Energy Consumption in Wireless Sensor Network

Energy is a limited resource in wireless sensor networks. In fact, the reduction of power consumption is crucial to increase the lifetime of low power sensor networks. Wireless sensor networks consist of small, autonomous devices with wireless networking capabilities. In order to further increase the applicability in real world applications, minimizing power consumption is one of the most critical issues. Therefore, accurate power model is required for the evaluation of wireless sensor networks. To estimate the lifetime of sensor node, the energy characteristics of sensor node are measured. Research in this area has been growing in the past few years given the wide range of applications that can benefit from such a technology. Based on the proposed model, the estimated lifetime of a battery powered sensor node can be increased significantly. Keywords—Sensor, Wireless Sensor Network, Energy Consumptio

Adaptive decentralized re-clustering protocol for wireless sensor networks

AbstractWireless sensor networks are composed of a large number of sensor nodes with limited energy resources. One critical issue in wireless sensor networks is how to gather sensed information in an energy efficient way since the energy is limited. The clustering algorithm is a technique used to reduce energy consumption. It can improve the scalability and lifetime of wireless sensor network. In this paper, we introduce an adaptive clustering protocol for wireless sensor networks, which is called Adaptive Decentralized Re-Clustering Protocol (ADRP) for Wireless Sensor Networks. In ADRP, the cluster heads and next heads are elected based on residual energy of each node and the average energy of each cluster. The simulation results show that ADRP achieves longer lifetime and more data messages transmissions than current important clustering protocol in wireless sensor networks

Resource Aware Sensor Nodes in Wireless Sensor Networks

Wireless sensor networks are continuing to receive considerable research interest due, in part, to the range of possible applications. One of the greatest challenges facing researchers is in overcoming the limited network lifetime inherent in the small locally powered sensor nodes. In this paper, we propose IDEALS, a system to manage a wireless sensor network using a combination of information management, energy harvesting and energy monitoring, which we label resource awareness. Through this, IDEALS is able to extend the network lifetime for important messages, by controlling the degradation of the network to maximise information throughput

AM-DisCNT: Angular Multi-hop DIStance based Circular Network Transmission Protocol for WSNs

The nodes in wireless sensor networks (WSNs) contain limited energy resources, which are needed to transmit data to base station (BS). Routing protocols are designed to reduce the energy consumption. Clustering algorithms are best in this aspect. Such clustering algorithms increase the stability and lifetime of the network. However, every routing protocol is not suitable for heterogeneous environments. AM-DisCNT is proposed and evaluated as a new energy efficient protocol for wireless sensor networks. AM-DisCNT uses circular deployment for even consumption of energy in entire wireless sensor network. Cluster-head selection is on the basis of energy. Highest energy node becomes CH for that round. Energy is again compared in the next round to check the highest energy node of that round. The simulation results show that AM-DisCNT performs better than the existing heterogeneous protocols on the basis of network lifetime, throughput and stability of the system.Comment: IEEE 8th International Conference on Broadband and Wireless Computing, Communication and Applications (BWCCA'13), Compiegne, Franc

Scale-free topology optimization for software-defined wireless sensor networks: A cyber-physical system

Due to the limited resource and vulnerability in wireless sensor networks, maximizing the network lifetime and improving network survivability have become the top priority problem in network topology optimization. This article presents a wireless sensor networks topology optimization model based on complex network theory and cyber-physical systems using software-defined wireless sensor network architecture. The multiple-factor-driven virtual force field and network division–oriented particle swarm algorithm are introduced into the deployment strategy of super-node for the implementation in wireless sensor networks topology initialization, which help to rationally allocate heterogeneous network resources and balance the energy consumption in wireless sensor networks. Furthermore, the preferential attachment scheme guided by corresponding priority of crucial sensors is added into scale-free structure for optimization in topology evolution process and for protection of vulnerable nodes in wireless sensor networks. Software-defined wireless sensor network–based functional architecture is adopted to optimize the network evolution rules and algorithm parameters using information cognition and flow-table configure mode. The theoretical analysis and experimental results demonstrate that the proposed wireless sensor networks topology optimization model possesses both the small-world effect and the scale-free property, which can contribute to extend the lifetime of wireless sensor networks with energy efficiency and improve the robustness of wireless sensor networks with structure invulnerability

Efficient Data Gathering in Wireless Sensor Networks Based on Matrix Completion and Compressive Sensing

Gathering data in an energy efficient manner in wireless sensor networks is an important design challenge. In wireless sensor networks, the readings of sensors always exhibit intra-temporal and inter-spatial correlations. Therefore, in this letter, we use low rank matrix completion theory to explore the inter-spatial correlation and use compressive sensing theory to take advantage of intra-temporal correlation. Our method, dubbed MCCS, can significantly reduce the amount of data that each sensor must send through network and to the sink, thus prolong the lifetime of the whole networks. Experiments using real datasets demonstrate the feasibility and efficacy of our MCCS method

EEHC: Event-driven Energy Optimization in Heterogeneous Clustered Wireless Sensor Networks

Wireless sensor networks are used in various applications worldwide. Large numbers small sized, inexpensive, low-powered sensor nodes are deployed in the target field to monitor or track particular objects. Sensor nodes have limited energy and computation capability. Energy optimization is an important task should be performed to improve the lifetime of the wireless sensor networks. Many researches focus only on continuous delivery model. This paper proposed energy efficient event-driven heterogeneous clustered wireless sensor network (EEHC) system. The results show that the proposed system reduced the energy consumption and longer lifetime than its comparatives