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A wireless body area network (WBAN) plays a crucial role in the health-care domain. With the emergence of technologies like the internet of things, there is increased usage of WBAN for providing quality health services. With wearable devices and sensors associated with human body, patient’s vital signs are captured and sent to doctor. The WBAN has number of sensor nodes that are resource constrained. The communications among the nodes are very crucial as human health information is exchanged. The purpose of this paper aims to have Quality of Service (QoS) with energy aware and control overhead aware. Maximizing network lifetime is also essential for the improved quality in services. There are many existing studies on QoS communications in WBAN.

In this paper, with the aim of energy-efficient WBAN for QoS, a cross-layer routing protocol is designed and implemented. A cross-layer routing protocol that is ad hoc on-demand distance vector (AODV)-based, energy and control overhead-aware (AODV-ECOA) is designed and implemented for energy-efficient routing in WBAN. The cross-layer design that involves multiple layers of open systems interconnection reference model, which will improve energy efficiency and thus QoS.

Implementation is simulated using the network simulator tool, i.e. NS-2. The proposed cross-layer routing protocol AODV-ECOA shows least bandwidth requirement by control packets, leading to less control overhead, highest packet delivery ratio and energy efficiency. The experimental results revealed that AODV-ECOA shows better performance over existing protocols such as AODV and POLITIC.

An efficient control overhead reduction algorithm is proposed for reducing energy consumption further and improves performance of WBAN communications to realize desired QoS.

In particular, this paper aims to systematically analyze a few prominent wireless sensor network (WSN) clustering routing protocols and compare these different approaches according to the taxonomy and several significant metrics.

In this paper, the authors have summarized recent research results on data routing in sensor networks and classified the approaches into four main categories, namely, data-centric, hierarchical, location-based and quality of service (QoS)-aware, and the authors have discussed the effect of node placement strategies on the operation and performance of WSNs.

Performance-controlled planned networks, where placement and routing must be intertwined and everything from delays to throughput to energy requirements is well-defined and relevant, is an interesting subject of current and future research. Real-time, deadline guarantees and their relationship with routing, mac-layer, duty-cycles and other protocol stack issues are interesting issues that would benefit from further research.

The paper aims to introduce an efficient routing algorithm for wireless sensor networks (WSNs). It proposes an improved evaporation rate water cycle (improved ER-WC) algorithm and outlining the systems performance in improving the energy efficiency of WSNs. The proposed technique mainly analyzes the clustering problem of WSNs when huge tasks are performed.

This proposed improved ER-WC algorithm is used for analyzing various factors such as network cluster-head (CH) energy, CH location and CH density in improved ER-WCA. The proposed study will solve the energy efficiency and improve network throughput in WSNs.

This proposed work provides optimal clustering method for Fuzzy C-means (FCM) where efficiency is improved in WSNs. Empirical evaluations are conducted to find network lifespan, network throughput, total network residual energy and network stabilization.

The proposed improved ER-WC algorithm has some implications when different energy levels of node are used in WSNs.

This research work analyzes the nodes’ energy and throughput by selecting correct CHs in intra-cluster communication. It can possibly analyze the factors such as CH location, network CH energy and CH density.

This proposed research work proves to be performing better for improving the network throughput and increases energy efficiency for WSNs.

Load balancing is an effective enhancement to the proposed routing protocol, and the basic idea is to share traffic load among cluster members to reduce the dropping probability due to queue overflow at some nodes. This paper aims to propose a novel hierarchical approach called distributed energy efficient adaptive clustering protocol (DEACP) with data gathering, load-balancing and self-adaptation for wireless sensor network (WSN). The authors have proposed DEACP approach to reach the following objectives: reduce the overall network energy consumption, balance the energy consumption among the sensors and extend the lifetime of the network, the clustering must be completely distributed, the clustering should be efficient in complexity of message and time, the cluster-heads should be well-distributed across the network, the load balancing should be done well and the clustered WSN should be fully connected. Simulations show that DEACP clusters have good performance characteristics.

