Sensing and communication coverage are among the most important trade-offs in Wireless Sensor Network (WSN) design. A minimum bound of sensing coverage is vital in scheduling, target tracking and redeployment phases, as well as providing communication coverage. Some methods measure the coverage as a percentage value, but detailed information has been missing. Two scenarios with equal coverage percentage may not have the same Quality of Coverage (QoC). In this paper, we propose a new coverage measurement method using Delaunay Triangulation (DT). This can provide the value for all coverage measurement tools. Moreover, it categorizes sensors as 'fat', 'healthy' or 'thin' to show the dense, optimal and scattered areas. It can also yield the largest empty area of sensors in the field. Simulation results show that the proposed DT method can achieve accurate coverage information, and provides many tools to compare QoC between different scenarios.

/pdf/delaunay-triangulation-as-a-new-coverage-measurement-method-1nso7z18dk.pdf

Delaunay triangulation as a new coverage measurement method in wireless sensor network.

Coverage preservation during a mission is a crucial issue for wireless sensor networks (WSNs). There are numerous methods to measure the coverage globally, such as circular, grid and non-circular models, but only a few algorithms can be used to measure the coverage locally, using a sensor. A local coverage measurement algorithm uses only the location of a sensor and its neighbors to calculate the coverage, either by having the location information or by determining this information. Absolute localization for location-based services determines sensor positions according to the global Cartesian coordinate system, usually with the help of a global positioning system (GPS) device. In some applications, such as local coverage measurement, the sectional position of neighbors related to a sensor is sufficient. For a GPS-free environment, this paper develops a local position estimation algorithm (LPEA), using triangulation rules, which contains estimation and estimation correction procedures. Simulation results demonstrated that the algorithm is superior to previous work on finding the exact location of neighbors. Moreover, the estimation error in finding the location of neighbors in a 100-m wide field is less than 5m whenever a minimum of eight neighbors is available. Furthermore, measuring coverage using the results of this LPEA is nearly identical to results where the locations of all sensors are known. In this paper, the circular model, the Delaunay triangulation (DT) coverage measurement model, was used, where the circular model, the circular model with shadowing effect and the circular probabilistic model are measurable through a DT coverage measurement. Simulation and real device experiments indicated that the algorithm is significantly accurate in terms of the local coverage measurement and accelerates the operation in coverage measurement algorithms in wireless sensor networks.

Local coverage measurement algorithm in GPS-free wireless sensor networks

Distributed Denial of Service (DDoS) attacks is very recent and popular devastating attack in the field of cyber society. Flooding DDoS attacks produce adverse effects for critical infrastructure availability, integrity and confidentiality. Current defense approaches cannot efficiently detect and filter out the attack traffic in real time. Online analysis of real time attack traffic and their impact and degradation of host and network based performance metrics becomes very essential. So, online measurement of these network performance metrics itself acts as an Intrusion detection system. The anomalies are the inference for network security analyst to suspect whether the network is under attack or not. Based on the assumption that the attacker flows are very aggressive than the legitimate users the proposed work provides sufficient bandwidth to genuine users during flooding DDoS attack. The Interface Based Rate Limiting (IBRL) algorithm proposed in this paper is used to mitigate the identified DDoS attacks. The implementation is carried out on an experimental testbed build up on Linux machines and Virtual routers. The experimental results show that there is considerable increase in the host and network based performance metrics for legitimate users even under DoS and DDoS attacks.

DDoS Detection using host-network based metrics and mitigation in experimental testbed

Wireless Sensor Networks (WSNs) coverage optimization is to maximize the coverage of WSNs while keeping service quality. This paper extends the problem to 2.5D and studies PSO based WSNs coverage optimization on Digital Elevation Models (DEMs). To compute network coverage on DEMs, a method of computing individual sensor node coverage is introduced. This paper also proposes an improved algorithm based on Dissipative Particle Swarm Optimization (DPSO). Simulation experiments show that the algorithm can effectively improve WSNs coverage on DEMs.

PSO based wireless sensor networks coverage optimization on DEMs

With applications ranging from environmental and health monitoring to military surveillance and inventory tracking, wireless sensor networks (WSNs) are changing the way we collect and use data and will be a major part of our technological future. The decreased manufacturing cost of these small devices has made it reasonable to deploy many sensor nodes—tens to thousands and more—over large and small indoor and outdoor areas for sensing tasks. With this increase in density data-gathering problems come. It would be useful if an IP-based host could collect information from multiple remote data-centric networks via transparent communication among sensor nodes and IP-based hosts, using a common application programming interface (API). Two APIs are presented for efficiently producing data in WSN and retrieving the data from an IP network. An associated WSN middleware layer called dynamic service is used to effectively interconnect these two APIs. These three components work together in harmony to enable IP-based hosts to gather sensed data from one or more remote WSNs through application-layer gateways which provide seamless interconnection between different remote WSNs and the IP network.

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Interconnection between IP Networks and Wireless Sensor Networks

The gateway realizes the fusion of wireless sensor network and external network. Some low performance gateways cannot meet the requirement of surge data collection. Consequently, a gateway that based on PXA270, using embedded Linux is designed to meet the requirement. To protect the data that transmitted by Ethernet through the gateway, a TCP/IP strategy is constituted, which can reduce the probability of data missing. To realize the communication of WSN and external network, the application layer program is designed. It can collect, process, transmit the data of WSN, and supply multi-clients services including data display or download concurrently. The client can visit the gateway via Website or command console.

The Design and Realization of Embedded Gateway Based on WSN

To improve the quality of service (QoS) in sensing coverage, wireless sensor networks (WSN) composed of immobile nodes and mobile nodes should optimize the distribution of mobile nodes after their random deployment. According to the pre-research work we know that the node density is closely relevant to QoS in sensing coverage when the nodes are randomly deployed in the target region. In this paper the target region is divided into different parts being not overlapped with the others, a modified particle swarm optimization (PSO) is proposed to optimize the node density of different parts according to the expectation of QoS in the parts and the virtual force between the nodes is proposed to adjust the position of mobile nodes. It is suggested by the simulated experiment results that the method proposed to optimize the mobile nodes in this paper can improve the QoS in sensing coverage.

Researching on Optimal Distribution of Mobile Nodes in Wireless Sensor Networks being Deployed Randomly

Wireless sensor networks are booming today. However the usual wireless sensor networks based on MCU are not suitable to measure fast dynamic signals. In this paper, the wireless sensor network provides a novel measurement for dynamic field systems. We designed an intelligent wireless field measurement system (WFMS) based on wireless sensor networks, which can be applied to measure the fast dynamic field signals. Changeable sampling rate is proposed according to the specific application background in the system. CPLD is used as the main controller for the high and changeable sampling rate and MCU cooperated with a transceiver for the communication of node. The most important significance of this design is that a ldquofirst-saving-then-transmission-mechanismrdquo (FSTTM) and a ldquowaiting-actionrdquo mechanism is built up, which based on the limited hardware resource in wireless sensor network. These mechanisms deal well with the relation of the system performance and limited resource. The experiments indicate that the system works well and its design is successful based on multi-hop network. The complicated system with intelligence can measure a field signal at changeable sampling rate reliably and accurately.

Li Sui

Papers

The Design and Realization of Embedded Gateway Based on WSN

Researching on Optimal Distribution of Mobile Nodes in Wireless Sensor Networks being Deployed Randomly

High Performance Wireless Field Measurement System Based on Wireless Sensor Network