Web-based social networking is increasingly gaining popularity due to the rapid development of computer networking technologies. However, social networking applications still cannot obtain a wider acceptance by many u...
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Web-based social networking is increasingly gaining popularity due to the rapid development of computer networking technologies. However, social networking applications still cannot obtain a wider acceptance by many users due to some unresolved issues, such as trust, security, and privacy. In social networks, trust is mainly studied whether a remote user behaves as expected by an interested user via other users, who are respectively named trustee, trustor, and recommenders. A trust graph consists of a trustor, a trustee, some recommenders, and the trust relationships between them. In this paper, we propose a novel FlowTrust approach to model a trust graph with network flows, and evaluate the maximum amount of trust that can flow through a trust graph using network flow theory. FlowTrust supports multi-dimensional trust. We use trust value and confidence level as two trust factors. We deduce four trust metrics from these two trust factors, which are maximum flow of trust value, maximum flow of confidence level, minimum cost of uncertainty with maximum flow of trust, and minimum cost of mistrust with maximum flow of confidence. We also propose three FlowTrust algorithms to normalize these four trust metrics. We compare our proposed FlowTrust approach with the existing RelTrust and CircuitTrust approaches. We show that all three approaches are comparable in terms of the inferred trust values. Therefore, FlowTrust is the best of the three since it also supports multi-dimensional trust.
In the paper a single machine time-dependent scheduling problem is considered. The processing time p(j) of each job is described by a function of the starting time t of the job, p(j) = 1 + alpha(j)t, where the job det...
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In the paper a single machine time-dependent scheduling problem is considered. The processing time p(j) of each job is described by a function of the starting time t of the job, p(j) = 1 + alpha(j)t, where the job deterioration rate alpha(j) >= 0 for j = 0, 1,..., n and t >= 0. Jobs are nonpreemptable and independent, there are no ready times and no deadlines. The criterion of optimality of a schedule is the total completion time. First, the notion of a signature for a given sequence of job deterioration rates is introduced, two types of the signature are defined and their properties are shown. Next, on the basis of these properties a greedy polynomial-time approximation algorithm for the problem is formulated. This algorithm, starting from an initial sequence, iteratively constructs a new sequence concatenating the previous sequence with new elements, according to the sign of one of the signatures of this sequence. Finally, these results are applied to the problem with job deterioration rates which are consecutive natural numbers, alpha(j) = j for j = 0, 1,..., n. Arguments supporting the conjecture that in this case the greedy algorithm is optimal are presented. (c) 2006 Elsevier B.V. All rights reserved.
As a multivariate generalization of the univariate median, projection depth median (PM) is unique, and enjoys a very high breakdown point, much higher than its affine equivariant competitors such as halfspace depth me...
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As a multivariate generalization of the univariate median, projection depth median (PM) is unique, and enjoys a very high breakdown point, much higher than its affine equivariant competitors such as halfspace depth median. Nevertheless, its computation is challenging. Until now PM can only be exactly computed efficiently for bivariate data. In this article, we develop an algorithm to approximate PM in higher dimensions. Some data examples indicate that the proposed algorithm performs well in terms of both accuracy and efficiency. As an application, we investigate the finite sample relative efficiency of PM by utilizing the Matlab implementation of this algorithm.
Given an edge-distance graph of a set of suppliers and clients, the bottleneck problem is to assign each client to a selected supplier minimizing their maximum distance. We introduce minimum quantity commitments to ba...
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Given an edge-distance graph of a set of suppliers and clients, the bottleneck problem is to assign each client to a selected supplier minimizing their maximum distance. We introduce minimum quantity commitments to balance workloads of suppliers, provide the best possible approximation algorithm, and study its generalizations and specializations. (c) 2005 Wiley Periodicals, Inc.
In this paper, we study the problem of discovering a timeline of events in a temporal network. We model events as dense subgraphs that occur within intervals of network activity. We formulate the event discovery task ...
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In this paper, we study the problem of discovering a timeline of events in a temporal network. We model events as dense subgraphs that occur within intervals of network activity. We formulate the event discovery task as an optimization problem, where we search for a partition of the network timeline into k non-overlapping intervals, such that the intervals span subgraphs with maximum total density. The output is a sequence of dense subgraphs along with corresponding time intervals, capturing the most interesting events during the network lifetime. A naive solution to our optimization problem has polynomial but prohibitively high running time. We adapt existing recent work on dynamic densest subgraph discovery and approximate dynamic programming to design a fast approximation algorithm. Next, to ensure richer structure, we adjust the problem formulation to encourage coverage of a larger set of nodes. This problem is NP-hard;however, we show that on static graphs a simple greedy algorithm leads to approximate solution due to submodularity. We extend this greedy approach for temporal networks, but we lose the approximation guarantee in the process. Finally, we demonstrate empirically that our algorithms recover solutions with good quality.
