Channel assignment in cellular radio using genetic algorithms

The channel assignment problem has become increasingly important in mobile telephone communication. Since the usable range of the frequency spectrum is limited, the optimal assignment problem of channels has become increasingly important. Recently Genetic Algorithms (GAs) have been proposed as new computational tools for solving optimization problems. GAs are more attractive than other optimization techniques, such as neural networks or simulated annealing, since GAs are generally good at finding an acceptably good global optimal solution to a problem very quickly. In this paper, a new channel assignment algorithm using GAs is proposed. The channel assignment problem is formulated as an energy minimization problem that is implemented by GAs. Appropriate GAs operators such as reproduction, crossover and mutation are developed and tested. In this algorithm, the cell frequency is not fixed before the assignment procedures as in the previously reported channel assignment algorithm using neural networks. The average generation numbers and the convergence rates of GAs are shown as a simulation result. When the number of cells in one cluster are increased, the generation numbers are increased and the convergence rates are decreased. On the other hand, with the increased minimal frequency interval, the generation numbers are decreased and the convergence rates are increased. The comparison of the various crossover and mutation techniques in a simulation shows that the combination of two points crossover and selective mutation technique provides better results. All three constraints are also considered for the channel assignments: the co-channel constraint, the adjacent channel constraint and the co-site channel constraint. The goal of this paper is the assignment of the channel frequencies which satisfied these constraints with the lower bound number of channels.     

New algorithms for multicast routing and wavelength assignment in multi-hop optical WDM networks

We study the problem of multicast routing and wavelength assignment (MC-RWA) in multi-hop optical WDM networks with respect to several target functions. Specially, we first study the MC-RWA problem under the target of minimize maximum hops, an efficient MC-RWA algorithm was proposed for that case. But for the objective of minimizing the total number of wavelength conversions, problem turns out to be NP-hard, we proposed a new approximation MC-RWA algorithm based on group Steiner tree. At last, combining the two objectives, a bi-factor approximation algorithm was introduced to minimize the both targets in the system simultaneously.     

Optimization of spare capacity in self-healing multicast ATM network using genetic algorithm

The objective of this paper is to optimize the amount of spare capacity reserved for the backup virtual paths (BVPs) in multicast asynchronous transfer mode networks. In this paper, we study the capacity and routing assignment problem arising in the design of self-healing networks using the VP concept. A major contribution of this work is to apply a genetic algorithm (GA) to the backup path search process instead of the trivial exhaustive search method. Experimental results indicate that both approaches have very comparable results in finding the multicast backup paths. Further, it also indicated that using a GA approach has a number of advantages over the exhaustive search approach, such as the computational requirement for a GA in finding good BVPs is small when compared to the exhaustive search method. A major drawback of our approach is that we cannot guarantee the finding of global optimum in real time.     

New hybrid genetic algorithms for the frequency assignment problem

This paper presents a new hybrid genetic algorithm used to solve a frequency assignment problem. The hybrid genetic algorithm presented uses two original mutation and two crossover operators. Theses operators use specialized information to enhance the quality of the solutions. The results obtained by our algorithm are better than the best known results obtained by other methods like tabu search and hybrid genetic algorithm. Our results are validated in the field of radio broadcasting and compared to the best existing solutions in this domain     

Deploying AL-FEC protection with online algorithms for multicast services over cellular networks

Reliability control is a key concern on the evolution of mobile multicast services. To this direction, the use of forward error correction (FEC) on the application layer is widely adopted in several mobile multicast standards. FEC is a feedback free error control method, where the transmitter introduces in advance redundant information within the source data to enable receivers recovering arbitrary data erasures. On multicast delivery where retransmission-based error recovery methods are not efficient, the most suitable error control method is the use of application layer forward error correction (AL-FEC) codes. In this work, we introduce novel AL-FEC deployment policies over mobile multicast environments utilizing online algorithms. We aim at the efficient application of AL-FEC protection with RaptorQ codes over multicast delivery in the context of competitive analysis. We provide a competitiveness analysis model of AL-FEC application over mobile multicast environments. Furthermore, we propose two online algorithms adjusting the introduced redundancy of AL-FEC protection according to several FEC encoding parameters and constraints of mobile multicast delivery.     

