A Survey on Wireless Network Simulators
18 Mar 2017-Bulletin of Electrical Engineering and Informatics (Universitas Ahmad Dahlan)-Vol. 6, Iss: 1, pp 62-69
TL;DR: Various Wireless Network Simulators are surveyed and compared to provide a virtual environment for an assortment of desirable features such as modeling a network based on a specific criteria and analyzing its performance under different scenarios.
Abstract: The Network simulator helps the developer to create and simulate new models on an arbitrary network by specifying both the behavior of the network nodes and the communication channels. It provides a virtual environment for an assortment of desirable features such as modeling a network based on a specific criteria and analyzing its performance under different scenarios. This saves cost and time required for testing the functionality and the execution of network. This paper has surveyed various Wireless Network Simulators and compared them.
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TL;DR: The main objective of the research is to investigate the feasibility and the application of high-level-based approaches to ease WSN design and present the future directions to cope with the limits of existing solutions.
Abstract: Wireless sensor networks (WSNs) have grown considerably in recent years and have a significant potential in different applications including health, environment, and military. Despite their powerful capabilities, the successful development of WSN is still a challenging task. In current real-world WSN deployments, several programming approaches have been proposed, which focus on low-level system issues. In order to simplify the design of the WSN and abstract from technical low-level details, high-level approaches have been recognized and several solutions have been proposed. In particular, the model-driven engineering (MDE) approach is becoming a promising solution. In this paper, we present a survey of existing programming methodologies and model-based approaches for the development of sensor networks. We recall and classify existing related WSN development approaches. The main objective of our research is to investigate the feasibility and the application of high-level-based approaches to ease WSN design. We concentrate on a set of criteria to highlight the shortcomings of the relevant approaches. Finally, we present our future directions to cope with the limits of existing solutions.
79 citations
Cites methods from "A Survey on Wireless Network Simula..."
...Several simulator environments are used for WSN research [27, 28]....
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TL;DR: This systematic literature review aims to analyze, basing its investigation on available literature, the adoption of a popular network simulator, namely ns-3, and its use in the scientific community, and how extensible it is in practice according to the experience of authors.
Abstract: Complexity of current computer networks, including e.g., local networks, large structured networks, wireless sensor networks, datacenter backbones, requires a thorough study to perform analysis and support design. Simulation is a tool of paramount importance to encompass all the different aspects that contribute to design quality and network performance (including as well energy issues, security management overheads, dependability), due to the fact that such complexity produces several interactions at all network layers that is not easily modellable with analytic approaches. In this systematic literature review we aim to analyze, basing our investigation on available literature, the adoption of a popular network simulator, namely ns-3, and its use in the scientific community. More in detail, we are interested in understanding what are the impacted application domains in which authors prefer ns-3 to other similar tools and how extensible it is in practice according to the experience of authors. The results of our analysis, which has been conducted by especially focusing on 128 papers published between 2009 to 2019, reveals that 10% of the evaluated papers were discarded because they represented informal literature; most of the studies presented comparisons among different network simulators, beyond ns-3 and conceptual studies related to performance assessment and validation and routing protocols. Only about 30% of considered studies present extensions of ns-3 in terms of new modules and only about 10% present effective case studies demonstrating the effectiveness of employing network simulator in real application, except conceptual and modeling studies.
59 citations
TL;DR: In this article, a network is trained based on parametric setup of expanding ring search mechanism (ERS) and random early detection (RED) technique to estimate network throughput, end to end (E2E) delay and packets delivery ratio (PDR) and is tested via wide-ranging simulations in varying network topologies.
Abstract: Routing protocols in Mobile Ad Hoc Networks (MANETs) play a pivotal role in ensuring quality of service (QoS) and improving network performance. Selection of optimal routing protocol and suitable parameters for a given network scenario is a major task that ultimately affects the behavior of network. This work exploits machine learning (ML) techniques for the selection of adequate routing parameters and protocol by regression of parameters in given network scenario to ensure optimal performance. The network is trained based on parametric setup of expanding ring search mechanism (ERS) and random early detection (RED) technique to estimate network throughput, end to end (E2E) delay and packets delivery ratio (PDR) and is tested via wide-ranging simulations in varying network topologies. Both RED and ERS mechanisms are aimed to control link and node level congestion in the reactive routing protocols and our aim is to select the best suited parameters for given network topologies based on ERS and RED parametric setups and improve performance for ensuring QoS. ML algorithms are trained and tested for their performance in varying network topologies. We have exploited these models with best performance for ERS and RED based routing in given topological arrangements. The performance of the ML algorithms is evaluated on the basis of root mean squared error (RMSE) and mean absolute error (MAE) for regression settings. Prediction models with up to par RMSE and MAE out-turns are attained and exploited for selection of suitable ERS and RED parameters and routing protocols in order to ensure the QoS for given network scenario. Variants of standard routing protocols are devised based on their performance and the ML techniques are exploited for prediction of QoS parameters to decide on the optimal variant that attains significant improvement in performance. Results are shown to confirm that considerable improvement in QoS is attained.
