Real-Time Energy Price-Aware Anycast RWA for Scheduled Lightpath Demands in Optical Data Center Networks

The energy consumption of the data center networks and the power consumption associated with transporting data to the users is considerably large, and it constitutes a significant portion of their costs. Hence, development of energy efficient schemes is very crucial to address this problem. Our research considers the fixed window traffic allocation model and the anycast routing scheme to select the best option for the destination node. Proper routing schemes and appropriate combination of the replicas can take care of the issue for energy utilization and at the same time help diminish costs for the data centers. We have also considered the real-time pricing model (which considers price changes every hour) to select routes for the lightpaths. Hence, we propose an ILP to handle the energyaware routing and wavelength assignment (RWA) problem for fixed window scheduled traffic model, with an objective to minimize the overall electricity costs of a datacenter network by reducing the actual power consumption, and using low-cost resources whenever possible

Joint dimensioning of server and network infrastructure for resilient optical grids/clouds

We address the dimensioning of infrastructure, comprising both network and server resources, for large-scale decentralized distributed systems such as grids or clouds. We design the resulting grid/cloud to be resilient against network link or server failures. To this end, we exploit relocation: Under failure conditions, a grid job or cloud virtual machine may be served at an alternate destination (i.e., different from the one under failure-free conditions). We thus consider grid/cloud requests to have a known origin, but assume a degree of freedom as to where they end up being served, which is the case for grid applications of the bag-of-tasks (BoT) type or hosted virtual machines in the cloud case. We present a generic methodology based on integer linear programming (ILP) that: 1) chooses a given number of sites in a given network topology where to install server infrastructure; and 2) determines the amount of both network and server capacity to cater for both the failure-free scenario and failures of links or nodes. For the latter, we consider either failure-independent (FID) or failure-dependent (FD) recovery. Case studies on European-scale networks show that relocation allows considerable reduction of the total amount of network and server resources, especially in sparse topologies and for higher numbers of server sites. Adopting a failure-dependent backup routing strategy does lead to lower resource dimensions, but only when we adopt relocation (especially for a high number of server sites): Without exploiting relocation, potential savings of FD versus FID are not meaningful

Energy Efficient Anycast Routing for Sliding Scheduled Lightpath Demands in Optical Grids

Optical grids have been thought as an answer to support large-scale data intensive applications. Data centers and Optical grids are largest and fastest growing consumers of electricity. Energy efficient routing schemes and traffic models can answer the problem of energy consumption. In Optical Grids, it is possible to select destination node from the set of possible destinations which is known as anycasting. We propose ILP formulations for flexible sliding scheduled traffic model, where setup and tear down times may vary within larger window frame. The problem of energy consumption is addressed by switching off ideal network components in low utilization periods. Our proposed novel formulation that exploits knowledge of demand holding times to optimally schedule demands achieved 7-13% reduction in energy consumption compared to previously best known model

Energy-efficient resource-provisioning algorithms for optical clouds

Rising energy costs and climate change have led to an increased concern for energy efficiency (EE). As information and communication technology is responsible for about 4% of total energy consumption worldwide, it is essential to devise policies aimed at reducing it. In this paper, we propose a routing and scheduling algorithm for a cloud architecture that targets minimal total energy consumption by enabling switching off unused network and/or information technology (IT) resources, exploiting the cloud-specific anycast principle. A detailed energy model for the entire cloud infrastructure comprising a wide-area optical network and IT resources is provided. This model is used to make a single-step decision on which IT end points to use for a given request, including the routing of the network connection toward these end points. Our simulations quantitatively assess the EE algorithm's potential energy savings but also assess the influence this may have on traditional quality-of-service parameters such as service blocking. Furthermore, we compare the one-step scheduling with traditional scheduling and routing schemes, which calculate the resource provisioning in a two-step approach (selecting first the destination IT end point and subsequently using unicast routing toward it). We show that depending on the offered infrastructure load, our proposed one-step calculation considerably lowers the total energy consumption (reduction up to 50%) compared to the traditional iterative scheduling and routing, especially in low-to medium-load scenarios, without any significant increase in the service blocking

Heuristic for Lowering Electricity Costs for Routing in Optical Data Center Networks

Optical data centers consume a large quantity of energy and the cost of that energy has a significant contribution to the operational cost in data centers. The amount of electricity consumption in data centers and their related costs are increasing day by day. Data centers are geographically distributed all around the continents and the growing numbers of data replicas have made it possible to find more cost effective network routing. Besides flat-rate prices, today, there are companies which offers real-time pricing. In order to address the energy consumption cost problem, we propose an energy efficient routing scheme to find least cost path to the replicas based on real-time pricing model called energy price aware routing (EPAR). Our research considers anycast data transmission model to find the suitable replica as well as the fixed window traffic allocation model for demand request to reduce the energy consumption cost of data center networks

Energy aware routing in optical grid networks

In the recent years due to rapid increase in the high-bandwidth applications there is a need for developing the energy efficient routing in the WDM optical Networks. Many researchers have addressed this problems in different ways by putting the network components into sleep mode or switching o the network components in low utilization periods. In this thesis our proposed method uses the principle of anycast routing, where it is possible to select any one of the possible destinations from the set of available destination nodes to complete the work. A novel genetic algorithm is used for solving this problem for scheduled lightpath demands (SLD), where the start and end times of the demands are known in advance.The fitness function used in the genetic algorithm not only minimizes the power consumption of the network but also minimizes the overall(transceiver) cost of the network by minimizing the total number of lightpaths needed to implement each logical edge. The proposed method minimizes the number of lightpaths and selects a suitable route for each demand so that the power consumed by the optical grid networks can be reduced, which results in significant energy savings