Top PDF Cooperative network-coding system for wireless sensor networks

Cooperative network-coding system for wireless sensor networks

Cooperative network-coding system for wireless sensor networks

In this paper, we propose two practical power- and bandwidth-efficient systems based on amplify-and-forward (AF) and decode-and-forward (DF) schemes to address the problem of information exchange via a relay. The key idea is to channel encode each source’s message by using a high-performance non-binary turbo code based on Partial Unit Memory (PUM) codes to enhance the bit-error-rate performance, then reduce the energy consumption and increase spectrum efficiency by using network coding (NC) to combine individual nodes’ messages at the relay before forwarding to the destination. Two simple and low complexity physical layer NC schemes are proposed based on combinations of received source messages at the relay. We also present the theoretical limits and numerical analysis of the proposed schemes. Simulation results under Additive White Gaussian Noise, confirm that the proposed schemes achieve significant bandwidth savings and fewer transmissions over the benchmark systems which do not resort to NC. Theoretical limits for capacity and Signal to Noise Ratio behaviour for the proposed schemes are derived. The paper also proposes a cooperative strategy that is useful when insufficient combined messages are received at a node to recover the desired source messages, thus enabling the system to retrieve all packets with significantly fewer retransmission request messages.
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Network coding based multipath routing for energy efficiency in wireless sensor networks

Network coding based multipath routing for energy efficiency in wireless sensor networks

Our previous work [17] presents network coding- based reliable disjoint and braided multipath routing (NC-RMR) for sensor networks in which improving reliability of multipath routing with network coding is the primary aim. In this article, network coding is employed to achieve energy efficiency in WSNs, and the mathematical models of multipath routing with and without network coding are inherited and developed. In [17], we employed two metrics (namely, SDR and NEC) to evaluate the performance of sensor networks. SDR is the number of successful delivered packets over the total packets sent by the source node, and NEC is nor- malized energy consumption which is equal to total energy consumption divided by SDR. In this article, the two metrics are also employed. There are some differ- ences between this article and the previous study [17]. First, a typical energy model is introduced to evaluate the energy consumption of sensor networks, and the influence of different network parameters on perfor- mance is also detailed. Second, we provide routing dis- covery algorithm, data disseminating algorithm, and routing maintenance algorithm to enable network cod- ing to be performed on a braided multipath network model. Third, some additional data and different analy- sis such as energy consumption, reliability, and optimal scheme for energy efficiency are provided.
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Cooperative Caching in Wireless Sensor Networks: A Survey

Cooperative Caching in Wireless Sensor Networks: A Survey

A wireless network is the collection of mobile nodes without the requirement of any centralized access point. Now a days, wireless networking is used for the commercial uses and it becomes the newly trend to adapt the wireless networks. There are the many applications for the wireless networks as it lies in the military, tactical and other security sensitive operations.

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Cooperative Spatial Multiplexing In Wireless Sensor Networks

Cooperative Spatial Multiplexing In Wireless Sensor Networks

Wireless sensor networks are an enabling technology for many future surveillance-oriented applications. Before a practical wireless sensor network is realized, however, significant challenges must be overcome. Chief among the obstacles to netted sensors is providing low power, robust communications between sensor nodes. Multiple Inputs, Multiple Output (MIMO) communication promises performance enhancements over conventional Single Input and Single Output (SISO) technology for the same radiated power

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Determination of Optimal Power for ZigBee-based Wireless Sensor Networks

Determination of Optimal Power for ZigBee-based Wireless Sensor Networks

The communication subsystem is an important energy intensive subsystem as such, power consumption must be minimized. In most cases, all the commercially available transceivers have a controlling functionality to regulate the transceiver between active and inactive states (idle and sleep) [1]. With the help of this system, the sensor node communicates with the base station and other nodes. To replace or change sensor nodes that are battery powered is difficult, especially in cases where huge numbers of nodes are deployed. Hence, every aspect of the network regarding sensing devices, communication algorithms, and localization algorithms must be energy efficient [7].
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Parity Check Network Coding for Multiple Access Relay Channel in Wireless Sensor Cooperative Communications

Parity Check Network Coding for Multiple Access Relay Channel in Wireless Sensor Cooperative Communications

