Wireless Sensor Networking

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SmartMesh Wireless Sensor Networking for Industrial IoT

SmartMesh Wireless Sensor Networking for Industrial IoT

SmartMesh networks communicate using a Time Synchronized Channel Hopping (TSCH) link layer, a technique pioneered by Dust Networks and a foundational building block of wireless mesh networking standards, such as WirelessHART (IEC62591) and IEEE 802.15.4e. In a TSCH network, all motes in the network are synchronized to within a few microseconds. Network communication is organized into time slots, which enables low power packet exchange, pair-wise channel hopping and full path diversity.

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Flood Prediction and Prevention through Wireless Sensor Networking (WSN): A Survey

Flood Prediction and Prevention through Wireless Sensor Networking (WSN): A Survey

The Intel Mote2 platform was used that integrates many essential components to enable high performance, energy efficient data processing. Its XScale processor with dynamic voltage and frequency scaling capability that allows applications for a balanced performance and energy needs by regulating the speeds between 13MHz and 624MHz. The Intel Mote2 includes 32MB of SDRAM and Flash enabling the decoupling of data collection and communication and a richer peripheral support which will provide higher data acquisition rates and improve sensor integration. The new hardware platform along with the next generation in-network processing system will alter the way water utilities, monitor and maintain the pipeline infrastructure. This paper inspires us to make a better hardware platform and a wireless sensor network system for flood prediction and prevention.
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Increasing the Lifetime of Wireless Sensor Networking Depending on Neighbors Relationship

Increasing the Lifetime of Wireless Sensor Networking Depending on Neighbors Relationship

It is now possible to generate sensor nodes that perform sensing and transmitting functions. However, some applications require hundreds or thousands of sensor nodes and these nodes needs to use their limited disposable energies quite attentively. Undoubtedly, it is important to design efficient sensor circuits. However, developing a good routing technique at that point is an equally important issue in terms of extending network life. The direct transmission has been examined first to overcome constraints. In such a method, the sensor node senses the environment and transmits the data directly to the base station. Although the method specified provides data security, it also leads to excessive power consumption. (Especially nodes that are far from the base station) die early due to the energy spent for transmission while they are supposed to do sensing. Consequently, they leave the field abandoned [10].
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AN ENERGY SAVING CLUSTERING ROUTING PROTOCOL BASED ON LEACH WITH ITS VARIANTS IN WIRELESS SENSOR NETWORKING

AN ENERGY SAVING CLUSTERING ROUTING PROTOCOL BASED ON LEACH WITH ITS VARIANTS IN WIRELESS SENSOR NETWORKING

The resource constrained nature of sensor nodes poses the unique challenges to the design of WSNs for their applications. Routing protocols must be energy-efficient to prolong the network lifetime. For this purpose, clustering routing protocol is the most common technique used for energy aware routing in WSN. LEACH has found one of the most energy efficient protocols used in WSN. In this survey, LEACH protocol has been discussed with its drawbacks and how these drawbacks are overcome by its descendants. A brief study of various improved versions of LEACH protocol has been done in order to compare performance of these descendants with the classical LEACH. Each of the routing protocol has its own advantages compared to the fundamental leach routing protocol. This paper also compares the features and performance of each hierarchical clustering routing protocol It is concluded from given survey that there is need to explore more robust, reliable and efficient protocols in future. The process of data aggregation and fusion among clusters is also one of an interesting problem to explore. It is needed to satisfy the constraints introduced by factors such as fault tolerance, topology change, cost, environment, scalability, and power consumption for realization of sensor networks. Since these constraints are highly specific and stringent for sensor networks, new wireless ad-hoc networking techniques will have to be explored further.
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Vhdl Implementation Of An Area Efficient Algorithm For Turbo Decoders Having Wireless Sensor Networking Applications

Vhdl Implementation Of An Area Efficient Algorithm For Turbo Decoders Having Wireless Sensor Networking Applications

In wireless sensor networks, for reliable data transmission, the data need to be encoded at the transmitter and then decoded at the receiver. So a turbo coding system consists of turbo encoders, interleavers and turbo decoders. The input data first enters the turbo encoder. From the turbo encoder, the encoded data passes through the noisy channel, then to the turbo decoder. The turbo decoder produces the decoded output.

