Topology Control Algorithm Research Articles

Distributed Topology Control Techniques for Wireless Sensor Networks: An Overview

The recent technological innovations and development like the Internet of Things (IoT), Smart Grids and Smart Environment applications tend to enhance the scalability, self-organizing capability of the mesh networks as well as the wireless sensor networks. As the wireless sensor network have limited energy resources, there is a need of utilizing these limitations in an efficient way in order to accomplish such advanced energy efficiency and better lifetime can be taken care by the operation of topology control methods. In this survey the issue of energy efficiency is formed upon and a comprehensive study of topology control technologies that can be used for enhancement of battery lifetime in WSNs is presented. An insight of how energy efficiency can be achieved by design is provided by review of the significant topology control algorithms based on the energy conservation approach adopted, those algorithms are classified further and evaluated on the basis of communication so as to aid the designer to select best suitable techniques for their applications. A number of open research issues for achieving the energy efficiency by means of controlling topology are identified based on the survey conducted.

Energy Efficient Hardware and Improved Cluster-Tree Topology for Lifetime Prolongation in ZigBee Sensor Networks

In wireless sensor networks, building energy-efficient systems is one of the major challenges. In such networks, nodes are usually supplied by low power and small batteries. Many factors are involved in the energy consumption, and this issue may be considered as a cross-layer problem, from the hardware architecture to the application layer. This paper aims at presenting a hybrid solution for sensor networks based on two main aspects. The first one is the hardware architecture, where we present a prototype of a sensor node we designed. This node proved its efficiency in terms of energy consumption. The second aspect is related to the topology construction and presents a new topology control algorithm based on graph computing. Thus, our system consists of a real indoor application for temperature and humidity monitoring, applicable to home automation or industrial monitoring. We performed the experiments using a set of sensor nodes deployed over a building and proved the efficiency of the system in terms of energy consumption, network lifetime and data delivery.

Energy Management Dynamic Control Topology In MANET

Topology management via per-node transmission power adjustment has been shown effective in extending network lifetime. The existing algorithms constructs static topologies which fail to take the residual energy of network nodes, and cannot balance energy consumption efficiently. To address this problem, a Light Weighted Distributed Topology Control algorithm EMDCT(Energy Management Dynamic Control Topology ) is proposed in this paper. Based on the link metric of the network, both the energy consumption rate level and residual energy levels at the two end nodes are considered. EMDCT generates a Dynamic Topology that changes with the variation of node energy without the aid of location information, each node determines its transmission power according to local network information, which reduces the overhead complexity of EMDCT greatly. The experiment results show that EMDCT preserves network connectivity and manitains minimum-cost property of the network also it can extend network lifetime more remarkably.

A Probabilistic and Highly Efficient Topology Control Algorithm for Underwater Cooperating AUV Networks.

The aim of the Smart and Networking Underwater Robots in Cooperation Meshes (SWARMs) project is to make autonomous underwater vehicles (AUVs), remote operated vehicles (ROVs) and unmanned surface vehicles (USVs) more accessible and useful. To achieve cooperation and communication between different AUVs, these must be able to exchange messages, so an efficient and reliable communication network is necessary for SWARMs. In order to provide an efficient and reliable communication network for mission execution, one of the important and necessary issues is the topology control of the network of AUVs that are cooperating underwater. However, due to the specific properties of an underwater AUV cooperation network, such as the high mobility of AUVs, large transmission delays, low bandwidth, etc., the traditional topology control algorithms primarily designed for terrestrial wireless sensor networks cannot be used directly in the underwater environment. Moreover, these algorithms, in which the nodes adjust their transmission power once the current transmission power does not equal an optimal one, are costly in an underwater cooperating AUV network. Considering these facts, in this paper, we propose a Probabilistic Topology Control (PTC) algorithm for an underwater cooperating AUV network. In PTC, when the transmission power of an AUV is not equal to the optimal transmission power, then whether the transmission power needs to be adjusted or not will be determined based on the AUV’s parameters. Each AUV determines their own transmission power adjustment probability based on the parameter deviations. The larger the deviation, the higher the transmission power adjustment probability is, and vice versa. For evaluating the performance of PTC, we combine the PTC algorithm with the Fuzzy logic Topology Control (FTC) algorithm and compare the performance of these two algorithms. The simulation results have demonstrated that the PTC is efficient at reducing the transmission power adjustment ratio while improving the network performance.

