Energy Consumption Of Data Transmission Research Articles

A Survey on Energy Efficient Optimal Routing in Wireless Sensor Networks

In recent years, Wireless sensor networks (WSNs) have been emerged as an important research area due to its wide spread application in various domains such as military sensing and tracking, environment monitoring, patient monitoring, etc. WSN also have various advantages in gathering the data also with data transmission as well. Even though WSN has such advantages, there is certain drawback related to the energy consumption for data transmission over the network. Wireless sensor networks basically depend on the availability of nodes for transmission and if some dead nodes are available on the designated path of transmission, there will be delay in communication and also will affect the energy consumptions. Also, when a particular node is transmitting any data packet with high power, it may lead to interference which will affect the proper transmission of data and wastage of power as well. For power level reduction proper methodology has to be followed starting with the clustering and designing of routing protocols in WSNs. We intend to develop an enhanced clustering algorithm for initial clustering of sensor nodes for data transmission. Nodes will be clustered based on working attributes. Once nodes are clustered into different groups, transmission path will be assigned. An energy efficient optimal protocol will be designed in our approach for routing to improve the energy utilization by optimal power utilization. For optimization, we can employ multi objective optimization techniques which can enhance the optimal selection of power utilization. The proposed scheme will be then compared with some existing techniques to show the efficiency of the proposed approach.

Research on routing optimization of WSNs based on improved LEACH protocol

LEACH routing protocol equalizes the energy consumption of the network by randomly selecting cluster head nodes in a loop, which will lead to the defect of unstable network operation. Therefore, in order to solve this problem, it is necessary to reduce the energy consumption of data transmission in the routing protocol and increase the network life cycle. However, there is also a problem that cluster heads count with a wide range and the cluster head forwarding data consumed greatly power in the LEACH, which remains to be solved. In this paper, we put forward an approach to optimize the routing protocol. Firstly, the optimal number of cluster head is calculated according to the overall energy consumption per round to reduce the probability of excessive cluster head distribution. Then, the cluster head is used as the core to construct the Voronoi Diagram. The nodes in the same Voronoi diagram become a cluster, that the energy consumption communication in intra-cluster would be less. Finally, in order to optimize the multi-hop routing protocol, an ant colony algorithm is added using a cluster head near the BS to receive and forward it from a remote cluster head. According to the MATLAB simulation data, the protocol can significantly prolong the lifetime of WSNs compared with the LEACH protocol and increase the energy efficiency per unit node in per round. Energy consumption of the proposed approach is only. The approach improved the First Node Death (FND) time by 127%, 22.2%, and 14.5% over LEACH, LEACH-C, and SEP, respectively.

A Hierarchical Topology Control Algorithm for WSN, Considering Node Residual Energy and Lightening Cluster Head Burden Based on Affinity Propagation

The low energy adaptive clustering hierarchy (LEACH) is the classical hierarchical topology control algorithm and still widely used today in wireless sensor networks. There are some problems in LEACH such us an unreasonable selection and uneven distribution of cluster heads, not considering the residual energy of nodes, the cluster head is overloaded and there is a high energy consumption of data transmission. In this paper, a topology control algorithm with double cluster heads and multi-hop based on affinity propagation clustering (APDC-M) was proposed. In APDC-M, firstly, a cluster head election algorithm with double choices based on the affinity propagation clustering algorithm (AP) and reference node strategy (APDC) was proposed. APDC is responsible to elect the fusion cluster head for node clustering. Secondly, a forwarding cluster head is elected within each cluster. The forwarding cluster head is responsible for the data transmission in order to reduce the energy consumption of a single cluster head. Lastly, the forwarding cluster heads complete the data transmission from a cluster to the base station by the shortest path inter-cluster multi-hop mode. The comparison simulation results show that APDC-M can make the cluster head election more reasonable and the cluster head distribution more uniform, and effectively reduce the energy consumption of the cluster head nodes when transmitting data, thus prolonging the network life.

