2,824 research outputs found
Data Aggregation Scheduling in Wireless Networks
Data aggregation is one of the most essential data gathering operations in wireless networks. It is an efficient strategy to alleviate energy consumption and reduce medium access contention. In this dissertation, the data aggregation scheduling problem in different wireless networks is investigated. Since Wireless Sensor Networks (WSNs) are one of the most important types of wireless networks and data aggregation plays a vital role in WSNs, the minimum latency data aggregation scheduling problem for multi-regional queries in WSNs is first studied. A scheduling algorithm is proposed with comprehensive theoretical and simulation analysis regarding time efficiency. Second, with the increasing popularity of Cognitive Radio Networks (CRNs), data aggregation scheduling in CRNs is studied. Considering the precious spectrum opportunity in CRNs, a routing hierarchy, which allows a secondary user to seek a transmission opportunity among a group of receivers, is introduced. Several scheduling algorithms are proposed for both the Unit Disk Graph (UDG) interference model and the Physical Interference Model (PhIM), followed by performance evaluation through simulations. Third, the data aggregation scheduling problem in wireless networks with cognitive radio capability is investigated. Under the defined network model, besides a default working spectrum, users can access extra available spectrum through a cognitive radio. The problem is formalized as an Integer Linear Programming (ILP) problem and solved through an optimization method in the beginning. The simulation results show that the ILP based method has a good performance. However, it is difficult to evaluate the solution theoretically. A heuristic scheduling algorithm with guaranteed latency bound is presented in our further investigation. Finally, we investigate how to make use of cognitive radio capability to accelerate data aggregation in probabilistic wireless networks with lossy links. A two-phase scheduling algorithm is proposed, and the effectiveness of the algorithm is verified through both theoretical analysis and numerical simulations
Aggregation Latency-Energy Tradeoff in Wireless Sensor Networks with Successive Inter- ference Cancellation
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Wireless industrial monitoring and control networks: the journey so far and the road ahead
While traditional wired communication technologies have played a crucial role in industrial monitoring and control networks over the past few decades, they are increasingly proving to be inadequate to meet the highly dynamic and stringent demands of today’s industrial applications, primarily due to the very rigid nature of wired infrastructures. Wireless technology, however, through its increased pervasiveness, has the potential to revolutionize the industry, not only by mitigating the problems faced by wired solutions, but also by introducing a completely new class of applications. While present day wireless technologies made some preliminary inroads in the monitoring domain, they still have severe limitations especially when real-time, reliable distributed control operations are concerned. This article provides the reader with an overview of existing wireless technologies commonly used in the monitoring and control industry. It highlights the pros and cons of each technology and assesses the degree to which each technology is able to meet the stringent demands of industrial monitoring and control networks. Additionally, it summarizes mechanisms proposed by academia, especially serving critical applications by addressing the real-time and reliability requirements of industrial process automation. The article also describes certain key research problems from the physical layer communication for sensor networks and the wireless networking perspective that have yet to be addressed to allow the successful use of wireless technologies in industrial monitoring and control networks
Aggregation Scheduling Algorithms in Wireless Sensor Networks
In Wireless Sensor Networks which consist of tiny
wireless sensor nodes with limited battery power, one of the most
fundamental applications is data aggregation which collects nearby
environmental conditions and aggregates the data to a designated
destination, called a sink node. Important issues concerning the
data aggregation are time efficiency and energy consumption due
to its limited energy, and therefore, the related problem, named
Minimum Latency Aggregation Scheduling (MLAS), has been the
focus of many researchers. Its objective is to compute the minimum
latency schedule, that is, to compute a schedule with the minimum
number of timeslots, such that the sink node can receive the
aggregated data from all the other nodes without any collision or
interference. For the problem, the two interference models, the graph
model and the more realistic physical interference model known as
Signal-to-Interference-Noise-Ratio (SINR), have been adopted with
different power models, uniform-power and non-uniform power (with
power control or without power control), and different antenna
models, omni-directional antenna and directional antenna models.
In this survey article, as the problem has proven to be NP-hard,
we present and compare several state-of-the-art approximation
algorithms in various models on the basis of latency as its
performance measure
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