In essence, the contribution of this paper is to employ network coding with additional parity-check bits generated from the two sources’ information bits in relay nodes with linear acceptable complexity. The extra parity-check bits are designed as side information to fill up the mutual information gap between Source-Destination and Relay- Destination transmissions and hence approach the MARC “Cut-Set” bound, which is not addressed in most of the previous research works. Specifically, this paper constructs a multidimensional LDPC code to realize the network coding in a cooperative pair of nodes, as the graphical description of LDPC can flexibly bridge distributed processing and can be customized to emulate a random coding scheme of any
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On the Embedded Intelligent Remote Monitoring and Control System of Workshop Based on Wireless Sensor Networks

On the Embedded Intelligent Remote Monitoring and Control System of Workshop Based on Wireless Sensor Networks

The embedded intelligent workshop remote measurement and control system adopts B/S model. In order to directly access to the intelligent measurement and control equipment unit from the measurement and control server or measurement and control manager, it is possible to install a server with web browsing function on the intelligent measurement and control equipment unit. Here, we adopt Boa as web server on the Linux platform, which will be convenient for system stability and efficient operation in the target system, and or use and maintenance with high reliability. Boa and a normal web server share similarity in the capability of receiving the request from clients, analyzing request, responding to request, and returning the result of request to client and other tasks. The difference between Boa and normal web server is that the HTTP request for processing of Boa enjoys high speed and efficiency, and therefore it will have a high value in the
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Optimized Routing for Cooperative Wireless Sensor Networks

Optimized Routing for Cooperative Wireless Sensor Networks

value of minimum energy along the paths every networks and select the path for the maximum value of this energy. Fig.2 demonstrates how the proposed method works. After node P has the created path in its home network (Sink1), it broadcasts a B-REQ to the visitor networks Net2 and Net3. When node Q and node R receive this B-REQ, they write their network ID in the header of the B-REQ and transmit it to their sink. After this procedure, the routes from node P to the sink via Net2 and Net3 are created, as shown in Tables I and II, respectively. When node P receives a data packet for Sink1, it selects a suitable route from the entries in its routing table as shown in Table I. In this case, node P selects node R, which has the maximum value for min Energy, as the next- hop node. As we described below, the proposed method tries to extend the lifetime of each network by cooperative forwarding. However, it may result in a case where a network shortens its lifetime by the burden of forwarding for visitor networks. To avoid such a situation, in the proposed method, a node which has less residual energy does not relay packets from visitor networks. Specifically, we define a value of cooperation threshold in each network as a metric to decide whether to forward packets from visitor networks or not. For this metric, each sink broadcasts the minimum value of residual energy among all the nodes in its home network to the nodes in its home network. When a node acquires the value, it compares with its own residual energy. If its own residual energy is smaller, it refuses to forward packets from visitor networks and applies itself to relay packets in its home network.
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Wireless sensor network system: Gas leakage detection and monitoring

Wireless sensor network system: Gas leakage detection and monitoring

Wireless sensing networks (WSN) are the effective means of process monitoring for many environmental phenomena such as pollution monitoring, traffic control, water irrigation, etc. A typical WSN system designed and developed can be made to function effectively to detect and monitor the gas leakages in the industrial sectors. Through this short communication, we report our d develop a WSN system that describes the deployment of sensor nodes and successively calibration of the sensor output as a function of the The sensor node attains early gas detection using a semiconductor gas an oxide), an arduino nano microcontroller, an arduino UNO microcontroller, X Bee and an arduino GSM shield. The node receives leaked gas signal from the leakage area and communicate it to the network coordinator wirelessly through the X Bee. When such an emergency is detected, the network coordinator alerts the user by sending SMS through the GSM shield and may autonomously control the source of gas emission through the exhaust fan. The system is further Instrument Software Architecture (VISA) of Lab VIEW software tool. The reliability and productivity of the system are the key concerns and influence the design and development choices for the system in terms of the hardware and software design
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Analysis and Improvement of Routing Protocol LEACH using TEEN, APTEEN and Adaptive Threshold in WSN

Analysis and Improvement of Routing Protocol LEACH using TEEN, APTEEN and Adaptive Threshold in WSN

A wireless sensor network consists of spatially distributed sensor nodes which sense physical and environmental condition like sound, pressure, temperature etc and pass the data to the main location through the network. The recent advances and improvement of micro electro-mechanical systems technology, integrated circuit technologies, microprocessor hardware, wireless communications, Ad-hoc networking routing protocols and embedded systems have made the concept of Wireless Sensor Networks. In WSN network life time and node energy efficiency are two most important terms .The aim of this study is to making an energy- efficient routing protocol which has a significant improvement on the overall lifetime of the sensor network and energy efficiency of nodes. LEACH is energy-efficient hierarchical based protocol that balances the energy efficiency, saves the node energy and hence the lifetime of the network. But Because of certain limitations of routing protocol LEACH, some schemes are proposed using protocols TEEN and APTEEN to overcome the drawback of LEACH. But TEEN and APTEEN has also some drawback and that drawback is removed by an advance scheme that is ADAPTIVE THRESHOLD. It gives better energy efficiency and improved network life time compared to LEACH, TEEN and APTEEN.
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Design of adaptive constellations and error protection coding for wireless network coding in 5 node butterfly networks

