Wei An

Effective sensor deployment based on field information coverage in precision agriculture

Coverage is an importance issue in wireless sensor networks. In this work, we first propose a novel notion of information coverage, which refers to the coverage efficiency of field information covered by deployed sensor nodes. On the basis of information coverage, we consider an optimization problem of how to partition the given field into multiple parcels and to deploy sensor nodes in some selected parcels such that the field information covered by the deployed sensor nodes meets the requirement. First, we develop two effective polynomial-time algorithms to determine the deployed locations of source nodes for information 1-coverage and q-coverage of the field, respectively, without consideration of communication, where information q-coverage implies that the field information in terms of information point is covered by at least q source nodes. Also, we prove the upper bound in the theoretical for the approximate solution derived by our proposed method. Second, another polynomial-time algorithm is presented for deriving the deployed locations of relay nodes. In the theoretical, this proposed algorithm can achieve the minimized number of relay nodes. Further, the related information 1-coverage algorithms are applied in our wireless sensor network-based automatic irrigation project in precision agriculture. Experimental results show the major trade-offs of impact factors in sensor deployment and significant performance improvements achieved by our proposed method. Copyright

The Maximized Relay Capacity and Optimal Data Transmission for Wireless Sensor Networks

In wireless sensor networks (WSNs), the nodes are usually powered by batteries with limited capacities, which has become one of the main challenges to the wide deployment of WSN-based applications. The overall network lifetime, which is usually determined by the node with the shortest lifetime because of the unbalanced energy consumption, becomes a major issue. Aiming at this, we consider the optimization problem of how to maximize the data amount that can be transmitted from the source node to the sink node, given an energy-limited wireless sensor network. Specifically, we first analyze the problem on the basis of the max-flow min-cut theorem to obtain the maximum relay capacity in terms of the number of successfully transmitted packets from the source node to the sink node, from the theoretical point of view. Then, we propose our algorithms to achieve the optimal solution. In this way, the expected network lifetime can be maximized. Further, we also prove the correctness of the proposed algorithms. Extensive simulations show that significant performance enhancement can be achieved by using our proposed algorithms.

Vulnerability-constrained multiple minimum cost paths for multi-source wireless sensor networks

In wireless sensor networks, one of the primary requirements is that sensor data acquired from the physical world can be interchanged with all interested collaborative entities in a secure, reliable manner. Because of highly unpredictable nature of the environments caused by malicious attacks or potential threats, minimizing transmission cost between source and sink nodes with jointly considering the security of the whole network is a critical issue. This paper considers two optimization problems of deriving the minimum cost paths from multiple source nodes to the sink node under the guaranteed level of the vulnerability. The link or node vulnerability is defined as a metric, which characterizes the degree of link or node sharing among paths. With the defined link vulnerability, the link vulnerability-constrained minimum cost paths problem is first formulated, and two polynomial-time algorithms are developed for deriving the optimal paths. For the node-vulnerability-constrained minimum cost paths problem, we adopt the network conversion and then achieve the optimal solution with previous proposed algorithms. The necessary condition for solution existence, the optimality of the proposed algorithms, and the related properties of tree network are further theoretically analyzed. Extensive simulations show the significant performance improvements achieved by our proposed algorithms.Copyright

Overall cost minimization for data aggregation in energy-constrained wireless sensor networks

In wireless sensor networks (WSNs), sensor nodes are usually powered by batteries of limited capacity, which results in dynamic changes of available paths for data aggregation due to node failures caused by energy depletion. For transmitting certain amount of data generated by source node, the overall transmission cost is affected by two major factors, using sequence of available paths and amount of data imposed on each path, which becomes a major issue significantly influencing the efficient usage of the networks. To address this issue, we consider the optimization problem of how to minimize the overall transmission cost of given data delivered from the source node to the sink node in the energy-constrained WSN. Specifically, we first describe the problem on the basis of the minimum cost flow theory and derive the upper bound for the data amount in terms of the number of packets that can be successfully transmitted from the source node to the sink node. Then, we propose specific algorithms to derive the optimal paths and their optimal data amounts, and then achieve the minimized overall transmission cost for the certain amount of data. Extensive simulations show that significant performance enhancement can be achieved by using our proposed algorithms.

Agriculture Cyber-Physical Systems

Abstract In this chapter, agriculture cyber-physical systems (ACPSs) are presented as the key technology to achieve precision agriculture. First, a typical architecture of ACPSs is explained. Then, some existing ACPSs and their applications, such as, soil moisture monitoring for irritation scheduling, soil mineral content monitoring for fertilization scheduling, weather monitoring for frost prevention, crop growth monitoring for disease prevention and harvest management, are reviewed. Moreover, as a study case of ACPSs, the issue of sensor deployment in an ACPS-enabled automatic irrigation system for field information coverage in precision agriculture is investigated. A field experiment is conducted to evaluate the performance of the proposed method for sensor deployment. Finally, future research directions of ACPSs are also provided.

