A practical framework for data collection in wireless sensor networks

Optimizing energy consumption for extending the lifetime in wireless sensor networks is of dominant importance. Groups of autonomous robots and unmanned aerial vehicles (UAVs) acting as mobile data collectors are utilized to minimize the energy expenditure of the sensor nodes by approaching the sensors and collecting their buffers via single hop communication, rather than using multihop routing to forward the buffers to the base station. This paper models the sensor network and the mobile collectors as a system-of-systems, and defines all levels and types of interactions. A practical framework that facilitates deploying heterogeneous mobiles without prior knowledge about the sensor network is presented. Realizing the framework is done through simulation experiments and tested against several performance metrics.<br /

ENHANCE FAIR ROUTING WITH RESOURCE FLEXIBLE NODE ALLOCATION IN WIRELESS SENSOR NETWORKS

Wireless sensor network is a network composed of a large number of sensor nodes with limited radio capabilities and one or a few sinks that collect data from sensor nodes. Sensor nodes are powered by small batteries, hence, the energy consumption in operating a WSN should be as low as possible. The wireless sensor network present all sensor nodes generate an equal amount of data packets in a WSN, nodes around a sink have to relay more packets and tend to die earlier than other nodes because the energy consumption of sensor nodes is almost completely dominated by data communication rather than by sensing and processing. Hence, the whole network lifetime can be prolonged by balancing the communication load at heavily loaded nodes around a sink. This problem is called the energy hole problem and is one of the most important issues for WSNs. Existing system analysis the heterogeneity of networks and a fair cooperative routing method, to avoid unfair improvement only on certain networks and to introduce one or a few shared nodes that can use multiple channels to relay data packets

A Review of Wireless Sensor Networks with Cognitive Radio Techniques and Applications

The advent of Wireless Sensor Networks (WSNs) has inspired various sciences and telecommunication with its applications, there is a growing demand for robust methodologies that can ensure extended lifetime. Sensor nodes&nbsp;are small equipment which may hold less electrical energy and preserve it until they reach the destination of the network. The main concern is supposed to carry out sensor routing process along with&nbsp;transferring information. Choosing the best route for transmission in a sensor node is necessary to reach the destination and conserve energy. Clustering in the network is considered to be an effective method for gathering of data and routing through the nodes in wireless sensor networks. The primary requirement is to extend network lifetime by minimizing the consumption of energy. Further integrating cognitive radio technique into sensor networks, that can make smart choices based on knowledge acquisition, reasoning, and information sharing may support the network's complete purposes amid the presence of several limitations and optimal targets. This examination focuses on routing and clustering using metaheuristic techniques and machine learning because these characteristics have a detrimental impact on cognitive radio wireless sensor node lifetime

A Systematic Packet Forwarding Approach for Overlapped Hetero Cooperative Sensor Network

Due to the limitation of energy and network lifetime, the routing protocols of wireless sensor network (WSN) must minimize energy consumption and thus extend the network lifetime. Systematic packet forwarding approach is the genuine classical routing protocol in WSN. A heterogeneous characteristics is introduced whileforwarding packet to the next node. During data transmission, we are using cooperative category routing to communicate with the sink node, so that it can utilize energy more effectively and evenly. By analysing the disadvantage of previous routing approach, this paper proposes an improved Systematic packet forwarding approach. The improved routing system can reduce energy consumption and thus prolong the network lifetime. In order to provide energy reduction concept to the improved routing system , this paper introduces energy pool it acts as a mediator for to control overall energy required for communication

Comparative Analysis of Algorithm for Cluster Head Selection in Wireless Sensor Network

One of the challenging issues to be studied in WSN is its energy saving so as to extend lifetime. The primary goal of node clustering is network preprocessing that is used to obtain information and limit energy consumed. To support high adaptability and better accumulation of information data, sensor nodes are often grouped into disconnected, non overlapping batches, groups of nodes called clusters. Clusters design hierarchical WSNs which incorporate adequate performance of finite reserves of sensor nodes and thus enhance network lifetime. In this paper different clustering algorithm are compared having different cluster head selection approach. Our paper presents review of different energy efficient cluster head selection algorithms in WSNs. DOI: 10.17762/ijritcc2321-8169.150312

An Improved Energy-Aware Distributed Unequal Clustering Protocol using BBO Algorithm for Heterogeneous Load Balancing