A Game Theoretical Approach for Topology Control in Wireless Ad Hoc Networks with Selfish Nodes

In ad hoc networks, a significant amount of energy available to devices is utilized in network management operations. Since devices have limited energy resources, therefore, they drop data packets of other nodes to reduce their energy consumption. This selfish behaviour increases number of retransmissions over the link which increases energy consumption of the source node, introduces time delays, and degrades throughput of the network. Although conventional distributed topology control solutions minimize energy utilization of the nodes by adjustment of transmission power, however, selfish behaviour by devices introduce additional complexity in design which make topology control a challenging task. In this paper, we proposed Energy Efficient Topology Control Algorithm (EETCA) using game theoretical approach, in which, utility of the node depends on selfishness of the neighbors, link traffic rate, and link length. In decision-making step, nodes remove the links with other nodes that have high drop rate under the condition that network remains connected. We show that Nash Equilibrium point of the proposed game results in Pareto optimal network topology. We compare results of EETCA with Optimum (OPT) and Minimum Least Power Path Tree (MLPT) algorithms presented in literature. We carried our simulations under multiple sources scenario which show that EETCA outperforms previous approaches when number of nodes in the network increases. Furthermore, we simulate the performance of Ad-hoc On-demand Distance Vector (AODV) routing protocol under EETCA topology and compare it with MLPT and OPT topologies. The results show that the ad hoc network constructed using proposed solution substantially improves throughput of AODV routing protocol as compared to MLPT and OPT topology control algorithms.

A decentralised topology control to regulate global properties of complex networks

In the last decade much research effort has been devoted to the investigation of the interplay between properties (i.e. synchronization, clustering, resilience to node fault) and topology of complex networks. Many algorithms have been proposed to construct a network topology with a given properties or to optimize them. These algorithms are static, off-line implemented and may require global network knowledge. In this paper we propose a simple decentralized topology control algorithm that by local actions carried out at the node allows to regulate network global properties. Additionally the algorithm is dynamic coping with both node and link faults and can be on-line implemented.

A systematic approach to constructing families of incremental topology control algorithms using graph transformation

In the communication system domain, constructing and maintaining network topologies via topology control algorithms is an important crosscutting research area. Network topologies are usually modeled using attributed graphs whose nodes and edges represent the network nodes and their interconnecting links. A key requirement of topology control algorithms is to fulfill certain consistency and optimization properties to ensure a high quality of service. Still, few attempts have been made to constructively integrate these properties into the development process of topology control algorithms. Furthermore, even though many topology control algorithms share substantial parts (such as structural patterns or tie-breaking strategies), few works constructively leverage these commonalities and differences of topology control algorithms systematically. In previous work, we addressed the constructive integration of consistency properties into the development process. We outlined a constructive, model-driven methodology for designing individual topology control algorithms. Valid and high-quality topologies are characterized using declarative graph constraints; topology control algorithms are specified using programmed graph transformation. We applied a well-known static analysis technique to refine a given topology control algorithm in a way that the resulting algorithm preserves the specified graph constraints. In this paper, we extend our constructive methodology by generalizing it to support the specification of families of topology control algorithms. To show the feasibility of our approach, we reengineering six existing topology control algorithms and develop e-kTC, a novel energy-efficient variant of the topology control algorithm kTC. Finally, we evaluate a subset of the specified topology control algorithms using a new tool integration of the graph transformation tool eMoflon and the Simonstrator network simulation framework.

Research on topology control in WSNs based on complex network model

A topology control algorithm based on mutual selection mechanism is proposed, combined with complex network model. It adopts node strength and spacing between nodes as the measuring parameters, selects the cluster head nodes based on mutual selection mechanism in the communication radius of nodes and builds the hierarchical topology. The algorithm can improve the clustering efficiency, shorten the average path length, save the energy of the nodes. The simulation and analysis of network evolving process and algorithm model are completed using MATLAB tools and the results verify the correctness and stability of the proposed algorithm model. The algorithm is suitable for large-scale node deployment in WSNs.

Heuristic‐based link quality preservation for reliable data delivery

SummaryDuring the link failure conditions in Voice over Internet Protocol applications, the backup of routing information is an important requirement to offer the reliable data delivery to the destination. But the maintenance of multiple paths is the difficult and time consuming for the dynamic environment. But the hops reduction between the source and destination and the interference occurrence causes the transmission in multiple times and that leads to minimum network lifetime. Hence, the preservation of link between the multiple hops is the necessary task to improve the performance. This paper validates the link quality with the 4 measures as received signal strength indicator, bandwidth, node mobility, and the number of connections. The link quality factor (LQF) measurement considers the signal and noise level in 5 operating conditions to allow the automatic identification of closest neighbors and their location. The integration of tabu list and the heuristic‐based fitness search algorithm constructs the routing path and updates the path to identify the link failure. The LQF estimation and the dynamic update provide an efficient data delivery path with less number of iterations. The comparative analysis between the proposed hybrid tabu‐heuristic–based LQF with the existing protocols such as Adhoc On‐Demand Vector (AODV), Optimized Link State Routing (OLSR), and the Interference‐based Topology Control algorithm for Delay‐constrained (ITCD) proves the effectiveness of tabu‐heuristic–based LQF regarding the throughput, energy, packet delivery ratio with the minimum delay, and rebroadcasting probabilities.