Coverage hole problem under sensing topology in flat wireless sensor networks

In flat wireless sensor networks, one fundamental issue is region coverage, which usually addresses whether the given region is sufficiently covered by sensing disks of sensor nodes or not. Although numerous research works have been carried out on region coverage, it still lacks in-depth understanding on the relations between region coverage and sensing topology defined with the intersections of sensing areas of sensor nodes. In this paper, we consider the region coverage problem by using the sensing topology proposed in our previous work. Based on the notion of sensing topology, we prove that the given region can be partitioned into a number of the smallest cells, each of which is defined by sensing links among sensor nodes. Then, we investigate the sufficient and necessary conditions for the existence of coverage holes for the specific polygon graph residing in the partitioned cells. Further, two polynomial time algorithms are presented for dividing the given region covered by the whole network and detecting the coverage holes existing in the interior area of the partitioned cells, respectively. The experiment results show that our proposed algorithms are effective for detecting the coverage holes. Copyright

Importance-based data transmission optimization in multi-source single-sink wireless sensor networks

Energy-efficient routing becomes one of the most critical technologies for sustaining the overall network lifetime of wireless sensor networks. In this paper, we propose a novel data transmission scheme between a number of specified source nodes and the single sink, which can efficiently restrict the usage frequency of each relay node, measured by the number of source nodes using it for data transmission. On the basis of the importance of source nodes that is closely related to deployed location, they form a descending sequence such that each node finds the minimum energy path earlier than the succeeding one. Then, the energy-efficient multiple path algorithm with the computational complexity of On3 is developed for deriving the minimum energy paths, where n is the number of nodes in the network. Also, a polynomial algorithm is presented for deriving the range of the feasible values of N0 serving as the threshold of the usage frequency of relay nodes, in which each can guarantee the existence of the solution. Further, we theoretically investigate the existence of the solution and the tree-structured solution using m-ary tree. Extensive simulation results show that our proposed scheme can achieve significant performance enhancement. Copyright

Achieving energy-neutral data transmission by adjusting transmission power for energy-harvesting wireless sensor networks

Recently, benefiting from rapid development of energy harvesting technologies, the research trend of wireless sensor networks has shifted from the battery-powered network to the one that can harvest energy from ambient environments. In such networks, a proper use of harvested energy poses plenty of challenges caused by numerous influence factors and complex application environments. Although numerous works have been based on the energy status of sensor nodes, no work refers to the issue of minimizing the overall data transmission cost by adjusting transmission power of nodes in energy-harvesting wireless sensor networks. In this paper, we consider the optimization problem of deriving the energy-neutral minimum cost paths between the source nodes and the sink node. By introducing the concept of energy-neutral operation, we first propose a polynomial-time optimal algorithm for finding the optimal path from a single source to the sink by adjusting the transmission powers. Based on the work earlier, another polynomial-time algorithm is further proposed for finding the approximated optimal paths from multiple sources to the sink node. Also, we analyze the network capacity and present a near-optimal algorithm based on the Ford-Fulkerson algorithm for approaching the maximum flow in the given network. We have validated our algorithms by various numerical results in terms of path capacity, least energy of nodes, energy ratio, and path cost. Simulation results show that the proposed algorithms achieve significant performance enhancements over existing schemes. Copyright

A Wireless Traffic QoS Optimization Algorithm Based on Fuzzy Measurement

—A cross-layer based QoS optimization algorithm for wireless traffic networking is presented in this paper. In terms of the fuzzy measure theory, we propose a nonlinear wireless traffic networking optimization model based on the Choquet integral. The model can characterize not only the protocol parameters’ significance but also the interdependency among those parameters on the QoS of data transmission by a nonadditive function. The distinct characteristic of the proposed model lies in that the contribution of interaction among the system parameters to the network performance can be evaluated quantitatively by a general nonlinear and non-additive integral. Once the network condition cannot satisfy the user’s QoS requirement, the most significant networking parameters can be adjusted to improve the data transmission performance and further achieve the user’s QoS demand. Finally, simulation results are given to verify the effectiveness and efficiency of the proposed method over the WLAN network.

Significance-based energy-efficient path selection for multi-source underwater sensor networks

Although numerous works have been done on optimising energy usage of sensors existing in Underwater Wireless Sensor Networks UWSNs, no work has been done on jointly considering the mutual interconnections among paths of multi-source nodes under the given network topology and acoustic channel conditions. In this work, we consider the problem of data transmission from multiple source nodes to the sink node. The main contributions of this work are: a node significance is defined based on the distance and source node statuses; b given a number of source nodes, we formulate the problem of energy-efficient multiple paths, and develop a polynomial-time algorithm for deriving the optimal paths; c to refine the feasible number of source nodes, the upper and lower bounds are derived based on the network topology and acoustic channel conditions. Extensive simulation results show that our proposed scheme can achieve significant performance enhancement over the existing ones.