Virtual Machines Embedding for Cloud PON AWGR and Server Based Data Centres

In this study, we investigate the embedding of various cloud applications in PON AWGR and Server Based Data Centres

Energy Efficient Cloud Networks

Cloud computing is expected to be a major factor that will dominate the future Internet service model. This paper summarizes our work on energy efficiency for cloud networks. We develop a framework for studying the energy efficiency of four cloud services in IP over WDM networks: cloud content delivery, storage as a service (StaaS), and virtual machines (VMS) placement for processing applications and infrastructure as a service (IaaS).Our approach is based on the co-optimization of both external network related factors such as whether to geographically centralize or distribute the clouds, the influence of users’ demand distribution, content popularity, access frequency and renewable energy availability and internal capability factors such as the number of servers, switches and routers as well as the amount of storage demanded in each cloud. Our investigation of the different energy efficient approaches is backed with Mixed Integer Linear Programming (MILP) models and real time heuristic

Joint optimization of power, electricity cost and delay in IP over WDM networks

In this paper, we investigate the joint optimization of power, electricity cost and propagation delay in IP over WDM networks employing renewable energy. We develop a mixed integer linear programming (MILP) model to jointly minimize the three parameters and compare its results to the results of optimizing these parameters individually. The models results show that the joint optimization maintains the power consumption and electricity cost savings obtained by the non-renewable powerminimized and the electricity cost-minimized models while hardly affecting the propagation delay. Compared to the delay-minimized model, the joint optimization model achieves power consumption and electricity cost savings of 73% and 74%, respectively under the non-bypass approach considering a unicasting traffic profile. The power and cost savings under an anycasting traffic profile increases to 82%

CORNETO: A Software System for Simulating and Optimizing Optical Networks

In this paper we present a software system that is being developed at the University of Leeds for simulating and optimizing energy efficient optical core networks. The system is called CORNETO, an acronym for CORe NETwork Optimization. The software implements many of the energy saving concepts, methods and computational heuristics that have been produced by the ongoing INTERNET, INTelligent Energy awaRe NETworks, project. The main objective of the software is to help network operators and planners green their networks while maintaining quality of service. In this paper we briefly describe the software and demonstrate its capabilities with two case studies

Internet of Things-aided Smart Grid: Technologies, Architectures, Applications, Prototypes, and Future Research Directions

Traditional power grids are being transformed into Smart Grids (SGs) to address the issues in existing power system due to uni-directional information flow, energy wastage, growing energy demand, reliability and security. SGs offer bi-directional energy flow between service providers and consumers, involving power generation, transmission, distribution and utilization systems. SGs employ various devices for the monitoring, analysis and control of the grid, deployed at power plants, distribution centers and in consumers' premises in a very large number. Hence, an SG requires connectivity, automation and the tracking of such devices. This is achieved with the help of Internet of Things (IoT). IoT helps SG systems to support various network functions throughout the generation, transmission, distribution and consumption of energy by incorporating IoT devices (such as sensors, actuators and smart meters), as well as by providing the connectivity, automation and tracking for such devices. In this paper, we provide a comprehensive survey on IoT-aided SG systems, which includes the existing architectures, applications and prototypes of IoT-aided SG systems. This survey also highlights the open issues, challenges and future research directions for IoT-aided SG systems

Cloud Virtual Network Embedding: Profit, Power and Acceptance

In this paper, we investigate maximizing the profit achieved by infrastructure providers (InPs) from embedding virtual network requests (VNRs) in IP/WDM core networks with clouds. We develop a mixed integer linear programming (MILP) model to study the impact of maximizing the profit on the power consumption and acceptance of VNRs. The results show that higher acceptance rates do not necessarily lead to higher profit due to the high cost associated with accepting some of the requests. The results also show that minimum power consumption can be achieved while maintaining the maximum profit

Energy efficiency of Optical OFDM-based networks

Orthogonal Frequency Division Multiplexing (OFDM) has been proposed as an enabling technique for elastic optical networks to support heterogeneous traffic demands. In this paper, we investigate the energy efficiency of rate and modulation adaptive optical OFDM-based networks. A mixed integer linear programming (MILP) model is developed to minimize the total power consumption of optical OFDM networks. We differentiate between two optimization schemes: power-minimized and spectrum-minimized optical OFDM-based networks. The results show that while similar power consumption savings of up to 31% are achieved by the two schemes compared to conventional IP over WDM networks, the spectrum-minimized optical OFDM is 51% more efficient in utilizing the spectrum compared to the power-minimized optical OFD