Introduction to Network Simulator NS2

Issariyakul, Teerawat; Hossain, Ekram

doi:10.1007/978-1-4614-1406-3

Cited by 269 publications

(181 citation statements)

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“…The performance evaluation of TERP is performed using Network Simulator version 2 (NS-2) [39]. Three set of experiments are carried out to evaluate the efficacy of TERP.…”

Section: Simulation and Resultsmentioning

confidence: 99%

A trust aware routing protocol for energy constrained wireless sensor network

et al. 2015

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The reliable data delivery is a challenging task in Wireless Sensor Networks (WSNs) due to dynamic and unpredictable changing behaviors of nodes. The traditional cryptographic and authentication based schemes can't be adopted due to their associated cost and incapability to counter nodes misbehavior attacks. Recently, trust based solutions have proved to be more effective to address nodes' misbehavior attacks. Apart from isolating misbehaving nodes, the existing trust based schemes lacks the capability to minimize link failure notifications due to transient transmission disruption which consequently give rise to frequent route breakages thereby undermining throughput and route stability. Moreover, the existing solutions give rise to high energy consumption and control overhead in pursuit of trust estimation and network-wide dissemination which not only adds to network congestion but also undermines network lifetime. In this paper, we present a Trust and Energy aware Routing Protocol (TERP) that B Adnan Ahmed makes use of a distributed trust model for the detection and isolation of misbehaving nodes. TERP incorporates a composite routing function that encompasses trust, residualenergy, and hop count of neighbor nodes in making routing decisions. This multi-facet routing strategy helps to balance out energy consumption among trusted nodes while routing data using shorter paths. Moreover, TERP intelligently evaluates the actual link breakage thereby avoiding unnecessary route discoveries. Simulation results demonstrate improved throughput, network lifetime and route stability of TERP when compared to existing work.

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“…The performance evaluation of TERP is performed using Network Simulator version 2 (NS-2) [39]. Three set of experiments are carried out to evaluate the efficacy of TERP.…”

Section: Simulation and Resultsmentioning

confidence: 99%

A trust aware routing protocol for energy constrained wireless sensor network

et al. 2015

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“…We performed the simulation of our data prediction model with NS-2 [25][26][27] using real temperature data set of Dickinson, North Dakota (Weather source ID: 17689) [28]. The temperature (degrees Fahrenheit) was sampled on hourly basis for the month of July 2009 (Fig.…”

Section: Simulation and Results Analysismentioning

confidence: 99%

Prediction Models for Energy Efficient Data Aggregation in Wireless Sensor Network

Sinha

Lobiyal

2015

Wireless Pers Commun

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In sensor networks, the periodically aggregated data often exhibit high temporal coherency. Huge energy consumption incurred in transmitting these redundant information results in network disconnection thereby leading to service disruption. In order to effectively manage the energy consumption in concurrent data gathering rounds, temporal data prediction model is proposed. The proposed model provides near accurate predictions that successfully restricts redundant transmissions. The communication energy conserved owing to successful predictions helps to increase the number of data cycles considerably. In addition, an energy prediction-based cluster head rotation algorithm is also presented for load balancing within clusters. Experimental outcomes show that the proposed prediction model significantly improves energy conservation by providing successful predictions per data gathering cycle. Results reveal lower magnitude of prediction error as compared to certain existing prediction methods.

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“…The network simulator NS2 (version NS2.35) was used for simulation of VANet. NS2 is one of the best network simulator which has been used and confirmed by many researchers [41]. Application of SUMO and NS2 for evaluating the proposed strategy helps overcome the limitations and complexities associated with implementing of the proposed strategy in real vehicular networks.…”

Section: Simulation Parameters and Scenariosmentioning

confidence: 99%