Energy-efficient data acquisition for accurate signal estimation in wireless sensor networks

Long-term monitoring of an environment is a fundamental requirement for most wireless sensor networks. Owing to the fact that the sensor nodes have limited energy budget, prolonging their lifetime is essential in order to permit long-term monitoring. Furthermore, many applications require sensor nodes to obtain an accurate estimation of a point-source signal (for example, an animal call or seismic activity). Commonly, multiple sensor nodes simultaneously sample and then cooperate to estimate the event signal. The selection of cooperation nodes is important to reduce the estimation error while conserving the network’s energy. In this paper, we present a novel method for sensor data acquisition and signal estimation, which considers estimation accuracy, energy conservation, and energy balance. The method, using a concept of ‘virtual clusters,’ forms groups of sensor nodes with the same spatial and temporal properties. Two algorithms are used to provide functionality. The ‘distributed formation’ algorithm automatically forms and classifies the virtual clusters. The ‘round robin sample scheme’ schedules the virtual clusters to sample the event signals in turn. The estimation error and the energy consumption of the method, when used with a generalized sensing model, are evaluated through analysis and simulation. The results show that this method can achieve an improved signal estimation while reducing and balancing energy consumption

Data Aggregation and Cross-layer Design in WSNs

Over the past few years, advances in electrical engineering have allowed electronic devices to shrink in both size and cost. It has become possible to incorporate environmental sensors into a single device with a microprocessor and memory to interpret the data and wireless transceivers to communicate the data. These sensor nodes have become small and cheap enough that they can be distributed in very large numbers into the area to be monitored and can be considered disposable. Once deployed, these sensor nodes should be able to self-organize themselves into a usable network. These wireless sensor networks, or WSNs, differ from other ad hoc networks mainly in the way that they are used. For example, in ad hoc networks of personal computers, messages are addressed from one PC to another. If a message cannot be routed, the network has failed. In WSNs, data about the environment is requested by the data sink. If any or multiple sensor nodes can return an informative response to this request, the network has succeeded. A network that is viewed in terms of the data it can deliver as opposed to the individual devices that make it up has been termed a data-centric network [26]. The individual sensor nodes may fail to respond to a query, or even die, as long as the final result is valid. The network is only considered useless when no usable data can be delivered. In this thesis, we focus on two aspects. The first is data aggregation with accurate timing control. In order to maintain a certain degree of service quality and a reasonable system lifetime, energy needs to be optimized at every stage of system operation. Because wireless communication consumes a major amount of the limited battery power for these sensor nodes, we propose to limit the amount of data transmitted by combining redundant and complimentary data as much as possible in order to transmit smaller and fewer messages. By using mathematical models and computer simulations, we will show that our aggregation-focused protocol does, indeed, extend system lifetime. Our secondary focus is a study of cross-layer design. We argue that the extremely specialized use of WSNs should convince us not to adhere to the traditional OSI networking model. Through our experiments, we will show that significant energy savings are possible when a custom cross-layer communication model is used

A Survey of Routing Issues and Associated Protocols in Underwater Wireless Sensor Networks

Underwater Wireless Sensor Network is newly emerging wireless technology in which small size sensors with limited energy, limited memory and bandwidth are deployed in deep sea water and various monitoring operation like tactical surveillance, environmental monitoring and data collection are performed through these tiny sensor. Underwater Wireless Sensor Network is used for exploration of underwater resources, oceanographic data collection, flood or disaster prevention, tactical surveillance system and unmanned underwater vehicles. Sensor node consist of small memory, central processing unit and antenna. Underwater network is much different from terrestrial sensor network as radio waves cannot be used in Underwater Wireless Sensor Network. Acoustic channels are used for communication in deep sea water. Acoustic Signals carries with itself many limitation. Such as Limited bandwidth, higher end to end delay, network path loss, higher propagation delay and dynamic topology. Usually these limitation results in higher energy consumption with less number of packets delivered. The main aim now a days is to operate sensor node having smaller battery for a longer time in network. This survey has discussed the state of the art Localization based and Localization free routing protocols. Routing associated issues in the area of Underwater Wireless Sensor Network has also been discussed

Cluster-based Routing Protocols for Energy-Efficiency in Wireless Sensor Networks

22 page

Stochastic Models and Adaptive Algorithms for Energy Balance in Sensor Networks

We consider the important problem of energy balanced data propagation in wireless sensor networks and we extend and generalize previous works by allowing adaptive energy assignment. We consider the data gathering problem where data are generated by the sensors and must be routed toward a unique sink. Sensors route data by either sending the data directly to the sink or in a multi-hop fashion by delivering the data to a neighbouring sensor. Direct and neighbouring transmissions require different levels of energy consumption. Basically, the protocols balance the energy consumption among the sensors by computing the adequate ratios of direct and neighbouring transmissions. An abstract model of energy dissipation as a random walk is proposed, along with rigorous performance analysis techniques. Two efficient distributed algorithms are presented and analyzed, by both rigorous means and simulation. The first one is easy to implement and fast to execute. The protocol assumes that sensors know a-priori the rate of data they generate. The sink collects and processes all these information in order to compute the relevant value of the protocol parameter. This value is transmitted to the sensors which individually compute their optimal ratios of direct and neighbouring transmissions. The second protocol avoids the necessary a-priori knowledge of the data rate generated by sensors by inferring the relevant information from the observation of the data paths. Furthermore, this algorithm is based on stochastic estimation methods and is adaptive to environmental change

