QoS multicast tree construction in IP/DWDM optical internet by bio-inspired algorithms

Copyright @ Elsevier Ltd. All rights reserved.In this paper, two bio-inspired Quality of Service (QoS) multicast algorithms are proposed in IP over dense wavelength division multiplexing (DWDM) optical Internet. Given a QoS multicast request and the delay interval required by the application, both algorithms are able to find a flexible QoS-based cost suboptimal routing tree. They first construct the multicast trees based on ant colony optimization and artificial immune algorithm, respectively. Then a dedicated wavelength assignment algorithm is proposed to assign wavelengths to the trees aiming to minimize the delay of the wavelength conversion. In both algorithms, multicast routing and wavelength assignment are integrated into a single process. Therefore, they can find the multicast trees on which the least wavelength conversion delay is achieved. Load balance is also considered in both algorithms. Simulation results show that these two bio-inspired algorithms can construct high performance QoS routing trees for multicast applications in IP/DWDM optical Internet.This work was supported in part ny the Program for New Century Excellent Talents in University, the Engineering and Physical Sciences Research Council (EPSRC) of UK under Grant EP/E060722/1, the National Natural Science Foundation of China under Grant no. 60673159 and 70671020, the National High-Tech Reasearch and Development Plan of China under Grant no. 2007AA041201, and the Specialized Research Fund for the Doctoral Program of Higher Education under Grant no. 20070145017

Telecommunications Network Planning and Maintenance

Telecommunications network operators are on a constant challenge to provide new services which require ubiquitous broadband access. In an attempt to do so, they are faced with many problems such as the network coverage or providing the guaranteed Quality of Service (QoS). Network planning is a multi-objective optimization problem which involves clustering the area of interest by minimizing a cost function which includes relevant parameters, such as installation cost, distance between user and base station, supported traffic, quality of received signal, etc. On the other hand, service assurance deals with the disorders that occur in hardware or software of the managed network. This paper presents a large number of multicriteria techniques that have been developed to deal with different kinds of problems regarding network planning and service assurance. The state of the art presented will help the reader to develop a broader understanding of the problems in the domain

A greedy ant colony forwarding algorithm for Named Data Networking

The Named Data Networking (NDN) is a newly proposed Internet architecture based on Content-Centric Networking, which transforms data, instead of hosts, into a first-class entity. However, one of the major challenges is supporting intelligent forwarding of Interests over multiple paths while allowing an unbounded name space. To address this challenge, this paper proposes a Greedy Ant Colony Forwarding (GACF) algorithm which uses the ISP-based aggregation to reduce the content naming space. There are two kinds of ants in GACF. One is Hello Ant which is used to discover the all possible paths and optimize them; the other is Normal Ant which is used to get data and reinforce the optimization of the paths simultaneously. The GACF algorithm is a Quality of Service aware forwarding algorithm. It adaptively reduces the impacts incited by the dynamic complex network

A Routing Algorithm Based on Ant Colony, Local Search and Fuzzy Inference to Improve Energy Consumption in Wireless Sensor Networks

Wireless sensor network is a new generation of networks in which the main aim is to collect data from the surrounding environment of network sensors. The major differences of wireless sensor networks with other networks are limited energy resources and relatively low processing capabilities. Therefore, managing power and reducing energy consumption are of great importance in these networks. In this paper, there was presented a mechanism for Wireless sensor network routing which can be more effective regarding the criteria of route length, end–to–end delay and network node energy for the quality of mechanism service. The proposed method used ant colony–based routing algorithm and local enquiry to find optimal routes. Also, a fuzzy inference system was used to determine the route quality which showed better performance compared with equation of route quality. The results of simulating mechanism showed that energy consumption and network efficiency had improved compared with those of previous methods.DOI:http://dx.doi.org/10.11591/ijece.v3i5.362

