Topology Control Algorithm Research Articles

On Minimizing the Impact of Mobility on Topology Control in Mobile Ad Hoc Networks

Although topology control has received much attention in stationary sensor networks by effectively minimizing energy consumption, reducing interference, and shortening end-to-end delay, the transience of mobile nodes in Mobile Ad hoc Networks (MANETs) renders topology control a great challenge. To circumvent the transitory nature of mobile nodes, k-edge connected topology control algorithms have been proposed to construct robust topologies for mobile networks. However, uniformly using the value of k for localized topology control algorithms in any local graph is not effective because nodes move at different speeds. Moreover, the existing k-edge connected topology control algorithms need to determine the value of k a priori, but moving speeds of nodes are unpredictable, and therefore, these algorithms are not practical in MANETs. A dynamic method is proposed in this paper to effectively employ k-edge connected topology control algorithms in MANETs. The proposed method automatically determines the appropriate value of k for each local graph based on local information while ensuring the required connectivity ratio of the whole network. The results show that the dynamic method can enhance the practicality and scalability of existing k-edge connected topology control algorithms while guaranteeing the network connectivity.

Traffic-based topology control algorithm for energy savings in multi-hop wireless networks

This paper presents a traffic-based topology control algorithm for multi-hop wireless networks, in order to optimize the global energy consumption while maximizing the aggregate throughput. Contrary to major related works, we do not consider that reducing transmission powers implies reducing interferences and that the traffic is uniformly distributed among the links. Thus, we propose to dynamically calculate the transmission power of nodes depending on the traffic. First, we redefine the N-hop interference model for varying transmission powers. Then, we define a function giving the minimum interference according to the transmission powers. We propose several algorithms minimizing this function: global optimization, local optimization, and distributed optimization for a limited computation cost. Our first algorithm is used as a reference for limited cases. We show by simulation that our heuristics are relevant compared to existing works.

An Energy-Balance Based Distributed Topology Control Algorithm for Wireless Sensor Networks

Topology control is an efficient approach which can reduce energy consumption for wireless sensor networks, and the current algorithms mostly focus on reducing the nodes’ energy consumption by power adjusting, but pay little attention to balance energy consumption of the whole network, which results in premature death of many nodes. Thus, a distributed topology control algorithm based on path-loss and residual energy (PRTC) is designed in this paper. This algorithm not only maintains the least loss links between nodes but also balances the energy consumption of the network. The simulation results show that the topology constructed by PRTC can preserve network connectivity as well as extend the lifetime of the network and provide good performance of energy consumption.

Sleep-based topology control in the Ad Hoc networks by using fitness aware learning automata

Learning automata have been found to be useful in the systems with incomplete knowledge. Therefore, it can be used as a tool to solve problems of Ad Hoc networks, where nodes are mobile and operate within a dynamic environment, which entails possibly unknown and time varying characteristics. In this paper, after a short review on the related works, learning automata and CEC algorithm, which is a sleep based topology control algorithm, a modified version (called MCEC) is proposed. In addition, a probabilistic algorithm is recommended to make decision about whether or not a node has to sleep. Furthermore, a distributed algorithm is recommended; in order to improve the proposed probabilistic algorithm, using learning automata. Finally, nominated algorithms have been simulated in both of the stationary and non-stationary networks. In conclusion, as the simulation results show, the proposed algorithms outperform corresponding topology control algorithms and reveal the effectiveness of using learning automata.

Self-stabilizing algorithm for efficient topology control in Wireless Sensor Networks

Wireless Sensor Networks lifetime mainly depends on energy saving efficiency. In this paper, we propose an energy-efficient self-stabilizing topology control protocol for WSN. We reduce the transmission power of each node so as to maintain network connectivity while saving maximum energy. Besides, we propose an approximation algorithm for minimum weighted connected dominating set that builds a virtual backbone formed by sensors with maximum energy. This backbone is used for efficient routing purpose. We proved the algorithm correctness and through our simulation results, we showed the efficiency of our proposed solution.