Differential data processing technique to improve the performance of wireless sensor networks

A wireless sensor network is a network composed of various types of sensors for the detection of magnetic, thermal, infrared, and acoustic fields, in addition to earthquakes and radio detecting and ranging (radar), among others. The size of the data collected from the various sensors is significant, and it is utilized in various applications such as artificial intelligence, data prediction, and analyses. However, the hardware of a wireless sensor node has limited energy and consumes a significant amount of energy for data transmission. Several studies have been conducted on multi-hop communication, clustering, and the compression/merging of data to increase energy efficiency in data transmission. In this study, the differential data processing (DDP) method is employed to reduce the size of the transmission data and improve the performance of wireless sensor networks. We propose node identification (ID)-based DDP and cluster header (CH)-based DDP. The node ID-based DDP transmits the initial collected aggregate data to the CH at the start of the collection, compares the previous collected data with the currently collected data, and then transfers the difference value to the CH. The CH is transmitted to the base station based on the smallest value of the collected data. The CH-based DDP collects data from the CH, generates reference data for the difference, and transmits the reference data at the time of cluster broadcasting. The member node performs differential processing on the collected data using the reference data transmitted to the CH. The performances of low-energy adaptive clustering hierarchy and DDP were compared. The simulation results revealed that the performance of the wireless sensor networks was improved by efficiently using the energy of the sensor nodes and by decreasing energy consumption in data transmission, given the reduction in the data size.

Correlation Techniques to Measure the Degree of Association Between Nodes of Different Protocols in MANETs, In Terms of Their Energy Consumption in Data Transmission

Several protocols have been using in networks, especially in MANETs, to increase efficiency in energy consumption of intermediate nodes while transmitting data packets to the destination node. Several protocols like energy efficient and energy consumption protocols are introduced in MANETs to increase the overall life time of MANETs. MANETs can’t survive for longer times without the property of energy consumption, as the available battery resources are very limited. Different protocols are implemented and tested, by simulation like NS2, on the basis of their energy consumption levels. To know the fairness and reliability of data obtained from different protocols, several statistical analysis methods are suggested. Finding the coefficient of correlation and rank correlation methods are very popular among them. These methods help to know the actual existing relation between the considered energy consumption data sets of intermediate nodes of two different protocols. This information will be very helpful to MANETs in estimating the required future energy consumption levels of its intermediate nodes and the degree of fairness between them.

An Energy-Efficient Region Source Routing Protocol for Lifetime Maximization in WSN

As the sensor layer of Internet of Things (IOT), enormous amount of sensor nodes are densely deployed in a hostile environment to monitor and sense the changes in the physical space. Since sensor nodes are driven with limited power batteries, it is very difficult and expensive for wireless sensor networks (WSNs) to extend network lifetime. In order to achieve reliable data transmission in WSNs, energy efficient routing protocol is a crucial issue in extending the network lifetime of a network. However, traditional routing protocols usually propagate throughout the whole network to discover a reliable route or employ some cluster heads to undertake data transmission for other nodes, which both require large amount energy consumption. In this paper, to maximize the network lifetime of the WSN, we propose a novel energy efficient region source routing protocol (referred to ER-SR). In ER-SR, a distributed energy region algorithm is proposed to select the nodes with high residual energy in the network as source routing node dynamically. Then, the source routing nodes calculate the optimal source routing path for each common node, which enables partial nodes to participate in the routing process and balances the energy consumption of sensor nodes. Furthermore, to minimize the energy consumption of data transmission, we propose an effective distance-based ant colony optimization algorithm to search the global optimal transmission path for each node. Simulation results demonstrate that ER-SR exhibits higher energy efficiency, and has moderate performance improvements on network lifetime, packet delivery ratio, and delivery delay, compared with other routing protocols in WSNs.

A channel-aware expected energy consumption minimization strategy in wireless networks

With the rapid development of wireless network technology, energy saving has become a very important topic to build a green network in wireless networks. Due to the time-varying characteristics of the channel, it is possible to obtain a higher utilization for energy by using the channel with good state in wireless communications. From the view of the data transmission energy consumption of the whole wireless network, this paper proposes an expected energy consumption minimization strategy (E2CMS) for data transmission based on the optimal stopping theory. Considering the maximum transmission delay and a given receiving power, E2CMS delays data to transmit until the best expected channel state is detected. In order to solve the problem, firstly, we construct an energy consumption minimization problem with quality of service constraints. Then, we prove that E2CMS is a pure threshold strategy by the optimal stopping theory and obtain the power threshold by solving a fixed-point equation using backward induction. Finally, simulations are performed in a typical small-scale fading channel model. E2CMS is compared with a variety of different transmission scheduling strategies. The results show that E2CMS has lower average energy consumption for per unit data and significantly improves the network performance.

