Tag Archive: 'Omnet++ Projects'

A recommender system architecture for predictive telecom network management

Current telecom networks generate massive amounts of monitoring data consisting of observations on network faults, configuration, accounting, performance, and security. Due to the ever increasing degree of complexity of networks, coupled with specific constraints (legal, regulatory, increasing scale of management in heterogeneous networks), the traditional reactive management approaches are increasingly stretched beyond their capabilities. A […]

Taming Cross-Technology Interference for WiFi and ZigBee Coexistence Networks

Recent studies show that WiFi interference has been a major problem for low power urban sensing technology ZigBee networks. Existing approaches for dealing with such interferences often modify either the ZigBee nodes or WiFi nodes. However, massive deployment of ZigBee nodes and uncooperative WiFi users call for innovative cross-technology coexistence without intervening legacy systems. In […]

Demonstration of multi-hop optical add-drop network with high frequency granular optical channel defragmentation nodes

Four nodes optical add-drop network with high frequency granular optical channel defragmentation has been demonstrated. All channels presents error-free operation and power penalties are less than 4 dB even after multi-hop transmission.

On the Existence and Linear Approximation of the Power Flow Solution in Power Distribution Networks

We consider the problem of deriving an explicit approximate solution of the nonlinear power equations that describe a balanced power distribution network. We give sufficient conditions for the existence of a practical solution to the power flow equations, and we propose an approximation that is linear in the active and reactive power demands of the […]

Engineering Parallel Algorithms for Community Detection in Massive Networks

The amount of graph-structured data has recently experienced an enormous growth in many applications. To transform such data into useful information, fast analytics algorithms and software tools are necessary. One common graph analytics kernel is disjoint community detection (or graph clustering). Despite extensive research on heuristic solvers for this task, only few parallel codes exist, […]

Robust Synchronization of Multiple Memristive Neural Networks With Uncertain Parameters via Nonlinear Coupling

This paper is concerned with the global robust synchronization of multiple memristive neural networks (MMNNs) with nonidentical uncertain parameters. A coupling scheme is introduced, in a general topological structure described by a direct or undirect graph, with a linear diffusive term and a discontinuous sign term. First, a set of sufficient conditions are derived based […]

Infinite Impulse Response Graph Filters in Wireless Sensor Networks

Many signal processing problems in wireless sensor networks can be solved by graph filtering techniques. Finite impulse response (FIR) graph filters (GFs) have received more attention in the literature because they enable distributed computation by the sensors. However, FIR GFs are limited in their ability to represent the global information of the network. This letter […]

Countermeasure for Reinforcement Swap Attack against Directed Diffusion in Wireless Sensor Networks

Directed Diffusion is a data centric protocol that focuses on the energy efficiency of the networks. It is interest based routing protocol in which communication occur hop-to-hop rather than end-to-end in wireless sensor networks. Hop-to-hop communication provides link diversity which helps to overcome obstacles like failure of intermediate node on communication path. Directed Diffusion protocol […]

Leveraging the Error Resilience of Neural Networks for Designing Highly Energy Efficient Accelerators

In the recent years, inexact computing has been increasingly regarded as one of the most promising approaches for slashing energy consumption in many applications that can tolerate a certain degree of inaccuracy. Driven by the principle of trading tolerable amounts of application accuracy in return for significant resource savings–the energy consumed, the (critical path) delay […]

Sparsity Enhanced Mismatch Model for Robust Intercell Interference Management in Heterogeneous Networks with Doubly-Selective Fading Channels

Transmission over doubly-selective fading (DSF) interference channel often relies on the use of robust precoder due to a lack of accurate channel state information, with performance often depending on the conservativeness of the mismatch model. Previously proposed mismatch models either have been deemed too conservative (deterministic models) or are prone to error due to inaccuracy […]