Research On Placement In Wireless Sensor Networks

Wireless Sensor Networks (WSNs) consist of a great number of sensor nodes which are composed of sensing unit, processing unit and communicating unit. Wireless sensor networks have a broad application prospect and great practical significance in human life, because WSNs are good for hiding, quick at network building, widespread, simple and inexpensive, easy to expand, small in size, large in scale, and they have flexible structure. WSNs can be used in various applications including:military, environment monitoring, health, space exploration, agriculture, intelligent home, and so on. However, there are many problems and challenges in wireless sensor networks, such as limited energy consumption, limited ability on storage, computing, and communications, low-bandwidth, etc. Therefore, researchers need to consider the various features of wireless sensor networks deeply, and make sure that wireless sensor networks can be efficientively and widely used. It is just the reason that there are a lot of protocols designed for wireless sensor networks, such as routing protocols, MAC protocols, topology control, data processing technology, and so on.However, most of the existing researches on WSNs are carried out after sensor nodes have been deployed, and some studies even completely ignore the structure of WSNs. These researches neglect that WSNs can be configurable. In fact, after sensor nodes are dispersed into the sensing field, we can take advantage of the mobility of sensor nodes, or adding some sensor nodes to rebuild the structure of WSNs, so that the performance of wireless sensor networks can enhanced significantly. This is the placement problem in wireless sensor networks that we will focus on in this paper.In fact, placement is the foundation of various applications in WSNs, because only if sensor nodes have been placed in the sensing field with specific number and positions, we could carry out the practical applications, and the design of all kinds of protocols. Placement is actually very important in wireless sensor networks, and in the past few years, there have been many placement algorithms for WSNs. Although, these placement algorithms focus on connectivity, coverage, energy consumption, congestion control, storage capacity and other issues in WSNs, there is still one or more shortcomings in these algorithms, such as:poor application background, too strong assumption, poor scalability, higher degree of complexity on computing and communications and so on. In response to this situation, we have conducted a wide range of investigation on placement problem in WSNs. Based on the weaknesses of wireless sensor networks, which are of poor transmission reliability, limited energy, limited storage and computing ability, the lack of placement algorithms for mobile sensor networks, we design a set of placement algorithms for wireless sensor networks.First of all, as WSNs have low reliability of data transmission, we study the problem of reliable relay node placement in wireless sensor networks, which aims to use minimum number of relay nodes to ensure the reliability of WSNs. We propose a set-cover based iterative algorithm for this problem which is to place minimum number of relay nodes for the reliability of two typical networks:single-tiered network and two-tiered network. We also prove that the performance ratio of the our placement algorithm is no worse than (1+[(2~1/2D-2r/2R)])(lnn-lnlnn+(?)(1)) for the single-tiered wireless sensor network, and the placement algorithm for the two-tiered network is no worse than (1+[(2~1/2d)/2R])(lnn-lnlnn+(?)(1)), where D is the size of the sensing field, n is the number of initial sensor nodes, constants R> r> 0 are the communication radius of relay node and sensor node.(?)Secondly, this paper studled relay node placement preblem for maximizing the lifetime of a wireless sensor network. Network lifetime is one of the most important research issues in wireless sensor networks. Through analyzing the impact of the positions and number of sensor nodes on network lifetime, we design placement algorithm to prolong the lifetime of WSNs. At first, some relay nodes are placed to connect the whole wireless sensor network through a greedy scheme to satisfy the basic requirement of WSNs. Next, some redundant relay nodes are placed to maximize the network lifetime. And then, we prove that the network lifetime can achieve maximum value through our algorithms.And then, we study the storage node placement problems in wireless sensor networks, to solve the problem that WSNs have limited storage and computing ability. By placing a certain number of storage nodes to store sensing data coming from back-fence sensor nodes, the data traffic in wireless sensor networks can be reduced. We first formulate the storage node placement problems, with modifying the shortcoming of the definition in the energy model of existing methods. And then, we proved that the storage node placement problem in wireless sensor networks is NP - hard; next we present a reverse-based greedy approximation algorithm for the problem, and we also prove that the performance ratio under worst-case of our algorithm is O(log n), where n is the number of sensor nodes.Finally, we study the placement problem in mobile wireless sensor networks, and we focus on the theoretical relationship between the mobile sensor density and sweep coverage. In mobile wireless sensor networks, there is no need to monitor each point in the sensing field continuously. In fact, periodic monitoring is sufficient to meet the needs of most applications in mobile wireless sensor networks. This new coverage model is called sweep coverage, which can save a large number of sensor nodes. In this paper, we first explored t-sweep coverage problem in mobile wireless sensor networks, and then, we gives a clear definition on it. Next, we calculate the minimum sensor density to satisfy t-sweep coverage. It is assumed that the speed of mobile sensor nodes is v, the sensing radius is R, scanning interval is t, then in mobile wireless sensor networks, if vt≥2(3~1/2)R, then the density of mobile nodes should be O(4/3vtR) to satisfy t-sweep coverage, otherwise, it is O(2/3(3~1/2)R2); in hybrid sensor networks with a certain number of static sensor nodes, if vt≥2(2~1/2)R, the density of mobile nodes should be O(4(2~1/2)/evtR), otherwise, it is O(2/eR2).