Connectivity constrained wireless sensor deployment using multiobjective evolutionary algorithms and fuzzy decision making

Deployment of sensor nodes is an important issue in designing sensor networks. The sensor nodes communicate with each other to transmit their data to a high energy communication node which acts as an interface between data processing unit and sensor nodes. Optimization of sensor node locations is essential to provide communication for a longer duration. An energy efficient sensor deployment based on multiobjective particle swarm optimization algorithm is proposed here and compared with that of non-dominated sorting genetic algorithm. During the process of optimization, sensor nodes move to form a fully connected network. The two objectives i.e. coverage and lifetime are taken into consideration. The optimization process results in a set of network layouts. A comparative study of the performance of the two algorithms is carried out using three performance metrics. The sensitivity analysis of different parameters is also carried out which shows that the multiobjective particle swarm optimization algorithm is a better candidate for solving the multiobjective problem of deploying the sensors. A fuzzy logic based strategy is also used to select the best compromised solution on the Pareto front.     

RFSMPF: Rank based forwarder selection in MCAST with fuzzy optimized path formation in wireless mesh network

Wireless Networks - Wireless mesh networks (WMN) is an emerging technology right now. WMN is an infrastructure of nodes that are wirelessly connected to each other. Due to the growth of wireless...     

Network selection based on multiple attribute decision making and group decision making for heterogeneous wireless networks

One of the key issues for radio resources management is network selection strategy in heterogeneous scenarios.In order to provide ubiquitous service,the paper puts forward a network selection algorithm based on multiple attribute decision making(MADM) and group decision making(GDM).Firstly,the proposed algorithm acquires attribute weights’ vectors of the subjective and objective decision makers based on MADM,and then the two attribute weights’ vectors are synthesized to be a new attribute weights’ vector by using GDM.Considering that the results of GDM should be reasonable and convincible,the criterion of consistency is adopted for judging the compatibility of group judgments.More specifically,the algorithm takes into account not only objective attributes of networks but also the preference of subscribers and traffic class.Hence it guarantees that the subscribers can not select the networks with poor performance depending on their preference.The simulation results show that the proposed algorithm can effectively reduce the handoff number and provide subscribers with satisfactory quality of service(QoS).     

Heterogeneous wireless network selection algorithm based on group decision

In the environment of heterogeneous wireless networks, it is vital to select a currently optimal network for applications and subscribers. The use of multiple attribute decision making （MADM） for heterogeneous network selection can provide subscribers with satisfactory service quality. Converting heterogeneous network selection into a MADM problem, the authors present an improved algorithm for MADM based on group decision theory. The algorithm combines weight vectors of multiple attribute decision making to obtain a combinational weight vector. Then the results＇ compatibility will be assessed. If they do not meet the requirements of compatibility, the judgment matrix will be modified until a comprehensive vector that satisfies compatibility requirements is produced. The vector is combined with simple weighting method （SAW） for network selection. Simulation shows that the algorithm can provide users with satisfactory quality of service （QoS）.     

Efficient routing for wireless mesh networks using a backup path

Wireless mesh networks (WMNs) have a proven record in providing viable solutions for some of the fundamental issues in wireless networks such as capacity and range limitations. WMN infrastructure includes clusters of mobile ad‐hoc networks connected through a fixed backbone of mesh routers. The mesh network can be constrained severely because of various reasons, which could result in performance degradation such as a drop in throughput or long delays. Solutions to this problem often focus on multipath or multichannel extensions to the existing ad‐hoc routing protocols. In this paper, we propose a novel solution by introducing an alternative path to the mesh backbone that traverses the mobile ad‐hoc networks part of the WMN. The new routing solution allows the mobile nodes (MNs) to establish direct communication among peers without going through the backbone. The proposed alternative ad‐hoc path is used only when the mesh backbone is severely constrained. We also propose, for the first time in WMNs, using MNs with two interfaces, one used in the mesh backbone communication and the other engaged in the ad‐hoc network. A scheme is presented for making the MN aware of link quality measures by providing throughput values to the ad‐hoc on‐demand distance vector protocol. We use piggybacking on route reply messages in ad‐hoc on‐demand distance vector to avoid incurring additional costs. We implemented our solution in an OPNET simulator and evaluated its performance under a variety of conditions. Simulation results show that the alternative ad‐hoc path provides higher throughput and lower delays. Delay analysis show that the throughput improvement does not impose additional costs. Copyright © 2012 John Wiley & Sons, Ltd.     