Collaborative Fusion for Distributed Target Classification Using Evidence Theory in IOT Environment

As an efficient strategy, collaborative fusion can promote the classification performance while decreasing data transmission energy consumption and bandwidth requirements. In practice, the appropriate reliability assessment plays an essential rule in the fusion process. In this paper, we mainly concentrate on the classification problem of distributed target in Internet of Things scenarios, and an effective collaborative fusion method in terms of internal reliability and relative reliability evaluation is proposed. The inner reliability reveals the potential classes of the target in accordance with the local hard decision made by distinct sensor. The relative reliability reflects the credibility of the soft decision represented by belief function. These two reliability measures are complementary with each other. In our proposed fusion method, the inner reliability is applied to transfer the local hard decision into rational soft decision, and the relative reliability is utilized to decrease the influence of conflicting soft decisions by making full use of the evidential discounting operation. The discounted soft decisions are related to the combination rule of Dempster–Shafer for the final target classification. Results of experiment show that compared with the traditional fusion method, this method has the better fusion performance.

WSN Data Transmission Algorithm Based on Spatial Data Aggregation

In this paper, considering the high energy consumption, loss of network lifetime and data leak in transmission during the data aggregation of the wireless sensor network, we propose an improved spatial data aggregation algorithm. Through comparison with traditional data aggregation algorithms, we verify the feasibility and rationality of the proposed algorithm and obtain the following conclusions: the proposed algorithm carries out node sensing and data aggregation within a certain area based on multiple dynamic routes. The calculation process does not require encryption and decryption, and is not affected by network topology, so it can better address the data aggregation problems in the dynamic change of network structure. Compared with other traditional data aggregation algorithms, the proposed algorithm has the advantages of low traffic, low energy consumption in data transmission, low probability of data leakage and high transmission accuracy. In data aggregation, 3 slices is the optimal quantity.

An Improved Rumor Routing Protocol Based on Optimized Intersection Angle Theory and Localization Technologies in WSN

Routing mechanism is a key issue in Wireless Sensor Networks, and rumor routing protocol can reduce energy consumption and extend the lifecycle of network with unicast mechanism. However, in Rumor Routing protocol, the transmission path of event message is not optimal and random forwarding mechanism will lead to routing loop. In this paper, we investigate Rumor Routing protocol, and propose an improved rumor routing protocol based on optimized intersection angle theory. Localization technology and vector intersection angle mechanism are brought into the new protocol as two metrics of route selection. The new mechanism can reduce the energy consumption of data transmission. We compare Rumor Routing protocol, GPSR protocol, a Rumor Routing-based protocol, and the improved protocol. Results of simulation experiments indicate that the improved routing protocol can reduce the energy consumption of routing path and extend the lifecycle of network.

Efficient data-forwarding method in delay-tolerant P2P networking for IoT services

These days Internet of Things (IoT), which consists of smart objects such as sensor nodes is the most important technology for providing intelligent services. In the IoT ecosystem, wireless sensor networks deliver collected information from IoT devices to a server via sink nodes, and IoT services are provided by peer-to-peer (P2P) networking between the server and the IoT devices. Particularly, IoT applications with wide service area requires the mobile sink nodes to cover the service area. To employ mobile sink nodes, the network adopts delay-tolerant capability by which delay-tolerant nodes try to transmit data when they connect to the mobile sink node in the application service field. However, if the connection status between a IoT device and a mobile sink node is not good, the efficiency of data forwarding will be decreased. In addition, retransmission in bad connection cause high energy consumption for data transmission. Therefore, data forwarding in the delay-tolerant based services needs to take the connection status into account. The proposed method predicts the connection status using naive Bayesian classifier and determines whether the delay tolerant node transmits data to the mobile sink node or not. Furthermore, the efficiency of the proposed method was validated through extensive computer simulations.

