Network planning and design

About: Network planning and design is a research topic. Over the lifetime, 12393 publications have been published within this topic receiving 229776 citations. The topic is also known as: network design.

Method and system for bandwidth allocation for multimedia services under aggregate traffic conditions

Abstract: A method and system are provided for calculating the most efficient bandwidth allocation for multimedia traffic under aggregate traffic conditions within a shared transmission medium, such as an ATM network, in a manner which maximizes long term revenue First, the total number of service groups within the network is specified by a network operator or a network designer Each service group may contain multiple different types of communication traffic Thereafter, for each service group, the number of users who utilize the services within that service group is determined The average idle sojourn time and average burst sojourn time for each system state are then determined for each service group Next, a specification of the peak rate, the probability that a user will access the service during a specified busy period, and an average session duration are determined A specification of the price of each service per unit time is then provided by the network operator as well as the total available bandwidth in bits per second Thereafter, these parameters are utilized to partition the bandwidth within the network among the various service groups so as to maximize long-run average system revenue

A matheuristic for the liner shipping network design problem

Abstract: We present an integer programming based heuristic, a matheuristic, for the liner shipping network design problem. This problem consists of finding a set of container shipping routes defining a capacitated network for cargo transport. The objective is to maximize the revenue of cargo transport, while minimizing the cost of operating the network. Liner shipping companies publish a set of routes with a time schedule, and it is an industry standard to have a weekly departure at each port call on a route. A weekly frequency is achieved by deploying several vessels to a single route, respecting the available fleet of container vessels. The matheuristic is composed of four main algorithmic components: a construction heuristic, an improvement heuristic, a reinsertion heuristic, and a perturbation heuristic. The improvement heuristic uses an integer program to select a set of improving port insertions and removals on each service. Computational results are reported for the benchmark suite LINER-LIB 2012 following the industry standard of weekly departures on every schedule. The heuristic shows overall good performance and is able to find high quality solutions within competitive execution times. The matheuristic can also be applied as a decision support tool to improve an existing network by optimizing on a designated subset of the routes. A case study is presented for this approach with very promising results.

Integer Programming and Network Models

Abstract: Basic Definitions and Results.- Integer Programming.- Network Path Models.- Network Flow and Network Design Models.

Decomposition-based multi-objective firefly algorithm for RFID network planning with uncertainty

Abstract: Graphical abstractDisplay Omitted HighlightsUncertainty is considered in RFID network planning.RFID network planning is modelled as a multi-objective optimization.A novel multi-objective firefly algorithm is proposed to solve multi-objective RFID network planning.Numerical experiments show the effectiveness of the proposed firefly algorithm for multi-objective RFID network planning. Radio frequency identification (RFID) is widely used for item identification and tracking. Due to the limited communication range between readers and tags, how to configure a RFID system in a large area is important but challenging. To configure a RFID system, most existing results are based on cost minimization through using 0/1 identification model. In practice, the system is interfered by environment and probabilistic model would be more reliable. To make sure the quality of the system, more objectives, such as interference and coverage, should be considered in addition to cost. In this paper, we propose a probabilistic-based multi-objective optimization model to address these challenges. The objectives to be optimized include number of readers, interference level and coverage of tags. A decomposition-based firefly algorithm is designed to solve this multi-objective optimization problem. Virtual force is integrated into random walk to guide readers moving in order to enhance exploitation. Numerical simulations are introduced to demonstrate and validate our proposed method. Comparing with existing methods, such as Non-dominated Sorting Genetic Algorithm-II and Multi-objective Particle Swarm Optimization approaches, our proposed method can achieve better performance in terms of quality metric and generational distance under the same computational environment. However, the spacing metric of the proposed method is slightly inferior to those compared methods.

System and Method for Performing Network Selection

Abstract: The system and methods of the various embodiments enable fine grained network selection decisions. This may allow a mobile network operator, a cable operator, or a Wi-Fi network operator to define network selection rules that are not only based upon network availability, time, and location, but also on network signal strength, signal to noise ratio, link speed, and cellular network radio parameters. These rules may also be complimented with local device based policies and parameters, which may possibly be based on user preferences and/or network operator preferences. The system and methods of the various embodiments also prevent inadvertent Wi-Fi network selection decisions by incorporating a time threshold parameter which defines a time period for which a wireless device must have detected a specific Wi-Fi access point prior to performing network selection.