Distributed k-connected fault-tolerant topology control algorithms with PSO in future autonomic sensor systems

Fault-tolerant topology control in Wireless Sensor Networks (WSNs) has drawn a significant amount of research interest and become a hot point. In this paper, we first propose a centralised k-connected fault-tolerant topology control algorithm with Particle Swarm Optimisation (PSO) called CKFTC-PSO. In CKFTC-PSO, we take both issues of node failure and power efficiency into consideration and give the mathematical model of k-connected fault-tolerant topology control problem. Inspired by physics of Genetic Algorithm (GA), the principles of mutation and crossover operator in GA are incorporated into the proposed CKFTC-PSO algorithm to achieve a better diversity and break away from local optima. Based on CKFTC-PSO, we then propose a distributed k-connected fault-tolerant topology control algorithm with PSO called DKFTC-PSO. DKFTC-PSO has better performance than CKFTC-PSO in power-efficiency while preserve k-connectivity. Simulation results are presented to demonstrate the effectiveness of the proposed algorithms.

Clustering Network Topology Control Method Based on Responsibility Transmission

The topology control is an effective approach which can improve the quality of wireless sensor network at all sides. Through studying the mechanism of sensor network data transmission, the nature of data transmission in wireless sensor network is concluded as a kind of responsibility transmission. By redefining the responsibility and availability of nodes, the strategy for cluster head selection is studied, the responsibility and availability is determined by the combination of the residual energy, location and current flow of nodes. Based on the above, new clustering network topology control algorithm based on responsibility transmission CNTCABRT and hierarchical multi-hop CNTCABRT is presented in this paper, whose algorithm structure is along the famous LEACH algorithm. Experimental result demonstrates its promising performance over the famous LEACH algorithm in the cluster head selection, the size of cluster, the deployment of nodes and the lifetime of nodes, and several innovative conclusions are proposed finally.

Coverage and connectivity guaranteed topology control algorithm for cluster‐based wireless sensor networks

AbstractOne of the most challenging issues in wireless sensor networks is to meet the requirements of coverage and connectivity under given energy constraints. Most existing coverage and connectivity algorithms work to form tree networks when sensor nodes do not have location information of themselves. However, a tree topology network does not perform well in terms of energy efficiency and scalability if compared with a cluster network. In this paper, a novel topology control algorithm called Adaptive Random Clustering (ARC) is proposed to form a cluster network with required coverage and connectivity without location information. The performance of its coverage intensity and connectivity is analyzed based on the characteristics of cluster topology, and their proper parameters are determined. ARC inherits an excellent energy efficiency from cluster topology and avoids the collisions and overhearing of data packets. A good scalability can be achieved as only a limited number of channels are needed in ARC for a large‐scale network. Furthermore, ARC can adjust the number of active nodes adaptively according to the required coverage to balance the energy consumption. Simulation results demonstrate that required coverage and connectivity can be satisfied and network lifetime is prolonged significantly. Copyright © 2010 John Wiley & Sons, Ltd.

Mobile IP-Based Protocol for Wireless Personal Area Networks in Critical Environments

Low-power Wireless Personal Area Networks (LoWPANs) are still in their early stage of development, but the range of conceivable usage scenarios and applications is tremendous. That range is extended by its inclusion in Internet with IPv6 Low-Power Personal Area Networks (6LoWPANs). This makes it obvious that multi-technology topologies, security and mobility support will be prevalent in 6LoWPAN. Mobility based communication increases the connectivity, and allows extending and adapting LoWPANs to changes in their location and environment infrastructure. However, the required mobility is heavily dependent on the individual service scenario and the LoWPAN architecture. In this context, an optimized solution is proposed for critical applications, such as military, fire rescue or healthcare, where people need to frequently change their position. Our scenario is health monitoring in an oil refinery where many obstacles have been found to the effective use of LoWPANs in these scenarios, mainly due to transmission medium features i.e. high losses, high latency and low reliability. Therefore, it is very difficult to provide continuous health monitoring with such stringent requirements on mobility. In this paper, a paradigm is proposed for mobility over 6LoWPAN for critical environments. On the one hand the intra-mobility is supported by GinMAC, which is an extension of IEEE 802.15.4 to support a topology control algorithm, which offers intra-mobility transparently, and Movement Direction Determination (MDD) of the Mobile Node (MN). On the other hand, the inter-mobility is based on pre-set-up of the network parameters in the visited networks, such as Care of Address and channel, to reach a fast and smooth handoff. Pre-set-up is reached since MDD allows discovering the next 6LoWPAN network towards which MN is moving. The proposed approach has been simulated, prototyped, evaluated, and is being studied in a scenario of wearable physiological monitoring in hazardous industrial areas, specifically oil refineries, in the scope of the GinSeng European project.