To solve the multi-dimensional event based query in wireless sensor networks, this paper proposes four bloom filter based query processing algorithms UBP, BBP, SRBP and PBP. The four algorithms proposed can be classif...
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To solve the multi-dimensional event based query in wireless sensor networks, this paper proposes four bloom filter based query processing algorithms UBP, BBP, SRBP and PBP. The four algorithms proposed can be classified into two classes: two bloom filter based precise algorithms, which are UBP and BBP, and two bloom filter based approximate algorithms, which are SRBP and PBP. By using the bloom filter and introducing the inaccuracy, the communication cost involved by the query processing can be reduced. For the two precise algorithms UBP and BBP, simulation results show that UBP consumes 51% less energy than BBP on average. UBP is better than BBP on energy consumption. For energy consumption comparison between the approximate algorithms and the precise algorithm UBP, simulation results show that SRBP consumes 18% less energy than UBP on average as while as PBP consume approximately the same energy as UBP on average. For query accuracy comparison between the approximate algorithms and the precise algorithm UBP, simulation results show that the average relative error between UBP and PBP is 14% and the average relative error between UBP and SRBP is 2%. SRBP is better than PBP on energy consumption and query accuracy respectively. UBP and SRBP are two preferred bloom filter based query processing algorithms. (C) 2013 Elsevier Ltd. All rights reserved.
作者：
DOBSON, GUniv of Rochester
Graduate Sch of Management Rochester NY USA Univ of Rochester Graduate Sch of Management Rochester NY USA
A worst-case analysis is given for the LPT (longest processing time) heuristic applied to the problem of scheduling independent tasks on uniform processors. A bound of 1912</span
A worst-case analysis is given for the LPT (longest processing time) heuristic applied to the problem of scheduling independent tasks on uniform processors. A bound of 1912
Fault diagnosis plays an important role on stable applications maintaining in wireless sensor networks (WSNs). Most existing researchers are concerned about the statics nodes-based diagnosis techniques, which are inco...
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Fault diagnosis plays an important role on stable applications maintaining in wireless sensor networks (WSNs). Most existing researchers are concerned about the statics nodes-based diagnosis techniques, which are incompetent to cope with those dynamically occurring faults. In this paper, we propose a novel mechanism isolating fault (IF) nodes that employs the mobile node as a scanner to diagnose the faults in WSNs. The mobile scanner can detect the fault nodes within its communication region by using sniffer. It can also control the transmitting route of nodes by modifying their links. Starting from the base station, the mobile scanner periodically selects and visits all monitoring stations and consequently explores all static nodes in the monitoring area. After detecting a fault node, the mobile scanner will prevent it from connecting to the other normal nodes. We aim at finding the least number of monitoring stations and discovering an optimal route. We first formulate the two research issues to hitting set problem and travel salesperson problem. We then solve these two nondeterministic polynomial time hard problems by proposing an approximate algorithm, weighted, and hierarchical IF, which only uses local information. The mobile scanner makes a decision by weighing both the significance and the priority of nodes level by level. The proposed mechanism IF maintains the stabile service of WSNs in a transparent manner. The simulation results show that our algorithm can effectively isolate fault nodes, alleviate the damages of network corrupting, and hence increase the resilience of WSNs. Copyright (c) 2013 John Wiley & Sons, Ltd.
Link quality is important and can greatly affect the performance of wireless transmission algorithms and protocols. Currently, researchers have proposed a variety of approaches to implement link quality estimation. Ho...
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Link quality is important and can greatly affect the performance of wireless transmission algorithms and protocols. Currently, researchers have proposed a variety of approaches to implement link quality estimation. However, the estimated result of link quality is not accurate enough and the error is large, so they may lead to the failure of routing algorithm and protocol. In this paper, a novel method is proposed to achieve the more accurate estimation of link quality than before. This method employs Bernoulli sampling-based algorithm to complete the estimation of link quality. The problem is modeled as calculation of estimators based on Bernoulli sampling data. The authors further prove that the calculation results are accurate by probability theory. Furthermore, according to link quality estimation, the authors also provide a centralized routing algorithm and a distributed improvement algorithm in order to switch the data transmission on the better quality link. Finally, the extensive experiment results indicate that the proposed methods obtain high performance in terms of energy consumption and accuracy.
In this paper, we study a machine scheduling problem with job transportation coordination. The orders including different amount of the same product will be delivered to their customers after being completed on a sing...
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In this paper, we study a machine scheduling problem with job transportation coordination. The orders including different amount of the same product will be delivered to their customers after being completed on a single machine and each order has a delivery due date which is promised by the manufacturer to its customer. A third-party logistics provider picks up the finished orders at the end of each day and charges each order a delivery cost, which is linearly decreasing with the delivery time and linearly increasing with its quantity. The goal is to find a schedule minimizing total delivery cost under the constraint that all the orders are delivered to the customers before the due dates. The problem is strongly NP-hard. We propose an improved approximate algorithm with worst-case ratio of , which improves the existing one with worst-case ratio of .
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