A Topology Control Strategy with Reliability Assurance for Satellite Cluster Networks in Earth Observation.

This article investigates the dynamic topology control problem of satellite cluster networks (SCNs) in Earth observation (EO) missions by applying a novel metric of stability for inter-satellite links (ISLs). The properties of the periodicity and predictability of satellites’ relative position are involved in the link cost metric which is to give a selection criterion for choosing the most reliable data routing paths. Also, a cooperative work model with reliability is proposed for the situation of emergency EO missions. Based on the link cost metric and the proposed reliability model, a reliability assurance topology control algorithm and its corresponding dynamic topology control (RAT) strategy are established to maximize the stability of data transmission in the SCNs. The SCNs scenario is tested through some numeric simulations of the topology stability of average topology lifetime and average packet loss rate. Simulation results show that the proposed reliable strategy applied in SCNs significantly improves the data transmission performance and prolongs the average topology lifetime.

Topology Control for Building a Large-Scale and Energy-Efficient Internet of Things

The IoT is one of the most significant recent innovations in information technologies, which has attracted extensive attention from both industry and academia due to its potential impact on various networking-related fields. The rapid development in IoT technologies has resulted in widespread application of this emerging networking paradigm in various disciplines. On the other hand, IoT faces some challenges that must be fully dealt with, among which scalability and energy efficiency are two critical issues. Topology control offers a promising approach to designing a large-scale and energy-efficient IoT. In this article, we first present a taxonomy of currently available topology control algorithms, and then propose a systematic approach to topology construction in IoT to achieve scalability and energy efficiency. We intend to provide researchers and practitioners with a big picture of the current research status in this area, and hope that this article may motivate more researchers to participate in largescale IoT design, development, and deployment.

Topology control based on the group mobility model for mobile wireless mesh backbone networks

In this paper, we study the characteristics and components of mobile wireless mesh backbone networks (MWMBNs). How to maintain the heterogeneous network connectivity in mobile scenarios is important. We propose a topology control algorithm based on the group mobility model for MWMBN to maintain network connectivity in mobile scenarios. It includes the following work: MWMBNs is classified into the mobile wireless backbone node group (MWBNG) and unit groups (UGs). the MWBNG is composed of all the MWBNs while the UG is composed of a MWBN and several TNs connect it. In the MWBNG, we propose the reference points assignment algorithm (RPAA) based on the RPGM model. In the UG, the TNs has different communication radius with the MWBNs', we propose the topology control algorithm based on tolerate zone using nomadic community mobility, the control algorithm does not need to use any control information to maintain topology control or to change the routing table. The TNs change the self-position to maintain the connectivity with the MWBN. The simulation results show the topology control algorithm based on the group mobility model for MWMBN to maintain the heterogeneous network connectivity when they move together.

Mobile-Aware Topology Control Potential Game: Equilibrium and Connectivity

Topology control (TC) is one of the most important techniques for connection establishments between entities in Internet of Things, especially in the scenario where there are no fixed infrastructures such as prompt sensor deployments, emergency communications, and vehicle–vehicle communications. The goal of TC is to assign per-node transmission power such that the resulting topology is energy efficient and also satisfies some global graph property such as connectivity. Among the literatures, however, few efforts focused on the issue of TC with interest-independent nodes. Besides, in a distributed mobile networks, nodes’ mobility can cause the dynamic network topology. As a result, nodes need to execute the TC algorithm periodically. To jointly consider nodes’ selfishness and mobility, we propose a potential game and mobility aware TC (PGMATC) framework based on mobility traces and potential game, where a practical utility function is designed by considering the expected utility for a TC period. Extensive simulations driven by actual data demonstrate that PGMATC can improve the network connectivity with quite a limited increase in energy consumption, compared with the traditional TC algorithms.

Probability of Interference-Optimal and Energy-Efficient Analysis for Topology Control in Wireless Sensor Networks

Because wireless sensor networks (WSNs) have been widely used in recent years, how to reduce their energy consumption and interference has become a major issue. Topology control is a common and effective approach to improve network performance, such as reducing the energy consumption and network interference, improving the network connectivity, etc. Many topology control algorithms reduce network interference by dynamically adjusting the node transmission range. However, reducing the network interference by adjusting the transmission range is probabilistic. Therefore, in this paper, we analyze the probability of interference-optimality for the WSNs and prove that the probability of interference-optimality increases with the increasing of the original transmission range. Under a specific transmission range, the probability reaches the maximum value when the transmission range is 0.85r in homogeneous networks and 0.84r in heterogeneous networks. In addition, we also prove that when the network is energy-efficient, the network is also interference-optimal with probability 1 both in the homogeneous and heterogeneous networks.