Design of adaptive constellations and error protection coding for wireless network coding in 5 node butterfly networks

induced by the feedback in the pre-rotation operation. To demonstrate the robustness of the proposed modulation and coding strategy, we compare the WBN performance results achieved by the Monte-Carlo numerical evaluation (see section 7.1) with USRP HW measurements. While in the numerical evaluation we still keep the idealized assumptions as defined by our system model (i.e. no direct source → destination channels, perfect channel phase pre- rotation), in the HW measurements we now allow all data communication to be performed through real wire- less channels (compare with the HW setup in Section 4.2), introducing inevitably some direct channel observation at both destinations. In addition, we allow the source phase pre-rotation to be switched off in the HW measurements. The channel SNRs γ MAC , γ HSI in the HW measurements
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Cooperative Coding and Caching for Streaming Data in Multihop Wireless Networks

Cooperative Coding and Caching for Streaming Data in Multihop Wireless Networks

At first, we need to initial the caching system to have uniform distributed cardinality. And this can be done easily in a centralized way. For example, we take the gateway node as the initialization control node. If there are P nodes in the network willing to cache the application data, then each of them will provide its reserved capacity to the gateway. Say that if we have B ∗ P units for caching, then the gateway will use a random generator to uniformly distribute cardinality vector to each node. And the overhead could be very low, since we only have to send P packets, each of which has the payload of B ∗ log 2 N bits. The overhead can be further decreased, if we piggyback those cardinality initialization vectors to some real data packets. After initialization, we will apply a simple data replacement strategy to maintain this uniformity.
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Modelling the guaranteed QoS for wireless sensor networks: a network calculus approach

Modelling the guaranteed QoS for wireless sensor networks: a network calculus approach

In this article, we have discussed the problem of the guaranteed QoS for flows. First, based on the arrival curve and the service curve in the network calculus, we have presented the system skeleton, involving the sensor node model on virtual buffer sharing, the flow source model and the two-layer scheduling model of sensor nodes and so on. Second, with the system skele- ton, we have not only drawn the node QoS model, such as the upper bounds on buffer queue length/ delay/effective bandwidth, but also drawn the single- hop/multi-hops QoS model, such as the upper bounds on single-hop/multi-hops delay/jitter/effective band- width. Finally, we have shown the practicability and the simplicity of the model and our approach using example results in the article. We can optimize net- work performances by designing reasonable regulators and schedulers of the WSNs nodes. A network calcu- lus approach is as a trade-off between complexity and accuracy. It is general, simple and practicable for pro- visioning the guaranteed QoS in the WSNs and other wireless networks with some characteristics of the dis- tribution and the multi-hops.
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Standards-based wireless sensor networks for power system condition monitoring

Standards-based wireless sensor networks for power system condition monitoring

The protocol augments the 802.15.4 MAC layer with support for the 6LoWPAN standard for IP version 6 enabled wireless sensor networks. Sensor nodes in an ISA100.11a network can take on multiple roles, either as routing nodes, sensing nodes or both. This allows for flexible deployments where sensors can be specifically configured with or without mesh routing functions, and additional non-sensing routing nodes can be added to the network to increase spatial diversity and hence network reliability. An example of how this feature could be effectively utilized in a substation environment is where routing nodes could be placed in regions with high magnetic flux powered by inductive energy harvesters such as the one developed in [17]. These nodes would be powered from the latent magnetic field, potentially offering a robust routing network with which to connect adjacent sensor nodes.
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User pairing in cooperative wireless network coding with network performance optimization

User pairing in cooperative wireless network coding with network performance optimization