11 citations
TL;DR: The landscape of available IoT and wireless sensor networks (WSNs) simulators and compares their performance using the Low Power Wide Area Network (LPWAN) communication technology called LoRa (Long Range), which has recently gained a lot of interest.
Abstract: The Internet of Things (IoT) is one of the most important emerging technologies, spanning a myriad of possible applications, especially with the increasing number and variety of connected devices. Several network simulation tools have been developed with widely varying focuses and used in many research fields. Thus, it is critical to simulate the work of such systems and applications before actual deployment. This paper explores the landscape of available IoT and wireless sensor networks (WSNs) simulators and compares their performance using the Low Power Wide Area Network (LPWAN) communication technology called LoRa (Long Range), which has recently gained a lot of interest. Using a systematic approach, we present a chronological survey of available IoT and WSNs simulation tools. With this, we categorized and content-analyzed published scientific papers in the IoT and WSNs simulation tools research domain by highlighting the simulation tools, study type, scope of study and performance measures of the studies. Next, we present an overview of LoRa/LoRaWAN technology by considering its architecture, transmission parameters, device classes and available simulation tools. Furthermore, we discussed three popular open-source simulation tools/frameworks, namely, NS-3, OMNeT++ (FLoRa) and LoRaSim, for the simulation of LoRa/LoRaWAN networks. Finally, we evaluate their performance in terms of Packet Delivery Ratio (PDR), CPU utilization, memory usage, execution time and the number of collisions.
8 citations
TL;DR: In this article, the authors proposed a methodological approach to evaluate WSN simulators, considering a methodological process and a set of qualitative and quantitative criteria, such as energy consumption modelling and scalability capacity.
Abstract: The large number of Wireless Sensor Networks (WSN) simulators available nowadays, differ in theirdesign, goals, and characteristics. Users who have to decide which simulator is the most appropriate for their particular requirements, are today lost, faced with a panoply of disparate and diverse simulators. Hence, it is obvious the need for establishing guidelines that support users in the tasks of selecting a simulator to suit their preferences and needs. In previous works, we pro- posed a generic and novel approach to evaluate networks simulators, considering a methodological process and a set of qualitative and quantitative criteria. In particularly, for WSN simulators, the criteria include relevant aspects for this kind of networks, such as energy consumption modelling and scalability capacity. The aims of this work are: (i) describe deeply the criteria related to WSN aspects; (ii) extend and update the state of the art of WSN simulators elaborated in our previous works to identify the most used and cited in scientific articles; and (iii) demonstrate the suitability of our novel methodological approach by evaluating and comparing the three most cited simulators, specially in terms of energy modelling and scalability capacities. Results show that our proposed approach provides researchers with an evaluation tool that can be used to describe and compare WSN simulators in order to select the most appropriate one for a given scenario.
7 citations
References
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TL;DR: This article describes best current practices for validating simulations and forvalidating TCP models across various simulation environments and discusses interactions between scale and model validation and future challenges for the community.
Abstract: Networking engineers increasingly depend on simulation to design and deploy complex, heterogeneous networks. Similarly, networking researchers increasingly depend on simulation to investigate the behavior and performance of new protocol designs. Despite such widespread use of simulation, today there exists little common understanding of the degree of validation required for various applications of simulation. Further, only limited knowledge exists regarding the effectiveness of known validation techniques. To investigate these issues, in May 1999 DARPA and NIST organized a workshop on Network Simulation Validation. This article reports on discussions and consensus about issues that arose at the workshop. We describe best current practices for validating simulations and for validating TCP models across various simulation environments. We also discuss interactions between scale and model validation and future challenges for the community.
95 citations
"A Survey on Wireless Network Simula..." refers background in this paper
...So to overcome these, it is necessary to know about different tools that are available and came to know about their benefits and drawbacks [4]....
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01 Jan 2009
TL;DR: This paper examines four WSN simulators: ns-2, Castalia (OMNeT++ based), TOSSIM, and COOJA/MSPSim, and defines a set of criteria to evaluate and compare the simulators, and provides short descriptions of simulators and tabular comparison based on the criteria.