A fuzzy decision scheme for relay selection in cooperative wireless sensor network

In energy‐constrained military wireless sensor networks, minimizing the bit error rate (BER) with little compromise on network lifetime is one of the most challenging issues. This paper presents a new relay selection based on fuzzy logic (RSFL) scheme which provides balance between these parameters. The proposed scheme considers node's residual energy and path loss of the relay‐destination link as the input parameters for the selection of the relay node. The relay node selection by fuzzy logic is based on prioritizing higher residual energy and minimum path loss. To evaluate the performance on wireless sensor network, we compare the proposed scheme with the three existing relay selection strategies, ie, random, maximum residual energy based relay selection (MaxRes), and minimum energy consumption based relay selection (MinEnCon). The simulation results of the proposed scheme in terms of network lifetime, BER, Network Survivability Index (NSI), and average energy of network nodes have been presented and compared with different relay selection schemes. The simulation results show that the proposed RSFL scheme has the lowest BER, moderate network lifetime, average energy, and NSI.     

Vertical handoff decision in 4G wireless networks using multi attribute decision making approach

Multi-interface terminal in heterogeneous wireless networks will have network access from diverse access technologies. Multiple attribute for decision making including user preference will increase the complexity of handoff process. Various approaches have been proposed to solve the complexity problem of handoff decision. In this paper, multi attribute decision making algorithms Analytic Hierarchy Process (AHP) method, Simple Additive Weighting (SAW), Total Order Preference by Similarity to the Ideal Solution (TOPSIS), and Grey Relational Analysis (GRA) methods have been proposed for handoff decision in a WiMAX–WLAN environment to facilitate user with better quality of service. AHP has been used for calculation of weights of decision parameters. Numerical results show that SAW, TOPSIS and GRA provide almost similar performance. SAW is very simple to implement but probability of error is less in GRA because values of decision attribute are directly used for ranking of alternatives. TOPSIS is sensitive to the attribute with high score.     

A genetic algorithm approach for multi-attribute vertical handover decision making in wireless networks

Mobile terminals can typically connect to multiple wireless networks which offer varying levels of suitability for different classes of service. Due to the changing dynamics of network attributes and mobile users’ traffic needs, vertical handovers across heterogeneous networks become highly desirable. Multiple attribute decision making (MADM) techniques offer an efficient approach for ranking competing networks and selecting the best one according to specific quality of service parameters. In this paper, a genetic algorithm (GA) is applied to optimize network attributes’ weighting by emphasizing ranking differences among candidate networks, thereby aiding correct decision making by reducing unnecessary handovers and ranking abnormalities. The performance of the proposed GA-based vertical handover is investigated with typical MADM techniques including Simple Additive Weighting (SAW) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). The results show that the proposed GA-based weight determination approach reduces the abnormality observed in the conventional SAW and TOPSIS techniques substantially. The results of this paper will help ensuring the application of MADM methods to more dynamic and challenging decision making problems encountered in wireless network.     

Route selection in IEEE 802.11 wireless mesh networks

This paper addresses the problem of route selection in IEEE 802.11 based Wireless Mesh Networks (WMNs). Traditional routing protocols choose the shortest path between two routers. However, recent research reveals that there can be enormous differences between links in terms of quality (link loss ratio, interference, noise etc) and therefore selecting the shortest path (hop count metric) is a poor choice. We propose a novel routing metric—Expected Link Performance (ELP) metric for wireless mesh networks which takes into consideration multiple factors pertaining to quality (link loss ratio, link capacity and link interference) to select the best end-to-end route. Simulation based performance evaluation of ELP against contemporary routing metrics shows an improvement in terms of throughput and delay. Moreover, we propose an extension of the metric called ELP-Gateway Selection (ELP-GS) which is an extension meant for traffic specifically oriented towards the gateway nodes in the mesh network. We also propose a gateway discovery protocol which facilitates the dissemination of ELP-GS in the network. Simulation results for ELP-GS show substantial improvement in performance.     

