Energy efficient in cluster head and relay node selection for wireless sensor networks

Wireless Sensor Networks (WSNs) are defined as networks of nodes that work in a cooperative way to sense and control the surrounding environment. However, nodes contain limited energy which is the key limiting factor of the sensor network operation. In WSN architecture, the nodes are typically grouped into clusters where one node from each cluster is selected as the Cluster Head (CH) and relays utilisation to minimise energy consumption. Currently, the selection of CH based on a different combination of input variables. Example of these variables includes residual energy, communication cost, node density, mobility, cluster size and many others. Improper selection of sensor node (i.e. weak signal strength) as CH can cause an increase in energy consumption. Additionally, a direct transmission in dual-hop communication between sensor nodes (e.g. CH) with the base station (BS) uses high energy consumption. A proper selection of the relay node can assist in communication while minimising energy consumption. Therefore, the research aim is to prolong the network lifetime (i.e. reduce energy consumption) by improving the selection of CHs and relay nodes through a new combination of input variables and distance threshold approach. In CH selection, the Received Signal Strength Indicator (RSSI) scheme, residual energy, and centrality variable were proposed. Fuzzy logic was utilized in selecting the appropriate CHs based on these variables in the MATLAB. In relay node selection, the selection is based on the distance threshold according to the nearest distance with the BS. The selection of the optimal number of relay nodes is performed using K-Optimal and K-Means techniques. This ensures that all CHs are connected to at least one corresponding relay node (i.e. a 2-tier network) to execute the routing process and send the data to BS. To evaluate the proposal, the performance of Multi-Tier Protocol (MAP) and Stable Election Protocol (SEP) was compared based on 100, 200, and 800 nodes with 1 J and random energy. The simulation results showed that our proposed approach, refer to as Energy Efficient Cluster Heads and Relay Nodes (EECR) selection approach, extended the network lifetime of the wireless sensor network by 43% and 33% longer than SEP and MAP, respectively. This thesis concluded that with effective combinations of variables for CHs and relay nodes selection in static environment for data routing, EECR can effectively improve the energy efficiency of WSNs

Diseño electrónico con panel solar para extender la vida de un nodo en una red inalámbrica de sensores (WSN)

En el presente trabajo se realizó el diseño de un sistema de recolección de energía de bajo costo, con un panel solar fotovoltaico (tipo monocristalino) y baterías recargables Ni-MH para lograr la autonomía energética de una placa NodeMCU v1.0/V3, dispositivo que es ideal para aplicaciones en redes WSN, ya que cuenta con un módulo Wi-Fi ESP-12E, para la comunicación inalámbrica con otros nodos. Por medio de instrumentos de medición como osciloscopios y multímetros se determina la corriente promedio con la que funciona el NodeMCU y con este valor se realizó el diseño del sistema de recolección de energía con el panel solar y baterías Ni-MH. Tras varias pruebas de funcionamiento se obtuvieron resultados exitosos al lograr el funcionamiento continuo (auto sostenible) del NodeMCU, para su uso en múltiples aplicaciones de IoT (Internet of Things).Actividad solar

A path energy control technique for energy efficiency on wireless sensor networks

Wireless Sensor Networks (WSNs) are being deployed in a wide range of application areas requiring high energetic efficiency to increase the application lifetime. Trading off power optimization and reliability has become one of the most significant concerns when dealing with modern systems based on WSNs to guarantee all nodes receive the transmitted data. This work presents a Path Energy Control Technique (PECT), which sets the transmission power of each node based on the path energy consumption. This setting blends three metrics: (i) Quality of the Path (QPth), (ii) Received Signal Strength Indicator (RSSI), and (iii) Data Packet Rate (DPR). Experimental results prove the efficacy of PECT in reducing the energy consumption up to 42% when compared to experiments with fixed transmission power, preserving the reliability of the data transmission.</p

A path energy control technique for energy efficiency on wireless sensor networks

Wireless Sensor Networks (WSNs) are being deployed in a wide range of application areas requiring high energetic efficiency to increase the application lifetime. Trading off power optimization and reliability has become one of the most significant concerns when dealing with modern systems based on WSNs to guarantee all nodes receive the transmitted data. This work presents a Path Energy Control Technique (PECT), which sets the transmission power of each node based on the path energy consumption. This setting blends three metrics: (i) Quality of the Path (QPth), (ii) Received Signal Strength Indicator (RSSI), and (iii) Data Packet Rate (DPR). Experimental results prove the efficacy of PECT in reducing the energy consumption up to 42% when compared to experiments with fixed transmission power, preserving the reliability of the data transmission.</p

Hybridization of enhanced ant colony system and Tabu search algorithm for packet routing in wireless sensor network

In Wireless Sensor Network (WSN), high transmission time occurs when search agent focuses on the same sensor nodes, while local optima problem happens when agent gets trapped in a blind alley during searching. Swarm intelligence algorithms have been applied in solving these problems including the Ant Colony System (ACS) which is one of the ant colony optimization variants. However, ACS suffers from local optima and stagnation problems in medium and large sized environments due to an ineffective exploration mechanism. This research proposes a hybridization of Enhanced ACS and Tabu Search (EACS(TS)) algorithm for packet routing in WSN. The EACS(TS) selects sensor nodes with high pheromone values which are calculated based on the residual energy and current pheromone value of each sensor node. Local optima is prevented by marking the node that has no potential neighbour node as a Tabu node and storing it in the Tabu list. Local pheromone update is performed to encourage exploration to other potential sensor nodes while global pheromone update is applied to encourage the exploitation of optimal sensor nodes. Experiments were performed in a simulated WSN environment supported by a Routing Modelling Application Simulation Environment (RMASE) framework to evaluate the performance of EACS(TS). A total of 6 datasets were deployed to evaluate the effectiveness of the proposed algorithm. Results showed that EACS(TS) outperformed in terms of success rate, packet loss, latency, and energy efficiency when compared with single swarm intelligence routing algorithms which are Energy-Efficient Ant-Based Routing (EEABR), BeeSensor and Termite-hill. Better performances were also achieved for success rate, throughput, and latency when compared to other hybrid routing algorithms such as Fish Swarm Ant Colony Optimization (FSACO), Cuckoo Search-based Clustering Algorithm (ICSCA), and BeeSensor-C. The outcome of this research contributes an optimized routing algorithm for WSN. This will lead to a better quality of service and minimum energy utilization