This work examines ways to improve energy efficiency in big data networks in Iraq under the veracity dimension by designing an IP/WDM Network in Iraq for processing big data and developing an algorithm that condenses the distinctive features of veracity. The analysis is based on preparing big data chunks for progressive processing after performing cleansing operations as proposed in this work. This is done in Processing Nodes (PNs) that consist of several servers and their associated network equipment, such as switches and routers. The PNs are distributed in the network for each city, and the cleansed data is handled at each PN, reducing the size of valuable data to be transmitted. Each cleansed chunk is also stored in a Backup Node (BN) for future use. Around a 50% power saving is achieved using this technique compared to the traditional method with no progressive processing.

The popularity of the Internet and the demand for 24/7 services uptime is driving system performance and reliability requirements to levels that today's data centers can no longer support. This paper examines the traditional monolithic conventional server (CS) design and compares it to a new design paradigm: the disaggregated server (DS) data center design. The DS design arranges data centers resources in physical pools, such as processing, memory, and IO module pools, rather than packing each subset of such resources into a single server box. In this paper, we study energy efficient resource provisioning and virtual machine (VM) allocation in DS-based data centers compared to CS-based data centers. First, we present our new design for the photonic DS-based data center architecture, supplemented with a complete description of the architectural components. Second, we develop a mixed integer linear programming (MILP) model to optimize VM allocation for the DS-based data center, including the data center communication fabric power consumption. Our results indicate that, in DS data centers, the optimum allocation of pooled resources and their communication power yields up to 42% average savings in total power consumption when compared with the CS approach. Due to the MILP high computational complexity, we developed an energy efficient resource provisioning heuristic for DS with communication fabric (EERP-DSCF), based on the MILP model insights, with comparable power efficiency to the MILP model. With EERP-DSCF, we can extend the number of served VMs, where the MILP model scalability for a large number of VMs is challenging. Furthermore, we assess the energy efficiency of the DS design under stringent conditions by increasing the CPU to memory traffic and by including high noncommunication power consumption to determine the conditions at which the DS and CS designs become comparable in power consumption. Finally, we present a complete analysis of the communication patterns in our new DS design and some recommendations for design and implementation challenges.

This article introduces an energy efficient heuristic that performs resource provisioning and Virtual Machine (VM) migration in the Disaggregated Server (DS) schema. The DS is a promising paradigm for future data centers where servers' components are disaggregated at the hardware unit levels and resources of similar type are combined in type respective pools, such as processing pools, memory pools and IO pools. We examined 1000 VM requests that demand various processing, memory and IO requirements. Requests have exponentially distributed inter arrival time and with uniformly distributed service duration periods. Resources occupied by a certain VM are released when the VM finishes its service duration. The heuristic optimises VMs allocation and dynamically migrates existing VMs to occupy newly released energy efficient resources. We assess the energy efficiency of the heuristic by applying increasing service duration periods. The results of the numerical simulation indicate that our power savings can reach up to 55% when compared to our pervious study where VM service duration is infinite and resources are not released.

With the dawn of cloud computing, data centers' power consumption has received increased attention. In this paper we evaluate the energy efficiency potential of exploiting the concept of Disaggregated Server (DS) design in data centers for efficient resource provisioning. A DS, is a new approach for future racks where servers are disaggregated and resources, such as processors, memory and IO ports are arranged in resource pools constructing processing pools, memory pools and IO pools. We developed a mixed integer linear programming (MILP) model for energy minimization of the virtual machine (VM) placement problem in data centres implementing DS approach. The results show that the average power savings are up to 49% for the different VM types considered.

In this paper we discuss the new paradigm of disaggregated servers (DS) and present our energy efficient heuristic for the energy minimization of virtual machine (VM) placement in data centres implementing the DS approach.

Stochastic assessment is a method to predict the severity and number of voltage sags at a bus of interest in the transmission network. In this paper, a technique using impedance matrix for stochastic assessment was developed to predict the voltage magnitudes due to faults at any bus in the electrical network. The proposed technique was applied to IEE 24- bus electrical network to illustrate its application. The results show that the proposed technique is able to compute the predicted voltage magnitude at any bus and the number of sags per year.

The envisaged increased penetration of distributed generation (DG) in electrical power networks poses challenging technical and contractual issues to both utilities and industry. Technical issues related to power quality, in particular to voltage-sag propagation and characteristics in networks with a large penetration of fixed speed wind DG are addressed. A comprehensive analysis of voltage-sag propagation in a realistic distribution network is performed. The influence of network topology, location and percentage of connected wind generation, network loading and load composition is investigated in detail. It is shown that the influence of DG on voltage-sag characteristics and propagation is strongly dependent on its location and on load composition.