Transmission power adjustment of wireless sensor networks using fuzzy control algorithm

Energy constraint is the most conspicuous characteristic in wireless sensor networks (WSN). Node deployment, dynamic topology control, and data transmission in WSN all consume a large amount of energy. Therefore, proper adjustment of transmission power (TP) contributes much energy saving. In this paper, a new TP adjustment method based on Fuzzy Control Theory, called FCTP, is proposed for the dynamic topology control. The simulation results show that this method is more robust to tolerate accidental interfere, more rapidly convergent, and more energy efficient than other TP adjustment approaches, which lead to longer network lifetime. Copyright © 2008 John Wiley & Sons, Ltd.     

Efficient distributed restoration path selection for shared mesh restoration

In MPLS/GMPLS networks, a range of restoration schemes will be required to support different tradeoffs between service interruption time and network resource utilization. In light of these tradeoffs, path-based end-to-end shared mesh restoration provides a very attractive solution. However, efficient use of bandwidth for shared mesh restoration strongly relies on the procedure for selecting restoration paths. We propose an efficient restoration path selection algorithm for restorable connections over shared bandwidth in a fully distributed MPLS/GMPLS architecture. We also describe how to extend MPLS/GMPLS signaling protocols to collect the necessary information efficiently. To evaluate the algorithm's performance, we compare it via simulation with two other well-known algorithms on a typical intercity backbone network. The key figure of merit for restoration bandwidth efficiency is restoration overbuild, i.e., the extra bandwidth required to meet the network restoration objective as a percentage of the bandwidth of the network with no restoration. Our simulation results show that our algorithm uses significantly less restoration overbuild (63%-68%) compared with the other two algorithms (83%-90%).     

High throughput route selection in multi-rate wireless mesh networks

Most existing Ad-hoc routing protocols use the shortest path algorithm with a hop count metric to select paths. It is appropriate in single-rate wireless networks, but has a tendency to select paths containing long-distance links that have low data rates and reduced reliability in multi-rate networks. This article introduces a high throughput routing algorithm utilizing the multi-rate capability and some mesh characteristics in wireless fidelity （WiFi） mesh networks. It uses the medium access control （MAC） transmission time as the routing metric, which is estimated by the information passed up from the physical layer. When the proposed algorithm is adopted, the Ad-hoc on-demand distance vector （AODV） routing can be improved as high throughput AODV （HT-AODV）. Simulation results show that HT-AODV is capable of establishing a route that has high data-rate, short end-to-end delay and great network throughput.     

Multipath selection and channel assignment in wireless mesh networks

In wireless networks, it is very important to optimize the number of channels, due to the limit on the number of usable channels in a given network. In addition, multimedia services with high QoS requirements with respect to throughput and delay have recently become popular. To satisfy these requirements, it has become important to find a way of providing multipath transmission. A channel assignment algorithm is presented that minimizes the number of required channels while satisfying the throughput requirements of source–destination pairs in multichannel, multiradio, multirate wireless mesh networks. A mathematical model is proposed that considers interference effect, link capacity, and throughput requirements. A novel channel assignment algorithm is developed that takes into account multipath selection, channel reusability, link capacity sharing, and global optimization. The performance of the algorithm is compared with that of CPLEX, using 24 network scenarios. The maximum gap between the CPLEX solutions and those of the proposed algorithm is, on average, only 4.8%.     

Distributed decision making policy for frequency band selection boosting RF energy harvesting rate in wireless sensor nodes

Wireless Networks - Emerging paradigms such as smart cities and Internet of Things are expected to be an intrinsic part of next generation communication standards. To bring these paradigms to life,...     

基于GMPLS的最优恢复路径选择算法

在总结、比较当前各种GMPLS恢复机制性能的基础上,结合了保护机制恢复时间快、恢复机制的资源利用率高的优点,提出了一种动态最优恢复路由选择算法.该算法不仅在出现多处网络故障的情况下,根据预留的恢复路径,动态寻找分配恢复路径,而且可以保证保护路径的资源利用率最优.     