With the rapid extension of IoT-based applications various distinct challenges are emerging in this area Among these concerns the node s energy efficiency has a special importance since it can directly affect the functionality of IoT-Based applications By considering data transmission as the most energy-consuming task in IoT networks clustering has been proposed to reduce the communication distance and ultimately overcome node energy wastage However cluster head selection as a non-deterministic polynomial-time hard problem will be challenging notably by considering node s heterogeneity and real-world IoT network constraints which usually have conflicts with each other Due to the existence of conflict among the main system parameters various solutions have been proposed in recent years that each of which only considered a few real-world limitations and parameter

Study on Different Topology Manipulation Algorithms in Wireless Sensor Network

Wireless sensor network (WSN) comprises of spatially distributed autonomous sensors to screen physical or environmental conditions and to agreeably go their information through the network to a principle area. One of the critical necessities of a WSN is the efficiency of vitality, which expands the life time of the network. At the same time there are some different variables like Load Balancing, congestion control, coverage, Energy Efficiency, mobility and so on. A few methods have been proposed via scientists to accomplish these objectives that can help in giving a decent topology control. In the piece, a few systems which are accessible by utilizing improvement and transformative strategies that give a multi target arrangement are examined. In this paper, we compare different algorithms' execution in view of a few parameters intended for every target and the outcomes are analyzed. DOI: 10.17762/ijritcc2321-8169.15029

Fair Routing for Overlapped Cooperative Heterogeneous Wireless Sensor Networks

In recent years, as WSNs (Wireless Sensor Networks) are diffused widely, multiple overlapping WSNs constructed on the same area become more common. In such a situation, their lifetime is expected to be extended by cooperative packet forwarding. Although some researchers have studied about cooperation in multiple WSNs, most of them do not consider the heterogeneity in characteristics of each WSN such as battery capacity, operation start time, the number of nodes, nodes locations, energy consumption, packet size and/or data transmission timing, and so on. In a heterogeneous environment, naive lifetime improvement with cooperation may not be fair. In this paper, we propose a fair cooperative routing method for heterogeneous overlapped WSNs. It introduces an energy pool to maintain the total amount of energy consumption by cooperative forwarding. The energy pool plays a role of broker for fair cooperation. Finally, simulation results show the excellent performance of the proposed method

Fuzzy logic-based guaranteed lifetime protocol for real-time wireless sensor networks

© 2015 by the authors; licensee MDPI, Basel, Switzerland. Few techniques for guaranteeing a network lifetime have been proposed despite its great impact on network management. Moreover, since the existing schemes are mostly dependent on the combination of disparate parameters, they do not provide additional services, such as real-time communications and balanced energy consumption among sensor nodes; thus, the adaptability problems remain unresolved among nodes in wireless sensor networks (WSNs). To solve these problems, we propose a novel fuzzy logic model to provide real-time communication in a guaranteed WSN lifetime. The proposed fuzzy logic controller accepts the input descriptors energy, time and velocity to determine each node’s role for the next duration and the next hop relay node for real-time packets. Through the simulation results, we verified that both the guaranteed network’s lifetime and real-time delivery are efficiently ensured by the new fuzzy logic model. In more detail, the above-mentioned two performance metrics are improved up to 8%, as compared to our previous work, and 14% compared to existing schemes, respectively

A 3D multi-objective optimization planning algorithm for wireless sensor networks

The complexity of planning a wireless sensor network is dependent on the aspects of optimization and on the application requirements. Even though Murphy's Law is applied everywhere in reality, a good planning algorithm will assist the designers to be aware of the short plates of their design and to improve them before the problems being exposed at the real deployment. A 3D multi-objective planning algorithm is proposed in this paper to provide solutions on the locations of nodes and their properties. It employs a developed ray-tracing scheme for sensing signal and radio propagation modelling. Therefore it is sensitive to the obstacles and makes the models of sensing coverage and link quality more practical compared with other heuristics that use ideal unit-disk models. The proposed algorithm aims at reaching an overall optimization on hardware cost, coverage, link quality and lifetime. Thus each of those metrics are modelled and normalized to compose a desirability function. Evolutionary algorithm is designed to efficiently tackle this NP-hard multi-objective optimization problem. The proposed algorithm is applicable for both indoor and outdoor 3D scenarios. Different parameters that affect the performance are analyzed through extensive experiments; two state-of-the-art algorithms are rebuilt and tested with the same configuration as that of the proposed algorithm. The results indicate that the proposed algorithm converges efficiently within 600 iterations and performs better than the compared heuristics