Energy Efficient Survivable IP-Over-WDM Networks With Network Coding

Musa, Mohamed O. I.; El-Gorashi, Taisir E. H.; Elmirghani, Jaafar M. H.

doi:10.1364/jocn.9.000207

Cited by 55 publications

(41 citation statements)

References 22 publications

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“…The result in (16) analytically confirms our heuristic in [23] that can provide close to optimal solution. The heuristic produces a good solution by employing the following principles • Select the minimum number of hops for the working and protection paths (minimising the first term of (16)) • Encode a demand with another demand that has the highest number of shared hops and closest demand volume (maximising the second term of (16)) • More weight is given to finding minimal hop paths than searching for better encoding pair (from the equation, the weight ratio of the first to second terms is 4:1) • Three heuristics can be conceived.…”

Section: + 1 Protection With Network Codingsupporting

confidence: 75%

“…The resource savings and therefore the power consumption reduction in this scheme depends on the network topology, the location and number of network coding enabled nodes as well as the nature of demands. In our previous paper [23] we studied the scheme and determined the optimum allocation using a MILP optimization model followed by 5 heuristics. The real time and most optimal version of the heuristics is called the Optimal search heuristic (OSH).…”

Section: + 1 Protection With Network Codingmentioning

confidence: 99%

“…In the previous work [23] we established that the star and the line topologies exhibits no network coding benefits as the concept of protection does not apply. Here we develop formulas and bounds for the full mesh and ring topologies for the case where protection paths are encoded together, and study the impact of the network size on the performance of network coding.…”

Section: Regular Topologiesmentioning

confidence: 99%

“…In our previous work [23] we proposed and designed a 1+1 protection scheme for core networks with network coding and optimized the network coding allocation and network operation using a mixed integer linear program and heuristics, providing encouraging results for energy efficiency improvement of up to 37% compared to the conventional 1+1 protection scheme. In this work we complement our study and analysis by deriving for the first time analytical bounds and close form arXiv:1804.02916v1 [cs.NI] 9 Apr 2018 expressions for the network coding as well as the conventional 1+1 protection scheme which verify the MILP and heuristic results in [23] and enable the performance of large networks to be determined easily. We also study large network sizes that are highly complex using the MILP approach, as well as provide a detailed study on the special full mesh and ring topologies…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Bounds for Energy-Efficient Survivable IP Over WDM Networks With Network Coding

Musa¹,

El-Gorashi²,

Elmirghani³

2018

J. Opt. Commun. Netw.

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In this work we establish analytic bounds for the energy efficiency of the 1+1 survivable IP over WDM networks using network coding. The analytic bounds are shown to be in close agreement with our previously reported results. They provide verification of the MILP and heuristics proposed previously and an efficient, compact means of evaluating the network results, and allow the performance of large networks to be determined easily.

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Section: + 1 Protection With Network Codingsupporting

confidence: 75%

Section: + 1 Protection With Network Codingmentioning

confidence: 99%

Section: Regular Topologiesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Bounds for Energy-Efficient Survivable IP Over WDM Networks With Network Coding

Musa¹,

El-Gorashi²,

Elmirghani³

2018

J. Opt. Commun. Netw.

Self Cite

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“…technology (ICT) industry [20]. Centralization of fog computing capacity in existing ICT infrastructure locations such as COs, CSs and private computing clusters can aid the realization of this goal, while the interconnecting network topologies can play an important role in optimally placing the fog nodes [21] - [23]. Furthermore, adoption of the server disaggregation concept in such locations can significantly improve their efficiency.…”

mentioning

confidence: 99%

Disaggregation for Improved Efficiency in Fog Computing Era

Ajibola

El-Gorashi

Elmirghani

2019

2019 21st International Conference on Transparent Optical Networks (ICTON)

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This paper evaluates the impact of using disaggregated servers in the near-edge of telecom networks (metro central offices, radio cell sites and enterprise branch office which form part of a Fog as a Service system) to minimize the number of fog nodes required in the far-edge of telecom networks. We formulated a mixed integer linear programming (MILP) model to this end. Our results show that replacing traditional servers with disaggregated servers in the near-edge of the telecom network can reduce the number of far-edge fog nodes required by up to 50% if access to near-edge computing resources is not limited by network bottlenecks. This improved efficiency is achieved at the cost of higher average hop count between workload sources and processing locations and marginal increases in overall metro and access networks traffic and power consumption.

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Cloud Fog Architectures in 6G Networks

Yosuf

Alahmadi

El-Gorashi

et al. 2021

Computer Communications and Networks

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prior to the advent of the cloud, storage and processing services were accommodated by specialized hardware, however, this approach introduced a number of challenges in terms of scalability, energy efficiency, and cost. Then came the concept of cloud computing, where to some extent, the issue of massive storage and computation was dealt with by centralized data centers that are accessed via the core network. The cloud has remained with us thus far, however, this has introduced further challenges among which, latency and energy efficiency are of the pinnacle. With the increase in embedded devices' intelligence came the concept of the Fog. The availability of massive numbers of storage and computational devices at the edge of the network, where some are owned and deployed by the end-users themselves but most by service operators. This means that cloud services are pushed further out from the core towards the edge of the network, hence reduced latency is achieved. Fog nodes are massively distributed in the network, some benefit from wired connections, and others are connected via wireless links. The question of where to allocate services remains an important task and requires extensive attention. This chapter introduces and evaluates cloud fog architectures in 6G networks paying special attention to latency, energy efficiency, scalability, and the trade-offs between distributed and centralized processing resources.

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Energy Efficient Survivable IP-Over-WDM Networks With Network Coding

Cited by 55 publications

References 22 publications

Bounds for Energy-Efficient Survivable IP Over WDM Networks With Network Coding

Bounds for Energy-Efficient Survivable IP Over WDM Networks With Network Coding

Disaggregation for Improved Efficiency in Fog Computing Era

Cloud Fog Architectures in 6G Networks

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