Conflict between Population and Urbanization Factors： Impact of Urban Heat Island on Energy Consumption Balance

High density of buildings and population in urban areas increases urban temperature, generally known as the urban heat island. Raised temperature, especially in SUlIuner, alms city centers into unwelcome hot areas, with direct effects on electricity demand and energy consttrnption for cooling buildings and increases the production of carbon dioxide and other pollutants. Therefore, by considering that the energy consumption in the world has been faced with intense crisis, it becomes increasingly important to study the effects of urban heat island on energy constunption in order to improve people＇s environment and decrease energy use in cities. This paper, therefore, is focused on urbanization and population size factors to understand tile influence way of these factors on formation of UHI and energy consumption balance. To achieve this aim, this paper explores literally the conceptual framework of confliction between population and urban structure, which produce UHI intensity and affected energy consumption balance. It is then discussed how these two factors can be affected and give implication to the city, and then, focuses on whether actions should be taken for balancing adaptation and mitigation UHI effects. It will be concluded by making the recommendations for preventive action and provide quality of life.

Routing strategy of reducing energy consumption for underwater data collection

Underwater Wireless Sensor Networks(UWSNs)are widely used in many fields,such as regular marine monitoring and disaster warning.However,UWSNs are still subject to various limitations and challenges:ocean interferences and noises are high,bandwidths are narrow,and propagation delays are high.Sensor batteries have limited energy and are difficult to be replaced or recharged.Accordingly,the design of routing protocols is one of the solutions to these problems.Aiming at reducing and balancing network energy consumption and effectively extending the life cycle of UWSNs,this paper proposes a Hierarchical Adaptive Energy-efficient Clustering Routing(HAECR)strategy.First,this strategy divides hierarchical regions based on the depth of the sensor node in a three-dimensional(3D)space.Second,sensor nodes form different competition radii based on their own relevant attributes and remaining energy.Nodes in the same layer compete freely to form clusters of different sizes.Finally,the transmission path between clusters is determined according to comprehensive factors,such as link quality,and then the optimal route is planned.The simulation experiment is conducted in the monitoring range of the 3D space.The simulation results prove that the HAECR clustering strategy is superior to LEACH and UCUBB in terms of balancing and reducing energy consumption,extending the network lifetime,and increasing the number of data transmissions.

Node deployment strategy optimization for wireless sensor network with mobile base station

The optimization of network performance in a movement-assisted data gathering scheme was studied by analyzing the energy consumption of wireless sensor network with node uniform distribution. A theoretically analytical method for avoiding energy hole was proposed. It is proved that if the densities of sensor nodes working at the same time are alternate between dormancy and work with non-uniform node distribution. The efficiency of network can increase by several times and the residual energy of network is nearly zero when the network lifetime ends.

A New Clustering Algorithm Using Adaptive Discrete Particle Swarm Optimization in Wireless Sensor Network

Wireless sensor networks (WSNs) are mainly characterized by their limited and non-replenishable energy supply. Hence, the energy efficiency of the infrastructure greatly affects the network lifetime. Clustering is one of the methods that can expand the lifespan of the whole network by grouping the sensor nodes according to some criteria and choosing the appropriate cluster heads(CHs). The balanced load of the CHs has an important effect on the energy consumption balancing and lifespan of the whole network. Therefore, a new CHs election method is proposed using an adaptive discrete particle swarm optimization (ADPSO) algorithm with a fitness value function considering the load balancing and energy consumption. Simulation results not only demonstrate that the proposed algorithm can have better performance in load balancing than low-energy adaptive clustering hierarchy (LEACH), hybrid energy-efficient distributed clustering (HEED), and dynamic clustering algorithm with balanced load (DCBL), but also imply that the proposed algorithm can extend the network lifetime more.

Mixed Communication Method on the Grid-based for Wireless Sensor Networks

When senors transmit their data to the sink via multi-hop communication, the sensors closer to the sink are burdened with heavy relay traffic and tend to die early. On the contrary, if all sensors transmit datas to the sink via single-hop communication, the sensors further from the sink will die much more quickly than those closer to the sink. In this paper, we first develop an analytical model to derive the optimal cluster radius. Then we propose a mixed communication method on grid-based where the sensors can transmit data to the sink in either single-hop or multi-hop. Finally, we conduct extensive experiments and show that our method outperforms LEACH and HEED in terms of network lifetime by balancing energy consumption.

MimiBS： Mimicking Base-Station to Provide Location PrivacyProtection in Wireless Sensor Networks

In a wireless sensor network (WSN), sink node/base station (BS) gathers data from surrounding nodes and sends them to a remote server via a gateway. BS holds important data. Therefore, it is necessary to hide its location from an inside/outside attacker. Providing BS location anonymity against a local and global adversary, we propose a novel technique called MimiBS 'Mimicking Base-Station'. The key idea is the integration of aggregator nodes (ANs) with sensor nodes (SNs), while fine tuning TTL (time to live) value for fake packets, and setting some threshold value for real packet counter rpctr. MimiBS creates multiple traffic-hotspots (zones), which shifts the focus from BS to the newly created ANs hotspots. Multiple traffic-hotspots confuse the adversary while determining the real BS location information. We defend the BS location information anonymity against traffic analysis attack, and traffic tracing attack. MimiBS gives an illusion of having multiple BSs, and thus, if the attacker knows any about AN, he/she will be deceived between the real BS and ANs. MimiBS outperforms BLAST (base-station location anonymity and security technique), RW (random walk), and SP (shortest path), while conducting routing without fake packets, with fake packets, without energy consideration, and with energy consideration respectively.