An Energy-efficient Transmission Scheme for Wireless Sensor Network with DSC and virtual MIMO

Energy efficiency is one of the primary performance parameters in wireless sensor network (WSN). The data collected by neighboring nodes in the high density WSN tend to have a high correlation which is directly transmitted to the sink node (DGN) will seriously reduce the energy efficiency of wireless sensor networks. For improving the energy efficiency of high node density WSN, We introduce distributed source coding (DSC) which can compress the high correlation source data into WSN based on virtual MIMO. In the simulation results indicate that DSC can effectively reduce the energy consumption in data transmission and improve the energy efficiency of the whole WSN.

INCREASE EFFICIENCY DATA PROCESSING WITH USING AN ADAPTABLE ROUTING PROTOCOL ON CLOUD IN WIRELESS SENSOR NETWORKS

Nowadays cloud computing is a major content in computer engineering, especially in wireless sensor networks. In this paper, we present a methodology on mobile cloud computing in wireless sensor networks. After referring to previous work and researches about wireless sensor networks and mobile cloud computing, communication problems and challenges, reference and data management in this networks are studied, then with combination of the ability to collect information in wireless sensor networks and the ability to data storage and data processing in mobile cloud computing, we present a new method that makes the transmission of sensors' data easy by a reliable, fast and safe way. In addition, using the Enhanced Developed Distributed Energy-Efficient Clustering routing protocol, energy consumption is optimized in the sensor nodes communication with each other and in presence mobile cloud, the required energy consumption for data transmission in a communication field decreases and a better bandwidth and higher storage and processing power is provided by these networks. In this method, the sensor wireless network requires less storage space for sensor nodes.

Fundamental Tradeoffs on Energy-Aware D2D Communication Underlaying Cellular Networks: A Dynamic Graph Approach

With the ever-increasing energy consumption in transmissions of explosive growing mobile data, energy-efficient solutions are needed to be integrated into the future mobile networks. The upcoming 5G networks support device-to-device (D2D) communication underlaying the cellular networks, which enables proximity cellular users to communicate directly with high data rate and low transmit power. In this paper, targeting the energy-aware D2D communications underlaying cellular system, we investigate the fundamental problems of what is the potential gains of D2D communications for energy saving, which are the fundamental reasons to decrease the energy consumption, and how about the tradeoffs between energy consumption and other network factors of available bandwidth, buffer size and service delay in large scale D2D communication networks. To answer the above challenging problems, we utilize a dynamic graph approach to model the system with human mobility for a realistic D2D communication scenario. Specifically, by formulating a mixed integer linear programming problem that minimizes the energy consumption for data transmission from the cellular base stations to the receivers through any possible ways of transmissions, we obtain the theoretical performance lower bound of system energy consumption, which shows that cellular D2D communications decrease the energy consumption about 65% averagely under the realistic scenario. Furthermore, the obtained fundamental tradeoffs reveal that energy consumption for large bandwidth can be kept at a low level with increase of the buffer size and service delay.

Developing a bi-objective model for a reliable mobile ad hoc network routing problem

Nowadays, mobile ad hoc networks (MANET), which consist of a set of mobile nodes communicate with each other wirelessly, are considerably attended. In the last decades, with regard to different considerations, data routing problem has been studied as a main issue, widely. In these networks, developing models which lead to a more economic and confident route has always been a desired target. Hence, in this paper, a bi-objective mathematical model for MANETs routing problem is proposed, which aims to minimize energy consumption of data transmission and maximize reliability of selected route, simultaneously. To define reliability of the network, failure rate of each link is considered. To solve the proposed bi-objective mathematical model, a Lp-metric method is used which transforms the model to a single one. Finally, a numerical example is used to evaluate the efficiency of proposed model. The results indicate adding reliability criterion as the second objective function leads to a more confident and efficient solution, which is based on both energy consumption and reliability criteria.

Adaptive Sensing with Reliable Guarantee under White Gaussian Noise Channels of Sensor Networks

Quality of sensing is a fundamental research topic in sensor networks. In this paper, we propose an adaptive sensing technique to guarantee the end-to-end reliability while maximizing the lifetime of sensor networks under additive white Gaussian noise channels. First, we conduct theoretical analysis to obtain optimal node numberN∗, node placementd∗, and node transmission structureP∗under minimum total energy consumption and minimum unit data transmission energy consumption. Then, because sensor nodes closer to the sink consume more energy, nodes far from the sink have more residual energy. Based on this observation, we propose an adaptive sensing technique to achieve balanced network energy consumption. It adopts lower reliability requirement and shorter transmission distance for nodes near the sink and adopts higher reliability requirement and farther transmission distance for nodes far from the sink. Theoretical analysis and experimental results show that our design can improve the network lifetime by several times (1–5 times) and network utility by 20% and the desired reliability level is also guaranteed.

