routing Algorithm Based on Collaborative Computing in Heterogeneous Sensor Networks

2021 ◽  
Vol 2021 ◽  
pp. 1-19
Author(s):  
Zeyu Sun ◽  
Guisheng Liao ◽  
Zhiguo Lv ◽  
Guozeng Zhao ◽  
Chuanfeng Li
Keyword(s):  
Network Lifetime ◽  
Data Transmission ◽  
Routing Algorithm ◽  
Base Station ◽  
Expected Value ◽  
Collaborative Computing ◽  
Simulation Experiments ◽  
Heterogeneous Sensor Networks ◽  
Efficiency And Effectiveness ◽  
Entire Network

In order to better improve the reliability of data transmission and extend the network lifetime, the paper proposes the Sensing Clustering Routing Algorithm Based on Collaborative Computing (SCR-CC). The proposed algorithm uses the characteristics of the perceptual radius, which obey the normal distribution, and gives the process of completing the expected value of the data transmission of any two nodes in the cluster. Secondly, the paper analysed the necessary conditions of the existence for the expected value of the number of neighbour nodes when the redundant nodes are closed and the working nodes meet arbitrary differences. Thirdly, the cluster angle formed by the base station and the cluster is used to optimize the clustering structure and complete the dynamic clustering process to achieve the energy balance of the entire network. Finally, the simulation experiments show that the proposed SCR-CC algorithm compared with the other three algorithms reduces the number of failed nodes by 11.37% on average and increases the network lifetime by 27.09% on average; therefore, the efficiency and effectiveness of the SCR-CC algorithm are verified.

scholarly journals FACC: A Novel Finite Automaton Based on Cloud Computing for the Multiple Longest Common Subsequences Search

2012 ◽  
Vol 2012 ◽  
pp. 1-17 ◽  
Author(s):  
Yanni Li ◽  
Yuping Wang ◽  
Liang Bao
Keyword(s):  
Data Mining ◽  
Cloud Computing ◽  
Finite Automaton ◽  
High Performance ◽  
Cost Effective ◽  
Amino Acid Sequences ◽  
Matched Pairs ◽  
Simulation Experiments ◽  
Longest Common Subsequences ◽  
Efficiency And Effectiveness

Searching for the multiple longest common subsequences (MLCS) has significant applications in the areas of bioinformatics, information processing, and data mining, and so forth, Although a few parallel MLCS algorithms have been proposed, the efficiency and effectiveness of the algorithms are not satisfactory with the increasing complexity and size of biologic data. To overcome the shortcomings of the existing MLCS algorithms, and considering that MapReduce parallel framework of cloud computing being a promising technology for cost-effective high performance parallel computing, a novel finite automaton (FA) based on cloud computing called FACC is proposed under MapReduce parallel framework, so as to exploit a more efficient and effective general parallel MLCS algorithm. FACC adopts the ideas of matched pairs and finite automaton by preprocessing sequences, constructing successor tables, and common subsequences finite automaton to search for MLCS. Simulation experiments on a set of benchmarks from both real DNA and amino acid sequences have been conducted and the results show that the proposed FACC algorithm outperforms the current leading parallel MLCS algorithm FAST-MLCS.

scholarly journals A Cuckoo Search Algorithm Using Improved Beta Distributing and Its Application in the Process of EDM

Crystals ◽  
2021 ◽  
Vol 11 (8) ◽  
pp. 916
Author(s):  
Dili Shen ◽  
Wuyi Ming ◽  
Xinggui Ren ◽  
Zhuobin Xie ◽  
Yong Zhang ◽  
...  
Keyword(s):  
Random Walk ◽  
Beta Distribution ◽  
Cuckoo Search ◽  
Scale Factor ◽  
Test Functions ◽  
Benchmark Test ◽  
Iteration Number ◽  
Benchmark Test Functions ◽  
Single Objective ◽  
Better Than

Lévy flights random walk is one of key parts in the cuckoo search (CS) algorithm to update individuals. The standard CS algorithm adopts the constant scale factor for this random walk. This paper proposed an improved beta distribution cuckoo search (IBCS) for this factor in the CS algorithm. In terms of local characteristics, the proposed algorithm makes the scale factor of the step size in Lévy flights showing beta distribution in the evolutionary process. In terms of the overall situation, the scale factor shows the exponential decay trend in the process. The proposed algorithm makes full use of the advantages of the two improvement strategies. The test results show that the proposed strategy is better than the standard CS algorithm or others improved by a single improvement strategy, such as improved CS (ICS) and beta distribution CS (BCS). For the six benchmark test functions of 30 dimensions, the average rankings of the CS, ICS, BCS, and IBCS algorithms are 3.67, 2.67, 1.5, and 1.17, respectively. For the six benchmark test functions of 50 dimensions, moreover, the average rankings of the CS, ICS, BCS, and IBCS algorithms are 2.83, 2.5, 1.67, and 1.0, respectively. Confirmed by our case study, the performance of the ABCS algorithm was better than that of standard CS, ICS or BCS algorithms in the process of EDM. For example, under the single-objective optimization convergence of MRR, the iteration number (13 iterations) of the CS algorithm for the input process parameters, such as discharge current, pulse-on time, pulse-off time, and servo voltage, was twice that (6 iterations) of the IBCS algorithm. Similar, the iteration number (17 iterations) of BCS algorithm for these parameters was twice that (8 iterations) of the IBCS algorithm under the single-objective optimization convergence of Ra. Therefore, it strengthens the CS algorithm’s accuracy and convergence speed.

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