Energy Efficient Wireless Sensor Research Articles

IoT Based Energy-Efficient Data Aggregation Wireless Sensor Network in Agriculture: A Review

Sensor nodes generate Wireless Sensor Networks (WSNs), these networks have considerable application in the areas of habitat safety, disaster management, surveillance in defense, security & many more areas. WSNs are compact in size, with short battery power & additionally their processing capabilities are low. This restriction of battery power makes them vulnerably faulty. In order to save this limited power, redundant data must be stored inside the sensor node during aggregation which will result in a reduction power dissipation associated with the sending of unnecessary data. By aggregating data, we can control energy consumption by reducing redundancy. Data aggregation is a really effective technique for WSN. In this paper we discuss the aggregation of data and their complex energy-efficient approach used for data aggregation in WSN. This paper highlights the latest innovations in WSNs vital for the research in agricultural domain, further we present their classification & did a comparative analysis of the discussed protocols, the nomenclature of energy saving & harvesting strategies used in agricultural monitoring. Further it discuss the difficulties and drawbacks of WSNs in context of agriculture, The presented comparative study will helpful in increasing number of data processing opportunities available through the Internet of Things (IoT).

STBCP: An Energy Efficient Sub-threshold Bee Colony-based Protocol for Wireless Sensor Networks

Background & Objective: In this paper, a new energy efficient LEACH-based protocol for wireless sensor network is presented. One of the main issues in Wireless Sensor Networks (WSNs) is the battery consumption. In fact, changing batteries is a time consuming task and expensive. It is even impossible in many remote WSNs. Methods: The main goal of the presented protocol is to decrease the energy consumption of each node and increase the network lifetime. Lower power consumption results in longer battery lifetime. This protocol takes the advantage of sub-threshold technique and bee colony algorithm in order to optimize the energy consumption of a WSN. Simulation results show that the energy consumption of the wireless sensor network reduces by 25 percent using STBCP in comparison with recent LEACHbased protocols. It has been shown that the average energy of the network remains balanced and the distribution of residual energy in each round is equitable. Conclusion: In addition, the lifetime of a network using STBCP protocol has been increased by 23 percent regarding recently presented routing protocols.

Review : Secure energy-efficient IoT based wireless sensor networks: Findings and Challenges

Review : Secure energy-efficient IoT based wireless sensor networks: Findings and Challenges

Effect of the position of base station in square fields of energy efficient small, medium and large-scale wireless sensor networks - internet-of-things

In the recent time, wireless sensor networks (WSNs) are an essential component of the internet-of-things (IoTs). This has given new platforms for applications of integrated WSN-IoTs. The connection between the physical and virtual world of internet demands heterogeneous sensor nodes either deployed in an independent manner or embedded within other wireless devices. Stability and lifespan of the system are also decided by an important factor of the location of base station (BS) in the clustering of sensor nodes. Coverage, connectivity and an efficient communication in WSN-IoT integrated systems is decided by the position of base station in the midpoints of the four sides of a square field. The clustering in heterogeneous broad transmission distance protocol (HT-BTDP) with different base station locations shows the results of stability and lifetime. HT-BTDP is compared to the previous existing heterogeneous protocols in small, medium and large-scale networks for peripheral midpoint placement of BS.

Fuzzy based Distributed Self-Organized Secured G-Cast Routing Protocol for Energy-Efficient Heterogeneous Wireless Sensor Networks

Fuzzy based Distributed Self-Organized Secured G-Cast Routing Protocol for Energy-Efficient Heterogeneous Wireless Sensor Networks

SCAN: A Sensor Deployment Algorithm in Hazardous Regions via Mobile Actuators

In this paper, we propose two novel robot-assisted energy-efficient wireless mobile sensor deployment algorithms to monitor hazardous, uneven, and obstacle-prone areas where human intervention is prohibited. The algorithms are designed to exploit the operation in two simple steps. Initially, the robot deploys the mobile sensors in suitable positions by exploring the intended region using two different methods: 1) basic SCAN 1 and 2) opportunistic SCAN. In basic SCAN, the robot explores the intended area using simple scanning to install sensors. On the other hand, in opportunistic SCAN, the robot explores the intended area and installs the sensors whenever possible and stays in that region to cover as much as it can. Then, the installed sensors run coverage algorithm to provide information about the empty neighborhood to the running robot. Initially, the robot starts from some reference point and deploys sensors avoiding any obstacles or boundaries without the help of GPS. Combining these algorithms with the coverage algorithm guarantees maximum coverage for different obstacle distributions and for different regions of interest. Extensive simulation experiments are conducted to evaluate these algorithms. Opportunistic SCAN algorithm provides maximum coverage with minimum travel distance for the robot compared with the basic SCAN algorithm and the backtracking algorithm. Our algorithm also eliminates the deadlock issue for the robots that is raised when back pointer is removed. 1 Scalable Coordinate Accumulation Network.

