Optimization models and methods for planning wireless mesh networks

Amaldi, E.; Capone, Antonio; Cesana, Matteo; Filippini, Ilario; Malucelli, Federico

doi:10.1016/j.comnet.2008.02.020

Cited by 209 publications

(115 citation statements)

References 22 publications

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“…However, until this technology is completely deployed the diversity in the set of deployable relays has produced a lot of research directly related to disaster/emergency response communications deployment (recently surveyed by [37]), or indirectly related in the form of akin mobile ad-hoc networking, wireless mesh (WMNs) or wireless sensor networks (WSNs). Relay/node deployment represents a very active research niche in WMNs as pointed out in [38][39][40][41][42] and more recently in [43].…”

Section: Related Workmentioning

confidence: 99%

Cost-efficient deployment of multi-hop wireless networks over disaster areas using multi-objective meta-heuristics

et al. 2018

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Section: Related Workmentioning

confidence: 99%

Cost-efficient deployment of multi-hop wireless networks over disaster areas using multi-objective meta-heuristics

et al. 2018

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“…Given that an appropriate network planning provides the basis for an effective energy management operation, we now present the basic planning model introduced in [32] and explain how that model is modified to obtain a general framework for energy management.…”

Section: A General Approach To Wmn Energy Managementmentioning

confidence: 99%

Energy Savings in Wireless Mesh Networks in a Time-Variable Context

2011

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Energy consumption of communication systems is becoming a fundamental issue and, among all the sectors, wireless access networks are largely responsible for the increase in consumption. In addition to the access segment, wireless technologies are also gaining popularity for the backhaul infrastructure of cellular systems mainly due to their cost and easy deployment. In this context, Wireless Mesh Networks (WMN) are commonly considered the most suitable architecture because of their versatility that allows flexible configurations. In this paper we combine the flexibility of WMN with the need for energy consumption reduction by presenting an optimization framework for network management that takes into account the trade off between the network energy needs and the daily variations of the demand. A resolution approach and a thorough discussion on the details related to WMN energy management are also presented.

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“…For improving the fault tolerance [8], we need to focus on both of the areas: the backbone coverage and last mile coverage. For achieving this we need to determine the following information:…”

Section: Proble M Definitionmentioning

confidence: 99%

“…The fault tolerance includes two major areas: last mile coverage fault tolerance and backbone coverage fault tolerance [8]. For achieving a fault tolerant WM N, we need such a backbone coverage that can deal with n number of faults.…”

Section: Proble M Definitionmentioning

confidence: 99%

“…The previously defined algorithms [8,11] had designed backbone coverage with minimum number of base stations in such a way that the end-to-end throughput requirements for Internet access in areas with no alternative high-speed wired connection can be done. These approaches lead to the connected backbone graph but do not provide fault tolerance.…”

Section: Related Workmentioning

confidence: 99%

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Fault Tolerant Wireless Mesh Network: An Approach

Gupta¹,

Bedi²

2011

IJCA

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Wireless mesh networks (WM Ns) have achieved significant development because of fast deployment, easy maintenance and low investment compared with traditional wireless networks. Since WM Ns are typically used as wireless backbones, they have the nature that the wireless communication is not constant. Hence, it is important to defend them against link or node failures. In this paper we present an innovative algorithm for fault-tolerant base station planning using antenna arrays in the backbone networks. The algorithm first detects the node's as well as link failure's and then rectifies them using our proposed algorithm. Our paper propose a solution for building a fault tolerant network that can tolerate up to n faults where n is the number of antenna arrays used.

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Optimization models and methods for planning wireless mesh networks

Cited by 209 publications

References 22 publications

Cost-efficient deployment of multi-hop wireless networks over disaster areas using multi-objective meta-heuristics

Cost-efficient deployment of multi-hop wireless networks over disaster areas using multi-objective meta-heuristics

Energy Savings in Wireless Mesh Networks in a Time-Variable Context

Fault Tolerant Wireless Mesh Network: An Approach

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