Terms Of Network Lifetime Research Articles

Energy‐efficient joint routing and power allocation optimisation in bit error rate constrained multihop wireless networks

Energy efficiency is a crucial design issue in energy-constrained wireless networks to ensure uninterrupted information exchange. With the requirement of average end-to-end bit error rate (BER), the problem of joint routing and power allocation optimisation in multihop wireless network is studied here for two network power management policies: one is to minimise overall transmit power and the other is to maximise network lifetime. The proposed minimum total power strategy is optimal for minimising the overall transmit power consumption in the network and is preferable in network with tethered energy resources. To maximise the lifetime of a network with battery-operated nodes, the authors have developed two residual energy-aware joint routing and power allocation strategies: path lifetime maximisation (PLM) strategy and minimum weighted total power (MWTP) strategy. A distributed implementation for these strategies is also presented. Simulation results demonstrate that the proposed strategies achieve significant power saving and prolong network lifetime considerably over traditional routing algorithm with individual link BER constraint. It has also been shown that at reasonably low route refresh interval, the MWTP strategy performs best in terms of network lifetime, whereas at very high route refresh interval, the PLM strategy is optimal for network lifetime maximisation.

Load management scheme for energy holes reduction in wireless sensor networks

In a wireless sensor network where sensors are arranged into a flat topology, sensors near the sink consume much more energy than sensors at the boundary of the network. Sensors near the sink relay many packets than far away sensors to the sink. After these sensors expire, energy holes are created near the sink. Therefore, other sensors cannot reach to the sink and the network becomes disconnected. In this paper, we propose some strategies that can balance energy consumption of the deployed sensors and reduce energy holes from the network by balancing the communication load as equally as possible. We performed extensive experiments on the proposed algorithm using various network scenarios and compared it with other existing algorithms. The experimental results verify the effectiveness and feasibility of the proposed work in terms of network lifetime, energy consumption, and other important network parameters.

Impact of using Mobile Sink on Hierarchical Routing Protocols for Wireless Sensor Networks

Wireless sensor networks (WSNs) are composed of many low cost, low power devices with sensing, local processing and wireless communication capabilities. In these networks energy constraint is very important. Routing protocols form one of the most important communication paradigms that greatly affect the performance of the wireless sensor networks. In this paper, we compare the performances of six hierarchical based routing protocols when mobile sink is used. We perform analytical simulations in terms of network lifetime and average energy consumption.

Cross-layer cluster-based energy-efficient protocol for wireless sensor networks.

Recent developments in electronics and wireless communications have enabled the improvement of low-power and low-cost wireless sensors networks (WSNs). One of the most important challenges in WSNs is to increase the network lifetime due to the limited energy capacity of the network nodes. Another major challenge in WSNs is the hot spots that emerge as locations under heavy traffic load. Nodes in such areas quickly drain energy resources, leading to disconnection in network services. In such an environment, cross-layer cluster-based energy-efficient algorithms (CCBE) can prolong the network lifetime and energy efficiency. CCBE is based on clustering the nodes to different hexagonal structures. A hexagonal cluster consists of cluster members (CMs) and a cluster head (CH). The CHs are selected from the CMs based on nodes near the optimal CH distance and the residual energy of the nodes. Additionally, the optimal CH distance that links to optimal energy consumption is derived. To balance the energy consumption and the traffic load in the network, the CHs are rotated among all CMs. In WSNs, energy is mostly consumed during transmission and reception. Transmission collisions can further decrease the energy efficiency. These collisions can be avoided by using a contention-free protocol during the transmission period. Additionally, the CH allocates slots to the CMs based on their residual energy to increase sleep time. Furthermore, the energy consumption of CH can be further reduced by data aggregation. In this paper, we propose a data aggregation level based on the residual energy of CH and a cost-aware decision scheme for the fusion of data. Performance results show that the CCBE scheme performs better in terms of network lifetime, energy consumption and throughput compared to low-energy adaptive clustering hierarchy (LEACH) and hybrid energy-efficient distributed clustering (HEED).

