Energy-efficient Topology Control Research Articles

Energy-Efficient Topology Control Mechanism for IoT-Oriented Software-Defined WSNs

In time-varying software-defined wireless sensor networks (SDWSNs) for Internet-of-Things (IoT) applications, the topology may change due to the interference or abnormal events, thus leading to network performance degradation. In this paper, an energy-efficient topology control (TC) mechanism applied for IoT-oriented SDWSNs is proposed to maximize the network energy efficiency (EE) during the dynamic topology maintenance. First, a hierarchical SDWSN architecture consisting of the cluster-based sensing network and the programmable relay network is presented. Second, two TC algorithms based on the link EE are proposed to apply in the cluster and relay sub-networks of SDWSN, respectively. In the cluster sub-network, the proposed distributed TC algorithm enables the link interference mitigation by employing power control and rate allocation in each cluster. In the relay sub-network, the proposed centralized TC algorithm first utilizes a specified model to construct the original topology. During the dynamic topology maintenance, the proposed centralized TC algorithm is realized by the value-iteration learning method based on a Markov decision process (MDP) model, upon which the state-transition probability (STP) of the relay sub-network is obtained, where the relay-network state is composed of the link, the queue, and the residual energy ratio states for all nodes in the relay sub-network. Finally, simulation results show that both two TC algorithms can improve the corresponding sub-network EE of time-varying SDWSN.

Energy efficient topology control in Underwater Wireless Sensor Networks

Topology control in Underwater Wireless Sensor Networks (UWSNs) has been an active area of research owing to unique challenges an underwater environment poses. Node mobility due to water currents creates problems in localization and data transfer. In this paper, we propose an energy efficient topology control for mobile UWSNs using Expectation Maximization (EM) and Vickrey–Clarke–Groves (VCG) Auction mechanism. In the first stage, followed by a water current induced topology disturbance, the designated cluster head runs the EM algorithm to find similar sensor nodes in its proximity. In the second stage, cluster head runs VCG auction mechanism to compensate sensor nodes for costs incurred during data transfer. This ensures seamless data transmission between sensor nodes of heterogeneous ownership leading to higher energy efficiency. Simulations present higher energy efficiency of the network post EM and VCG steps. Comparison with existing protocols demonstrates superior performance of the protocol proposed in this paper.

An energy-efficient topology control algorithm for optimizing the lifetime of wireless ad-hoc IoT networks in 5G and B5G

Wireless ad-hoc IoT (WAIoT) is promising in providing connections for a considerable amount of devices in the next generation (5G and beyond 5G) networks. A challenge in WAIoT networks is that most network nodes are not stable due to the limited power supply (such as a battery). In this paper, we focus on balancing node residual energy and node degree to prolong the network lifetime. We first present a statistic-based algorithm (named ED-index) for evaluating the network topology and further develop an energy-efficient topology control algorithm (named EDTC). The EDTC algorithm leverages the maximum spanning tree algorithm to build a robust backbone topology and utilizes the proposed ED-index algorithm to re-introduce some edges to the topology. We also present a graph convolutional network (GCN) based algorithm to imitate the initial EDTC algorithm through learning. In the random communication experiment, the proposed EDTC algorithm achieves two times the network lifetime than the state-of-the-art. Moreover, the GCN-based EDTC algorithm saves around 99% optimization time than the initial EDTC algorithm when the number of network nodes is 100.

An Energy-Efficient Topology Control Algorithm for Earth Building Monitoring Using Heterogeneous Wireless Sensor Networks

An earth building is still popular in the villages of China, which should be carefully monitored in the wet and rainy area using new information technology, e.g., sensor networks. However, how to design an energy-efficient and robust scheme in the heterogeneous wireless sensor networks (HWSN) is a critical issue, since the network should be long-time available and node failure may lead to data delivery unreliable and network collapse. In this paper, an energy-efficient topology control (EETC) algorithm is proposed for energy saving and load balancing of the network. In EETC, cluster heads are selected by the geometric method and well-distributed in the monitor area, while the non-cluster head members in each cluster are adjusted by Minimal Cost Maximal Flow (MCMF) so as to permit each cluster has the similar number of the cluster member. Furthermore, we design topology maintenance with partial adjustment using Breadth First Search (BFS) and shortest-path routing protocol in order to prolong the network lifetime. The simulation result shows that EETC is not only reliable to forward the data for HWSN but also has a longer lifetime than LEACH, EDFCM, EDCS, SPEZ and CREEP.