Dynamic wavelength assignment for multicast in all-optical WDM networks to maximize the network capacity

We study the problem of wavelength assignment for multicast in order to maximize the network capacity in all-optical wavelength-division multiplexing networks. The motivation behind this work is to minimize the call blocking probability by maximizing the remaining network capacity after each wavelength assignment. While all previous studies on the same objective concentrate only on the unicast case, we study the problem for the multicast case. For a general multicast tree, we prove that the multicast wavelength assignment problem of maximizing the network capacity is NP-hard and propose two efficient greedy algorithms. We also study the same problem for a special network topology, a bidirectional ring network, which is practically the most important topology for optical networks. For bidirectional ring networks, a special multicast tree with at most two leaf nodes is constructed. Polynomial time algorithms for multicast wavelength assignment to maximize the network capacity exist under such a special multicast tree with regard to different splitting capabilities. Our work is the first effort to study the multicast wavelength assignment problem under the objective of maximizing network capacity.     

Scalable fair reliable multicast using active services

Scalability is of paramount importance in the design of reliable multicast transport protocols, and requires careful consideration of a number of problems such as feedback implosion, retransmission scoping, distributed loss recovery, and congestion control. In this article, we present a reliable multicast architecture that invokes active services at strategic locations inside the network to comprehensively address these challenges. Active services provide the ability to quickly and efficiently recover from loss at the point of loss. They also exploit the physical hierarchy for feedback aggregation and effective retransmission scoping with minimal router support. We present two protocols, one for packet loss recovery and another for congestion control, and describe an experimental testbed where these have been implemented. Analytical and experimental results are used to demonstrate that the active services architecture improves resource usage, reduces latency for loss recovery, and provides TCP-friendly congestion control     

基于遗传算法的光电干扰资源优化分配研究

结合光电信息系统作战运筹中目标分配原则，及军事运筹理论，建立了干扰资源优化分配模型。给出了基于遗传算法的模型求解方法及步骤，阐述了遗传算法在光电干扰资源分配中的应用，并进行了实例仿真，得出了最佳干扰资源分配方案。仿真结果证明，该方法对于约束条件复杂的优化模型求解是有效、可行的，为光电信息系统指挥控制决策提供了有力支持。     

多媒体通信的成组多点广播路由算法

多点广播是一源点传送信息到多个目的节点,成组多点广播是一组节点内部互相进行多点广播。成组多点广播的路由算法是为组内的每一个节点建立一棵路由树,用于点到多点的广播通信。本文提出一种新的成组广播路由算法,它比传统的成组广播路由算法在性能上有了一定的提高,同时更为简洁。     

Energy-saving scheduling for LTE multicast services

In the Long Term Evolution （LTE） downlink multicast scheduling, Base Station （BS） usually allocates transmit power equally among all Resource Blocks （RBs）, it may cause the waste of transmit power. To avoid it, this paper put forward a new algorithm for LTE multicast downlink scheduling called the Energy-saving based Inter-group Proportional Fair （EIPF）. The basic idea of EIPF is to calculate an appropriate transmitting power for each group according to its data rate respectively, and then follow the inter-group proportional fair principle to allocate RBs among multicast groups. The results of EIPF simulation show that the proposed algorithm not only can reduce the transmit power of BS effectively but also improve the utilization rate of energy.     

QoS-based multicast routing optimization algorithms for Internet

Most of the multimedia applications require strict Quality-of-Service （QoS） guarantee during the communication between a single source and multiple destinations. The paper mainly presents a QoS Multicast Routing algorithms based on Genetic Algorithm （QMRGA）. Simulation results demonstrate that the algorithm is capable of discovering a set of QoS-based near optimized, non-dominated multicast routes within a few iterations, even for the networks environment with uncertain parameters.     

