This paper presents an approach to simulate complex hierarchical process chains resulting from large logistics networks in OMNeT++, a discrete event simulation environment designed for communication networks. For this purpose OMNeT++ has been integrated as a new simulation engine into the ProC/B toolset which is designed for the analysis and optimization of large logistics networks. The paper h...

Community structure can be observed in many natural, biological and social networks. Studies suggest that these communities may have organized in a hierarchical manner while some communities overlap with others. This paper introduces an algorithm to detect such hierarchical and overlapping community structures in networks based on the concept of maximal cliques. It introduces an alternate modul...

This paper describes the concept of routing in wireless sensor networks. Routing algorithm provides reliable path from source to destination. Energy efficiency is main constraint in Wireless Sensor Networks. For improving life time and energy consumption various routing algorithms have been proposed. In this paper describe the hierarchical routing techniques. Hierarchical routing includes tree ...

Based on spiking neuron models and different receptive field models, hierarchical networks are proposed to process visual stimuli, in which multiple overlapped objects are represented by different orientation bars. The main purpose of this paper is to show that hierarchical spiking neural networks are able to segment the objects and bind their pixels to form shapes of objects using local excita...

We propose a framework for the creation and maintenance of multicast trees in hierarchical ATM networks. This framework aims at coping with an inherent difficulty of topology aggregating in such networks. The main idea of the proposed framework is to distribute the tree topology information among a set of hierarchical Multicast Group Servers (MGSs) nominated for each multicast tree, while keepi...

Hierarchical fuzzy neural networks can use less rules to model nonlinear system with high accuracy. But the normal training method for hierarchical fuzzy neural networks is very complex. In this paper we modify the backpropagation approach and employ a time-varying learning nte that is determined from input-output data and model stnicture. Stable learning algorithms for the premise and the cons...

In reality, most economic entities are hierarchical organizations. But in the hierarchical organizations tacit knowledge can be transferred across different hierarchies even across different departments. By use of complex networks technology, a hierarchical organization's framework is modeled in this paper. Through quantifying a number of technical datas we analyze and have a research on the tr...

In this article, we compare two self-organization and hierarchical routing protocols for ad hoc networks. These two protocols apply the reverse approach from the classical one, since they use a reactive routing protocol inside the clusters and a proactive routing protocol between the clusters. We compare them regarding the cluster organization they provide and the routing that is then performed...

We generalize the degree-organizational view of real-world networks with broad degree distributions in a landscape analog with mountains (high-degree nodes) and valleys (low-degree nodes). For example, correlated degrees between adjacent nodes correspond to smooth landscapes (social networks), hierarchical networks to one-mountain landscapes (the Internet), and degree-disassortative networks wi...