Improving sensor network performance with wireless energy transfer

Through recent technology advances in the field of wireless energy transmission Wireless Rechargeable Sensor Networks have emerged. In this new paradigm for wireless sensor networks a mobile entity called mobile charger (MC) traverses the network and replenishes the dissipated energy of sensors. In this work we first provide a formal definition of the charging dispatch decision problem and prove its computational hardness. We then investigate how to optimise the trade-offs of several critical aspects of the charging process such as: a) the trajectory of the charger; b) the different charging policies; c) the impact of the ratio of the energy the Mobile Charger may deliver to the sensors over the total available energy in the network. In the light of these optimisations, we then study the impact of the charging process to the network lifetime for three characteristic underlying routing protocols; a Greedy protocol, a clustering protocol and an energy balancing protocol. Finally, we propose a mobile charging protocol that locally adapts the circular trajectory of the MC to the energy dissipation rate of each sub-region of the network. We compare this protocol against several MC trajectories for all three routing families by a detailed experimental evaluation. The derived findings demonstrate significant performance gains, both with respect to the no charger case as well as the different charging alternatives; in particular, the performance improvements include the network lifetime, as well as connectivity, coverage and energy balance properties

Data Collection Protocols in Wireless Sensor Networks

In recent years, wireless sensor networks have became the effective solutions for a wide range of IoT applications. The major task of this network is data collection, which is the process of sensing the environment, collecting relevant data, and sending them to the server or BS. In this chapter, classification of data collection protocols are presented with the help of different parameters such as network lifetime, energy, fault tolerance, and latency. To achieve these parameters, different techniques such as multi-hop, clustering, duty cycling, network coding, aggregation, sink mobility, directional antennas, and cross-layer solutions have been analyzed. The drawbacks of these techniques are discussed. Finally, the future work for routing protocols in wireless sensor networks is discussed

Energy hole mitigation through cooperative transmission in wireless sensor networks

The energy balancing capability of cooperative communication is utilized to solve the energy hole problem in wireless sensor networks. We first propose a cooperative transmission strategy, where intermediate nodes participate in two cooperative multi-input single-output (MISO) transmissions with the node at the previous hop and a selected node at the next hop, respectively. Then, we study the optimization problems for power allocation of the cooperative transmission strategy by examining two different approaches: network lifetime maximization (NLM) and energy consumption minimization (ECM). For NLM, the numerical optimal solution is derived and a searching algorithm for suboptimal solution is provided when the optimal solution does not exist. For ECM, a closed-form solution is obtained. Numerical and simulation results show that both the approaches have much longer network lifetime than SISO transmission strategies and other cooperative communication schemes. Moreover, NLM which features energy balancing outperforms ECM which focuses on energy efficiency, in the network lifetime sense

A Novel Routing Protocol For Wireless Sensor Networks With Improved Energy Efficient LEACH

Wireless Sensor Networks (Wsns) Have Been Widely Considered As One Of The Most Important Technologies For The Twenty-First Century. A Typical Wireless Sensor Network(WSN) Used For Environmental Condition Monitoring, Security Surveillance Of Battle-Fields, Wildlife Habitat Monitoring, Etc. Cluster-Based Hierarchical Routing Protocols Play An Essential Role In Decreasing The Energy Consumption Of Wireless Sensor Networks (Wsns). A Low-Energy Adaptive Clustering Hierarchy (LEACH) Has Been Proposed As An Application-Specific Protocol Architecture For Wsns. However, Without Considering The Distribution Of The Cluster Heads (Chs) In The Rotation Basis, The LEACH Protocol Will Increase The Energy Consumption Of The Network. To Improve The Energy Efficiency Of The WSN, We Propose A Novel Modified Routing Protocol In This Paper. The Newly Proposed Improved Energy-Efficient LEACH (IEE-LEACH) Protocol Considers The Residual Node Energy And The Average Energy Of The Networks. To Achieve Satisfactory Performance In Terms Of Reducing The Sensor Energy Consumption, The Proposed IEE-LEACH Accounts For The Numbers Of The Optimal Chs And Prohibits The Nodes That Are Closer To The Base Station (BS) To Join In The Cluster Formation. Furthermore, The Proposed IEE-LEACH Uses A New Threshold For Electing Chs Among The Sensor Nodes, And Employs Single Hop, Multi-Hop, And Hybrid Communications To Further Improve The Energy Efficiency Of The Networks. The Simulation Results Demonstrate That, Compared With Some Existing Routing Protocols, The Proposed Protocol Substantially Reduces The Energy Consumption Of Wsns

Data-driven design of intelligent wireless networks: an overview and tutorial

Data science or "data-driven research" is a research approach that uses real-life data to gain insight about the behavior of systems. It enables the analysis of small, simple as well as large and more complex systems in order to assess whether they function according to the intended design and as seen in simulation. Data science approaches have been successfully applied to analyze networked interactions in several research areas such as large-scale social networks, advanced business and healthcare processes. Wireless networks can exhibit unpredictable interactions between algorithms from multiple protocol layers, interactions between multiple devices, and hardware specific influences. These interactions can lead to a difference between real-world functioning and design time functioning. Data science methods can help to detect the actual behavior and possibly help to correct it. Data science is increasingly used in wireless research. To support data-driven research in wireless networks, this paper illustrates the step-by-step methodology that has to be applied to extract knowledge from raw data traces. To this end, the paper (i) clarifies when, why and how to use data science in wireless network research; (ii) provides a generic framework for applying data science in wireless networks; (iii) gives an overview of existing research papers that utilized data science approaches in wireless networks; (iv) illustrates the overall knowledge discovery process through an extensive example in which device types are identified based on their traffic patterns; (v) provides the reader the necessary datasets and scripts to go through the tutorial steps themselves