Lifetime maximization has witnessed continuous attention from academia as well as industries right from the inception of Wireless Sensor Networks (WSNs). Recently, mobile sink, trajectory based forwarding and energy supply based node selection have been suggested in literature for optimizing residual energy of nodes. In the most of these approaches, energy consumption has been minimized focusing on the optimization of one particular parameter. The consideration of impact of more than one parameters on energy consumption is lacking in literature. In this context, this paper proposes Huffman coding and Ant Colony Optimization based Lifetime Maximization (HA-LM) technique for randomly distributed WSNs. In particular, ACO based multiple paths exploration and Huffman based optimal path selection consider the impact of two network parameters on energy consumption. The parameters include path length in terms of hop count and residual energy in terms of load of nodes of the path and the least energy node. The construction of multiple paths from source to the sink is mathematically derived based on the concept of two types of ants; namely, Advancing Ant (A-ANT) and Regressive Ant (R-ANT) in ACO. The optimal path is identified from the available multiple paths using Huffman coding. Analytical and simulation results of HA-LM are comparatively evaluated with the state-of-the-art techniques considering four performance metrics; namely, average residual energy, energy consumption, number of alive sensors and standard deviation of energy. The comparative performance evaluation attests the superiority of the proposed technique to the state-of-the-art techniques.

Green computing for wireless sensor networks: optimization and huffman coding approach

Electronic wireless sensors could help to reduce medical costs by using smart devices while patients stay at home. For over a decade, the demand for a new low power wireless standard has been growing worldwide for various commercial applications, such as home and building automation, health, sports and fitness, medical, sensor networking, and even the automotive field. Electronic wireless sensors are connected to smart devices of patients using wireless connectivity systems, such as Bluetooth which is classified into two main technologies: classic-Bluetooth and Bluetooth Low Energy (BLE). BLE is an emerging low-power wireless technology that is expected to be used to communicate with electronic wireless sensors in the medical field. Devices using BLE wireless technology are expected to consume a fraction of the power of classic-Bluetooth enabled products for Bluetooth communication. In many cases, products will be able to operate for more than a year on a coin cell battery without recharging. That will allow sensors such as thermometers to operate continuously, communicating intermittently with other devices such as smart devices. This may increase the concerns for privacy, because remote, low- power, continuously on sensors would be present in devices with BLE. This paper reports the results of a transmission experiment with stream data using BLE, although BLE is inefficient for transferring large quantities of data. The goal of this paper is to introduce BLE wireless technology and to report results obtained when medical stream data was transmitted using BLE.

Transmission of ECG data with the patch-type ECG sensor system using Bluetooth Low Energy

DDEUDSC: A Dynamic Distance Estimation using Uncertain Data Stream Clustering in mobile wireless sensor networks

This article illustrates the conclusions drawn from the development of Internet-of-Things (IoT) systems intended to monitor the ambient parameters, including the quality of the air in different environments, both indoor and outdoor. The design and development in the context of IoT is severely influenced by requirements for small form factor, easy to use, measurement devices, which are deployed in combination with scalable, web-based or portable, applications. The particular case of Bluetooth Low Energy (BLE) technology, miniaturization, and power and cost efficiency were the major aspects taken into account in the research presented here. The considered systems focus on living spaces, classrooms, university amphitheaters and laboratories, and office buildings, and target the achievement of a lifetime of the measurement devices as long as possible. Our experimental results indicate an operating period between a couple of months and 3 years for wireless sensing devices powered by a single off-the-shelf battery, depending on the measurement and transmission rates. All the developed systems are suitable for the implementation of scenarios in the context of IoT and offer future development possibilities in terms of measurement and energetic capabilities, which are supported by the rapid progress in the integrated circuit (IC) industry and by firmware optimization.

Lessons Learned From the Development of Wireless Environmental Sensors

A wireless sensor network is a sensing system composed of a few or thousands of sensor nodes. These nodes, however, are powered by internal batteries, which cannot be recharged or replaced, and have a limited lifespan. Traditional two-tier networks with one sink node are thus vulnerable to communication gaps caused by nodes dying when their battery power is depleted. In such cases, some nodes are disconnected with the sink node because intermediary nodes on the transmission path are dead. Energy load balancing is a technique for extending the lifespan of node batteries, thus preventing communication gaps and extending the network lifespan. However, while energy conservation is important, strategies that make the best use of available energy are also important. To decrease transmission energy cost and prolong network lifespan, a three-tier wireless sensor network is proposed, in which the first level is the sink node and the third-level nodes communicate with the sink node via the service sites on the second level. Moreover, this study aims to minimize the number of service sites to decrease the construction cost. Statistical evaluation criteria are used as benchmarks to compare traditional methods and the proposed method in the simulations.

