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Wafaa B. M. Fadlelmula

Publications and source records attributed to Wafaa B. M. Fadlelmula.

6 recordsLinked to original sources

Energy-Efficient Joint Optimization of VLC and Fog Computing Resources Allocation

In this paper, we consider an indoor networking architecture in which visible light communication (VLC) provides wireless connectivity between users and distributed fog computing resources and an energy-efficient passive optical network (PON)- based backhaul interconnects the VLC access points (APs). We investigate the joint optimization of the allocation of VLC and fog computing resources aiming to minimize processing and networking power consumption. We develop a mixed-integer linear programming (MILP) model that jointly optimizes access points (APs) selection, wavelength assignment and fog computing resources allocation to serve the requests of users. Compared to a statically preconfigured AP selection and wavelength assignment based on maximizing signal-to-interference-plus-noise ratio (SINR) independently of fog resource placement, the joint optimization achieves lower average total power consumption, driven by a reduction in processing power. These savings are attributed to the ability of the joint optimization to allow AP sharing across users and selecting more energy-efficient wavelengths that still satisfy quality of service (QoS) requirements.

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Energy Efficient Point-to-Point PON-based Architecture for the Backhaul of a VLC System

This paper proposes a point-to-point passive optical network (P2P-PON) architecture as an energy-efficient and low-latency backhaul solution for visible light communication (VLC)-enabled indoor fog computing systems. The proposed architecture passively interconnects VLC access points and distributed in-building fog servers through dedicated optical links, enabling flexible peer-to-peer connectivity and efficient traffic aggregation. A mixed integer linear programming (MILP) framework is developed to jointly optimize processing resource allocation, traffic routing, power consumption, and end-to-end queuing delay across a multi-layer fog computing infrastructure. The model explicitly captures the power consumption of both networking and processing elements and incorporates a piecewise linear approximation of an M/M/1 queuing model to represent delay-sensitive applications. The performance of the proposed P2P-PON architecture is evaluated and compared against an arrayed waveguide grating router (AWGR)-based PON architecture under multiple indoor traffic scenarios. The results show that the proposed P2P-PON architecture reduces total power consumption by up to 64\% under power-aware optimization and by 15\% under delay-aware optimization, while reducing average end-to-end queuing delay by up to 76\% compared to the AWGR-PON architecture, due to the improved in-building connectivity and more effective utilization of distributed fog resources.

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Energy-efficient PON-based Backhaul Connectivity for a VLC-enabled Indoor Fog Computing Environment

In this paper, we consider the use of visible light communication (VLC) to provide connectivity to indoor fog computing resources and propose an energy-efficient passive optical network (PON)-based backhaul architecture to support the VLC system. We develop a mixed-integer linear programming (MILP) model to optimize the allocation of computing resources over the proposed architecture, aiming to minimize processing and networking power consumption. We evaluate the performance of the proposed architecture under varying workload demands and user distributions. Comparative analysis against a backhaul architecture that is based on the state-of-the-art spine-and-leaf (S&L) network design demonstrates total power savings of up to 82%. Further comparison with centralized cloud processing shows improvements in energy efficiency of up to 93%. Additionally, we examine the improvements in energy efficiency obtained by splitting tasks among multiple processing nodes and propose enhancements to the architecture including dynamic bandwidth allocation, increased wavelength bandwidth and improved connectivity within rooms to alleviate networking bottlenecks. Furthermore, we introduce an inter-building architecture that leverages resources from neighboring buildings to support high-demand scenarios.

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Energy Efficient Resource Allocation for Demand Intensive Applications in a VLC Based Fog Architecture

In this paper, we propose an energy efficient passive optical network (PON) architecture for backhaul connectivity in indoor visible light communication (VLC) systems. The proposed network is used to support a fog computing architecture designed to allow users with processing demands to access dedicated fog nodes and idle processing resources in other user devices (UDs) within the same building. The fog resources within a building complement fog nodes at the access and metro networks and the central cloud data center. A mixed integer linear programming (MILP) model is developed to minimize the total power consumption associated with serving demands over the proposed architecture. A scenario that considers applications with intensive demands is examined to evaluate the energy efficiency of the proposed architecture. A comparison is conducted between allocating the demands in the fog nodes and serving the demands in the conventional cloud data center. Additionally, the proposed architecture is compared with an architecture based on state-of-art Spine-and-Leaf (SL) connectivity. Relative to the SL architecture and serving all the demands in the cloud, the adoption of the PON-based architecture achieves 84% and 86% reductions, respectively.

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Energy Efficient PON Backhaul Network for a VLC Based Fog Architecture

In this paper, an energy efficient passive optical network (PON) architecture is proposed for backhaul connectivity in indoor visible light communication (VLC) systems. The proposed network is used to support a fog computing architecture allowing users with processing demands to access dedicated fog nodes and idle processing resources in other user devices within a building. The fog resources within a building complement fog nodes at higher layers of the access and metro networks and the central cloud data center. A mixed integer linear programming (MILP) model is developed to minimize the total power consumption associated with serving demands over the proposed architecture. The results show that the PON backhaul network improves the energy efficiency of fog computing by 66% for networking and 12% for processing compared to an architecture based on state-of-the-art Spine-and-Leaf connectivity.

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Caching Video-on-Demand in Metro and Access Fog Data Centres

This paper examines the utilization of metro fog data centres and access fog datacentres with integrated solar cells and Energy Storage Devices (ESDs) to assist cloud data centres in caching Video-on-Demand content and hence, reduce the networking power consumption. A Mixed Integer Linear Programming (MILP) model is used to optimize the delivery of the content from cloud, metro fog, or access fog datacentres. The results for a range of data centre parameters show that savings by up to 38% in the transport network power consumption can be achieved when VoD is optimally served from fully renewable-powered cloud or metro fog data centres or from access fog data centres with 250 m2 solar cells. Additional 8% savings can be achieved when using ESDs of 100 kWh capacity in the access fog data centres.

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