Clustering problem is one of the hottest issues in wireless sensor networks (WSNs). The strategy for selection of cluster head has not been sufficiently investigated. In this paper,we propose a hormone-based clusterin...
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Clustering problem is one of the hottest issues in wireless sensor networks (WSNs). The strategy for selection of cluster head has not been sufficiently investigated. In this paper,we propose a hormone-based clustering algorithm (HCA) inspired by the communication mechanism of bioendocrine system to prolong the lifetime of the sensor nodes. Two kinds of hormones,cluster hormone and member hormone,are used in the algorithm. Hormone message can promote a node to become a cluster head or a member node. Comparative experiment shows that the proposed algorithm has effectively prolong the lifetime of WSN compared with LEACH[1] and HEED[2].
Interactive population-based incremental learning (IPBIL) is an effective method to solve optimization problems with implicit performance indices. It can significantly reduce user fatigue compared with interactive evo...
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ISBN:
(纸本)9781424463473
Interactive population-based incremental learning (IPBIL) is an effective method to solve optimization problems with implicit performance indices. It can significantly reduce user fatigue compared with interactive evolutionary computation (IEC). However,each run of IPBIL can only find one solution or some similar solutions. Thus it is not suitable for multimodal optimization problems with implicit performance indices. To solve this problem,we propose an IPBIL with multiple probability vectors (IPBIL-MPV) in this work. The key idea is to utilize multiple probability vectors to catch different search directions and thus find more than one solutions. We perform a subjective experiment in which IPBIL-MPV is applied to a fashion design problem. The experimental results show that IPBIL-MPV can find several distinct solutions in a run. Thus it is an effective method to solve multimodal optimization problems with implicit performance indices.
This paper proposes an emotional harmony composition system using a series of predefined rules and interactive genetic algorithm. Two kinds of rules are defined: One is harmony composition rules used for composing har...
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This paper proposes an emotional harmony composition system using a series of predefined rules and interactive genetic algorithm. Two kinds of rules are defined: One is harmony composition rules used for composing harmony and the other is harmony emotion rules which may indicate the mapping between harmonic elements and a specific emotion of either happiness or sadness. Interactive genetic algorithm is applied to incorporate users' subjective perception in the generated harmony. Both subjective and objective experiments are conducted to prove the effectiveness of our approach.
Buffer overflow (BOF) is one of the major vulnerabilities that lead to non-secure software. Testing an implementation for BOF vulnerabilities is challenging as the underlying reasons of buffer overflow vary widely. Th...
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One of the main objective of spectrum sensing is to detect spectrum opportunity quickly and accurately. Both of the two aspects can be improved by hardware upgrading and software optimization. In this paper, we concen...
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We present a novel method of Object-Oriented test case generation based on UML state diagrams and Label Transition System (LTS). The procedure is based on model-based testing techniques with test cases generated from ...
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We investigate the evolutionary prisoner's dilemma game (PDG) on weighted Newman-Watts (NW) networks. In weighted NW networks, the link weight ωij is assigned to the link between the nodes i and j as: ωij = (...
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We investigate the evolutionary prisoner's dilemma game (PDG) on weighted Newman-Watts (NW) networks. In weighted NW networks, the link weight ωij is assigned to the link between the nodes i and j as: ωij = (ki · kj)^β, where ki(kj) is the degree of node i(j) and β represents the strength of the correlations. Obviously, the link weight can be tuned by only one parameter β. We focus on the cooperative behavior and wealth distribution in the system. Simulation results show that the cooperator frequency is promoted by a large range of β and there is a minimal cooperation frequency around β = -1. Moreover, we also employ the Gini coefficient to study the wealth distribution in the population. Numerical results show that the Gini coefficient reaches its minimum when β≈ -1. Our work may be helpful in understanding the emergence of cooperation and unequal wealth distribution in society.
The security problem for Peer-to-peer (P2P) systems has been gradually recognized as an important topic of P2P applications. Among existing solution for P2P security, how to establish trust relationship among peers is...
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The security problem for Peer-to-peer (P2P) systems has been gradually recognized as an important topic of P2P applications. Among existing solution for P2P security, how to establish trust relationship among peers is a key problem in demand. This paper proposes a novel dynamical trust construction schema based on fuzzy decision and Extended automated trust negotiation (EATN). The presented approach adopts fuzzy trust graph to describe the trust information in the P2P systems. Trust relationship among peers can be constructed by the combination of the fuzzy trust graph, fuzzy path search algorithm and EATN. The relevant application case indicates the schema is feasible. The simulations also show that the presented schema can improve the interactive success ratio by enhancing the trust relationship in the P2P systems.
software testing is an effective way to find software errors. Generating a good test suite is the key. A program invariant is a property that is true at a particular program point or points. The property could reflect...
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software testing is an effective way to find software errors. Generating a good test suite is the key. A program invariant is a property that is true at a particular program point or points. The property could reflect the program's execution over a test suite. Based on this point, we integrate the random test case generation technique and the invariant extraction technique, achieving automatic test case generation and selection. With the same invariants, compared with the traditional random test case generation technique, the experimental results show that the approach this paper describes can generate a smaller test suite.
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