A WSN consists of large number of wireless capable sensor devices working collaboratively to achieve a common objective. One or more sinks [or base stations (BS)] which collect data from all sensor devices. These sinks are the interface through which the WSN interacts with the outside world. Challenges in WSN arise in implementation of several services, and there are so many controllable and uncontrollable parameters (Chirihane, 2015) by which the implementation of WSN is affected, e.g. energy conservation. Clustering is an efficient way to reduce energy consumption and extend the life time of the network, by performing data aggregation and fusion to reduce the number of transmitted messages to the BS (Chirihane, 2015). Nodes of the network are organized into the clusters to process and forwarding the information, while lower energy nodes can be used to sense the target, and DEACP makes no assumptions on the size and the density of the network. The number of levels depends on the cluster range and the minimum energy path to the head. The proposed protocol reduces the number of dead nodes and the energy consumption, to extend the network lifetime. The rest of the paper is organized as follows: An overview of related work is given in Section 2. In Section 3, the authors propose an energy efficient level-based clustering routing protocol (DEACP). Simulations and results of experiments are discussed in Section 4. In Section 5, the authors conclude the work presented in this paper and the scope of further extension of this work.

The authors have proposed the DEACP approach to reach the following objectives: reduce the overall network energy consumption, balance the energy consumption among the sensors and extend the lifetime of the network, the clustering must be completely distributed, the clustering should be efficient in complexity of message and time, the cluster-heads should be well-distributed across the network, the load balancing should be done well, the clustered WSN should be fully connected. Simulations show that DEACP clusters have good performance characteristics.

Wireless sensor networks consist of a large number of nodes with limited battery power and sensing components, which can be used for sensing specified events and gather wanted or interesting information via wireless links. It will enable the reliable monitoring of a variety of environments for both civil and military applications. There is a need of energy‐efficient message collection and power management methods to prolong the lifetime of the sensor network. Many methods, such as clustering algorithm, are investigated for power saving reason, however, they only consider reducing the amount of message deliveries by clustering but not the load balance of the clusters to extend the maximum lifetime of the network. Therefore, in this paper, we propose a fully distributed, randomized, and adaptable clustering mechanism named autonomous clustering and message passing (ACMP) protocol for improving energy efficiency in wireless sensor networks. Sensor nodes, according to ACMP, can cluster themselves autonomously by their remaining energy and dynamically choose a corresponding cluster head (CH) to transfer the collected information. Sensor nodes adjust an appropriate power level to form clusters and use minimum energy to exchange messages. The network topology is changed dynamically depending on the CH's energy. Moreover, by maintaining the remaining energy of each node, the traffic load is distributed to all nodes and thus prolong the network lifetime efficiently. Simulation results show that ACMP can achieve a highly energy saving effect as well as prolong the network lifetime.

With the increasing acclaim of Wireless Sensor Networks and its diverse applications, research has been directed into optimising and prolonging the network lifetime. Energy efficiency has been a critical factor due to the energy resource impediment of batteries in sensor nodes. The proposed routing algorithm therefore aims at extending lifetime of sensors by enhancing load distribution in the network. The scheme is based on the chain-based routing technique of the PEGASIS (Power Energy GAthering in Sensor Information Systems) protocol and uses Ant Colony Optimisation to obtain the optimal chain. The contribution of the proposed work is the integration of the clustering method to PEGASIS with Ant Colony Optimisation to reduce redundancy of data, neighbour nodes distance and transmission delay associated with long links, and the employment an appropriate cluster head selection method. Simulation results indicates proposed method’s superiority in terms of residual energy along with considerable improvement regarding network lifetime, and significant reduction in delay when compared with existing PEGASIS protocol and optimised PEG-ACO chain respectively.

In a wireless sensor network (WSN), the sensor nodes are distributed in the network, and in general, they are linked through wireless intermediate to assemble physical data. The nodes drop their energy after a specific duration because they are battery-powered, which also reduces network lifetime. In addition, the routing process and cluster head (CH) selection process is the most significant one in WSN. Enhancing network lifetime through balancing path reliability is more challenging in WSN. This paper aims to devise a multihop routing technique with developed IIWEHO technique.

In this method, WSN nodes are simulated originally, and it is fed to the clustering process. Meanwhile, the CH is selected with low energy-based adaptive clustering model with hierarchy (LEACH) model. After CH selection, multipath routing is performed by developed improved invasive weed-based elephant herd optimization (IIWEHO) algorithm. In addition, the multipath routing is selected based on certain fitness functions like delay, energy, link quality and distance. However, the developed IIWEHO technique is the combination of IIWO method and EHO algorithm.

