Research On Data Collection In Wireless Sensor Networks

Data collection in wireless sensor networks is very important research issues in re-cent years. Extensive researches on this issue have been conducted. Data collection need to collect sensing data from the monitored area through wireless sensor networks. In data collection applications, the users first need to deploy a large number of specifical sensor nodes in the monitored region. The deployed sensor nodes then automatically connected as a network. Data collection is to collect sensing data in the form of multi-hop transmis-sion process to the basestation. There are many research problems in data collection, from data collection protocol to multi-channel scheduling, from static network data collection to mobile network data collection, and so on. This article will study how to reduce the amount of transmissions in data collection, data collection protocols, increasing network throughput and so on.First, this paper studies how to reduce the amount of data in data collection problem in multi-application sharing wireless sensor networks. This paper proposes the interval data sharing problem。Different from current studies where each application requires a single data sampling during each task, we study the problem where each application re-quires an continuous interval of data sampling in each task instead. Our problem is to investigate how to transmit as less data as possible over the network, and meanwhile the transmitted data satisfies the requirements of all the applications. The proposed problem is a nonlinear nonconvex optimization problem. In order to lower the high complexity for solving a nonlinear nonconvex optimization problem in resource restricted sensor n-odes, an approximation algorithm is provided. A special instance of this problem is also analyzed. This special instance can be solved with a dynamic programming algorithm in polynomial time. Three online algorithms are also provided to process the continually coming tasks. The time and memory complexity of each algorithm are analyzed in this paper.Second, this paper studies how to reduce the amount of data in multiple count prob-lem in aggregation process. Different from typical count problem, This paper identifies the multiple count problem in wireless sensor networks. Multiple count problem needs to count the items belonging to multiple categories. For each category, the total number of the items belonging to this category is calculated. Therefore, the returned result is a set of values instead of a single value. The multiple count problem incurs more communication overhead. This paper proposes a distributed approximate multiple count algorithm which can derive an error bounded result under a specified communication cost constraint for each node. Furthermore, the weighted multiple count problem is investigated where dif-ferent kinds of items to be counted have different weights. The error bound, the bound of data amount and the bound of memroy usage of the proposed algorithm are analyzed in this paper.Third, this paper studies the geographic routing protocol in data collection process. In a geographic routing protocol, data packets can be routed to the destination sensor n-ode through a small amount of local routing information. Geographic routing algorithms usually require planar graphs derived from the original network topologies. The only practical algorithm brings in overheads in deleting and adding cross links. In order to re-duce the overhead, a high-reliable and low-cost geographic routing protocol is proposed. This protocol divides the whole network into numbers of regular regions, and tries to per-form a region-greedy routing on the virtual node of a region when the node-greedy routing fails. It has high reliability since the transmissions between regions can reduce the aver-age length of the routing paths. Furthermore, RPR has low cost because its planarization phase does not check or delete cross links.Forth, This paper studies how to maximize the throught for periodic data aggregatio in a TDMA multi-radio network. For more practical, the interference model in this paper is the practical physical interference model SINR. We aim to reduce the required number of time slots, so as to collect a stream of aggregated data as fast as possible. We propose a distributed scheduling algorithm whose upper bound of the required number of time slots is analyzed. The algorithm proposed in this is distributed, whose scheduling cost is lower than the centralized algorithms. The goal of this is to minimzed the time slots in the TMDA scheduling, thus maximize the throught.