Improving the Network Lifetime of MANETs through Cooperative MAC Protocol Design

Cooperative communication, which utilizes nearby terminals to relay the overhearing information to achieve the diversity gains, has a great potential to improve the transmitting efficiency in wireless networks. To deal with the complicated medium access interactions induced by relaying and leverage the benefits of such cooperation, an efficient Cooperative Medium Access Control (CMAC) protocol is needed. In this paper, we propose a novel cross-layer distributed energy-adaptive location-based CMAC protocol, namely DEL-CMAC, for Mobile Ad-hoc NETworks (MANETs). The design objective of DEL-CMAC is to improve the performance of the MANETs in terms of network lifetime and energy efficiency. A practical energy consumption model is utilized in this paper, which takes the energy consumption on both transceiver circuitry and transmit amplifier into account. A distributed utility-based best relay selection strategy is incorporated, which selects the best relay based on location information and residual energy. Furthermore, with the purpose of enhancing the spatial reuse, an innovative network allocation vector setting is provided to deal with the varying transmitting power of the source and relay terminals. We show that the proposed DEL-CMAC significantly prolongs the network lifetime under various circumstances even for high circuitry energy consumption cases by comprehensive simulation study.

Effect of using Mobile Sink on Chain-based Routing Protocols in Wireless Sensor Networks

In this paper, we examine some protocols related to WSNs. To evaluate the efficiency of different routing schemes, we compare six chain based routing protocols; Power Efficient Gathering in Sensor Information Systems (PEGASIS), Power Efficient Gathering in Sensor Information System Extended (PEGASIS-E), Chain Oriented SEnsor Network (COSEN), Energy Efficient Chain Based Sensor Network (ECBSN), Improved Energy Efficient Chain Based Sensor Network (IECBSN), and Energy-Aware PEGASIS-Based Hierarchal Routing Protocol for Wireless Sensor Networks (EAPHRN). Two scenarios are discussed to compare the performances of chain based routing protocols; in the first scenario static sink is used and in the second one mobile sink is used. We perform analytical simulations in terms of network lifetime and average energy consumption.

Chain-based communication in cylindrical underwater wireless sensor networks.

Appropriate network design is very significant for Underwater Wireless Sensor Networks (UWSNs). Application-oriented UWSNs are planned to achieve certain objectives. Therefore, there is always a demand for efficient data routing schemes, which can fulfill certain requirements of application-oriented UWSNs. These networks can be of any shape, i.e., rectangular, cylindrical or square. In this paper, we propose chain-based routing schemes for application-oriented cylindrical networks and also formulate mathematical models to find a global optimum path for data transmission. In the first scheme, we devise four interconnected chains of sensor nodes to perform data communication. In the second scheme, we propose routing scheme in which two chains of sensor nodes are interconnected, whereas in third scheme single-chain based routing is done in cylindrical networks. After finding local optimum paths in separate chains, we find global optimum paths through their interconnection. Moreover, we develop a computational model for the analysis of end-to-end delay. We compare the performance of the above three proposed schemes with that of Power Efficient Gathering System in Sensor Information Systems (PEGASIS) and Congestion adjusted PEGASIS (C-PEGASIS). Simulation results show that our proposed 4-chain based scheme performs better than the other selected schemes in terms of network lifetime, end-to-end delay, path loss, transmission loss, and packet sending rate.

A Novel Method of Modeling Wireless Sensor Network Using Fuzzy Graph and Energy Efficient Fuzzy Based k-Hop Clustering Algorithm

Clustering is one of the widely used methods to save energy, increase spatial re usability, and scalability. In this paper, we have proposed a new fuzzy graph based modeling approach for wireless sensor network which takes into account the dynamic nature of network, volatile aspects of radio links and physical layer uncertainty. The fuzzy graph constructs fuzzy neighborhoods which are used to identify all the prospective member nodes of a cluster. For computation of optimum centrality of a cluster, we have defined a new centrality metric namely fuzzy k-hop centrality. The proposed centrality metric considers residual energy of individual nodes, link quality, hop distance between the prospective cluster head and respective member nodes to ensure better cluster head selection and cluster quality. Finally, a new computationally inexpensive clustering algorithm has been developed. The simulation results demonstrate that the proposed algorithm resulted in prolonged network lifetime in terms of clustering rounds, scalability, higher energy efficiency and uniform cluster head and cluster members distribution, as compare to LEACH-ERE and CHEF.