Energy Efficient Multi-Hop Wireless Sensor Networks with CMIMO-SM Scheme

Energy efficiency is one of the important hot issues in wireless sensor networks. In this paper, a multi-hop scheme based on a cooperative multi-input multi-outputspatial modulation technique is proposed in order to improve energy efficiency in WSN. In this scheme, the sensor nodes are grouped into clusters in order to achieve a multi-input multi-output system; and a simple forwarding transmission scenario is considered so that the intermediate clusters only forward packets originated from the source cluster down to the sink cluster. In order to verify the performance of the proposed system, the bit energy consumption formula is derived and the optimal number of hopsis determined. By qualitative experiments, the obtained results show that the proposed scheme can deliver the data over multiple hops consuming optimal energy consumption per bit.

Investigation of In-Network Data Mining Approach for Energy Efficient Data Centric Wireless Sensor Networks

The continuous improvement in hardware design and advances in wireless communication have enabled the deployment of various wireless applications. Wireless sensor network applications become essential tools for monitoring the activity and evolution of our surrounding environment. However, the wireless sensor nodes are highly resource constrained in terms of limited processing speed, run time memory, persistent storage, communication bandwidth and finite energy. Therefore, for energy efficient in-network data retention and query processing, data mining approach is highly required that reduces the storage space, energy and communication cost consumption. This paper investigates the data mining approach for clustering sensor networks. Results show 99.88% less storage space, 37.6% reduced energy and 80% increased query throughput is achieved using data mining approach for wireless sensor networks.

Energy Efficient Multi-Hop Wireless Sensor Networks with Cooperative MIMO Scheme

For wireless sensor networks, energy efficiency is one of the most important subjects in recent research. In this paper, an energy-efficient multi-hop scheme based on cooperative MIMO (multiple-input multiple-output) technique is proposed for wireless sensor networks. Different from other papers, we consider a single cluster transmission scenario in which energy consumption is optimized by selecting the hop length and modulation constellation size. The optimal energy consumption formula is derived and proved mathematically. In addition, the minimum energy consumption per bit is calculated numerically.

Node Classification Based on Functionality in Energy-Efficient and Reliable Wireless Sensor Networks

Energy efficiency and reliability are two important factors when we design a wireless sensor network (WSN). In this paper, we proposed an energy-efficient and reliable hierarchical mechanism for WSNs. We utilized clustering structure to decrease energy consumption. Because cluster head plays an important role in WSN, we designed a substitute of cluster head (SCH) in order to guarantee the data propagation reliability. Based on different functionalities of sensor nodes we creatively classify sensor nodes into five categories: branch node (BN), cluster head (CH), substitute of cluster head (SCH), intermedium node (IN), and normal node. By adopting different MAC and network strategies for different node categories, energy consumption can be greatly reduced and data reliability can be significantly increased in the proposed WSN mechanism. The simulation results showed that this proposed mechanism realized the objective in aspects of energy efficiency and reliability.

A Mobile Agent Routing Algorithm in Dual-Channel Wireless Sensor Network

A mobile agent routing algorithm (MARA) is presented in this paper, and then based on the dual-channel communication model, the two-layer network combination optimization strategy is also proposed. Since this strategy deals with the collision between packets and the multicast suppression in channel competitive process well, the blocking probability of network and the error rate of packet transmission can be cut down by utilizing this strategy. Furthermore, a restore rule for the failure optimal route is presented too. By using this rule, the optimal route can restore quickly in the local of fail nodes and most of the information of original optimal route can be reserved. Compared with other existing algorithms like ant colony optimization-based dynamic energy-efficient mobile agent routing algorithm (ADEEMA) and mobile agent-based wireless sensor network (MAWSN), simulation results show that MARA performs better in improving the success rate of packet transmission and cutting down the delay of communication. The success rate of packet transmission is improved 15%. Simultaneously, this algorithm can keep the ant agents away from the nodes with less residual energy in searching for the optimal route. This way can make the energy of each nodes on the optimal route overall decline and hence improve the lifetime of network.

HS-Sift: hybrid spatial correlation-based medium access control for event-driven sensor networks

Energy efficient dense wireless sensor network design makes extensive use of spatial redundancy and appropriate MAC mechanism. CSMA is integrated with TDMA while filtering out the spatial correlation with a so-called HS-Sift MAC protocol. The entire sensing region is divided into three sub-areas for different channel access methods. The nodes near to the border sleep most of the time, nodes close to the event claim high channel utilisation and those lie in between compete under different priorities. A software simulation verifies effectiveness of the proposed scheme for energy consumption and access delays.