The Effects of Using Some Different Types of Learning Automata on Presentation of Adaptive Neighbor-Based and Energy Efficient Topology Control Protocols in Wireless Sensor Networks

The high number of nodes and dynamic and periodic topological changes, as well as constraints in the physical size of nodes, energy resources, and power of processing are some characteristics of sensor networks that make them different from other networks. One method to overcome these constraints is topology control with the aim of reducing energy consumption and increasing the network’s capacity, which has the most influence on the network’s efficiency, especially in terms of energy consumption and lifetime. In consideration of learning Automata’s abilities, such as low computational load and adaptability to changes via low environmental feedbacks, in this paper, neighbor-based topology control protocols based on learning Automata have been proposed somehow that all nodes are equipped with Automata. The nodes try to adapt their selected actions with required conditions for creating a connected and energy efficient network by selecting the best radio range for themselves. This approach finally forms a proper topology, and in this way it lowers the network’s energy consumption in its lifetime. The exclusive characteristic of these methods is the high number of transmission ranges that each node can select as transmission radius. In the first proposed protocol, a P-model environment is used for learning phase, but in the second proposed protocol, a Q-model environment is applied. Simulation results show favorite functionality of proposed protocols in comparison with some other similar protocols from topology control point of view, as well as high improvement of achieved results for the Q-model environment.

Energy efficient topology control for multi-hop relay cellular networks based on flow management

The rapid expansion of mobile communication networks has led to a significant increase of energy consumption, and the energy consumption of wireless access networks accounted for nearly 90%. As an important form of the wireless access networks, multi-hop relay networks have been widely deployed in the existing cellular networks. Consequently, improving the energy efficient of multi-hop relay cellular networks is crucial for communication networks. In this paper, we design an energy flow management framework for multi-hop relay cellular networks, which contains routing planning, traffic adjustment and power allocation. In order to reduce the energy consumption and guarantee the system capacity, a heuristic algorithm is designed in this paper, which mixes the ant colony algorithm with convex optimization theory. In order to verify the effect of the proposed algorithm, we make numerical simulation and compare it with other network management strategies, such as ant colony algorithm, shortest path routing strategy and greedy algorithm. Simulation results show that by our algorithm, the energy consumption can be reduced compared with the ant colony algorithm, shortest path and greedy algorithm while ensuring the demand of quality of service (QoS).

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.

Reliable and energy efficient topology control in probabilistic Wireless Sensor Networks via multi-objective optimization

In Wireless Sensor Networks (WSNs) instead of using the possible network connectivity to its maximum extent, a deliberate choice must be made to restrict the topology of the network. Constructing a virtual backbone network using Connected Dominating Sets (CDS) is a promising choice for topology control. Currently, almost all existing studies employ heuristic and/or meta-heuristic optimizations for formulating minimum-sized CDS under the deterministic network model. In this paper, we address the problem of constructing energy efficient CDS in WSNs while improving network reliability. The problem is modelled as a multi-objective optimization that simultaneously maximizes two contradictory parameters: reliability and energy efficiency. Unlike most of the existing studies, the reliability parameter is expressed as a probabilistic inference using probabilistic network model due to uncertainty in connections among sensor nodes. Extensive simulation results indicate that the proposed approach in this paper achieves more reliability, longer stability period and more energy efficient CDS compared to other approaches in the literature.

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 Novel Energy Efficient Topology Control Scheme Based on a Coverage-Preserving and Sleep Scheduling Model for Sensor Networks.

In high-density sensor networks, scheduling some sensor nodes to be in the sleep mode while other sensor nodes remain active for monitoring or forwarding packets is an effective control scheme to conserve energy. In this paper, a Coverage-Preserving Control Scheduling Scheme (CPCSS) based on a cloud model and redundancy degree in sensor networks is proposed. Firstly, the normal cloud model is adopted for calculating the similarity degree between the sensor nodes in terms of their historical data, and then all nodes in each grid of the target area can be classified into several categories. Secondly, the redundancy degree of a node is calculated according to its sensing area being covered by the neighboring sensors. Finally, a centralized approximation algorithm based on the partition of the target area is designed to obtain the approximate minimum set of nodes, which can retain the sufficient coverage of the target region and ensure the connectivity of the network at the same time. The simulation results show that the proposed CPCSS can balance the energy consumption and optimize the coverage performance of the sensor network.

