Liao Wenxing

A Game-Theoretic and Energy-Efficient Algorithm in an Improved Software-Defined Wireless Sensor Network

Because wireless sensor networks (WSNs) are becoming increasingly integrated into daily life, solving the energy efficiency problem of such networks is an urgent problem. Many energy-efficient algorithms have been proposed to reduce energy consumption in traditional WSNs. The emergence of software-defined networks (SDNs) enables the transformation of WSNs. Some SDN-based WSNs architectures have been proposed and energy-efficient algorithms in SDN-based WSNs architectures have been studied. In this paper, we integrate an SDN into WSNs and an improved software-defined WSNs (SD-WSNs) architecture is presented. Based on the improved SD-WSNs architecture, we propose an energy-efficient algorithm. This energy-efficient algorithm is designed to match the SD-WSNs architecture, and is based on the residual energy and the transmission power, and the game theory is introduced to extend the network lifetime. Based on the SD-WSNs architecture and the energy-efficient algorithm, we provide a detailed introduction to the operating mechanism of the algorithm in the SD-WSNs. The simulation results show that our proposed algorithm performs better in terms of balancing energy consumption and extending the network lifetime compared with the typical energy-efficient algorithms in traditional WSNs.

Mathematical Modeling and Analysis Methodology for Opportunistic Routing in Wireless Multihop Networks

Modeling the forwarding feature and analyzing the performance theoretically for opportunistic routing in wireless multihop network are of great challenge. To address this issue, a generalized geometric distribution (GGD) is firstly proposed. Based on the GGD, the forwarding probability between any two forwarding candidates could be calculated and it can be proved that the successful delivery rate after several transmissions of forwarding candidates is irrelevant to the priority rule. Then, a discrete-time queuing model is proposed to analyze mean end-to-end delay (MED) of a regular opportunistic routing with the knowledge of the forwarding probability. By deriving the steady-state joint generating function of the queue length distribution, MED for directly connected networks and some special cases of nondirectly connected networks could be ultimately determined. Besides, an approximation approach is proposed to assess MED for the general cases in the nondirectly connected networks. By comparing with a large number of simulation results, the rationality of the analysis is validated. Both the analysis and simulation results show that MED varies with the number of forwarding candidates, especially when it comes to connected networks; MED increases more rapidly than that in nondirectly connected networks with the increase of the number of forwarding candidates.

A quality of service–aware preemptive tidal flow queuing model for wireless multimedia sensor networks in the smart grid environment

The smart grid incorporates a two-way communication system between customers and the utility for advanced monitoring and intelligent control of supply and demand. Wireless multimedia sensor network can be treated as an organic supplement and a peripheral network in this two-way communication system. However, the challenging smart grid environment makes it difficult to achieve a high quality of service in wireless multimedia sensor network. This article proposes a prioritization mechanism that considers the heterogeneous characteristics of smart grid traffic. Specifically, an innovative channel allocation and traffic scheduling scheme, named the preemptive tidal flow queuing model, is presented. This scheme achieves differentiated services for diverse communication data when the wireless multimedia sensor network accesses the core network and ensures the performance for high-priority data at the expense of the performance for low-priority data. Simulation analyses show that the performance for high-priority messages can be reliably guaranteed and that the preemptive tidal flow queuing model satisfies the requirements for a wireless multimedia sensor network operating in the smart grid environment. This article offers three main contributions: the development of a prioritization mechanism specifically for a wireless multimedia sensor network in the smart grid environment, the proposal of the preemptive tidal flow queuing model, and the presentation of formulas and simulations to verify the performance of the preemptive tidal flow queuing model.

Hop count limitation analysis in wireless multi-hop networks

Recent studies about wireless multi-hop networks mainly focus on two aspects, network performance and network strategy. A mass of models and algorithms about network connectivity, path reliability, and node mobility have been proposed to improve network performance. However, hop count, an important factor of wireless multi-hop networks, is rarely researched. In this article, we propose some feasible research methods to figure out the connections between hop count and network connectivity, and path reliability and node mobility, respectively. By modeling the network connectivity, path reliability, and node mobility, we get the maximum hop count of arbitrary wireless multi-hop network. This study shows that the hop count limitation has great effect on network stability. With an increase in hop count, the network stability gets worse. Thinking about this situation, we propose some feasible advices to avoid the hop count limitation problem, which may provide some useful theoretical foundation for further study on wireless multi-hop networks.

Design of multi-energy-space-based energy-efficient algorithm in novel software-defined wireless sensor networks

Energy efficiency has always been a hot issue in wireless sensor networks. A lot of energy-efficient algorithms have been proposed to reduce energy consumption in traditional wireless sensor networks. With the emergence of software-defined networking, researchers have demonstrated the feasibility of software-defined networking over traditional wireless sensor networks. Thus, energy-efficient algorithms in software-defined wireless sensor networks have been studied. In this article, we propose an energy-efficient algorithm based on multi-energy-space in software-defined wireless sensor networks. First, we propose a novel architecture of software-defined wireless sensor networks according to current research on software-defined wireless sensor networks. Then, we introduce the concept of multi-energy-space which is based on the residual energy. Based on the novel architecture of software-defined wireless sensor networks and the concept of multi-energy-space, we give a detailed introduction of the main idea of our multi-energy-space-based energy-efficient algorithm. Simulation results show that our proposed algorithm performs better in energy consumption balance and network lifetime extension compared with the typical energy-efficient algorithms in traditional wireless sensor networks.

The Impacts of Weak Links on Routing Process in Large Scale Multi-Hop Networks

In wireless multi-hop networks, especially large scale wireless multi-hop networks, the feasibility of routing strategies is of vital significance. However, the basic function of routing strategies, the ability of finding a path from source to destination, is seldom researched. In this paper, we apply a Markov chain to model the routing discovery process of wireless multi-hop networks with arbitrary routing strategies. Taking the fading characteristics of wireless channel into consideration, we analyze the impacts of weak links on routing algorithms in wireless multi-hop networks. The probability of routing success and the distribution of hop count are discussed in detail and their close-form solutions are given. Simulation and theoretical results show that, with the increase of the network scale, the impact of weak links gets stronger and even makes the routing strategies unusable. Our research has pointed out the relations between the performance of routing strategies and the network scale under the impact of weak links. The results have important significance for routing strategy designing and network planning.

An Overhead-Optimizing Task Scheduling Strategy for Ad-hoc Based Mobile Edge Computing

In this paper, an overhead-optimizing multi-device task scheduling strategy for ad-hoc-based mobile edge computing system is proposed. This task scheduling strategy takes the opportunity consumption, time delay, energy consumption, and monetary cost into account, aiming at minimizing the overhead of each mobile device. First, a system model for ad-hoc-based mobile edge computing is presented and the overhead of mobile device is analyzed. Second, the task scheduling problem is formulated as a distributed multi-device task scheduling game. Then, by constructing a potential function, the task scheduling game is proved to be a potential game, which possesses a property of finite improvement and always owns a Nash equilibrium. Next, an overhead-optimizing multi-device task scheduling algorithm is designed and the computational complexity is analyzed. Finally, simulations are conducted to evaluate the effectiveness of the proposed strategy. The results show that the proposed task scheduling strategy can effectively minimize the overhead of the mobile device and successfully complete the tasks.