The performance of developed optimization method is estimated with different metrics, like distance, energy, delay and throughput and achieved improved performance for the proposed method.

This paper presents an effectual multihop routing method, named IIWEHO technique in WSN. The developed IIWEHO algorithm is newly devised by incorporating EHO and IIWO approaches. The fitness measures, which include intra- and inter-distance, delay, link quality, delay and consumption of energy, are considered in this model. The proposed model simulates the WSN nodes, and CH selection is done by the LEACH protocol. The suitable CH is chosen for transmitting data through base station from the source to destination. Here, the routing system is devised by a developed optimization technique. The selection of multipath routing is carried out using the developed IIWEHO technique. The developed optimization approach selects the multipath depending on various multi-objective functions.

This paper aims to propose a new node energy-efficient algorithm with energy threshold to replace cluster heads. The proposed algorithm uses node ranking to elect cluster heads based on energy levels and positions of the nodes in reference to the base station (BS) used as a sink for gathered information. Because the BS calculates the number of rounds a cluster head can remain for as a cluster head in advance, this reduces the amount of energy wasted on replacing cluster heads each round which is the case in most existing algorithms, thus prolonging the network lifetime. In addition, a hybrid redundant nodes duty cycle is used for nodes to take turn in covering the monitored area is shown to improve the performance further.

Authors designed and implemented the proposed algorithm in MATLAB. The performance of the proposed algorithm was compared to other well-known algorithms using different evaluation metrics. The performance of the proposed algorithm was enhanced over existing ones by incorporating different mechanisms such as the use of an energy-based threshold value to replace CHs and the use of a hybrid duty-cycle on nodes.

Through simulation, the authors showed how the proposed algorithm outperformed PEGASIS by 15 per cent and LEACH by almost 70 per cent for the network life-time criterion. They found that using a fixed pre-defined energy threshold to replace CHs improved the network lifetime by almost 15 per cent. They also found that the network lifetime can be further improved by almost 7 per cent when incorporating a variable energy threshold instead of a fixed value. In addition to that, using hybrid-redundant nodes duty-cycle has improved the network lifetime by an additional 8 per cent.

The authors proposed an energy-efficient clustering algorithm for WSNs using node ranking in electing CHs and energy threshold to replace CHs instead of being replaced every round.

This chapter investigates the trends in international and European legal and policy regulation of the process related to carbon capture and storage (CCS). The global endeavor that seeks to limit carbon dioxide emissions has come to recognize CCS as an indispensable ally. This chapter offers an up-to-date and comprehensive commentary to the relatively new and developing area of international regulation of the process of CCS, a dimension that might yield significant effects on the environment and, overall, sustainable development. It reveals a constantly growing trend of an enhanced awareness about the indispensable role and effects of the CCS on wider climate aspirations and, to that effect, also a need for a stable and effective international regulatory framework. The key barriers that are preventing the wider implementation of CCS projects, however, relate primarily to two extra-regulatory processes, which is the policy uncertainty at national levels and financial shortcomings. This background presents a window of opportunity for entrepreneurship and policy invention.

The purpose of this paper is to utilise a “Wuli-Shili-Renli (WSR)” system approach to create models for complex smart building energy management and evaluate the establishment of a building energy management platform.

The complexity and diversity of the data and demands of the energy management platform mean that it is necessary to analyse comprehensively. This paper uses a WSR system approach to handle, and optimise, the relationship between demands and participants and improve the whole platform. Then, this paper establishes comprehensive evaluation models to analysis the current energy management platforms by using the best integration platform as the baseline.

The WSR conceptual model clarifies the relationship between the elements and elements of the energy management platform clearly and provides the appropriate analytical methods with which to resolve key platform construction issues. The comprehensive evaluation based on a WSR system approach can take into account the systematic effect, so it is more accurate.

The correlation degree between the layers of the energy management platform is rarely reflected.

This paper improves the modelling method used in the WSR system approach and demonstrates that the comprehensive evaluation based on the WSR system approach analyses the energy management platform for public buildings in a synthetic approach.