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High-performance networks are capable of provisioning dedicated channels through circuit/lambda-switching or MPLS/GMPLS techniques to support large-scale data transfer. These dedicated links are typically shared by multiple users through advance resource reservations, resulting in varying bandwidth availability in future time periods. Most previous efforts were focused on centralized bandwidth scheduling to improve the utilization of network resources and meet the transport requirements of application users. These centralized scheduling schemes imply the use of a central control plane, posing significant reliability and scalability challenges as the network size rapidly grows. We propose distributed algorithms for path computation and bandwidth scheduling in response to four basic bandwidth reservation requests: (i) fixed bandwidth in a fixed slot, (ii) highest bandwidth in a fixed slot, (iii) first slot with fixed bandwidth and duration, and (iv) all slots with fixed bandwidth and duration. These algorithms are developed through a rigorous extension of the classical breadth first search and Bellman-Ford algorithms to a completely distributed manner, and their performances are evaluated and analyzed through extensive simulations.

Data transmission from sensor nodes to a base station or a sink node often incurs significant energy consumption, which critically affects network lifetime. We generalize and solve the problem of deploying multiple base stations to maximize network lifetime in terms of two different metrics under one-hop and multihop communication models. In the one-hop communication model, the sensors far away from base stations always deplete their energy much faster than others. We propose an optimal solution and a heuristic approach based on the minimal enclosing circle algorithm to deploy a base station at the geometric center of each cluster. In the multihop communication model, both base station location and data routing mechanism need to be considered in maximizing network lifetime. We propose an iterative algorithm based on rigorous mathematical derivations and use linear programming to compute the optimal routing paths for data transmission. Simulation results show the distinguished performance of the proposed deployment algorithms in maximizing network lifetime.

There are an increasing number of high-performance networks that provision dedicated channels through circuit-switching or MPLS/GMPLS techniques to support bulk data transfer in large-scale science or e-commerce applications. These dedicated links are typically shared by multiple users through advance reservations, resulting in varying bandwidth availability in future time periods. Therefore, efficient advance bandwidth reservation algorithms are needed to improve the utilization of network resources and meet the transport requirements of application users. We investigate the bandwidth-oriented path computation problem for two types of data transfer: (i) fixed path with variable bandwidth and (ii) variable path with variable bandwidth to minimize the transfer end time of a given data size. We prove that both problems are NP-complete and propose a heuristic algorithm for each of them. Extensive simulation results illustrate the performance superiority of the proposed heuristics over methods based on greedy strategies.

Sensor network lifetime is largely affected by the energy consumption for data transmission from sensor nodes to a base station. We generalize and solve the problems of deploying multiple base stations in sensor networks using one-hop and multi-hop communication models to maximize network lifetime. Under the one-hop communication model, the sensors far away from base stations always deplete their energy much faster than others. We propose an optimal solution for small-scale networks and a heuristic approach for large-scale ones based on the smallest enclosing circle algorithm that deploys a base station at the geometric center of each cluster. Under the multi-hop communication model, both the base station locations and the data routing scheme need to be considered in maximizing network lifetime. We propose an iterative algorithm based on rigorous mathematical derivations and use linear programming to compute the optimal routing path for benchmark purposes. Extensive simulation results show superior network lifetime performance of the proposed deployment algorithms in comparison with existing ones.

The significance of high-performance dedicated networks has been well recognized due to the rapidly increasing number of large-scale applications that require high-speed data transfer. Efficient algorithms are needed for path computation and bandwidth scheduling in dedicated networks to improve the utilization of network resources and meet diverse user requests. We consider two periodic bandwidth scheduling problems: multiple data transfer allocation (MDTA) and multiple fixed-slot bandwidth reservation (MFBR), both of which schedule a number of user requests accumulated in a certain period. MDTA is to assign multiple data transfer requests on several pre-specified network paths to minimize the total data transfer end time, while MFBR is to satisfy multiple bandwidth reservation requests, each of which specifies a bandwidth and a time slot. For MDTA, we design an optimal algorithm and provide its correctness proof; for MFBR, we prove it to be NP-complete and propose a heuristic algorithm, Minimal Bandwidth and Distance Product Algorithm (MBDPA). Extensive simulation results illustrate the performance superiority of the proposed MBDPA over a greedy heuristic approach and provide valuable insight into the advantage of periodic bandwidth scheduling over instant bandwidth scheduling.

There are an increasing number of high- performance networks that provision dedicated channels through circuit-switching or MPLS/GMPLS techniques to support large- scale data transfer. The available bandwidths on these dedicated links vary over time and therefore efficient bandwidth scheduling algorithms are needed to improve the utilization of network resources and satisfy diverse user requirements. Based on different path and bandwidth constraints, we formulate four instant scheduling problems for a data transfer request: (i) variable path with variable bandwidth (VPVB), (ii) fixed path with variable bandwidth (FPVB), (iii) variable path with fixed bandwidth (VPFB), and (iv) fixed path with fixed bandwidth (FPFB), with the common objective to minimize transfer end time for a given data size. We design an optimal algorithm for each of these scheduling problems with polynomial- or pseudo- polynomial-time complexity with respect to the network size and total number of time slots in a bandwidth reservation table.

An increasing number of high performance research network testbeds and production networks have the capability of provisioning dedicated channels for high speed data transfer in support of large scale scientific applications. Each dedicated channel in these networks typically consists of one or more physical links that are shared by multiple applications in both time and bandwidth through in advance reservation. The design of efficient bandwidth scheduling algorithms is critical to maximizing the utilization of dedicated network resources and meeting diverse end-to-end transport performance requirements. The topology of a dedicated network is represented by a graph, where each link maintains a list of residual bandwidths specified as segmented constant functions of time. Given a graph with an aggregated time-bandwidth table combining the reservation information on all links, designated source, and destination vertices, and a specified data size, we formulate and investigate five bandwidth scheduling problems to minimize the data transfer end time under different path and bandwidth constraints: (i) variable path with variable bandwidth (VPVB), which computes the widest (highest bandwidth) path in each time slot; (ii) fixed path with variable bandwidth (FPVB), which computes a fixed path with varying bandwidths across different time slots; (iii) variable path with fixed bandwidth (VPFB), which computes one path in each time slot with the same bandwidth; (iv) fixed path with fixed bandwidth (FPFB), which computes a fixed path with a constant bandwidth; and (v) multiple fixed paths with fixed bandwidths (MFPFB), which computes multiple concurrent fixed paths with constant bandwidths. Among these problems, VPVB represents the most flexible scenario where the network resources are fully utilized and the minimal transfer end time is achieved, while FPFB imposes the most stringent transport conditions by fixing both path and bandwidth. We design an optimal algorithm for each of these scheduling problems. VPVB is solved using an extension of the classical Dijkstra's algorithm, and FPVB is solved using Maximum Permutation Algorithm, which tries all possible permutations of throughputs at different time slots to obtain the minimal transfer end time. The algorithm for VPFB, FPFB, and MFPFB are based on Adjacent Time Slots Search, which finds the minimum transfer end time by examining the possibility of data transfer in any number of contiguous time slots. All these algorithms are of polynomial or pseudo polynomial time complexity with respect to the network size and the total number of time slots in a bandwidth reservation table.