Sustainability Enhancement Multihop Clustering in Cognitive Radio Sensor Networks

A cognitive radio based hybrid data-type clustering (CR-HDC) algorithm is proposed to maximize network energy efficiency of cognitive radio (CR) sensor networks (CRSNs). By analyzing the overall energy consumption of CRSNs under various conditions, the optimal transmission range of a sensor node can be obtained for both when spectrum handoff (SHO) is applied and when it is not. Simulation results show that CR-HDC achieves performance enhancements in terms of network lifetime and the number of packets received at the base station (BS) compared to when applying the centralized low energy adaptive clustering hierarchy (LEACH-C) or hybrid data-type clustering (HDC) to CRSN environments.

An Energy-Balanced Mechanism for Hierarchical Routing in Wireless Sensor Networks

In wireless sensor networks (WSNs), energy-constrained sensor nodes are always deployed in hazardous and inaccessible environments, making energy management a key problem for network design. The mechanism of RNTA (redundant node transmission agents) lacks an updating mechanism for the redundant nodes, causing an unbalanced energy distribution among sensor nodes. This paper presents an energy-balanced mechanism for hierarchical routing (EBM-HR), in which the residual energy of redundant nodes is quantified and made hierarchic, so that the cluster head can dynamically select the redundant node with the highest residual energy grade as a relay to complete the information transmission to the sink node and achieve an intracluster energy balance. In addition, the network is divided into several layers according to the distances between cluster heads and the sink node. Based on the energy consumption of the cluster heads, the sink node will decide to recluster only in a certain layer so as to achieve an intercluster energy balance. Our approach is evaluated by a simulation comparing the LEACH algorithm to the HEED algorithm. The results demonstrate that the BEM-HR mechanism can significantly boost the performance of a network in terms of network lifetime, data transmission quality, and energy balance.

Wireless Sensor Network Clustering Using Particles Swarm Optimization For Reducing Energy Consumption

Wireless sensor networks (WSN ) is composed of a large number of small nodes with limited functionality. The most important issue in this type of networks is energy constraints. In this area several researches have been done from which clustering is one of the most effective solutions. The goal of clustering is to divide network into sections each of which has a cluster head (CH). The task of cluster heads collection, data aggregation and transmission to the base station is undertaken. In this paper, we introduce a new approach for clustering sensor networks based on Particle Swarm Optimization (PSO) algorithm using the optimal fitness function, which aims to extend network lifetime. The parameters used in this algorithm are residual energy density, the distance from the base station, intra-cluster distance from the cluster head. Simulation results show that the proposed method is more effective compared to protocols such as (LEACH, CHEF, PSO-MV) in terms of network lifetime and energy consumption.

Enhanced Balanced Cluster Lifetime Prolonging Protocol for Wireless Sensor Network

In enhanced balanced cluster lifetime prolonging protocol we investigate that how balance cluster approach work in heterogeneous environment by applying same network structure in heterogeneous environment. Dividing network in four equal static balanced cluster so that all the clusters have almost equal number of nodes. This will help in even load distribution of network and this will increase the network lifetime and energy of the network. Simulation-based evaluations are performed to compare the performance of EBCLPP against BCLPP balanced cluster lifetime prolonging protocol and EDDEEC Enhanced Developed Distributed Energy-Efficient Clustering for Heterogeneous Wireless Sensor .Our experiment results show that EBCLPP outperforms BCLPP and EDDEEC in terms of network lifetime and power consumption minimization. In heterogeneous wireless sensor network optimization of energy is the main issue. In previous scheme the clusters where formed dynamically and the cluster head selection was based on the probability. Formation of clusters dynamically lead to loss of energy in every round which affected the network lifetime and energy of every node. We investigate that how balance cluster approach work for heterogeneous wireless sensor network in this scheme we are forming the balance cluster in the start of network operation in order to reduce the overhead of cluster formation after every round. We divide sensor nodes in four cluster and all the cluster have almost equal number of nodes. And by doing so the cluster does not even get unbalanced as nodes in all the clusters are almost same. Cluster head selection is mapped to homogenous network that is done by finding the weight of nodes in the cluster and so the node having highest energy will become cluster head for the round. In this case all the nodes whether they are super nodes or normal nodes all the nodes get the chance to become the cluster head. This will increase the number of nodes alive over time and also the average energy per node.

