随着社会的发展，人们对环境保护的重视，如何对环境进行智能监测控制具有重大的研究意义。水质监测系统架构及网络设计，先设计了以声波实现通信和组网水下数据采集节点，再在每个区域(水面)加入数据汇集节点，数据汇集节点采用ZigBee系统进行自动组网和数据汇集，由GPRS传递给服务器。 With the development of society, people pay more attention to environmental protection. How to intelligently monitor and control the environment has important research significance. Water quality monitoring system architecture and network design, first designed underwater acoustic communication and network data acquisition node, then added data acquisition nodes in each region (water), which used ZigBee system for automatic networking and data collection, by GPRS are passed to the server.

伴随着3G网络时代的到来，物联网的应用渗透到工业生产和人们日常生活的各个角落。传感器的设计和生产正朝着集成化、微型化、智能化的方向发展，无线通讯网络在信息传输与处理技术的支持下已经取得了突破性的进展。其应用前景十分广阔，在工农业生产监控、城市交通管理、生物医疗技术、野外环境监测、物流管理、智能化家电等领域具有重要的科研和应用价值。本文通过对已有算法的深入研究和比较，我们发现水环境物联网监测云是下一步水环境监测发展趋势，在国内外是首次提出，且在国内受到很大的重视，适用于我国广大的不同水域。 With the advent of the era of 3Gnetwork, the application of Internet of things permeates every corner of the industrial production and people’s daily life. Sensor design and production are moving in the direction of integration, miniaturization, intelligent, and wireless communication network with the support of information transmission and processing technology has made a breakthrough progress. Its application prospect is very broad. In industrial and agricultural production monitoring, urban traffic management, biomedical technology, field environment monitoring, logistics management, intelligent home appliances and other fields, it has important scientific and application value. In this article, through in-depth study and comparison of existing algorithm, we find out that water environment monitoring cloud is the next step development trend of water environment monitoring. The idea has been put forward for the first time both at home and abroad. At home it is regarded very seriously, and it is suitable for the different waters in our country.

we propose a method of Cloud-Ocean Computing to push the intelligent processing of the data to the front end. Ocean Computing and Cloud Computing work together, Ocean Computing is an important support for Cloud Computing. For Ocean Computing, we put forward two ways. The first way is to take a compressed sensing method which extracts valuable information from the original data intelligently. The second way is to fuse multi-sensor data and make intelligent identification and prediction. We did the experiment on the first way, and the experiment is shown to exhibit significantly enhanced performance with respect to reducing energy consumption and shortening transmission time.

this planet and many oceanic and maritime applications seem relatively slow in exploiting the state-of-the-art info-communication technologies. The natural and man-made disasters that have taken place over the last few years have aroused significant interest in monitoring oceanic environments for scientific, environmental, commercial, safety, homeland security and military needs. The shipbuilding and offshore engineering industries are also increasingly interested in technologies like sensor networks as an economically viable alternative to currently adopted and costly methods used in seismic monitoring, structural health monitoring, installation and mooring, etc. Underwater sensor networks (UWSNs) are the enabling technology for wide range of applications like monitoring the strong influences and impact of climate regulation, nutrient production, oil retrieval and transportation The underwater environment differs from the terrestrial radio environment both in terms of its energy costs and channel propagation phenomena. The underwater channel is characterized by long propagation times and frequency-dependent attenuation that is highly affected by the distance between nodes as well as by the link orientation. Some of other issues in which UWSNs differ from terrestrial are limited bandwidth, constrained battery power, more failure of sensors because of fouling and corrosion, etc. This paper presents several fundamental key aspects and architectures of UWSNs, emerging research issues of underwater sensor networks and exposes the researchers into networking of underwater communication devices for exciting ocean monitoring and exploration applications. I. INTRODUCTION The Earth is a water planet. Around 70% of the surface of earth is covered by water. This is largely unexplored area and recently it has fascinated humans to explore it. Natural or man-made disasters that have taken place over the last few years have aroused significant interest in monitoring oceanic environments for scientific, environmental, commercial, safety, homeland security and military needs. The shipbuilding and offshore engineering industries are also increasingly interested in technologies like wireless sensor

th , 2013; revised: Aug. 27 th , 2013; accepted: Sep. 4 th , 2013 Copyright © 2013 Yunbing Hu, Xiangyu Mu. This is an open access article distributed under the Creative Commons Attribution License, which per- mits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Abstract: With the advent of the era of 3G network, the application of Internet of things permeates every corner of the industrial production and people's daily life. Sensor design and production are moving in the direction of integration, miniaturization, intelligent, and wireless communication network with the support of information transmission and processing technology has made a breakthrough progress. Its application prospect is very broad. In industrial and agri- cultural production monitoring, urban traffic management, biomedical technology, field environment monitoring, logis- tics management, intelligent home appliances and other fields, it has important scientific and application value. In this article, through in-depth study and comparison of existing algorithm, we find out that water environment monitoring cloud is the next step development trend of water environment monitoring. The idea has been put forward for the first time both at home and abroad. At home it is regarded very seriously, and it is suitable for the different waters in our country.