Source-adaptive multilayered multicast algorithms for real-timevideo distribution

Layered transmission of data is often recommended as a solution to the problem of varying bandwidth constraints in multicast video applications. Multilayered encoding, however, is not sufficient to provide high video quality and high network utilization, since bandwidth constraints frequently change over time. Adaptive techniques capable of adjusting the rates of video layers are required to maximize video quality and network utilization. We define a class of algorithms known as source-adaptive multilayered multicast (SAMM) algorithms. In SAMM algorithms, the source uses congestion feedback to adjust the number of generated layers and the bit rate of each layer. We contrast two specific SAMM algorithms: an end-to-end algorithm, in which only end systems monitor available bandwidth and report the amount of available bandwidth to the source, and a network-based algorithm, in which intermediate nodes also monitor and report available bandwidth. Using simulations that incorporate multilayered video codecs, we demonstrate that SAMM algorithms can exhibit better scalability and responsiveness to congestion than algorithms that are not source-adaptive. We also study the performance trade-offs between end-to-end and network-based SAMM algorithms     

Wire-antenna designs using genetic algorithms

There is a large class of electromagnetic radiators designated as wire antennas. As a rule, an inductive process is used to design these antennas. Either an integral equation is formulated or a simulator is used that gives the current distributions on the wires of the antenna, from which the electromagnetic properties of the antenna can then be determined. Once the antenna properties are known, the parameters are optimized, using guides such as intuition, experience, simplified equations, or empirical studies. However, using an electromagnetics simulator in conjunction with a genetic algorithm (GA), it is possible to design an antenna using a completely deductive approach: the desired electromagnetic properties of the antenna are specified, and the wire configuration that most closely produces these results is then synthesized by the algorithm. In this paper, we describe four antennas designed using GAs. The first is a monopole, loaded with a modified folded dipole that was designed to radiate uniform power over the hemisphere at a frequency of 1.6 GHz. The second antenna consists of seven wires, the locations and lengths of which are determined by the GA alone, that radiates waves with right-hand-circular polarization at elevation angles above 10°, also at 1.6 GHz. The last two antennas are modified Yagis. One is designed for a broad frequency band and very low sidelobes at a center frequency of 235 MHz. The other is designed for high gain at a single frequency of 432 MHz. We have built and tested these antennas     

Thinned arrays using genetic algorithms

Large arrays are difficult to thin in order to obtain low sidelobes. Traditional statistical methods of aperiodic array synthesis fall far short of optimum configurations. Traditional optimization methods are not well suited for optimizing a large number of parameters or discrete parameters. This paper presents how to optimally thin an array using genetic algorithms. The genetic algorithm determines which elements are turned off in a periodic array to yield the lowest maximum relative sidelobe level. Simulation results for 200 element linear arrays and 200 element planar arrays are shown. The arrays are thinned to obtain sidelobe levels of less than -20 dB. The linear arrays are also optimized over both scan angle and bandwidth.<>     

Optimization of wavelength assignment for QoS multicast in WDMnetworks

This paper discusses quality-of-service (QoS) multicast in wavelength-division multiplexing (WDM) networks. Given a set of QoS multicast requests, we are to find a set of cost suboptimal QoS routing trees and assign wavelengths to them. The objective is to minimize the number of wavelengths in the system. This is a challenging issue. It involves not only optimal QoS multicast routing, but also optimal wavelength assignment. Existing methods consider channel setup in WDM networks in two separate steps: routing and wavelength assignment, which has limited power in minimizing the number of wavelengths. In this paper, we propose a new optimization method, which integrates routing and wavelength assignment in optimization of wavelengths. Two optimization algorithms are also proposed in minimizing the number of wavelengths. One algorithm minimizes the number of wavelengths through reducing the maximal link load in the system; while the other does it by trying to free out the least used wavelengths. Simulation results demonstrate that the proposed algorithms can produce suboptimal QoS routing trees and substantially save the number of wavelengths     