Overview of Topology Control in Wireless Sensor Networks

Topology control is one of the most importance issues in performance optimization for wireless sensor network. It can prolong network lifetime, reducing radio interference, ensuring network connectivity and coverage. In this survey paper, we discuss the design object of topology control, study the different network topology models and graph models which used in topology control, typical topology control algorithms are also analyzed through the angle of power control and sleep scheduling. Finally, we summarize the present situation and problems which still remained to be solved.

Movement Control Algorithms for Improving Topology Control Performance in Ad Hoc Networks

在无线Ad Hoc 网络中,拓扑控制算法能够使节点的传输功率小于最大传输功率,从而可以节省网络能量,提高网络容量.由于节点分布的随机性,在节点较为稀疏的区域,拓扑控制算法存在着局限性,因而提出了移动控制算法来改善拓扑控制算法的性能.在保证网络连通性的前提下,算法首先根据收集到的信息,通过构造网络最小生成树确定较长的通信链路,并移动网络中的部分节点使这些链路缩短,从而显著减小网络中较大的通信半径,提高了拓扑控制的性能.仿真实现了PMST-P,PMST-UV和LMST-LUV 这3 种移动控制算法,并对它们的性能进行了讨论和相互比较.;In Ad Hoc networks, topology control is designed to save energy and increase network capacity by enabling nodes to use proper transmission power, which is usually much smaller than the maximal transmission power. However, the randomicity of network deployment and node movement results in a non-uniform distribution of nodes. In a region where nodes are sparse, the distance between two nodes may be much longer than that in a dense region, so the transmission power is not able decrease and does not depend on which topology control algorithm is adopted. For the first time, this paper proposes movement control algorithms to improve performance of topology control by moving a subset of nodes to desiring positions. Based on the minimum spanning tree of the network topology graph, addition links are determined. Moreover, addition links are shortened and large communication range may be reduced by moving some nodes. Three movement algorithms, PMST-P, PMST-UV and LMST-LUV, are realized, and their performance is compared with each other with respect to maximum communication range, total moving distance and etc. using simulations.

A Topology Control Algorithm of 3D Wireless Sensor Networks Based on Energy Consumption and Robustness Trade-off

A Topology Control Algorithm of 3D Wireless Sensor Networks Based on Energy Consumption and Robustness Trade-off

An Quantitative Study on the Impact of N-Tiers in the Performance of Topology Control Algorithms for Wireless Sensor Networks

An Quantitative Study on the Impact of N-Tiers in the Performance of Topology Control Algorithms for Wireless Sensor Networks

Connected Dominating Set Topology Control Algorithm of Heterogeneous Wireless Sensor Networks

By using the theory of minimum connected dominating set,the issue of topology optimization for heterogeneous wireless sensor networks is studied.Considering the heterogeneous feature of sensor nodes' communication capabilities,a function named area energy consumption rate has been built by integrating the quality of communication links,the transmission range and the remaining energy of nodes.This function has been used to estimate the energy consumption rate of communication areas and determine the selection of dominating nodes.Thus,a distributed topology control algorithm which is minimum connected,has been proposed.The experimental results show that network topology constructed by this algorithm has reliable communication links and high efficiency of energy utilization.It has the potential to significantly prolong the lifecycle of heterogeneous wireless sensor networks.

Edge betweenness centrality: A novel algorithm for QoS-based topology control over wireless sensor networks

In this paper we propose a novel topology-control algorithm, called edge betweenness centrality (EBC). EBC is based on the concept of betweenness centrality, which has been first introduced in the context of social network analysis (SNA), and measures the “importance” of each node in the network. This information allows us to achieve high quality of service (QoS) in wireless sensor networks by evaluating relationships between entities of the network (i.e., edges), and hence identifying different roles among them (e.g., brokers, outliers), thus controlling information flow, message delivery, latency and energy dissipation among nodes. The experimental evaluation and analysis of EBC in comparison to other state-of-the-art topology control algorithms shows that our algorithm outperforms the competitor ones in all observed cases.

