Enhancement of Self-organisation in Wireless Networking through a Cross-Layer Approach

Razzaque, Mohammad Abdur; Dobson, Simon; Nixon, Paddy

doi:10.1007/978-3-642-11723-7_10

Cited by 8 publications

(5 citation statements)

References 24 publications

(29 reference statements)

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“…According to many research papers, as mentioned earlier, a self-organized system should acquire its organized characteristics without intervention from outside sources [9,12]; however, some other researchers mention that outside sources should be kept out of the loop as much as possible [13,14]. The vision of autonomic computing would only be complete through acquired knowledge i.e.…”

Section: A Revisting the State-of-the-artmentioning

confidence: 99%

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Supporting Self-Organization with Logical-Clustering Towards Autonomic Management of Internet-of-Things

Rahman¹,

Kanter²,

Rahmani

2015

ijacsa

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Abstract-One of the challenges for autonomic management in Future Internet is to bring about self-organization in a rapidly changing environment and enable participating nodes to be aware and respond to changes. The massive number of participating nodes in Internet-of-Things calls for a new approach in regard of autonomic management with dynamic selforganization and enabling awareness to context information changes in the nodes themselves. To this end, we present new algorithms to enable self-organization with logical-clustering, the goal of which is to ensure that logical-clustering evolves correctly in the dynamic environment. The focus of these algorithms is to structure logical-clustering topology in an organized way with minimal intervention from outside sources. The correctness of the proposed algorithm is demonstrated on a scalable IoT platform, MediaSense. Our algorithms sanction 10 nodes to organize themselves per second and afford high accuracy of nodes discovery. Finally, we outline future research challenges towards autonomic management of IoT.

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Section: A Revisting the State-of-the-artmentioning

confidence: 99%

“…In general, self-organization can be considered as a system which organizes itself automatically i.e. without any intervention from outside sources [9,12]. However, keeping outside source completely out of the loop is still a research challenge.…”

Section: Introductionmentioning

confidence: 99%

Supporting Self-Organization with Logical-Clustering Towards Autonomic Management of Internet-of-Things

Rahman¹,

Kanter²,

Rahmani

2015

ijacsa

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“…A cross-layer architecture proposed in [ 14 ] supports network level context awareness in communications. Context is categorized into either “local view” context that is inferred from within a sensor node, or “global view” context that is obtained from external of the node.…”

Section: Related Workmentioning

confidence: 99%

Ambient Intelligence Context-Based Cross-Layer Design in Wireless Sensor Networks

Liu

Seet

Al-Anbuky

2014

Sensors

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By exchanging information directly between non-adjacent protocol layers, cross-layer (CL) interaction can significantly improve and optimize network performances such as energy efficiency and delay. This is particularly important for wireless sensor networks (WSNs) where sensor devices are energy-constrained and deployed for real-time monitoring applications. Existing CL schemes mainly exploit information exchange between physical, medium access control (MAC), and routing layers, with only a handful involving application layer. For the first time, we proposed a framework for CL optimization based on user context of ambient intelligence (AmI) application and an ontology-based context modeling and reasoning mechanism. We applied the proposed framework to jointly optimize MAC and network (NET) layer protocols for WSNs. Extensive evaluations show that the resulting optimization through context awareness and CL interaction for both MAC and NET layer protocols can yield substantial improvements in terms of throughput, packet delivery, delay, and energy performances.

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“…As presented in [4], self-organization can be implemented in two different levels: infrastructure and application. While the first one aims at self-organization in various communication layers of network management (Data Link, Network, Transport), the second one intends to provide self-organization above such layers.…”

Section: Introductionmentioning

confidence: 99%

ABMQ: An Agent-Based Modeler and Simulator for Self-Organization in MANETs using Qt

Noormohammadpour,

Salehi,

Pari

et al. 2013

Preprint

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Agent-Based Modeling and Simulation (ABMS) is a simple and yet powerful method for simulation of interactions among individual agents. Using ABMS, different phenomena can be modeled and simulated without spending additional time on unnecessary complexities. Although ABMS is well-matured in many different fields such as economic, social, and natural phenomena, it has not received much attention in the context of mobile ad-hoc networks (MANETs). In this paper, we present ABMQ, a powerful Agent-Based platform suitable for modeling and simulation of self-organization in wireless networks, and particularly MANETs. By utilizing the unique potentials of Qt Application Framework, ABMQ provides the ability to easily model and simulate self-organizing algorithms, and then reuse the codes and models developed during simulation process for building real third-party applications for several desktop and mobile platforms, which substantially decreases the development time and cost, and prevents probable bugs that can happen as a result of rewriting codes.

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Enhancement of Self-organisation in Wireless Networking through a Cross-Layer Approach

Cited by 8 publications

References 24 publications

Supporting Self-Organization with Logical-Clustering Towards Autonomic Management of Internet-of-Things

Supporting Self-Organization with Logical-Clustering Towards Autonomic Management of Internet-of-Things

Ambient Intelligence Context-Based Cross-Layer Design in Wireless Sensor Networks

ABMQ: An Agent-Based Modeler and Simulator for Self-Organization in MANETs using Qt

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