obile elements, which can traverse the deployment area and convey the observed data from static sensor nodes to a base station, have been introduced for energy efficient data collection in wireless sensor networks (WSNs). However, most existing solutions only plan a single path for the mobile element, which may lead to quick energy depletion for the sensor nodes that are far away from the path. In this paper, for data collection in WSNs, we study the multi-path planning (MPP) problem for the mobile element to prolong the lifetime of WSNs. Observing the intractability of the problem, two MPP heuristic schemes, namely fixed-K and adaptive-K, are proposed. The central idea of these schemes is to plan multiple paths and have the mobile element follow them in turn to balance the energy consumption on individual sensor nodes, thus extending the lifetime of WSNs. The proposed schemes are evaluated through extensive simulations. The results show that, compared to that of the single path solution, the multi-path approaches can extend the lifetime of WSNs by up to four times. Moreover, the adaptive-K scheme treats the sensor nodes more fairly with less variation on their energy consumptions.

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Within the context of multiple mobile, and networked robot systems, this chapter explores the current state of the art. After a brief introduction, we first examine architectures for multirobot cooperation, exploring the alternative approaches that have been developed. Next, we explore communications issues and their impact on multirobot teams in Sect. 53.3, followed by a discussion of networked mobile robots in Sect. 53.4. Following this we discuss swarm robot systems in Sect. 53.5 and modular robot systems in Sect. 53.6. While swarm and modular systems typically assume large numbers of homogeneous robots, other types of multirobot systems include heterogeneous robots. We therefore next discuss heterogeneity in cooperative robot teams in Sect. 53.7. Once robot teams allow for individual heterogeneity, issues of task allocation become important; Sect. 53.8 therefore discusses common approaches to task allocation. Section 53.9 discusses the challenges of multirobot learning, and some representative approaches. We outline some of the typical application domains which serve as test beds for multirobot systems research in Sect. 53.10. Finally, we conclude in Sect. 53.11 with some summary remarks and suggestions for further reading.

With the recent advances in Micro Electro-Mechanical Systems (MEMS) and underwater imaging sensors, and cameras, underwater multimedia sensor networks (UMSNs) have been proposed and drawn the immediate attention of the research community. Underwater multimedia sensor networks enable several new applications, such as target tracking, advanced coastal multimedia surveillance, undersea explorations, image acquisition and classification, environmental monitoring, and disaster prevention. However, the practical realization of these currently designed and envisioned applications directly depends on reliable and quality-aware communication capabilities of the deployed UMSNs. This paper presents a comprehensive performance evaluation of error concealment and error correction algorithms for quality-aware image transmission over UMSNs. Specifically, different combinations of multipath transport,watermarking-based error concealment (EC), forward error correction (FEC) and adaptive retransmission mechanisms have been evaluated to combat underwater channel impairments and mitigate packet losses due to node failures and intrinsic underwater acoustic channel characteristics. In addition, two novel image quality assessment metrics have been proposed to obtain the predicted quality of the image depending on the channel and node failures. Comparative performance evaluations show that the EC approach reconstructs the distorted image as closely as the original one while avoiding the burden of retransmissions and consequent delay.

With the proliferation of mobile devices, an increasing number of sensing applications are using mobile sensor networks. These mobile networks are severely energy-constrained, and energy usage is one of the most common causes of failure in their deployments. In these networks, nodes that exhaust their energy before the targeted system lifetime degrade system performance; nodes that run past the system lifetime cannot fully utilize their stored energy. Although much work has focused on policies to reduce and regulate energy usage in fixed and dense networks, intermittently connected networks have been largely overlooked. Due to variations in hardware, software, node mobility, and environment, it is especially difficult for intermittently connected mobile networks to improve operations collectively in a dynamic environment. Here, we present and evaluate Collaborative Adaptive Targeted System Lifetime (CA-TSL), an adaptive policy that enforces a system-wide targeted lifetime in an intermittently connected system by adapting node energy usage to an estimated desired energy profile. For evaluation, we present both real-system and large-scale simulated results. Our approach improves sink data reception by an average of 50 percent, and an additional 30 percent when a density estimation technique is also employed. In addition, it reduces system lifetime variations by up to 5.5 ×.

With the development of society, people pay more attention to environmental protection. How to intelligently monitor and control the environment has important research significance. Water quality monitoring system architecture and network design, first designed underwater acoustic communication and network data acquisition node, then added data acquisition nodes in each region (water), which used ZigBee system for automatic networking and data collection, by GPRS are passed to the server.