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Water Quality Measurement System with Wireless Sensor Networking

Water Quality Measurement System with Wireless Sensor Networking

The setup requires sensor module for sensing a required data, wireless module for data transmission through radio channel and a gateway module which is Arduino development board as monitoring centre. This paper proposes a Sensor-Based Water Pollution Detection, which will detect the pollutant present in the water. The sensor turbidity pH will be kept at any water surface and the data captured by the sensor will be given to Arduino board, then the data are transmitted wirelessly using Zigbee module after calculating the inference from the sensed data.
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Water Quality Measurement System with Wireless Sensor Networking

Water Quality Measurement System with Wireless Sensor Networking

Water pollution is one of the key threats for the green globalization. To prevent the water pollution, first we have to detect the pollutant. There are various sensors which include pH, turbidity, conductivity and temperature sensor for such parameter detections [1]. Routinely monitored parameters of water quality are temperature, pH, turbidity, conductivity, dissolved oxygen (DO), Chemical Oxygen Demand (COD), biochemical oxygen demand (BOD), ammonia nitrogen, nitrate, nitrite, phosphate, various metal ions and so on[7]. Traditional methods that are not only costly but also lack capability for real-time data capture, analyses and fast dissemination of information [3].
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Smart Home Networking: Lessons from Combining Wireless and Powerline Networking

Smart Home Networking: Lessons from Combining Wireless and Powerline Networking

Integrating the power grid technology with renewable power generation technologies, Demand Response (DR) pro- grams enabled by the Advanced Metering Infrastructure (AMI) were introduced into the power grid in the interest of both utilities and residents. They help to achieve load balance and increase the grid reliability by encouraging residents to reduce their power usage during peak load periods in return for incentives. To automate this process, appliances, in-house sensors, and the AMI controller need to be networked together. In this paper, we compare mainstream net- work technologies applicable to home appliance control and propose a solution combining Power Line Communication (PLC) with wireless communication in smart homes for the purpose of energy saving. We extended NS-2, a popular network simulator, to model such combined network scenarios. Using a number of different routing strategies, we then model and evaluate the network performance of DR programs in smart homes in such a combined network.
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An Architecture for Software Defined Wireless Networking

An Architecture for Software Defined Wireless Networking

allow the network to offer the service provider an application programming interface (API) to control how the networks behave to serve traffic that matches a certain set of rules (of course, the degree of control would depend on the agree- ments between network operators and service providers, and the kind of requested control). Furthermore, through this API the provider is also able to dynamically change the forwarding paths of the flows (in both directions), so traffic traverses opportunistically deployed middleware, which can serve, for instance, as data caches or video transcoders. Finally, the provider, now act- ing as a true service composer, can use the API to change the behavior of the wireless last mile in three ways: first, by dynamically prioritizing traffic at the last hop, so in case of poor wireless conditions, some packets (e.g., I frames of a video stream) are provided with better service than others (e.g., B frames), because they are marked as more important; second, by being aware of the service experienced by the user, thus timely adapting following his/her prefer- ences; and third, by supporting traffic on- and off-loading based on these preferences and the availability of different communication links (each with a different performance vs. cost trade-off). In this way, the provider personalizes the operation of the network after the user’s behavior and preferences.
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Wireless Networking Tutorial - Basic Setup

Wireless Networking Tutorial - Basic Setup

Ringtones When you click the Fun & Games tab→Ringtones link, you can view information about the different ringtones that are supported and how to download those ringtones to your wireless phone. Ringtones allow you to add personality to your phone by having it play a song or special tones when it rings.