Mixed Communication Method on the Grid-Based for Wireless Sensor Networks

When senors transmit their data to the sink via multi-hop communication, the sensors closer to the sink are burdened with heavy relay traffic and tend to die early. On the contrary, if all sensors transmit datas to the sink via single-hop communication, the sensors further from the sink will die much more quickly than those closer to the sink. In this paper, we first develop an analytical model to derive the optimal cluster radius. Then we propose a mixed communication method on grid-based where the sensors can transmit data to the sink in either single-hop or multi-hop. Finally, we conduct extensive experiments and show that our method outperforms LEACH and HEED in terms of network lifetime by balancing energy consumption.

Mixed Communication Method on the Grid-Based for Wireless Sensor Networks

When senors transmit their data to the sink via multi-hop communication, the sensors closer to the sink are burdened with heavy relay traffic and tend to die early. On the contrary, if all sensors transmit datas to the sink via single-hop communication, the sensors further from the sink will die much more quickly than those closer to the sink. In this paper, we first develop an analytical model to derive the optimal cluster radius. Then we propose a mixed communication method on grid-based where the sensors can transmit data to the sink in either single-hop or multi-hop. Finally, we conduct extensive experiments and show that our method outperforms LEACH and HEED in terms of network lifetime by balancing energy consumption.

An Intelligent Routing Algorithm in Wireless Sensor Networks Based on Reinforcement Learning

Lifetime enhancement has been a hot issue in Wireless Sensor Networks (WSNs). To prolong the network lifetime of WSNs, this paper proposes an intelligent routing algorithm named RLLO. RLLO makes uses of the superiority of reinforcement learning (RL) and considers residual energy and hop count to define the reward function. It is to uniformly distribute the energy consumption and improve the packet delivery without additional cost. This proposed algorithm has been compared with Energy Aware Routing (EAR) and improved EAR (I-EAR). Simulation results show that RLLO gains a significant improvement in terms of network lifetime and packet delivery over these two algorithms.

A hybrid clustering technique using quantitative and qualitative data for wireless sensor networks

Clustering is an efficient method to organize sensor nodes in Wireless Sensor Networks (WSNs) for data transmissions and energy saving. To perform clustering, many methods require geographic location data for calculating the distance between sensor nodes. But location data may not always be available due to Global Positioning System (GPS) failures or may not be practical in consideration of all sensor nodes due to the high cost and energy consumption of GPS. Alternatively, Received Signal Strength (RSS) or RSS Indicator (RSSI) has been used to estimate the distance. But many studies have shown that RSS or RSSI is not reliable in practice. In order to mitigate these realistic problems, this paper proposes a hybrid clustering protocol – Hybrid Distributed Hierarchical Agglomerative Clustering (H-DHAC) – which uses both quantitative location data and binary qualitative connectivity data in clustering for WSNs. Our simulation results reveal that H-DHAC only has a slightly lower percentage of compromise in performance in terms of network life time and total transmitted data compared to similar approaches that use complete location data. However, H-DHAC still outperforms the well known clustering protocols, e.g., LEACH and LEACH-C. On the other hand, the cost of H-DHAC can be significantly lower in comparison to those approaches that use complete quantitative location data, as GPS is not required for all sensor nodes. In addition, H-DHAC still can be operational in the presence of GPS failures.

