Online reconfiguration of channel assignment in Multi-Channel Multi-Radio wireless mesh networks

Franklin, A. Antony; Balachandran, Athula; Murthy, C. Siva Ram

doi:10.1016/j.comcom.2012.04.006

Cited by 15 publications

(10 citation statements)

References 30 publications

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“…The simulations assume IEEE 802.11a as the physical layer technology, and the raw data rate is set to 54 Mbps. Previous research indicates that the channel switching delay of an IEEE 802.11a interface is between 40 to 80 μ s. The authors of further proposed a channel assignment re‐configuration model to quantitatively evaluate network throughput degradation and channel switching overhead. This study assumes a fixed overhead of 40 μ s for channel switching, and future research will consider a more complete cost model, such as that in .…”

Section: Simulation Resultsmentioning

confidence: 99%

An end‐to‐end channel allocation scheme for a wireless mesh network

Tsao

Huang

et al. 2013

Int J Communication

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SUMMARYCo-channel interference seriously influences the throughput of a wireless mesh network. This study proposes an end-to-end channel allocation scheme (EECAS) that extends the radio-frequency-slot method to minimize co-channel interference. The EECAS first separates the transmission and reception of packets into two channels. This scheme can then classify the state of each radio-frequency-slot as transmitting, receiving, interfered, free, or parity. A node that initiates a communication session with a quality of service requirement can propagate a channel allocation request along the communication path to the destination. By checking the channel state, the EECAS can determine feasible radio-frequency-slot allocations for the end-to-end path. The simulation results in this study demonstrate that the proposed approach performs well in intra-mesh and inter-mesh communications, and it outperforms previous channel allocation schemes in end-to-end throughput.

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Section: Simulation Resultsmentioning

confidence: 99%

An end‐to‐end channel allocation scheme for a wireless mesh network

Tsao

Huang

et al. 2013

Int J Communication

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“…In addition, there are also some research papers [10,34,35,36,38] aiming to solving the problem with Link scheduling in the field of wireless mesh networks. This is with the assumption that synchronous coordination is supported at link levels.…”

Section: Related Workmentioning

confidence: 99%

“…This is with the assumption that synchronous coordination is supported at link levels. These works can be classified based on their channel assignment types to static channel assignment as in [13,37,38] or dynamic channel assignment as in [39][40][41]. Firstly, in static channel assignments channels are allocated to radios and links for relatively long period of time.…”

Section: Related Workmentioning

confidence: 99%

“…In [37], the problem also formulated as LP problem and is solved in two steps where additional constraints are added to the problem based on the solution obtained from the first step. In [38], the link load is first estimated by distributing the new load of each flow on all available predefined paths based on hop count. A heuristic algorithm is proposed for handling the channel assignment problem.…”

Section: Related Workmentioning

confidence: 99%

“…Recently, there are also some exploration literatures [35,36,38,[43][44][45][46] for re-configuration problem in MR-WMN. A heuristic algorithm proposed in [43] to deal with the channel re-assignment problem.…”

Section: Related Workmentioning

confidence: 99%

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State-Aware Re-configuration Model for Multi-Radio Wireless Mesh Networks

Omar

Hashim

Hassan³

et al. 2016

KSII TIIS

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Joint channel assignment and routing is a well-known problem in multi-radio wireless mesh networks for which optimal configurations is required to optimize the overall throughput and fairness. However, other objectives need to be considered in order to provide a high quality service to network users when it deployed with high traffic dynamic. In this paper, we propose a re-configuration optimization model that optimizes the network throughput in addition to reducing the disruption to the mesh clients' traffic due to the re-configuration process. In this multi-objective optimization model, four objective functions are proposed to be minimized namely maximum link-channel utilization, network average contention, channel re-assignment cost, and rerouting cost. The latter two objectives focus on reducing the re-configuration overhead. This is to reduce the amount of disrupted traffic due to the channel switching and path rerouting resulted from applying the new configuration. In order to adapt to traffic dynamics in the network which might be caused by many factors i.e. users' mobility, a centralized heuristic re-configuration algorithm called State-Aware Joint Routing and Channel Assignment (SA-JRCA) is proposed in this research based on our re-configuration model. The proposed algorithm reassigns channels to radios and re-configures flows' routes with aim of achieving a tradeoff between maximizing the network throughput and minimizing the re-configuration overhead. The ns-2 simulator is used as simulation tool and various metrics are evaluated. These metrics include channel-link utilization, channel re-assignment cost, rerouting cost, throughput, and delay. Simulation results show the good performance of SA-JRCA in term of packet delivery ratio, aggregated throughput and re-configuration overhead. It also shows higher stability to the

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An adaptive interference‐aware and traffic‐aware channel assignment strategy for backhaul networks

Iqbal

Abdullah

Qureshi

2019

Concurrency and Computation

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With the introduction of service-centric applications, the provision of quality of service (QoS) would be a challenge in both classical as well as IoT Networks. 1 The value can be added by monitoring these networks in priority areas and spontaneously levelling the traffic, so that network congestion could be avoided. 2,3 Wireless Mesh Networks (WMNs) are gaining in attraction for metropolitan operations as well as being considered successful for IoT communication. Typically, a wireless mesh network is composed of access points, called Mesh Routers (MRs), which interwork hops to hop to form a larger backhaul network.However, these MRs perform additional functionalities as compared to traditional routers, eg, self-healing. The MRs are usually statically placed and of fixed transmission power in contrast to the classical routers used in ad-hoc networks, which typically vary. Hence, in WMNs', interference can be more controlled. [4][5][6][7][8][9] Similarly, MRs in WMN can have multiple radios and thus interference estimation should be based on all radios, which does not usually pose a difficulty in ad hoc networks as routers are equipped with only a single radio. 10 Hence, a comparatively better performance and throughput can be achieved in WMN against ad-hoc networks. However, MRs equipped with multiple radios can also experience some complexities as parallel transmissions in close proximity cannot occur on the same channel at the same time. Assigning each radio, a different channel is practically not possible as this may result in logical disconnection of the network topology. 11There are 3 non-overlapping channels in IEEE 802.11b that are least interfered eg, channels 1, 6, and 11. [12][13][14][15] Besides the fact that the number of available channels is usually less than the number of radios in proximity, this paper discusses the problem of assigning a limited number of Concurrency Computat Pract Exper. 2020;32:e5650.wileyonlinelibrary.com/journal/cpe

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Online reconfiguration of channel assignment in Multi-Channel Multi-Radio wireless mesh networks

Cited by 15 publications

References 30 publications

An end‐to‐end channel allocation scheme for a wireless mesh network

An end‐to‐end channel allocation scheme for a wireless mesh network

State-Aware Re-configuration Model for Multi-Radio Wireless Mesh Networks

An adaptive interference‐aware and traffic‐aware channel assignment strategy for backhaul networks

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