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Multicarrier Access and Routing for Wireless Networking

Multicarrier Access and Routing for Wireless Networking

The wireless access and routing system is shown in Figure 2. Wireless terminals within each cell access the corresponding radio port by orthogonal multicarrier code-division multiple access (MC-CDMA) [5]. The uplink transmission and recep- tion is described below, in Section 2.1. The received signal at the REN is routed by the switch module to the destina- tion output port. The source-destination information is sup- plied by the control unit. The switch module is an M-input, M-output, nonblocking, routing fabric which is described in Section 2.2. The output port signal is transmitted in the downlink and received by the wireless terminal as described in Section 2.3.
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Era of Deep Learning in Wireless Networking

Era of Deep Learning in Wireless Networking

In [14] (2013) presented an analytically discussion about energy efficiency of Medium Ac- cess Control (MAC) protocols for Wireless Body Area Sensor Networks (WBASNs). For this purpose, different energy efficient MAC protocols with their respective energy optimization techniques; Low Power Listening (LPL), Scheduled Contention and Time Division Multiple Access (TDMA), are elabo- rated. They also analytically compared path loss models for In-body, On-body and Off-body communi- cations in WBASNs. These three path loss scenarios are simulated in MATLAB and results shown that path loss is more in In-body communication because of less energy level to take care of tissues and organs located inside human body. Secondly, power model for WBASNs of Carrier Sense Multiple Access with Collision Avoidance (CSMA/CA) and beacon mode is also presented. The results shown that power of CSMA/CA mode is less as compared to beacon mode. Finally, they suggested that hybrid mode is more useful to achieve optimization in power consumption, which consequently results in high energy efficiency.
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Wireless Home Networking for Dummies pdf

Wireless Home Networking for Dummies pdf

We expect that 802.11a/b/g products — all-in-one devices — will be the stan- dard device that’s deployed in most home networks. This enables the home network to be able to communicate with the protocols that it senses. We think, however, that it’s going to be some time before this is a really seamless activity. There are lots of issues of dealing with multiple protocols in the same wireless area, and these are growing pains that will be worked through over time. For most home networks, IEEE 802.11b wireless networks are the best choice because they’re the least expensive, offer the best signal range, and provide more than adequate data speed. It’s a great way to get started. However, the prices for the faster (and compatible) 802.11g products are dropping so fast that we urge you to look at upgrading to the faster g standardized products. If you find that 802.11a is best for you, that’s okay, too. The reality is, however, that the combined 802.11a/b/g units “future-proof” you the best and are likely what will be on the shelves almost exclusively within a few years. So you can take either fork in the wireless road. Buy low-cost 802.11b units now and upgrade to a nice 802.11 a/b/g unit in a few years when costs have come down and all the kinks are worked out. Or, buy one of the a/b/g units now and upgrade your firmware every once in a while to take advantage of bug fixes and new functionality.
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Role of ZigBee Technology in Wireless Networking

Role of ZigBee Technology in Wireless Networking

Abstract—Zigbee technology is a kind of newly arisen wireless network technology has low frequency, short distance communication, low speed, low power consumption, and low cost, wireless mesh networking Technology. It, Application of Zigbee wireless communication technology, is Industrial control and monitoring sensor networks, building automation, home control and automation, toys and games etc. and With the rapid development of IT industry and the strong functional expansion of SCM, Zigbee wireless communication technology will play an important role in wireless sensor network (WSN). In this paper, Zigbee wireless communication technology and the process of establishing Zigbee network are introduced, the application of Zigbee wireless communication technology is studied in the real world. The ZigBee standard provides network, security, and application support services operating on top of the IEEE 802.15.4 Medium Access Control (MAC) and Physical Layer (PHY) wireless standard. It employs a suite of technologies to enable scalable, self- organizing, self-healing networks that can manage various data traffic patterns.
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Wireless Sensor Network

Wireless Sensor Network

It is known that power consumption is the main constraint on the sensor network, there is a focus on increasing the lifetimes of sensor nodes through power generation, power conservation, and power management. Now a day, research is in designing small MEMS RF components for transceivers, including capacitors, inductors, etc. Micro-sized inductors are a challenge in this area. MEMS power generating device is developed which vibrates at the frequency of the external vibrating source and create the electoral energy. [2]

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Cumulus Humilis : wireless mesh networking for gliders