An Enhanced Energy Aware Coverage Preservation with Static Clustering for WSN

wireless sensor network consists of a huge number of sensor nodes associated via wireless medium. Nodes in a WSN are organized with limited battery energy and thus improvement on network lifetime by reducing energy-usage is of extreme important. One of the solutions to minimize such energy-usage is associate clustering of network nodes. In this paper an associate clustering scheme in WSN is proposed where cluster heads are formed by creating a probable associate list is in descending order in which cluster heads are organized according to their residual energy. We have conducted simulation-based evaluations to compare the performance of EEACPSC against Energy Aware Coverage Preservation and Lifetime Enhancement Protocol (EACPLEP) and Enhanced-Energy Efficient Protocol with Static Clustering (E3PSC). Our experiment results show that EEACPSC outperforms EACPELP and E3PSC in terms of network lifetime and power consumption minimization. And its results come out in 3D form.

Performance Evaluation of Energy Efficient Clustering Protocol for Cluster Head Selection in Wireless Sensor Network

Wireless sensor network are emerging in various fields like environmental monitoring, mining, surveillance system, medical monitoring. LEACH protocol is one of the predominantly used clustering routing protocols in wireless sensor networks. In Leach each node has equal chance to become a cluster head which make the energy dissipated of each node be moderately balanced. We have pioneered an improved algorithm named as Novel Leach based on Leach protocol. The proposed algorithm shows the significant improvement in network lifetime .Comparison of proposed algorithm is done with basic leach in terms of network life time, cluster head selection, energy consumption, and data transmission to base station. The simulation results shows that proposed algorithm can reduce network energy consumption and prolong network life commendably. Simulation of our protocol is done with Matlab.

A multipath energy-conserving routing protocol for wireless ad hoc networks lifetime improvement

Ad hoc networks are wireless mobile networks that can operate without infrastructure and without centralized network management. Traditional techniques of routing are not well adapted. Indeed, their lack of reactivity with respect to the variability of network changes makes them difficult to use. Moreover, conserving energy is a critical concern in the design of routing protocols for ad hoc networks, because most mobile nodes operate with limited battery capacity, and the energy depletion of a node affects not only the node itself but also the overall network lifetime. In all proposed single-path routing schemes a new path-discovery process is required once a path failure is detected, and this process causes delay and wastage of node resources. A multipath routing scheme is an alternative to maximize the network lifetime. In this paper, we propose an energy-efficient multipath routing protocol, called AOMR-LM (Ad hoc On-demand Multipath Routing with Lifetime Maximization), which preserves the residual energy of nodes and balances the consumed energy to increase the network lifetime. To achieve this goal, we used the residual energy of nodes for calculating the node energy level. The multipath selection mechanism uses this energy level to classify the paths. Two parameters are analyzed: the energy threshold beta and the coefficient alpha. These parameters are required to classify the nodes and to ensure the preservation of node energy. Our protocol improves the performance of mobile ad hoc networks by prolonging the lifetime of the network. This novel protocol has been compared with other protocols: AOMDV and ZD-AOMDV. The protocol performance has been evaluated in terms of network lifetime, energy consumption, and end-to-end delay.

Energy-aware routing algorithm for wireless sensor networks

The main constraint of wireless sensor networks (WSNs) is the limited and generally irreplaceable power source of the sensor nodes. Therefore, designing energy saving routing algorithm is one of the most focused research issues. In this paper, we propose an energy aware routing algorithm for cluster based WSNs. The algorithm is based on a clever strategy of cluster head (CH) selection, residual energy of the CHs and the intra-cluster distance for cluster formation. To facilitate data routing, a directed virtual backbone of CHs is constructed which is rooted at the sink. The proposed algorithm is also shown to balance energy consumption of the CHs during data routing process. We prove that the algorithm achieves constant message and linear time complexity. We test the proposed algorithm extensively. The experimental results show that the algorithm outperforms other existing algorithms in terms of network lifetime, energy consumption and other parameters.