Sumit Naiksatam

Elastic reservations for efficient bandwidth utilization in LambdaGrids

We introduce the concept of elastic reservation of bandwidth capacity to mitigate the problem of bandwidth fragmentation in LambdaGrids and present a network model which can support elastic reservations. We also define the Elastic Scheduling Problem (ESP), which succinctly captures the optimal utilization objective of elastic reservations. Analysis of ESP reveals that it is an NP-complete problem. Hence we present a heuristic algorithm, Squeeze In Stretch Out (SISO), for tackling ESP in polynomial time. SISO achieves good bandwidth utilization in simulation and efficiently handles the dynamic sharing of bandwidth between advance and immediate reservation requests. We also explore the impact of cost incentives for adopting elastic reservations on both the service provider and the user. In general, the approach for elastic reservation and scheduling presented in this paper is applicable to any concurrently accessible resource where the usage characteristics are quasi-flexible.

DWDM-RAM: enabling Grid services with dynamic optical networks

Advances in Grid technology enable the deployment of data-intensive distributed applications, which require moving terabytes or even petabytes of data between data banks. The current underlying networks cannot provide dedicated links with adequate end-to-end sustained bandwidth to support the requirements of these Grid applications. DWDM-RAM is a novel service-oriented architecture, which harnesses the enormous bandwidth potential of optical networks and demonstrates their on-demand usage on the OMNInet. Preliminary experiments suggest that dynamic optical networks, such as the OMNInet, are the ideal option for transferring such massive amounts of data. DWDM-RAM incorporates an OGSI/OGSA compliant service interface and promotes greater convergence between dynamic optical networks and data intensive Grid computing.

Analyzing the advance reservation of lightpaths in lambda-grids

The scheme of advance reservations in dynamically provisioned optical networks is novel, and there are no grid-based applications designed to utilize this scheme. We formally define and analyze this scheme and present a constrained mathematical model for advance reservations. We also introduce FONTS - the Flexible Optical Network Traffic Simulator, a tool for simulating advance reservation, on-demand, and periodic data transfer requests. FONTS is based on a stochastic model and incorporates a variety of variables, which have been identified to accurately model advance reservation requests. FONTS validates the mathematical model and also helps to analyze complex scenarios beyond the scope of this paper.

DWDM-RAM: a data intensive Grid service architecture enabled by dynamic optical networks

Next generation applications and architectures (for example, Grids) are driving radical changes in the nature of traffic, service models, technology, and cost, creating opportunities for an advanced communications infrastructure to tackle next generation data services. To take advantage of these trends and opportunities, research communities are creating new architectures, such as the Open Grid Service Architecture (OGSA), which are being implemented in new prototype advanced infrastructures. The DWDM-RAM project, funded by DARPA, is actively addressing the challenges of next generation applications. DWDM-RAM is an architecture for data-intensive services enabled by next generation dynamic optical networks. It develops and demonstrates a novel architecture for new data communication services, within the OGSA context, that allows for managing extremely large sets of distributed data. Novel features move network services beyond notions of the network as a managed resource, for example, by including capabilities for dynamic on-demand provisioning and advance scheduling. DWDM-RAM encapsulates optical network resources (Lambdas, lightpaths) into a Grid service and integrates their management within the Open Grid Service Architecture. Migration to emerging standards such as WS-Resource Framework (WS-RF) should be straightforward. In initial applications, DWDM-RAM targets specific data-intensive services such as rapid, massive data transfers used by large scale eScience applications, including: high-energy physics, geophysics, life science, bioinformatics, genomics, medical morphometry, tomography, microscopy imaging, astronomical and astrophysical imaging, complex modeling, and visualization.

Retrospective Scheduling of Elastic Bandwidth Reservations in LambdaGrids

Tfie ability to reserve network bandwidth is critical for the success of high-performance grid applications. While reservation of lightpaths in dynamically switched optical networks facilitates guaranteed bandwidth, it is also imperative to effectively schedule these bandwidth reservations so as to orchestrate workflows involving computational, storage, and network resources. However, reservation can often lead to bandwidth fragmentation which significantly reduces system utilization and increases the blocking probability of requests. In this paper, we present a dynamic bandwidth scheduling scheme which exploits the quasi-flexible nature of bandwidth reservations and mitigates the problem of bandwidth fragmentation in LambdaGrids

Efficient bandwidth utilization in LambdaGrids using pricing incentives

The ability to reserve network bandwidth is a critical factor for the success of high-performance grid applications. Reservation of lightpaths in dynamically switched optical networks facilitates guaranteed bandwidth. However, reservation of bandwidth can often lead to bandwidth fragmentation which significantly reduces system utilization and increases the blocking probability of the network. An interesting approach to mitigating this problem is to induce quasi-flexibility in the user requests. A smart scheduling strategy can then exploit this quasi-flexibility and optimize bandwidth utilization. However, there has to be an incentive for flexibility from the users perspective as well. In this paper, we explore how the network service provider (NSP) can influence user flexibility by dynamically engineering pricing incentives. Ultimately, user flexibility will lead to efficient network utilization, reduce the price for the users, and increase the revenue for the NSP.

Engineering pricing incentives for efficient bandwidth utilization in LambdaGrids

The ability to reserve network bandwidth is a critical factor for the success of high-performance grid applications. Reservation of lightpaths in dynamically switched optical networks facilitates guaranteed bandwidth. However, reservation of bandwidth can often lead to bandwidth fragmentation which significantly reduces system utilization and increases the blocking probability of requests. An interesting approach to mitigating this problem is to induce quasi-flexibility in the user requests. A smart scheduling strategy can then exploit this quasi-flexibility and optimize bandwidth utilization. However, there has to be an incentive for flexibility from the users perspective as well. In this paper, we explore how the Network Service Provider (NSP) can influence user flexibility by dynamically engineering pricing incentives. Ultimately, user flexibility will lead to efficient network utilization, reduce the price for the users, and increase the revenue for the NSP.

Triumph of the Bandwidth Commons: Elastic Reservations, Price Incentives, and Request Realignement in LambdaGrids

Reservation of lightpaths in dynamically switched optical networks facilitates guaranteed bandwidth. However, reservation of bandwidth can often lead to bandwidth fragmentation which significantly reduces system utilization and increases the blocking probability of requests. An interesting approach to mitigating this problem is to induce quasi-flexibility in the user requests. A smart scheduling strategy can then exploit this quasi- flexibility and optimize bandwidth utilization. However, there has to be an incentive for flexibility from the users perspective as well. In this paper, we explore how the network service provider (NSP) can influence user flexibility by dynamically engineering pricing incentives and by suggesting request realignment to overcome reservation contention. Ultimately, user flexibility will lead to efficient network utilization, reduce the price for the users, and increase the revenue for the NSP.