Cumulus Humilis : wireless mesh networking for gliders

During cross-country flights, it is common to carry a mobile computer in the cockpit of the glider. The mobile computers are used to assist the pilot with naviga- tion and computation of the optimal speed for the pilot to fly. For these purposes, the mobile computer is connected to a GPS receiver and gathers a vast amount of information during the flight. The exchange of this information has the potential to provide insight not only to the pilot himself but also to other pilots and people on the ground. If the information could be sent to the ground, family and friends of the pilots could watch the flight live. If a pilot experiences an emergeny situation, a search-and-rescue team can directly know his location. This can be vital for the pilot’s survival. Also, information from the ground can be of great value to the pi- lot. Delivery of large-scale weather developments to the pilot enables him to adapt his strategy early and not to be surprised by the changing weather conditions. For example when high clouds approach, block incoming sunlight and thus reduce the formation of rising air, the pilot could then be informed to head home earlier to prevent an outlanding. During measurement flights, the real-time communication of sensor readings and feedback from the ground to the pilot can greatly improve the productivity of each measurement flight.
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in Wireless Sensor Networks

in Wireless Sensor Networks

In this paper, we propose Adaptive Fusion Steiner Tree (AFST), a routing scheme that not only optimizes over both transmission and fusion costs, but also adaptively adjusts its fusion decisions for sensor nodes. By evaluating whether fusion is beneficial to the network based on fusion/transmission costs and network/data structures, AFST dynamically assigns fusion decisions to routing nodes during the route construction process. Analytically we prove that AFST out- performs MFST. Through an extensive set of simulations, we demonstrate that AFST provides significant energy saving over MFST (up to 70%) and other routing algorithms under a wide range of system setups. By adapting both the routing tree and fusion decisions to various network conditions, including fusion cost, transmission cost, and data structure, AFST provides a routing algorithm suitable for a broad range of applications.
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Cyber-physical networking for wireless mesh infrastructures

Cyber-physical networking for wireless mesh infrastructures

Abstract. This paper presents a novel approach for cyber- physical network control. “Cyber-physical” refers to the inclusion of different parameters and information sources, ranging from physical sensors (e.g. energy, temperature, light) to conventional network information (bandwidth, de- lay, jitter, etc.) to logical data providers (inference systems, user profiles, spectrum usage databases). For a consistent processing, collected data is represented in a uniform way, analyzed, and provided to dedicated network management functions and network services, both internally and, through an according API, to third party services. Specifically, in this work, we outline the design of sophisticated energy man- agement functionalities for a hybrid wireless mesh network (WLAN for both backhaul traffic and access, GSM for ac- cess only), disposing of autonomous energy supply, in this case solar power. Energy consumption is optimized under the presumption of fluctuating power availability and con- siderable storage constraints, thus influencing, among oth- ers, handover and routing decisions. Moreover, advanced situation-aware auto-configuration and self-adaptation mech- anisms are introduced for an autonomous operation of the network. The overall objective is to deploy a robust wireless access and backbone infrastructure with minimal operational cost and effective, cyber-physical control mechanisms, espe- cially dedicated for rural or developing regions.
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Optimal resource allocation in wireless communication and networking

Optimal resource allocation in wireless communication and networking

Optimal design of wireless systems in the presence of fading involves the instantaneous allocation of resources such as power and frequency with the ultimate goal of maximizing long term system properties such as ergodic capacities and average power consumptions. This yields a distinctive problem structure where long term average variables are determined by the expectation of a not necessarily concave functional of the resource allocation functions. Despite their lack of concavity it can be proven that these problems have null duality gap under mild conditions permitting their solution in the dual domain. This affords a significant reduction in complexity due to the simpler structure of the dual function. The article discusses the problem simplifications that arise by working in the dual domain and reviews algorithms that can determine optimal operating points with relatively lightweight computations. Throughout the article concepts are illustrated with the optimal design of a frequency division broadcast channel.
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Advanced Networking (MSCSP) + Wireless Internet (II, IN)

Advanced Networking (MSCSP) + Wireless Internet (II, IN)

– Internet Service Providers (ISP) and Internet infrastructure provider target the mobile market. State of the Wireless Data Business.[r]

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