Algebraic connectivity aided energy-efficient topology control in selfish ad hoc networks

Topology control is a technique to assign per-node's transmit parameters so as to get the network topology with the best possible network performance given some optimization criteria, such as energy-efficient connectivity. In this paper, we investigate energy-efficient topology control for wireless ad-hoc networks in the presence of selfish nodes. A non-cooperative game aided topology control approach is developed for minimizing the potential transmit power, whilst maintaining the network connectivity. The utility function is conceived by virtue of algebraic connectivity, which is a fine metric to measure the connectivity redundancy of a network. We prove the existence of Nash Equilibrium (NE) and demonstrate that the NE is Pareto optimal as well. Specifically, two fully distributed topology controls--algebraic connectivity-based Max-Improvement (ACMI) algorithm and $$\delta$$ź-Improvement (ACDI) algorithm--are proposed to find the NE topologies. Both ACMI and ACDI can easily construct the stable topologies with a low information-overhead of the order O(n), where n is the number of nodes. Simulations demonstrate that our algorithms observably eliminate the redundancy of the maximum power topology and embrace several other attractive topological features.

CDS -BASED ENERGY EFFICIENT TOPOLOGY CONTROL ALGORITHM IN WIRELESS SENSOR NETWORKS

Wireless Sensor Networks (WSNs) are a self organized network which consists of large number of sensor nodes that collects the data in a various environment [1, 2]. The sensors work on battery that have limited lifetime so it is a challenge to create an energy efficient network that can reduce the energy consumption and interference in the network graph and thereby extend the network lifetime [2]. For saving energy and extending network lifetime the topology is a well-known technique in WSNs and the widely used topology control strategy is the construction of Connected Dominating Set (CDS) [3, 4]. In this paper, we construct a CDS based energy efficient topology control algorithm i.e. GCDSTC for WSNs. The performance analysis includes the study of GCDSTC algorithm in terms of complexity and compares it with EBTC (Energy Balanced Topology Control) algorithm. The simulation results indicate that the GCDSTC algorithm reduce the energy consumption and interference in the network graph, in order to enhance the network lifetime.

Simulation Time and Energy Test for Topology Construction Protocol in Wireless Sensor Networks

Coverage area and energy consumption are very big challenges in the field of Wireless Sensor Networks (WSNs) as it affects the number of sensors, connectivity and network. Since the sensors are operating on battery of limited power, it is a challenging aim to design an energy efficient Topology Control protocol, which can minimize the energy and thereby extend the lifetime of the network. Through this paper an attempt has been made in terms of simulation time and spent energy in construction of topology in the sensor network by comparing Just Tree and K-neigh Tree protocols. The result shows that K-neigh Tree protocol consumes less energy than Just Tree protocol.

Energy-efficient topology control algorithm for maximizing network lifetime in wireless sensor networks with mobile sink

Uneven energy consumption is an inherent problem in wireless sensor networks characterized by multi-hop routing and many-to-one traffic pattern. Such unbalanced energy dissipation can significantly reduce network lifetime. In this paper, we study the problem of prolonging network lifetime in large-scale wireless sensor networks where a mobile sink gathers data periodically along the predefined path and each sensor node uploads its data to the mobile sink over a multi-hop communication path. By using greedy policy and dynamic programming, we propose a heuristic topology control algorithm with time complexity O(n(m+nlogn)), where n and m are the number of nodes and edges in the network, respectively, and further discuss how to refine our algorithm to satisfy practical requirements such as distributed computing and transmission timeliness. Theoretical analysis and experimental results show that our algorithm is superior to several earlier algorithms for extending network lifetime.

Connected k-Coverage Topology Control for Area Monitoring in Wireless Sensor Networks

One of the design challenges in Wireless sensor network (WSN) is to save limited energy resource to prolong the lifetime of the network without affecting their communication connectivity or sensing coverage . In dense WSN, the sensing areas of sensor node may overlap with each other. In general, the larger the overlap of the sensing range, the more redundant data will be generated with more energy consumption. In WSN, connected dominating set (CDS) has been used for energy efficient topology control, where a virtual backbone is formed, which allows communication between any arbitrary pair of nodes in the network. Nodes which are not in CDS can go to sleep state for energy conservation. Applications related to security and reliability require a certain amount of active nodes to ensure desired level of coverage at all time. These active nodes should be connected to reduce the delay during the communication. Therefore, it is necessary to construct a fault-tolerant CDS that continues to function during node or link failure, for both coverage and connectivity requirements of WSN. In this paper, we propose k-coverage connected dominating set (k-CCDS) for connected area coverage. We also propose a weight metric named weighted coverage cost (WCC), which consists of energy of sensing neighbors. The proposed protocol selects a CDS based on WCC to ensure that every non-dominating node is connected with the CDS even if $$k-1$$k-1 dominating nodes are dead. This CDS is named k-CCDS, in which every non-dominating node is covered by atleast k dominating nodes. Simulation results show that it performs better when comparing with A3Cov in terms of CDS size, coverage, energy consumption and lifetime of the network.