Efficient routing and wavelength assignment for multicast in WDMnetworks

The next generation multimedia applications such as video conferencing and HDTV have raised tremendous challenges on the network design, both in bandwidth and service. As wavelength-division-multiplexing (WDM) networks have emerged as a promising candidate for future networks with large bandwidth, supporting efficient multicast in WDM networks becomes eminent. Different from the IP layer, the cost of multicast at the WDM layer involves not only bandwidth (wavelength) cost, but also wavelength conversion cost and light splitting cost. It is well known that the optimal multicast problem in WDM networks is NP-hard. In this paper, we develop an efficient approximation algorithm consisting of two separate but integrated steps: multicast routing and wavelength assignment. We prove that the problem of optimal wavelength assignment on a multicast tree is not NP-hard; in fact, an optimal wavelength assignment algorithm with complexity of O(NW) is presented. Simulation results have revealed that the optimal wavelength assignment beats greedy algorithms by a large margin in networks using many wavelengths on each link such as dense wavelength-division-multiplexing (DWDM) networks. Our proposed heuristic multicast routing algorithm takes into account both the cost of using wavelength on links and the cost of wavelength conversion. The resulting multicast tree is derived from the optimal lightpaths used for unicast     

Optimal ThrowBoxes assignment for big data multicast in VDTNs

Nowadays, vehicles have been equipped with various kinds of sensors which produce so called big data constantly. Among them, multimedia contents form the major part of the total generated data. They are usually shared among vehicles in a region of interest with less concerns on delay criteria. Therefore, to reduce cost, these data will be delivered using a carry-and-forward method in a Vehicular Delay Tolerant Network. Since the volume of these data is not negligible, not only delivery utility but also memory space usage must be considered while designing forwarding strategy. ThrowBoxes have been utilized to increase encountering opportunities. In this paper, we develop an optimal data packet assignment algorithms to achieve global maximum delivery utilities among ThrowBoxes. We evaluate the proposed scheme with the real world data trace. The results show that our scheme achieves better performance in terms of delay, delivery ratio, cost and other metrics.

     

Admission control algorithms for multicast sessions with multiplestreams

Real-time multicast communication is considered, in which each destination makes an individual bid for delivery of a subset of real-time hierarchically encoded streams that are offered to the session by the source. The objective is to customize stream delivery to destinations, based on their requests and network constraints. Admission control procedures, which consider requests for multiple streams from multiple destinations and resolve contention when users' requests exceed available network resources, are presented. Specifications for four admission control procedures are presented and their properties analyzed. A performance measure for admission control is defined to be the total gain for the source that equals the sum of bids by the users taking delivery of the streams they ordered. Simulation results of the performance of the procedures are presented and compared to the performance of an optimal, but highly complex, admission control algorithm. In this paper the assumption is that the routing tree is already in place and the focus is on managing users' requests and deciding on which stream to deliver to each destination. This is done by signaling protocols that transfer messages containing users' requests and resource allocation commands between a source and the destinations. In addition, admission control protocols take users' requests and network resources as their input and issue as outputs the decisions on which request to admit (and allocate resources for) and which to reject     

Fast capacity estimation algorithms for manets using directional antennas

In this letter,capacity estimation for Mobile Ad hoc NETworks (MANETs) using direc- tional antennas are studied.Two Matrix-based Fast Calculation Algorithms (MFCAs) are proposed to estimate the network capacity in a network scenario in which there is no channel sharing among multiple sessions and traffic is sensitive to delay with an end-to-end delay constraint.The first algo- rithm MFCA-1 is used to estimate network capacity in a situation where all links have the same delay. It estimates the maximum number of k-hop sessions in a network based on the k-hop adjacency matrix of the network.The second algorithm MFCA-2 is used to estimate network capacity in a situation where different links may have different delays.It calculates the maximum number of sessions in a network with an end-to-end delay constraint based on the adjacency matrix and the link-delay matrix of the network.Numerical and simulation results show that both MFCA-1 and MFCA-2 can calculate network capacity much faster than the well-known Brute-Force Search Algorithm (BFSA) but with the same accuracy.     

Polynomial time algorithms for multicast network code construction

The famous max-flow min-cut theorem states that a source node s can send information through a network (V, E) to a sink node t at a rate determined by the min-cut separating s and t. Recently, it has been shown that this rate can also be achieved for multicasting to several sinks provided that the intermediate nodes are allowed to re-encode the information they receive. We demonstrate examples of networks where the achievable rates obtained by coding at intermediate nodes are arbitrarily larger than if coding is not allowed. We give deterministic polynomial time algorithms and even faster randomized algorithms for designing linear codes for directed acyclic graphs with edges of unit capacity. We extend these algorithms to integer capacities and to codes that are tolerant to edge failures.