Abstract: This paper is inspired by the lack of detailed wireless sensor network (WSN) simulator surveys. We examine four WSN simulators: ns-2, Castalia (OMNeT++ based), TOSSIM, and COOJA/MSPSim, and define a set of criteria to evaluate and compare the simulators. We provide short descriptions of simulators and tabular comparison based on the criteria. Since none of the simulators under survey is a universal solution, rough guidelines on which simulator to use in particular situation are given.
73 citations
"A Survey on Wireless Network Simula..." refers background or methods in this paper
...Open Source Network simulators are of different types viz NS2, NS3, OMNET++, JSIM, OPNET, QualNet, MATLAB, etc....
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...With the help of MATLAB, one can Develop Algorithms for Digital Signal Processing....
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...OMNET++ (Objective Modular Network Testbed in C++) OMNET++ [3, 6-9, 11-14, 16-20] is a general purpose, extensible, modular, componentbased, open architecture discrete event based network simulator....
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...Comparative Study of Various Network Simulators Table 1 shows the comparative study of the different open source simulators (NS2, NS3, J-Sim, OMNeT++, OPNET, QUALNET and MATLAB)[3, 6, 7, 9, 10, 15-17, 19, 21-23]....
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...All these open source network simulators (NS2, NS3, J-Sim, OMNeT++, OPNET, QUALNET and MATLAB) are useful for academic as well as industries point of view, as it helps students and researchers for doing research....
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TL;DR: It is rather complex, or even unfeasible, to model analytically a WSN and it usually leads to oversimplified analysis with limited confidence, therefore, simulation is essential to study WSN.
Abstract: Wireless sensor network have recently come into prominence because they hold the potential to revolutionize segment of our economy and life with its wide applications. Unlike a centralized system, a sensor network is formed by large numbers of networked sensing nodes. They are having unique set of resource constraints such as finite onboard battery power and limited network communication bandwidth. Since running real experiments is costly and time consuming, simulation is essential to study Wireless Sensor Networks (WSN). It is rather complex, or even unfeasible, to model analytically a WSN and it usually leads to oversimplified analysis with limited confidence. Therefore, simulation is essential to study WSN. The word "wise" in the title indicate the meaning most appropriate according to their usage and testing
31 citations
TL;DR: The key objective of this work is to review various tools available for the emerging Wireless Sensor Network and its services suitable for different categories of applications by performing different functions thus paving the way for changes in Information and Communication field in the upcoming years.
Abstract: success of Wireless Sensor Networks lies in the fact that the tools available for detecting the failures are demonstrated in many long term implementations. WSNs are scarce or limited resources, delicate, difficult in analysis and prone to mistakes easily by nature. With the ease of tools installations increases, nowadays the causes of failure identification in such a network becomes efficient. Due to the high cost and increased time consumption of deployment of WSNs, almost in all the fields, many experimental tools are used before real environment implementation. From 2005 onwards, these tools are rapidly increased in number and performance proportionately with the emerged new technologies. In this survey, many tools are discussed and compared with several features for implementation. Even though many tools are developed for different applications, still there exists open challenges' regarding its reachability, suppleness, simplicity, locality of nodes and protection. To avoid these issues, WSNs platforms and operating systems has to be matured by having improved diagnostic capability. The key objective of this work is to review various tools available for the emerging Wireless Sensor Network and its services suitable for different categories of applications by performing different functions thus paving the way for changes in Information and Communication field in the upcoming years. KeywordsSensor Networks, Experimental tools, Information and Communication field.
6 citations
"A Survey on Wireless Network Simula..." refers background or methods in this paper
...Open Source Network simulators are of different types viz NS2, NS3, OMNET++, JSIM, OPNET, QualNet, MATLAB, etc....
[...]
...With the help of MATLAB, one can Develop Algorithms for Digital Signal Processing....
[...]
...OMNET++ (Objective Modular Network Testbed in C++) OMNET++ [3, 6-9, 11-14, 16-20] is a general purpose, extensible, modular, componentbased, open architecture discrete event based network simulator....
[...]
...Comparative Study of Various Network Simulators Table 1 shows the comparative study of the different open source simulators (NS2, NS3, J-Sim, OMNeT++, OPNET, QUALNET and MATLAB)[3, 6, 7, 9, 10, 15-17, 19, 21-23]....
[...]
...All these open source network simulators (NS2, NS3, J-Sim, OMNeT++, OPNET, QUALNET and MATLAB) are useful for academic as well as industries point of view, as it helps students and researchers for doing research....
[...]
01 Jan 2001
1 citations
"A Survey on Wireless Network Simula..." refers methods in this paper
...Simulation tools are classified into several norms which are as shown in Figure 3 [5]: a....
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