Retracted: Reliable and Energy Efficient Topology Control Algorithm Based on Connected Dominating Set for Wireless Sensor Network

Retracted: Reliable and Energy Efficient Topology Control Algorithm Based on Connected Dominating Set for Wireless Sensor Network

Topology Control for Harvesting Enabled Wireless Sensor Networks: A Design Approach

While there has been a lot of research on energy efficient topology control protocols destined for different applications, topology control has never been explored in the presence of harvesting enabled sensors. Largely, researchers in this domain have considered a fixed battery design. We argue that arrival of harvesting enabled sensors necessitates rethink of topology control. The objective of topology control in this context should not be to minimize the spent energy and maintain a reduced topology, but to maximize fault tolerance in the network and increase the sensing coverage region. In this work, we first describe a taxonomy of existing topology control schemes and analyze the impact of reduced topology over fault tolerance and sensing coverage. We then describe the necessity of new design parameters in the presence of harvest-able ambient energy. We also outline guiding principles for designing a harvesting enabled topology control scheme. To cater for whether such a scheme is feasible or not, an insight is also provided onto the solar energy availability from solar radiations for near perpetual operation--as an example of available ambient energy. Based on the insight gained from the solar radiations availability, we explain why new design parameters are required for performance measurement of harvesting enabled sensors. The mathematical and empirical findings reveal that the topology control strategies, which do not take into account harvesting opportunity, are unable to provide better results in terms of fault tolerance and sensing coverage.

Energy-Efficient Topology Control With Selective Diversity in Cooperative Wireless Ad Hoc Networks: A Game-Theoretic Approach

Due to the scarce bandwidth and limited power supply in mobile terminals, performance and energy consumption in wireless communications must be continually focused upon. Cooperative transmissions improve the capacity performance of wireless ad hoc networks (WANETs). However, when energy efficiency is considered, the advantage of user cooperation over non-cooperation does not always exist since it involves multiple nodes with more energy consumption in transmissions. To exploit the benefits of user cooperation in cooperative WANETs, we propose a distributed energy-efficient selective diversity (EESD) topology control to improve energy efficiency, which jointly considers network capacity and energy consumption in terms of bits per Joule . EESD forms transmission coalitions via cooperative manner (i.e, diversity) selection, by taking into account the cost of channel information exchange. We then formulate EESD as a coalition game and propose an adaptive coalition formation algorithm for EESD with proved convergence property and stable coalition structures. Simulation results show the performance improvement of EESD in energy efficiency and network lifetime compared to the existing topology control schemes.

Energy-Efficient Topology Management With Interference Cancellation in Cooperative Wireless Ad Hoc Networks

With recent advances in parallel cooperative trans- missions between multiple source-destination pairs, interference cancellation (IC) can be achieved to improve the capacity per- formance of wireless networks. However, from energy efficiency perspective, user cooperation may not be always appealing, since the increased data rate of one user comes at the price of the energy consumed by another user. In this paper, we study the potential benefits/drawbacks of cooperative communications on network-level issues, such as the capacity and the energy efficiency. We show that, in terms of network energy efficiency, coopera- tive communications do not always outperform non-cooperative communications, and cooperative communications should be dy- namically applied in topology control to optimize the overall net- work energy efficiency. Specifically, we propose an energy-efficient topology control scheme by jointly considering the capacity and energy consumption of non-cooperative and cooperative commu- nications. Simulation results are presented to show the effective- ness of the proposed scheme.

An energy efficient localized topology control algorithm for wireless multihop networks

Localized topology control is attractive for obtaining reduced network graphs with desirable features such as sparser connectivity and reduced transmit powers. In this paper, we focus on studying how to prolong network lifetime in the context of localized topology control for wireless multi-hop networks. For this purpose, we propose an energy efficient localized topology control algorithm. In our algorithm, each node is required to maintain its one-hop neighborhood topology. In order to achieve long network lifetime, we introduce a new metric for characterizing the energy criticality status of each link in the network. Each node independently builds a local energy-efficient spanning tree for finding a reduced neighbor set while maximally avoiding using energy-critical links in its neighborhood for the local spanning tree construction. We present the detailed design description of our algorithm. The computational complexity of the proposed algorithm is deduced to be O(mlog n), where m and n represent the number of links and nodes in a node's one-hop neighborhood, respectively. Simulation results show that our algorithm significantly outperforms existing work in terms of network lifetime.