QoS Topology Control with Energy Efficiency for MANET

Nowadays, a number of modern applications require Ad Hoc network to provide QoS guarantee and it has received much attention. In this paper, we propose an efficiently QoS topology control algorithm. Our algorithm dynamically adjusts transmission power of mobile nodes to construct new topology which can meet bandwidth and end-to-end delay constraints as well as minimize the total energy consumption in network. It can be modeled as a problem of multi-commodity flows and easily be implemented. Simulation results show that the algorithm has a better performance and will provide an effective solution for realizing multimedia applications in mobile network.

Interference-Aware Dynamic Algorithms for Energy-Efficient Topology Control in Wireless Ad Hoc and Sensor Networks

In wireless ad hoc and sensor networks, energy is a scarce resource and a considerable amount of energy is dissipated due to interference. Therefore, interference is one of the major challenges in wireless ad hoc and sensor networks. It alters or disrupts a message as it is being transmitted along a channel between source and destination. Since the messages are disrupted when the interference occurs, they have to be detected and the interfered messages have to be retransmitted. In this paper, we propose central and distributed heuristic algorithms for reducing average interference in a receiver-centric interference model. In the literature, the minimum spanning tree (MST) algorithm is generally used through the interference coverage graph directly or indirectly in order to generate minimum average interference topology. Our algorithm, dynamic average interference (DAI), however, generates lower average interference as well as more sparse topology than MST. We realized that if the transmission ranges of nodes are taken into consideration at each stage of the topology control algorithm, the interference of links are changed dynamically. This interference changing enables up to 22% more energy saving than the MST algorithm. Thus, DAI provides energy saving by reducing the interference as far as possible in generated topology.

Localized and configurable topology control in lossy wireless sensor networks

Wireless sensor networks (WSNs) introduce new challenges to topology control due to the prevalence of lossy links. We propose a new topology control formulation for lossy WSNs. In contrast to previous deterministic models, our formulation captures the stochastic nature of lossy links and quantifies the worst-case path quality in a network. We develop a novel localized scheme called configurable topology control (CTC). The key feature of CTC is its capability of flexibly configuring the topology of a lossy WSN to achieve desired path quality bounds in a localized fashion. Furthermore, CTC can incorporate different control strategies (per-node/per-link) and optimization criteria. Simulations using a realistic radio model of Mica2 motes show that CTC significantly outperforms an representative traditional topology control algorithm called LMST in terms of both communication performance and energy efficiency. Our results demonstrate the importance of incorporating lossy links of WSNs in the design of topology control algorithms.

On the Topology Design of Integrated Wireless Networks

Topology clustering, constructing overlay graphs, adding relay nodes, or creating a “small-world” network by building some shortcuts etc, topology control schemes are able to achieve the scalability, resilience, and fault-tolerance for wireless communication networks. In this article, we take a different approach to reach such aim for heterogeneous integrated wireless networks by generating a topology such that the resulting network is “scale-free”. Thereby we propose a topology control algorithm based on the “scale-free” complex network concept and directed proximity graph theory for integrated wireless networks with non-uniform transmission ranges. In this algorithm, the topology is also generated by new nodes’ growth and preferential attachment procedure, but where each new node connects to the existing nodes in its directed attachable proximity in terms of certain probability at each time step. Each node’s directed attachable proximity graph is generated from its directed reachable proximity graph that is built by regulating its transmission power based on locally collected information. The simulation experiments are provided to validate our claims.

Topology Control Using Efficient Power Management

Problem statement: Effective Topology control will improve the performance and the capacity of Mobile Ad-hoc networks by building reliable network structure. Approach: Power level is used as the basis for topology control since it reduces spatial interference while increasing the effective channel capacity and network lifetime. Results: In this study, we design a topology control using efficient power management algorithm using clustering. In this study, initially the cluster-head is selected based on the factors power level, stability and connectivity. Then, the connectivity of each node of the cluster with the cluster- head is checked. If the connectivity is less than a minimum connectivity threshold, then it is increased by increasing the power level. If the connectivity is higher than a maximum threshold, then the cluster-head reduces its power level. Conclusion/Recommendations: By simulation results, we show that the proposed topology control algorithm outperforms existing topology control algorithms in terms of by increased node life time and reduced power consumption.