Improving group decision making: a fuzzy GSS approach

Group decision-making methods have been developed extensively, but their adaptation for use in organizations has been problematic. According to Arrow's (1963) Impossibility theorem, one conceivable reason is that a group decision outcome could never satisfy all decision makers' individual preferences. In order to accommodate individual decision maker's preferences in a group decision-making task, this correspondence presents a fuzzy multiperson multicriteria decision making (MMCDM) model and a structured group decision-making process. The fuzzy MMCDM model includes fuzzy individual preference generation and group preference aggregation. The structured decision-making process keeps the group interaction on track, so that the fuzzy MMCDM model can be effectively applied to the group decision-making task. Based on the proposed model and the decision-making process, a fuzzy group support system (GSS) has been developed and applied to a group assessment task. An empirical study was conducted and the experiment results showed that use of the fuzzy GSS enhanced individual understanding, consensus, and satisfaction of the group decision outcome     

Path selection algorithms for fault tolerance in wireless mesh networks

Recently Wireless Mesh Networks (WMNs) have emerged as a key technology for providing high-bandwidth networking among peer nodes over a specific coverage area. Features such as low cost, ease of deployment, self-configuration and self-healing make them one of the most promising global telecommunication systems. Despite their advantages, however, several research challenges remain in all protocol layers. In this paper, we address the main challenging issues related to the routing aspects in a WMN. Routing in such networks is performed through multi-hop paths where intermediate nodes cooperatively make forwarding decisions based on their knowledge regarding the network topology. However, in an unideal dynamic environment due to frequent or rare node failures/misbehavior, traditional ad-hoc routing protocols suffer from high routing overhead or energy consumption. Motivated by this, we propose several path selection algorithms which adapt to such topology dynamics. The main objective of these routing schemes is to provide fault tolerance without sacrificing the energy and computational complexity efficiency. Numerical investigations, based on extensive simulations, validate the effectiveness of our proposals even when faulty nodes subsist in the environment.     

认知无线Mesh网络中基于马氏决策模型的MAC协议

为解决认知无线Mesh网络中专用控制信道较难获得的问题,提出一种基于POMDP的机会式频谱接入MAC协议,在不需要中心控制器和专用控制信道的协调下,实现动态频谱感知和接入。仿真结果表明,基于POMDP的接入策略能够有效提高网络频谱利用率和吞吐量,性能最优,而基于贪心算法的接入策略,在降低计算复杂度的同时,获得了较好的性能,实用性较强。     

Cooperative spectrum sensing in cognitive radio network using multiobjective evolutionary algorithms and fuzzy decision making

The cognitive radio has emerged as a potential solution to the problem of spectrum scarcity. Spectrum sensing unit in cognitive radio deals with the reliable detection of primary user’s signal. Cooperative spectrum sensing exploits the spatial diversity between cognitive radios to improve sensing accuracy. The selection of the weight assigned to each cognitive radio and the global decision threshold can be formulated as a constrained multiobjective optimization problem where probabilities of false alarm and detection are the two conflicting objectives. This paper uses evolutionary algorithms to solve this optimization problem in a multiobjective framework. The simulation results offered by different algorithms are assessed and compared using three performance metrics. This study shows that our approach which is based on the concept of cat swarm optimization outperforms other algorithms in terms of quality of nondominating solutions and efficient computation. A fuzzy logic based strategy is used to find out a compromise solution from the set of nondominated solutions. Different tests are carried out to assess the stability of the simulation results offered by the heuristic evolutionary algorithms. Finally the sensitivity analysis of different parameters is performed to demonstrate their impact on the overall performance of the system.     

EPTR: expected path throughput based routing protocol for wireless mesh network

For effective routing in wireless mesh networks, we proposed a routing metric, expected path throughput (EPT), and a routing protocol, expected path throughput routing protocol (EPTR), to maximize the network throughput. The routing metric EPT is based on the estimated available bandwidth of the routing path, considering the link quality, the inter- and intra-flow interference and the path length. To calculate the EPT of a routing path, we first calculate the expected bandwidth of the link and the clique, and then consider the decay caused by the path length. Based on EPT, a distributed routing protocol EPTR is proposed, aiming to balance the network load and maximize the network throughput. Extensive simulations are conducted to evaluate the performance of the proposed solution. The results show that the proposed EPTR can effectively balance the network load, achieve high network throughput, and out-perform the existing routing protocols with the routing metrics previously proposed for wireless mesh networks.