Energy Efficiency Metrics in Cognitive Radio Networks: A Hollistic Overview

Due to the explosive progression in the number of users for new generation wireless communication networks which includes cognitive radio networks, energy efficiency has been a fundamental factor affecting its development and performance.  In order to adeptly access and analyze the energy efficiency of a cognitive radio network, a standardized metric for this purpose is required. As a starting point, in this article we provided an analysis for energy efficiency metrics of a cognitive radio network in respect to its design and operation. The performance metrics and metrics developed at the different levels of a cognitive radio network are also studied. Establishing a comprehensive metric for evaluating, measuring and reporting the energy efficiency of cognitive radio networks is a crucial step in achieving an energy-efficient cognitive radio network

Scheduling Sleeping Nodes in High Density Cluster-based Sensor Networks

In order to conserve battery power in very dense sensor networks, some sensor nodes may be put into the sleep state while other sensor nodes remain active for the sensing and communication tasks. In this paper, we study the node sleep scheduling problem in the context of clustered sensor networks. We propose and analyze the Linear Distance-based Scheduling (LDS) technique for sleeping in each cluster. The LDS scheme selects a sensor node to sleep with higher probability when it is farther away from the cluster head. We analyze the energy consumption, the sensing coverage property, and the network lifetime of the proposed LDS scheme. The performance of the LDS scheme is compared with that of the conventional Randomized Scheduling (RS) scheme. It is shown that the LDS scheme yields more energy savings while maintaining a similar sensing coverage as the RS scheme for sensor clusters. Therefore, the LDS scheme results in a longer network lifetime than the RS scheme

Enhanced VGDRA for Dynamic WSN

Sensor Nodes are fundamental blocks of Wireless Sensor Networks. The focus of researchers is still on reducing the energy dissipation by the sensor nodes over time. Sensor nodes once deployed have a fixed amount of energy available to them. In order to use the energy efficiently the sensor nodes are grouped together based on the tasks performed by them. These groups of sensor nodes are known as clusters. Each cluster is headed by a cluster head connecting the cluster with the base station. Energy consumption is directly proportional to the distance from the base station. The concept of network lifetime is closely related to the energy consumption and area coverage in wireless sensor network. The main aim of the proposed technique is to select cluster heads in such a way that they extend the network lifetime and increase throughput of the network. The efficiency of the proposed cluster head selection technique is that it covers energy consumption and routes selection for data delivery from sensor node to the base station. In this paper an Enhanced Virtual Grid-based Dynamic Routes Adjustment Scheme is proposed presenting a set of rules for the selection of cluster heads in such a way that the energy consumption by the cluster heads is balanced throughout the network and it does not get over exploited

Device-to-device based path selection for post disaster communication using hybrid intelligence

Public safety network communication methods are concurrence with emerging networks to provide enhanced strategies and services for catastrophe management. If the cellular network is damaged after a calamity, a new-generation network like the internet of things (IoT) is ready to assure network access. In this paper, we suggested a framework of hybrid intelligence to find and re-connect the isolated nodes to the functional area to save life. We look at a situation in which the devices in the hazard region can constantly monitor the radio environment to self-detect the occurrence of a disaster, switch to the device-to-device (D2D) communication mode, and establish a vital connection. The oscillating spider monkey optimization (OSMO) approach forms clusters of the devices in the disaster area to improve network efficiency. The devices in the secluded area use the cluster heads as relay nodes to the operational site. An oscillating particle swarm optimization (OPSO) with a priority-based path encoding technique is used for path discovery. The suggested approach improves the energy efficiency of the network by selecting a routing path based on the remaining energy of the device, channel quality, and hop count, thus increasing network stability and packet delivery

Performance and energy efficiency in wireless self-organized networks

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Practical and Context-Aware Resource Adaptation in Mobile Networks

