Towards modeling complex wireless sensor networks using agents and networks: A systematic approach

Batool, Komal; Niazi, Muaz A.; Sadik, Sarmad; Shakil, Anam Riaz Risham

doi:10.1109/tencon.2014.7022378

Cited by 8 publications

(4 citation statements)

References 30 publications

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“…They suggest that this could be applied to predict properties of complex engineered systems such as WSNs, and by extension the IoT. Batool et al [104] discussed the development of a NetLogo agent-based model for CAS. This looks to be a promising approach for modelling the IoT as a CAS using agents.…”

Section: Complex Adaptive Systems Theory and The Iotmentioning

confidence: 99%

Research Challenges for the Internet of Things: What Role Can OR Play?

Ryan

Watson²

2017

Systems

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Abstract:The Internet of Things (IoT) is an extension of the Internet in which large numbers of "things", including sensors, actuators and processors, in addition to human users, are networked and able to provide high resolution data on their environment and exercise a degree of control over it. It is still at an early stage of development, and many problems/research challenges must be solved before it is widely adopted. Many of these are technical, including interoperability and scalability, as billions of heterogeneous devices will be connected, but deciding on how to invest in the IoT is a challenge for business, and there are also major social, legal and ethical challenges, including security and privacy of data collection, which must be resolved. As the future IoT will be a multi-national, multi-industry, multi-technology infrastructure, the paper reviews the global standardization efforts that are underway to facilitate its worldwide creation and adoption. The main purpose of the paper is to give a broad survey, based on published literature, of the methods of Operations Research (OR), both the mathematical tools and techniques of "hard" OR, and the various approaches of Systems Thinking, including "soft" OR, which may assist in dealing with these problems. A subset of these is described in greater depth to better convey what might be involved in applying OR and Systems Thinking to the IoT. It is suggested that OR has a role to play in balancing the technical and non-technical research challenges which confront the IoT.

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Section: Complex Adaptive Systems Theory and The Iotmentioning

confidence: 99%

Research Challenges for the Internet of Things: What Role Can OR Play?

Ryan

Watson²

2017

Systems

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“…Extensive experiments were conducted by using the NetLogo event simulator [10,[43][44][45] to validate the effectiveness of FRAT. For comparison, we also added GTMS [18] and ATRM [36] into the simulator because both of them are independent of any specific routing mechanism.…”

Section: Experimental Methods and Parametersmentioning

confidence: 99%

Fast, Resource-Saving, and Anti-Collaborative Attack Trust Computing Scheme Based on Cross-Validation for Clustered Wireless Sensor Networks

Liu

2020

Sensors

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The trust computing mechanism has an increasing role in the cooperative work of wireless sensor networks. However, the computing speed, resource overhead, and anti-collaborative attack ability of a trust mechanism itself are three key challenging issues for any open and resource-constrained wireless sensor networks. In this study, we propose a fast, resource-saving, and anti-collaborative attack trust computing scheme (FRAT) based on across-validation mechanism for clustered wireless sensor networks. First, according to the inherent relationship among three network entities (which are made up of three types of network nodes, namely base stations, cluster heads, and cluster members), we propose the cross-validation mechanism, which is effective and reliable against collaborative attacks caused by malicious nodes. Then, we adopt a fast and resource-saving trust computing scheme for cooperation between between cluster heads or cluster members. This scheme is suitable for wireless sensor networks because it facilitates resource-saving. Through theoretical analysis and experiments, the feasibility and effectiveness of the trust computing scheme proposed in this study are verified.

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“…Batool and Niazi in [6], presented a novel hybrid approach for modeling internet of things (IoT)-based complex scenario using standard complex networks such as small-world, scale-free, random and lattice network. In [21], novel agent-based and complex network-based modeling approaches are used in the wireless sensor network domain. In this work, different standard complex network such as small-world, scale-free, and random network is used.…”

Section: Comparison With Previous Workmentioning

confidence: 99%

Towards Agent-Based Model Specification of Smart Grid: A Cognitive Agent-Based Computing Approach

Barišić

Poór

Bach

2019

Interdiscip. Descr. Complex Syst.

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A smart grid can be considered as a complex network where each node represents a generation unit or a consumer. Whereas links can be used to represent transmission lines. One way to study complex systems is by using the agent-based modeling (ABM) paradigm. An ABM is a way of representing a complex system of autonomous agents interacting with each other. Previously, a number of studies have been presented in the smart grid domain making use of the ABM paradigm. However, to the best of our knowledge, none of these studies have focused on the specification aspect of ABM. An ABM specification is important not only for understanding but also for replication of the model. In this study, we focus on development as well as specification of ABM for smart grid. We propose an ABM by using a combination of agent-based and complex networkbased approaches. For ABM specification, we use ODD and DREAM specification approaches. We analyze these two specification approaches qualitatively as well as quantitatively. Extensive experiments demonstrate that DREAM is a most useful approach as compared with ODD for modeling as well as for replication of models for smart grid. Cognitive agent-based computing approachNiazi and Hussain in [8] presented a unified cognitive agent-based computing approach for agent-based and complex network-based modeling. This approach involves the process of taking any complex system from the real world and to convert it into a suitable simple model by using specific modeling level such as exploratory or descriptive agent-based approach. The exploratory approach involves the use of agents to explore the complex system, identifies which agent-based model is feasible for the specific problem, then develops the proof concept and also explains what kind of data is required for validation and verification of the model. The Descriptive agent-based model level is the process of presenting ABM specification in the form of pseudo-code, a complex network of the model and social network analysis. Other modeling levels involve complex network and validation/ verification of the model. Descriptive agent-based modelingDescriptive agent-based modeling (DREAM) is a cognitive agent-based computing approach developed by Niazi in [3]. DREAM offers an ABM specification technique which comprises of developing a complex network of the ABM, pseudo-code specification model and social network analysis of the network model. It offers a detailed description of ABM as well as visual based analysis. It provides an easy translation of network model into pseudo-code followed by ABM development. In figure 1, Dream methodology has been shown. Figure 1: DREAM methodology for ABM specification adopted from [3]. We can see that it starts from a basic understanding of the model, then followed by developing a complex network of the model. There are two steps after network formation, one is to present pseudocode specification, this step allows for the actual code translation, second after network formation is by applying social network analysis t...

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Towards modeling complex wireless sensor networks using agents and networks: A systematic approach

Cited by 8 publications

References 30 publications

Research Challenges for the Internet of Things: What Role Can OR Play?

Research Challenges for the Internet of Things: What Role Can OR Play?

Fast, Resource-Saving, and Anti-Collaborative Attack Trust Computing Scheme Based on Cross-Validation for Clustered Wireless Sensor Networks

Towards Agent-Based Model Specification of Smart Grid: A Cognitive Agent-Based Computing Approach

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