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An Energy Balancing Strategy Based on Hilbert Curve and Genetic Algorithm for Wireless Sensor Networks

Transmission power optimization is the most significant factor in prolonging the lifetime and maintaining the connection quality of wireless sensor networks. Un-optimized transmission power of nodes either interferes with or fails to link neighboring nodes. The optimization of transmission power depends on the expected node degree and node distribution. In this study, an optimization approach to an energy-efficient and full reachability wireless sensor network is proposed. In the proposed approach, an adjustment model of the transmission range with a minimum node degree is proposed that focuses on topology control and optimization of the transmission range according to node degree and node density. The model adjusts the tradeoff between energy efficiency and full reachability to obtain an ideal transmission range. In addition, connectivity and reachability are used as performance indices to evaluate the connection quality of a network. The two indices are compared to demonstrate the practicability of framework through simulation results. Furthermore, the relationship between the indices under the conditions of various node degrees is analyzed to generalize the characteristics of node densities. The research results on the reliability and feasibility of the proposed approach will benefit the future real deployments.

https://www.mdpi.com/1424-8220/13/3/3951/pdf

A Transmission Power Optimization with a Minimum Node Degree for Energy-Efficient Wireless Sensor Networks with Full-Reachability

In this study, we propose an ACS with flip-flop search strategy to find the route from source node to destination node in an Ad hoc network topology. A flip-flop search strategy is to alternate the search direction towards either high pheromone area or low pheromone area iteratively in the evolution process. The proposed Flip-Flop search strategy effectively solves the pheromone-excess problem in ACS. The ants are allowed to select reverse path to avoid the ants affected by the high pheromone concentration and disable the ability of discover new search area in routing phase. In simulations, the proposed Flip-Flop Ant Colony System (FFACS) is compared with Traditional Ant Colony System in conditions of various deployment densities and topologies of wireless sensor network. The results show that the FFACS has promising ability of discover new search area to reach the better optimal solution than the TACS has. In addition, the robustness and the stability of FFACS are better than TACS.

A new scheme of ant colony system algorithm to discovery optimal solution with flip-flop search

In this paper, an optimization of adaptive transmission with guarantee connection degree of nodes for wireless sensor networks is proposed. The proposed optimization realizes a novel approach to topology control based a power-adaptation scheme. According to the density of deployed nodes, an expected connection degree of nodes and the operational condition are derived. Afterward, the transmission power is adapted to the minimum strength but is sufficient to guarantee node degrees. The benefits of the proposed approach include the reduction and the equalization of power dissipation in nodes. The proposal is applied on a hierarchical network composed of node clusters to manage transmission distances of nodes in a cluster. The present approach guarantees each pair of nodes in a cluster to be connected. The simulation results are obtained in case of uniform-distribution node deployment. The error, defined as the difference of the actual connection degree of nodes and the expected, is around 10%. Besides, the error decreases as the expected connection degree of nodes increasing. The evidence shows that the proposed approach is reliable and stable.

An optimization of adaptive transmission with guarantee connection degree for wireless sensor networks

In this paper, an optimization of adaptive transmission with guarantee connection degree of nodes with various node distributions for wireless sensor networks is studied. First, a proposed optimization realizing a novel approach to topology control based a power-adaptation scheme is presented. According to the density of deployed nodes and an expected connection degree of nodes, an optimal transmission range of nodes are derived. Afterward, the transmission power is adapted to the minimum strength but sufficient to guarantee node degrees. Besides, the relationship between node distributions and reachability is studied and the proposal is applied on a hierarchical network composed of node clusters to manage transmission ranges of nodes in a cluster. The simulation results verify the performance of the proposed approach in cases of Uniform-distribution, Poisson-distribution and Exponential-distribution node deployments. Numeric results show that the proposed approach is reliable and stable. Additionally, the simulation results suggest various deployment strategies corresponding to node.

A Study of Adaptive Transmission Approach to Guarantee Connection Degree in Various Node Location Distributions for Wireless Sensor Networks

In this paper, we propose a novel scheme of data hiding for halftone image which is extended from Fu and Oscar's DHSPT method (data hiding smart pair toggling), it is named as DHADPT (data hiding by absolute difference pair toggling). In this method, we embed the binary data into the halftone image with reference to the original multitone image by evaluating the absolute difference between the neighboring gray-level pixels. The location with minimum sum of the absolute differences of the eight neighboring locations will be the candidate to hide bit data. Experimental results prove its superiority to the original DHSPT method (with higher modified peak signal-to-noise ratio [MPSNR]).

Chih-Cheng Lo

Papers

A Transmission Power Optimization with a Minimum Node Degree for Energy-Efficient Wireless Sensor Networks with Full-Reachability

A new scheme of ant colony system algorithm to discovery optimal solution with flip-flop search

An optimization of adaptive transmission with guarantee connection degree for wireless sensor networks

A Study of Adaptive Transmission Approach to Guarantee Connection Degree in Various Node Location Distributions for Wireless Sensor Networks

Halftone Image Data Hiding with Reference to Original Multitone Image