With the proliferation of various portable devices such as smart phones, netbooks and tablets, it becomes more important to design and implement effective resource management schemes with (i) the increasing number of users in the network and (ii) the expectation of frequent and fast mobility of network users. In this dissertation, we conclude that the key to solve the problem in mobile networks is adaptive resource allocation, which requires the system to behave in an adaptive manner considering the dynamic network conditions and various context of mobile users. Specifically, we study the following critical resource allocation issues in this dissertation: (i) rate adaptation; (ii) station handoff; (iii) load balancing; and (iv) power saving, for each we have proposed an adaptive scheme, implemented it in the MadWifi device driver, and demonstrated its effectiveness via experiments

Joint routing protocol and image compression algorithm for prolonging node lifetime in wireless sensor network

Wireless sensor network (WSN) are among the emerging modern technologies, with a vast range of application in different areas. However, the current WSNs technology faces a key challenge in terms of node lifetime and network connectivity due to limited power resource of the node. The conventional data routing protocols do not consider the power available at the node on the path from source to sink, thus they result in the exhaustion and eventual death of nodes surrounding the sink node, thus generating routing holes reducing the network throughput. In order to address the issue in this research presents a novel protocol based on equal power consumption at all network nodes. The consume power fairly (CPF) protocol achieves a high power efficiency by distributing power consumption equal on all the network nodes. The protocol compares the power available on all the paths from source to sink and then selects the path with highest power. Additionally in order to reduce the transmitted data size, a lossy image compression technique based on adaptive Haar wavelet transform has been implemented. The simulation designs based on MATLAB consists of 100 randomly distributed nodes over an area of 100 m2, with 30 Kbits and 40 Kbits of packet sizes. The comparison between the proposed CPF protocol and the energy aware protocol has been carried out on the basis of number of iterations and the dead nodes in the network. Thorough simulations have been carried out based on different number of network iterations to validate the potential of the proposed solution. Moreover the implemenetation of multiscale retinex technique results in image enhancement and impoved classification. An implementation of the CPF protocol and image compression technique on a 100 node network with 500 iterations, results in the death of 13 nodes as compard to 38 dead nodes with energy aware protocol for the same network. Thus the performance comparision of CPF and energy aware protocol demonstrates an improvement of 81.19% for the energy consumption of the network. Thus the proposed algorithm prolongs the network under consideration by 57 – 62% as compared to networks with conventional routing protocols

Graph-theoretic channel modeling and topology control protocols for wireless sensor networks

This report addresses two different research problems: (i) It presents a wireless channel model that reduces the complexity associated with high order Markov chains; and (ii) presents energy efficient topology control protocols which provide reliability while maintaining the topology in an energy efficient manner. For the above problems, real wireless sensor network traces were collected and extensive simulations were performed for evaluating the proposed protocols. Accurate simulation and analysis of wireless networks are inherently dependent on accurate models which are able to provide real-time channel characterization. High-order Markov chains are typically used to model errors and losses over wireless channels. However, complexity (i.e., the number of states) of a high-order Markov model increases exponentially with the memory-length of the underlying channel. In this report, a novel graph-theoretic methodology that uses Hamiltonian circuits to reduce the complexity of a high-order Markov model to a desired state budget is presented. The implication of unused states in complexity reduction of higher order Markov model is also explained. The trace-driven performance evaluations for real wireless local area network (WLAN) and wireless sensor network (WSN) channels demonstrate that the proposed Hamiltonian Model, while providing orders of magnitude reduction in complexity, renders an accuracy that is comparable to the Markov model and better than the existing reduced state models. Furthermore, a methodology to preserve energy is presented to increase the network lifetime by reducing the node degree forming an active backbone while considering network connectivity. However, in energy stringent wireless sensor networks, it is of utmost importance to construct the reduced topology with the minimal control overhead. Moreover, most wireless links in practice are lossy links with connectivity probability which desires that a routing protocol provides routing flexibility and reliability at a minimum energy consumption cost. For this purpose, distributed and semi-distributed novel graph-theoretic topology construction protocols are presented that exploit cliques and polygons in a WSN to achieve energy efficiency and reliability. The proposed protocols also facilitate load rotation under topology maintenance, thereby extending the network lifetime. In addition to the above, the report also evaluates why the backbone construction using connected dominating set (CDS) in certain cases remains unable to provide connected sensing coverage in the area covered. For this purpose, a novel protocol that reduces the topology while considering sensing area coverage is presented