With the advances in technology, Underwater Acoustic Sensor Networks (UW-ASNs) will make it possible to explore and observe the ocean, which covers two-thirds of the Earth's surface. Unlike terrestrial sensor networks, UW-ASNs use acoustic links to explore natural undersea resources and gather scientific data in collaborative monitoring missions. By using the acoustic wave as a means of communication, UW-ASNs are inherently confronted with long and variable propagation delay and high transmission power consumption. These limitations can be overcome by sharing the limited channel resources in an efficient and reliable manner, which can be done by carefully designing MAC protocols. In this survey, we review the unique aspects of UW-ASNs in detail and existing MAC protocols. Finally, we suggest future directions for research on UW-A MAC protocols.

With 250,000 NTD invested, 6 man power allocated, and 9 month time elapsed, we present BL-Live. The seemingly dumb, senseless BL Hall at National Taiwan University is transformed to an intelligent office building by a 30+ node sensor network. Two everyday services, Elevator Report and Smart Office, are implemented to better utilize the resources of the building and of the building residents. Our experience allows us to re-examine technical issues such as manufacturing cost, form factor, deployment, data communication, and energy efficiency. Many of the lessons we learn are not only surprising but also inspiring, which in turn leads us to think that more deployment experience and experience sharing are critical to the advances and commercialization of sensor networks

Wireless terrestrial networks are usually designed in 2D plane, but in real life they form 3D space. In these networks, node placement strategy is one of the most important design problems. The idea is to deploy a number of nodes in an effective way to achieve communication between them. The volumetric quotient, which is the ratio of the transmission range to the sensing range of each node, is used as the main measure of the placement strategy. Researchers use polyhedrons to model 3D networks. As the volumetric quotient increases, we need less number of nodes for full coverage. In this paper, we proposed a cone model which gives a higher volumetric quotient than polyhedrons. The inspiration comes from satellite foot-print. For example, the number of nodes for truncated octahedron placement strategy is found to be 46.35% higher than the cone placement strategy. We also achieved full coverage with cone tessellation.

Wireless sensor “motes” is small or tiny embedded systems equipped with radios for wireless communication in the networks, which depend on batteries as a power source. The development of Medium Access Control (MAC) protocols which search is for to minimize the energy consumption in the wireless sensor network. Recent contention based MAC protocols reduce energy usage by placing the radio in a low power sleep state when not sending or receiving the message. In this paper the main emphasis is on the analysis of the Contention Based MAC Protocols and energy consumption in the networks. Based on the work done by various researchers conclude that S-MAC is the backbone of all the MAC protocols for wireless sensor networks. Our proposed work investigated the energy usage and compared the performance of IEEE 802.11 MAC protocol with S-MAC protocol on different modes like without periodic sleep and with periodic sleep on different performance metrics like Remaining Energy vs Time, Energy consumption vs global packet id and Average End to End Delay vs Time. The performance of S-MAC protocol improves on the basis of duty-cycle parameter, which determines the length of sleep period in a frame and this parameter is a variable. So changing the duty cycle will change the performance of S-MAC protocol. Finally, we have used the different routing protocol with S-MAC to evaluate the energy consumption. The experimented worked done on Network Simulator Ns2- 2.34.

Wireless sensor networks have numerous exciting applications in virtually all fields of science and engineering, including health care, industry, military, security, environmental science, geology, agriculture, and social studies. The routing protocols developed for these distributed sensor networks need to be energy efficient and scalable. Geographic information based routing algorithms have been demonstrated to represent an effective way of finding the appropriate next hop relay nodes by utilizing the location information while avoiding the large number of control packets necessary for route discovery in wireless sensor networks. In this thesis, we propose Energy Aware Geographic Routing Protocol (EAGRP) routing algorithm in a wireless sensor network. Where, we optimize the greedy forwarding mode. The proposed protocol is an efficient and energy conservative routing technique for multi-hop wireless sensor networks. The significance of this study is that there have been very limited investigations of the effect of mobility models on routing protocol performance in Wireless Sensor Networks. We have considered the influence of random way point mobility models on the performance of EAGRP routing protocol. We evaluate the performance of EAGRP against three other protocol approaches GPSR, DSR, AODV. Our simulation results indicate that the proposed algorithm gives better performance in terms of higher packet delivery ratio, throughput, energy consumption, routing overhead, and delay. In wireless sensor networks, congestion occurs when the traffic load being offered exceeds the available capacity of sensor nodes. In most applications, every sensor node will send the event it has sensed to a destination node. This operation makes the sensors closer to the destination, resulting in congestion. Congestion may cause packets loss, lower network throughput and sensor energy waste. Therefore, effective congestion control and loss recovery approach can be considered as effective solution to this problem. We modify TCP congestion control for use in wireless sensor networks. We show that by slightly modifying the algorithm of the TCP, it can be made to respond better to wireless links, while maintaining its advantages on the wired networks at the same time. This is certainly a very desirable feature as the conventional TCP in most cases contradicts to the demands of the wireless links of the network. Simulation results indicate that in wireless sensor networks, modified TCP outperforms traditional TCP algorithm in terms of sending data and information due to its better average throughput, average end-to-end delay, average retransmission, congestion window size, and energy consumption in both high and low traffic.

