Category Archive: 'M.TECH OMNET++ PROJECT'

Impact of Solar Panels on Power Quality of Distribution Networks and Transformers

This paper presents an investigation on the impact of solar panels (SPs) on the power quality of distribution networks and transformers. Both solar farms and residential rooftop SP are modeled with the distribution network according to Canadian Utility data. Total harmonic distortion of voltages and currents on both sides of the distribution transformer are monitored […]

Joint Resource Allocation for Throughput Enhancement in Cognitive Radio Femtocell Networks

In cognitive radio femtocell network (CRFN), secondary users (SUs) cooperatively sense a spectrum band to decide the presence of primary network. However, this sensing overhead generally degrades the throughput performance. The prior work, to resolve this problem, proposed algorithms either to decrease the time spent in sensing or to decrease the number of SUs participating […]

VoteTrust: Leveraging Friend Invitation Graph to Defend against Social Network Sybils

Online social networks (OSNs) suffer from the creation of fake accounts that introduce fake product reviews, malware and spam. Existing defenses focus on using the social graph structure to isolate fakes. However, our work shows that Sybils could befriend a large number of real users, invalidating the assumption behind social-graph-based detection. In this paper, we […]

Mixed H-Infinity and Passive Filtering for Discrete Fuzzy Neural Networks With Stochastic Jumps and Time Delays

In this brief, the problems of the mixed H-infinity and passivity performance analysis and design are investigated for discrete time-delay neural networks with Markovian jump parameters represented by Takagi-Sugeno fuzzy model. The main purpose of this brief is to design a filter to guarantee that the augmented Markovian jump fuzzy neural networks are stable in […]

On analyzing Indian cellular traffic characteristics for energy efficient network operation

Recent proliferation of mobile devices and high market demand have pushed power consumption of cellular networks to high levels in India. At the same time, the marginal gains to telecom operators for providing services have dwindled. Thus, a gap is slowly building up in the demand and supply of telecom services. The effect is adverse […]

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, […]