In grid networks, distributed resources are interconnected by wide area network to support compute and data-intensive applications, which require reliable and efficient transfer of gigabits (even terabits) of data. Different from best-effort traffic in Internet, bulk data transfer in grid requires bandwidth reservation as a fundamental service. Existing reservation schemes such as RSVP are designed for real-time traffic specified by reservation rate, transfer start time but with unknown lifetime. In comparison, bulk data transfer requests are defined in terms of volume and deadline, which provide more information, and allow more flexibility in reservation schemes, i.e., transfer start time can be flexibly chosen, and reservation for a single request can be divided into multiple intervals with different reservation rates. We define a flexible reservation framework using time-rate function algebra, and identify a series of practical reservation scheme families with increasing generality and potential performance, namely, FixTime-FixRate, FixTime-FlexRate, FlexTime-FlexRate, and Multi-Interval. Simple heuristics are used to select representative scheme from each family for performance comparison. Simulation results show that the increasing flexibility can potentially improve system performance, minimizing both blocking probability and mean flow time. We also discuss the distributed implementation of proposed framework.
Time-indexed reservation is needed when considering advance reservation of bandwidth @cite_10 , which allows requesting bandwidth before actual transfer is ready to happen. For example, a scheduled tele-conference may reserve bandwidth for a specified future time interval. @cite_2 shows that advance reservation causes bandwidth fragmentation in time axis, which may significantly reduce accept probability of requests arriving later. To address the problem, they propose the concept of , which defines advance reservation request with flexible start time and rate.
@cite_10 @cite_2
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In general, two types of resource reservations in computer networks can be distinguished: immediate reservations which are made in a just-in-time manner and advance reservations which allow to reserve resources a long time before they are actually used. Advance reservations are especially useful for grid computing but also for a variety of other applications that require network quality-of-service, such as content distribution networks or even mobile clients, which need advance reservation to support handovers for streaming video. With the emerged MPLS standard, explicit routing can be implemented also in IP networks, thus overcoming the unpredictable routing behavior which so far prevented the implementation of advance reservation services. The impact of such advance reservation mechanisms on the performance of the network with respect to the amount of admitted requests and the allocated bandwidth has so far not been examined in detail. We show that advance reservations can lead to a reduced performance of the network with respect to both metrics. The analysis of the reasons shows a fragmentation of the network resources. In advance reservation environments, additional new services can be defined such as malleable reservations and can lead to an increased performance of the network. Four strategies for scheduling malleable reservations are presented and compared. The results of the comparisons show that some strategies increase the resource fragmentation and are therefore unsuitable in the considered environment while others lead to a significantly better performance of the network. Besides discussing the performance issue, the software architecture of a management system for advance reservations is presented. With the fast development of the Internet, more and more distributed applications will require guaranteed quality of service and maintain minimum network resource during their running sessions. Reservation in advance provides a solution for the need of reserving the network resource for future use like we make reservations in advance in our daily business. Routing has a critical effect on the network reservation process. In this paper, we propose a hierarchical data structure, the bandwidth tree, which records the intervals of available link bandwidth instead of unit time slot. The storage space and searching time complexity under this data structure are independent of the size of the time slots. This overcomes the difficulty in previously proposed research in which larger time slot size loses routing accuracy while smaller time slot size significantly increases routing complexity. The new data structure significantly improves the running time complexity for routing procedures under a variety of QoS requirements. Bandwidth is an extremely valuable and scarce resource in mobile networks; therefore, efficient mobility-aware bandwidth reservation is necessary to support multimedia applications (e.g., video streaming) that require quality of service (QoS). In this paper, we propose a distributed bandwidth reservation scheme called the mobility-prediction-aware bandwidth reservation (MPBR) scheme. The objective of MPBR is to reduce handoff call dropping rate and maintain acceptable new call blocking rate while providing efficient bandwidth utilization. MPBR consists of 1) a handoff time estimation (HTE) scheme that aims to estimate the time windows when a user will perform handoffs along the path to his destination, 2) an available bandwidth estimation (ABE) scheme that aims to estimate in advance available bandwidth, during the computed time windows in the cells to be traversed by the user to his destination, and 3) an efficient call admission control (ECaC) scheme that aims to control bandwidth allocation in the network cells. The simulation results show that MPBR outperforms existing schemes in terms of reducing handoff call dropping rate. The problem we consider is motivated by allocating bandwidth slots to communication requests on a satellite channel under real time constraints. Accepted requests must be scheduled on nonintersecting rectangles in the time bandwidth Cartesian space with the goal of maximizing the benefit obtained from accepted requests. This problem turns out to be equal to the maximization version of the well known Dynamic Storage Allocation problem when storage size is limited and requests must be accommodated within a prescribed time interval. We present constant approximation algorithms for the problem introduced in this paper using as a basic step the solution of a fractional Linear Programming formulation. This problem has been independently studied by Bar- [BNBYF+00] with different techniques. Our approach gives an improved approximation ratio for the problem.