A Network Topology Control Algorithm Based on Mobile Nodes

Topology control is of great significance to reduce energy consumption of wireless sensor network nodes and prolong network lifetime. Different tasks taken by nodes may lead to node failures and fractures of data transmission links, hence undermining the overall network performance. In response to such problems, this paper presents a network topology control algorithm based on mobile nodes that fully considers node energy, node degree and network connectivity. Furthermore, a topology control model is established to analyze weak network topology areas and carry out local topology refactoring. Finally, a simulation experiment demonstrates that the presented algorithm is advantageous in balanced network energy consumption and network connectivity.

A systematic approach to constructing incremental topology control algorithms using graph transformation

Communication networks form the backbone of our society. Topology control algorithms optimize the topology of such communication networks. Due to the importance of communication networks, a topology control algorithm should guarantee certain required consistency properties (e.g., connectivity of the topology), while achieving desired optimization properties (e.g., a bounded number of neighbors). Real-world topologies are dynamic (e.g., because nodes join, leave, or move within the network), which requires topology control algorithms to operate in an incremental way, i.e., based on the recently introduced modifications of a topology. Visual programming and specification languages are a proven means for specifying the structure as well as consistency and optimization properties of topologies. In this paper, we present a novel methodology, based on a visual graph transformation and graph constraint language, for developing incremental topology control algorithms that are guaranteed to fulfill a set of specified consistency and optimization constraints. More specifically, we model the possible modifications of a topology control algorithm and the environment using graph transformation rules, and we describe consistency and optimization properties using graph constraints. On this basis, we apply and extend a well-known constructive approach to derive refined graph transformation rules that preserve these graph constraints. We apply our methodology to re-engineer an established topology control algorithm, kTC, and evaluate it in a network simulation study to show the practical applicability of our approach.

Probability Model Based Energy Efficient and Reliable Topology Control Algorithm

Topology control is an effective method for improving the performance of wireless sensor networks (WSNs). Many topology control algorithms can achieve high energy efficiency by dynamically changing the transmission range of nodes. However, these algorithms prefer to choose short multihop communication links rather than the long directly communication links which also energy efficient probabilistic. Note that these fact, in this paper, we propose a mathematic model to explore the probability that the long directly communication links are more energy efficient than the short links. We investigate the properties of this probability and find out the optimal transmission range which has highest probability of energy efficient. Based on this conclusion, we propose the energy efficient and reliable topology control algorithm (ERTC) to maintain the r-range for the nodes instead of the k-connection; moreover, ERTC can achieve energy efficient and network connection at the same time.

A distributed battery recovery aware topology control algorithm for wireless sensor networks

A distributed battery recovery aware topology control algorithm for wireless sensor networks

Robust topology construction method with radio interface constraint for multi-radio multi-channel wireless mesh network using directional antennas

Multi-radio and multi-channel wireless mesh networks using directional antenna (MR-MC DWMN) greatly improve the spatial reuse of wireless channels and increase network capacity. However, the number of directional radio interfaces in MR-MC DWMN affects topology reliability and survivability. This article focuses on the construction of robust topology with radio interface constraints in MR-MC DWMN. Because of the limitation of the number of directional radio interfaces, we first formulate this topology optimization problem with directional radio interface constraints to be equivalent to establish k-connected topology with node degree constraints and then propose a robust topology construction algorithm with directional radio interface constraint. We define the link weight based on node degree and then use graph theory to construct the robust topology with node degree constraints. The proposed constructing robust topology with directional radio interface constraint can not only establish k-connected topology but also minimize the maximum node degree and meet the requirement of radio interface constraints. Simulation shows that constructing robust topology with directional radio interface constraint obtains less maximum node degree and average path length than existing k-connected topology control algorithms under the limitation of directional radio interfaces. Moreover, the constructing robust topology with directional radio interface constraint achieves better network performance than other algorithms.

FICTC: fault-tolerance-and-interference-aware topology control for wireless multi-hop networks

K-connectivity-based topology control can improve fault-tolerant performance of multi-hop wireless networks. Existing algorithms mainly focused on preserving the same k-connectivity between any two nodes. However, in practical network deployments, the algorithms enforcing k-connectivity degrade network performance, when the topology requires heterogeneous nodal fault-tolerant requirements. In this paper, we aim to develop interference-aware topology control based on the different k ij connectivities between any two nodes and propose a fault-tolerance-and-interference-aware topology control (FICTC) algorithm. It can be proved that FICTC can meet different fault-tolerant requirements between any two nodes, and is the optimum solution for min-max network interference. Simulation results show that FICTC not only leads to weaker interference, but also achieves higher throughput and lower end-to-end (E2E) delay than existing fault-tolerant topology control schemes.