Research on HWSN Node Covering Algorithm

This paper first introduces the types and characteristics of HWSN, expounds its typical architecture, through comparing with homogeneous wireless sensor network, the performance of HWSN is quantitative calculated, analysis results show that HWSN can improve the reliability of data transmission, reduce the energy consumption of data transmission, reduce the delay of data transmission, and with the increase of network scale, highlight the advantages of heterogeneous networks. HWSN covering algorithm performance evaluation indexes are given finally.

Modeling Energy Consumption of Data Transmission Over Wi-Fi

Wireless data transmission consumes a significant part of the overall energy consumption of smartphones, due to the popularity of Internet applications. In this paper, we investigate the energy consumption characteristics of data transmission over Wi-Fi, focusing on the effect of Internet flow characteristics and network environment. We present deterministic models that describe the energy consumption of Wi-Fi data transmission with traffic burstiness, network performance metrics like throughput and retransmission rate, and parameters of the power saving mechanisms in use. Our models are practical because their inputs are easily available on mobile platforms without modifying low-level software or hardware components. We demonstrate the practice of model-based energy profiling on Maemo, Symbian, and Android phones, and evaluate the accuracy with physical power measurement of applications including file transfer, web browsing, video streaming, and instant messaging. Our experimental results show that our models are of adequate accuracy for energy profiling and are easy to apply.

Energy-aware routing for delay-sensitive underwater wireless sensor networks

The energy reduction is a challenging problem in the applications of underwater wireless sensor networks (UWSNs). The embedded battery is difficult to be replaced and it has an upper bound on its lifetime. Multihop relay is a popular method to reduce energy consumption in data transmission. The energy minimum path from source to destination in the sensor networks can be obtained through the shortest path algorithm. However, because of the node mobility, the global path planning approach is not suitable for the routing in UWSNs. It calls for an energy-efficient routing protocol for the high dynamic UWSNs. In this paper, we propose the modified energy weight routing (MEWR) protocol to deal with the energy-efficient routing of delaysensitive UWSNs. MEWR is a low flooding routing protocol. It can tolerate the node mobility in UWSNs and achieve a low end-to-end packet delay. MEWR can provide lower energy consumption than the existing low delay routing protocols through the dynamic sending power adjustment. The simulation results demonstrate the effectiveness of MEWR.

A cycle-based data aggregation scheme for grid-based wireless sensor networks.

In a wireless sensor network (WSN), a great number of sensor nodes are deployed to gather sensed data. These sensor nodes are typically powered by batteries so their energy is restricted. Sensor nodes mainly consume energy in data transmission, especially over a long distance. Since the location of the base station (BS) is remote, the energy consumed by each node to directly transmit its data to the BS is considerable and the node will die very soon. A well-designed routing protocol is thus essential to reduce the energy consumption. In this paper, we propose a Cycle-Based Data Aggregation Scheme (CBDAS) for grid-based WSNs. In CBDAS, the whole sensor field is divided into a grid of cells, each with a head. We prolong the network lifetime by linking all cell heads together to form a cyclic chain so that the gathered data can move in two directions. For data gathering in each round, the gathered data moves from node to node along the chain, getting aggregated. Finally, a designated cell head, the cycle leader, directly transmits to the BS. CBDAS performs data aggregation at every cell head so as to substantially reduce the amount of data that must be transmitted to the BS. Only cell heads need disseminate data so that the number of data transmissions is greatly diminished. Sensor nodes of each cell take turns as the cell head, and all cell heads on the cyclic chain also take turns being cycle leader. The energy depletion is evenly distributed so that the nodes' lifetime is extended. As a result, the lifetime of the whole sensor network is extended. Simulation results show that CBDAS outperforms protocols like Direct, PEGASIS, and PBDAS.