Wireless sensor networks have emerged as a new information-gathering paradigm in a wide range of applications, such as medical treatment, battlefield surveillance, emergency response, etc. This paper proposes a new data-gathering mechanism for large-scale wireless sensor networks by introducing mobility into the network. A mobile data collector, for convenience called an M-collector, could be a mobile robot or a vehicle equipped with a powerful transceiver and battery, working like a mobile base station and gathering data while moving through the field. An M-collector starts the data-gathering tour periodically from the static data sink, polls each sensor while traversing its transmission range, then directly collects data from the sensor in single-hop communications, and finally transports the data to the static sink. Deployment of sensor network in hostile environment makes it mainly vulnerable to battery drainage . The motivation of a large portion of research efforts has been to maximize the network lifetime, where the lifetime of network is measured from the instant of deployment to the point when one of the nodes has exhausted its limited power source and becomes in- operational commonly referred as first node failure. But there is a class of resource consumption attack called vampire attack which permanently disables the whole network by quickly draining nodes battery. Forwarding as well as discovery phase of the protocol are considered to avoid an attack. Discovery phase is considered to avoid vampire attack.

Wireless sensor networks have been an active research area for about a decade due to their adaptability to applications involving long-term environmental monitoring. Recent technologies make it possible that a small device equipped with multi-purposed sensors, small CPU and memory, wireless transmitter and receiver, and software can form a network, measure some quantitative phenomena and communicate with each other seamlessly. In wireless sensor networks, one of the basic applications is to monitor events and measure values at places that people cannot reach easily or where a long term sensing task is required. In this case, we need to know the properties of diverse types of sensor network queries and data that are different from traditional ones. Also, we need to solve the intrinsic sensor network problem, energy saving, since users want to gather data for a long term and it is generally not feasible to replace batteries in sensor devices after the sensors are deployed. In order to solve this problem, first, we classify sensor network queries and find a suitable network system that includes different routing and storage types for each type of query. Second, energy efficient indexing and data gathering methods for sensor networks are studied. In energy efficient indexing, we propose a sectioned tree index, which divides the network area into several squares and each square has a local index subtree organized within that square. Local trees are interconnected to form one big tree in the network. Local trees are also built based on any algorithm that is energy consumption aware at each sub-root node in a locally centralized way. In energy efficient data gathering, we create energy-efficient data gathering routing tree when we consider two-way communication for reliable transmission and collision prevention. This makes the problem intractable, and we prove our problem is NP-complete by showing that a known NP-complete problem is a special case of our problem. In order to get an energy-efficient routing tree, we propose several heuristic techniques that backtrack one or two steps (BT1 and BT2). We give various values as parameters in measuring energy equation and simulate our proposed algorithms in diverse conditions.

Wireless sensor networks has been widely used. Energy problem is one of the important problems influencing the complete application. Sensor nodes use batteries as power source and have quite limit lifetime. So, efficiency of energy management becomes a key requirement in wireless sensor network design. Based on particle swarm optimization and ant colony optimization, a comprehensive algorithm with weight analysis has been proposed in the paper. In the algorithm, optimization method would be firstly used to determine the nodes number; then, particle  swarm optimization would be used to divide the networks into some clusters; finally, ant colony optimization is used to require the best transmission path and select the cluster head. The simulation results show that the new algorithm has higher energy efficiency and balanced energy consumption. It can extend the network lifetime.

Wireless sensor networks are primarily characterized by inadequate energy supply. Therefore, development of an energy efficient protocol can play an important role in impacting the network lifetime. Typically, communication is the most energy expensive act that nodes perform and limited energy of nodes is the main obstacle. An efficient cluster arrangement might be a solution. Though optimum clustering in wireless sensor networks is an NP-Hard problem, at present, bio-inspired metaheuristic approaches are very popular in solving them. This paper presents a centralized energy-aware clustering algorithm for wireless sensor networks using the novel bio mimic cuckoo search algorithm. The cost function was defined, with the goal of maximizing the network lifetime and minimizing the intra-cluster distance. The performance of the proposed algorithm is evaluated with well-known centralized and decentralized clustering protocols. The results derived from simulations show that proposed solution can enhance network lifetime over its comparatives.