Search

This paper focuses on the event-triggered zero-gradient-sum algorithms for a distributed convex optimization problem over directed networks. The communication process is driven by trigger conditions monitored by nodes. The proposed trigger conditions are decentralized and just depend on each node’s own state. In the continuous-time case, we propose an algorithm based on a sample-based monitoring scheme. In the discrete-time case, we propose a new event-triggered zero-gradient-sum algorithm which is suitable for more general network models. It is proved that two proposed event-triggered algorithms are exponentially convergent if the design parameters are chosen properly and the network topology is strongly connected and weight-balanced. Finally, we illustrate the advantages of the proposed algorithms by numerical simulation. [ABSTRACT FROM AUTHOR]

An x-star network is an information network which consists of centers with connections among themselves, and different type attributes linking to these centers. As x-star networks become ubiquitous, extracting knowledge from x-star networks has become an important task. Similarity search in x-star network aims to find the centers similar to a given query center, which has numerous applications including collaborative filtering, community mining and web search. Although existing methods yield promising similar results, such as SimRank and P-Rank, they are not applicable for massive x-star networks. In this paper, we propose a structural-based similarity measure, NetSim, towards efficiently computing similarity between centers in an x-star network. The similarity between attributes is computed in the pre-processing stage by the expected meeting probability over attribute network that is extracted from the whole structure of x-star network. The similarity between centers is computed online according to the attribute similarities based on the intuition that similar centers are linked with similar attributes. NetSim requires less time and space cost than existing methods since the scale of attribute network is significantly smaller than the whole x-star network. For supporting fast online query processing, we develop a pruning algorithm by building a pruning index, which prunes candidate centers that are not promising. Extensive experiments demonstrate the effectiveness and efficiency of our method through comparing with the state-of-the-art measures. [ABSTRACT FROM AUTHOR]

Computer generated holograms are often exploited to implement optical encryption schemes. This paper proposes the integration of dynamic visual cryptography (an optical technique based on the interplay of visual cryptography and time-averaging geometric moiré) with Gerchberg–Saxton algorithm. A stochastic moiré grating is used to embed the secret into a single cover image. The secret can be visually decoded by a naked eye if only the amplitude of harmonic oscillations corresponds to an accurately preselected value. The proposed visual image encryption scheme is based on computer generated holography, optical time-averaging moiré and principles of dynamic visual cryptography. Dynamic visual cryptography is used both for the initial encryption of the secret image and for the final decryption. Phase data of the encrypted image are computed by using Gerchberg–Saxton algorithm. The optical image is decrypted using the computationally reconstructed field of amplitudes. [ABSTRACT FROM AUTHOR]

Highlights: [•] An adaptive period sensing optimization scheme for cognitive radio is proposed. [•] Our scheme is based on a multi-objective genetic algorithm formulation. [•] We evaluated the sensing overhead, transmission opportunities and interference to PU. [•] Our scheme has a superior performance when compared to related literature. [•] It provides different levels of protection to PU communication. [ABSTRACT FROM AUTHOR]

Highlights: [•] We proposed prioritized proactive spectrum handoff decision schemes. [•] Proposed schemes are modeled using a preemptive resume priority (PRP) M/G/1 queue. [•] Handoff delay is reduced by the proposed schemes. [ABSTRACT FROM AUTHOR]

Highlights: [•] We introduce novel fault-tolerant architecture and efficient reconfiguration schemes. [•] We propose an efficient algorithm for producing maximum target arrays. [•] We develop an algorithm for optimizing communication performance of target arrays. [•] We provide an approach for calculating the theoretical maximum target array. [ABSTRACT FROM AUTHOR]

Abstract: In this paper, contention resolution scheme based on burst segmentation and deflection routing in the core node and composite burst assembly scheme at the edge node are proposed. In the core node, contention is resolved through incorporating prioritized burst segmentation with deflection routing scheme. The burst segmentation scheme allows the tail of original bursts or the head of contending bursts to be segmented. The segmented burst is scheduled on the optimum deflection path by deflection routing scheme. At the edge of the network, a composite burst assembly scheme combines packets of different classes into the same burst, placing the highest priority packets in the middle and low priority packets at the tail and the head of the burst. The priority lowers gradually from the middle of the burst to the ends. An analytical model is proposed to evaluate the contention resolution scheme through calculating packet loss probability and the normalized end-to-end delay. Results show that high-priority bursts have significantly lower packet loss probability and delay than low-priority. So the contention resolution scheme which incorporates burst segmentation with deflection routing tends to perform better than the scheme only with burst segmentation or deflection routing. [Copyright &y& Elsevier]