A Survey on Underwater Acoustic Sensor Network Routing Protocols

Underwater acoustic sensor networks (UASNs) have become more and more important in ocean exploration applications, such as ocean monitoring, pollution detection, ocean resource management, underwater device maintenance, etc. In underwater acoustic sensor networks, since the routing protocol guarantees reliable and effective data transmission from the source node to the destination node, routing protocol design is an attractive topic for researchers. There are many routing algorithms have been proposed in recent years. To present the current state of development of UASN routing protocols, we review herein the UASN routing protocol designs reported in recent years. In this paper, all the routing protocols have been classified into different groups according to their characteristics and routing algorithms, such as the non-cross-layer design routing protocol, the traditional cross-layer design routing protocol, and the intelligent algorithm based routing protocol. This is also the first paper that introduces intelligent algorithm-based UASN routing protocols. In addition, in this paper, we investigate the development trends of UASN routing protocols, which can provide researchers with clear and direct insights for further research

BSRS: Best Stable Route Selection Algorithm for Wireless Sensor Network Applications

Topological changes in sensor networks frequently render routing paths unusable. Such recurrent path failures have detrimental effects on the network ability to support QoS-driven services. Because of connectivity richness in sensor networks, there often exist multiple paths between a source and a destination. Since many applications require uninterrupted connectivity of a session, the ability to find long-living paths can be very useful. In this paper, we propose Best Stable Route Selection (BSRS) approach based on Artificial Bee Colony based search algorithm, ensures that contributes stable quality performance of network and to calculate the best stable path services randomly based on QoS parameter requirements and existing circulation load; so that efficient route selection can easily capture by designing of proposed BSRS approach. The implementation of the proposed BSRS technique is implemented using NS2 simulation environment and the AODV routing protocol is used to incorporate the proposed algorithm. The experimental results are measured in terms of end to end delay, throughput, packet delivery ratio, and energy consumption and routing overhead. The results show the proposed BSRS algorithm improves the flexibility of network node and performance of network when multiple inefficient paths exist

Bi-velocity discrete particle swarm optimization and its application to multicast routing problem in communication networks

This paper proposes a novel bi-velocity discrete particle swarm optimization (BVDPSO) approach and extends its application to the NP-complete multicast routing problem (MRP). The main contribution is the extension of PSO from continuous domain to the binary or discrete domain. Firstly, a novel bi-velocity strategy is developed to represent possibilities of each dimension being 1 and 0. This strategy is suitable to describe the binary characteristic of the MRP where 1 stands for a node being selected to construct the multicast tree while 0 stands for being otherwise. Secondly, BVDPSO updates the velocity and position according to the learning mechanism of the original PSO in continuous domain. This maintains the fast convergence speed and global search ability of the original PSO. Experiments are comprehensively conducted on all of the 58 instances with small, medium, and large scales in the OR-library (Operation Research Library). The results confirm that BVDPSO can obtain optimal or near-optimal solutions rapidly as it only needs to generate a few multicast trees. BVDPSO outperforms not only several state-of-the-art and recent heuristic algorithms for the MRP problems, but also algorithms based on GA, ACO, and PSO

Energy Aware Ant Colony Optimization (ENAANT) to Enhance Throughput in Mobile Ad hoc Networks

Mobile Ad hoc Network (MANET) is a network of mobile nodes having communication without a predefined infrastructure. The applications of MANETs are increasing from home appliances to defense communications. As the mobile nodes are operated by the batteries, all the processes which are taking place in the node should aware of the consumed energy. Maintaining the link stability is one of the challenges and it is one of the factors to ensure the high throughput in the networks. Due to the limited energy, the links of the networks often goes off which affects the throughput of MANETs. Energy aware ACO is proposed to optimize the utilization of energy that is available in the mobile nodes to increase throughput by ensuring link stability. Based on the remaining energy and the amount of packets to be sent, the nodes are selected for routing. The simulation is done through Network Simulator 2 and the results show that the proposed research work performs well in increasing the throughput