The communication with the common destination (BS) is performed over two phases, and each phase con- sists of two time slots. This is depicted in Figure 2, where it is assumed that nodes i and j constitute a pair, where i, j ∈ {1,…, N}, and i ≠ j. Node i transmits its packet to the destination in the first time slot during the first (direct transmission) phase, while node j listens. Subsequently, j transmits its packet in the second time slot while i listens. This is followed by the second (net- work coding) phase of transmission. Now, if i decoded the packet of j in the previous phase, it combines this packet with its own packet and sends the network-coded packet to the destination in the first time slot. Other- wise, it sends an additional packet for itself. Meanwhile, j does the same in the second time slot of the second phase. This two-source packet transmission model is in- spired by the incremental network coding scheme pro- posed in [9]. Both nodes employ channel coding for error detection and correction, as practiced in modern wireless communication networks.
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Spatially coupled LDPC coding in cooperative wireless networks

Spatially coupled LDPC coding in cooperative wireless networks

Cooperative communications in wireless networks pro- vides improved transmit diversity and spectral efficiency [1]. Judiciously designed signal forwarding at the relay and an accurate detection at the destination can greatly enhance the system performance. Popular relay protocols are amplify-and-forward (AF) and decode-and-forward (DF) [2]. In the AF protocol, the relay transmits an ampli- fied version of the received signal to the destination. In the AF, no noise suppression is performed; therefore, that protocol suffers from severe noise propagation and power inefficiency under poor channel conditions. By using a detector/decoder at the relay, the DF protocol allows for re-generating the transmitted signal, such that the noise propagation can be avoided. However, any decoding error in the regenerated signal can cause a performance degra- dation at the destination.
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An Energy Efficient Congestion control Technique for Wireless Sensor Networks

An Energy Efficient Congestion control Technique for Wireless Sensor Networks

Without sacrificing the application’s reliability, sensor nodes operating in this mode use their traffic context information to reduce unnecessary intrusions and the channel load [4]. The operation is based on the periodical broadcast of 1-hop CAMs (Cooperative Awareness Messages) on a common channel, referred as the communication channel. CAM carries the information such as node energy and node position. The data exchanged through CAMs are used to reduce congestion in the link level. Each sensor node uses the specific positions of neighboring sensor node to reconfigure its application requirements and the resulting transmission parameters.
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Power Saving Strategies In Wireless Sensor 
                      Networks Using Cross Layer Design

Power Saving Strategies In Wireless Sensor Networks Using Cross Layer Design

experience higher number of errors, so energy efficiency can be maximized by optimal packet size. The modulation at physical layer can be changed depending upon the remaining capacity of the battery. The number of packets in the system (in buffer or queue or being in transmission) can affect the constellation size of the modulation scheme. The lifetime of the network can be extended by using varying data rate at each node in the routing path. Reducing transmission rates at critical node (energy constrained) also results in extended network lifetime. If data rate is increased, the probability of encountering errors also increases, so a higher value of SNR (Signal to Noise Ratio) would be required at the transmitting end to have an acceptable value of BER (Bit Error Rate) at the receiving end. Higher SNR means higher transmitting power and therefore, more energy consumption. Based on the data rate requirements, modulation scheme can be selected. The modulation scheme, with certain BER threshold values and SNR can be used to calculate the transmit power. The optimal transmit power increases with increase in the data rate (vulnerable time is decreased but thermal noise is also increased) while a carefully chosen data rate can have high impact on transmit power and network lifetime.
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Data Dissemination in Wireless Sensor Networks with Network Coding

Data Dissemination in Wireless Sensor Networks with Network Coding

This paper studies data dissemination in wireless sensor networks with network coding to achieve energy e ffi ciency. In order to quickly complete the whole process of data dissemination, at each time slot in the recovery process, we aim to transmit an encoded packet such that the expected number of active sensors that can decode out one “wanted” packet is maximized. A maximum weight clique model is proposed here to achieve such an objective. We further study the impact of packet loss probability and sleep probability on network coding gain. We also analyze the impact of sleep probability on energy saving gain and derive a threshold which can be used to decide whether the current sleep scheduling is effective on energy saving or not. The simulation results verify the work proposed in the paper.
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Wireless Mine Surveillance with Data Logging

Wireless Mine Surveillance with Data Logging

Wireless sensor networks applied in monitoring coal mine security, breaks through the traditional methods and ideas, which improves the practical ability and flexibility of monitoring system. This system not only can monitor all kinds of parameters under the coal mine, but also can alarm automatically when environmental parameters are abnormal to exceed the limitation, which help improve the level of monitoring safety production and reduce accidents in the coal mine. Therefore, the Mine Safety Monitoring system put forward in this article quite meets the need of the hour. Traditional mine security system can be effectively replaced by the surveillance and safety system proposed in the paper.
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