Evolutionary forwarding games in delay tolerant networks: Equilibria,mechanism design and stochastic approximation

In this paper, we apply evolutionary games to non-cooperative forwarding control in Delay Tolerant Networks (DTNs). The main focus is on mechanisms to rule the participation of the relays to the delivery of messages in DTNs. Thus, we express the success probability as a function of the competition that takes place within a large population of mobiles, and we characterize the effect of reward-based mechanisms on the performance of such systems. Devices acting as active relays, in fact, sacrifice part of their batteries in order to support message replication and thus increase the probability to reach the destination. In our scheme, a relay can choose the strategy by which they participate to the message relaying. A mobile that participates receives a unit of reward based on the reward mechanism selected by the network. A utility function is introduced as the difference between the expected reward and the energy cost, i.e., the cost spent by the relay to sustain forwarding operations. We show how the evolution dynamics and the equilibrium behavior (called Evolutionary Stable Strategy – ESS) are influenced by the characteristics of inter contact time, energy expenditure and pricing characteristics.We extend our analysis to mechanisms that the system can introduce in order to have the message delivered to the destination with high probability within a given deadline and under energy constraints which bound the number of released copies per message. Finally, we apply our findings in order to devise decentralized forwarding algorithms that are rooted in the theory of stochastic approximations. Thus, we demonstrate that the ESS can be attained without complete knowledge of the system state and letting the source monitor number of released copies per message only. We provide extensive numerical results to validate the proposed scheme.     

Fairness-related challenges in mobile opportunistic networking

The fundamental challenge in opportunistic networking, regardless of the application, is when and how to forward a message. Rank-based forwarding techniques currently represent one of the most promising methods for addressing this message forwarding challenge. While these techniques have demonstrated great efficiency in performance, they do not address the rising concern of fairness amongst various nodes in the network. Higher ranked nodes typically carry the largest burden in delivering messages, which creates a high potential of dissatisfaction amongst them. In this paper, we adopt a real-trace driven approach to study and analyze the trade-offs between efficiency, cost, and fairness of rank-based forwarding techniques in mobile opportunistic networks.Our work comprises three major contributions. First, we quantitatively analyze the trade-off between fair and efficient environments. Second, we demonstrate how fairness coupled with efficiency can be achieved based on real mobility traces. Third, we propose FOG, a real-time distributed framework to ensure efficiency–fairness trade-off using local information. Our framework, FOG, enables state-of-the-art rank-based opportunistic forwarding algorithms to ensure a better fairness–efficiency trade-off while maintaining a low overhead. Within FOG, we implement two real-time distributed fairness algorithms; Proximity Fairness Algorithm (PFA), and Message Context Fairness Algorithm (MCFA). Our data-driven experiments and analysis show that mobile opportunistic communication between users may fail with the absence of fairness in participating high-ranked nodes, and an absolute fair treatment of all users yields inefficient communication performance. Finally our analysis shows that FOG-based algorithms ensure relative equality in the distribution of resource usage among neighbor nodes while keeping the success rate and cost performance near optimal.     

An update-based step-wise optimal cache replacement for wireless data access

Many network applications requires access to most up-to-date information. An update event makes the corresponding cached data item obsolete, and cache hits due to obsolete data items become simply useless to those applications. Frequently accessed but infrequently updated data items should get higher preference while caching, and infrequently accessed but frequently updated items should have lower preference. Such items may not be cached at all or should be evicted from the cache to accommodate items with higher preference. In wireless networks, remote data access is typically more expensive than in wired networks. Hence, an efficient caching scheme considers both data access and update patterns can better reduce data transmissions in wireless networks. In this paper, we propose a step-wise optimal update-based replacement policy, called the Update-based Step-wise Optimal (USO) policy, for wireless data networks to optimize transmission cost by increasing effective hit ratio. Our cache replacement policy is based on the idea of giving preference to frequently accessed but infrequently updated data, and is supported by an analytical model with quantitative analysis. We also present results from our extensive simulations. We demonstrate that (1) the analytical model is validated by the simulation results and (2) the proposed scheme outperforms the Least Frequently Used (LFU) scheme in terms of effective hit ratio and communication cost.     

Generalizing the CHOKe flow protection

This paper proposes a simple and stateless active queue management (AQM) scheme, called geometric CHOKe (gCHOKe), to protect responsive flows from unresponsive ones. gCHOKe has its root in and is a generalization of the original CHOKe. It provides an additional power of protection, achieved by introducing an extra flow matching trial following each successful flow comparison of packets. The maximum number of comparisons permitted for an arrival can be controlled by a parameter called maxcomp. The quality of flow protection improves with maxcomp. Compared to the plain CHOKe (which is just the simplest case of gCHOKe), our analysis and simulations show that the scheme can achieve over 20% improvement in the bounds of both bandwidth and buffer space used by an aggressive flow. In addition, up to 14% of the total link capacity can be saved from the unresponsive flow, allowing responsive or rate-adaptive flows to obtain a better share of resources in the router.     

Mobile Underwater Sensor Networks for Protection and Security: Field Experience at the UAN11 Experiment

The EU‐funded project UAN (Underwater Acoustic Network) was aimed at conceiving, developing, and testing at sea an innovative and operational concept for integrating underwater and above‐water sensors in a unique communication system to protect offshore and coastline critical infrastructures. This work gives details on the underwater part of the project. It introduces a set of original security features and gives details on the integration of autonomous underwater vehicles (AUVs) as mobile nodes of the network and as surveillance assets, acoustically controlled by the command and control center to respond against intrusions. Field results are given of the final UAN project sea trial, UAN11, held in May 2011 in Norway. During the experimental activities, a UAN composed of four fixed nodes, two AUVs, and one mobile node mounted on the supporting research vessel was operated continuously and integrated into a global protection system. In this article, the communication performance of the network is reported in terms of round‐trip time, packet loss, and average delivery ratio. The major results of the experiment can be thus summarized: the implemented network structure was successful in continuously operating over five days with nodes seamlessly entering and exiting the network; the performance of the network varied greatly with fluctuations in the acoustic channel; the addition of security features induced a minor degradation in network performance with respect to channel variation; the AUVs were successfully controlled from a remote station through acoustic signals routed by the network. © 2013 Wiley Periodicals, Inc.     

HSV自适应混合高斯模型的运动目标检测

在目前的计算机视觉应用中,从视频序列中提取出运动目标是一个研究热点。针对传统方法在复杂多变环境下不能很好地检测出运动目标且运算量较大的问题,根据HSV颜色空间的特点,提出了一种基于HSV颜色空间的自适应混合高斯背景建模和阴影消除的方法。首先,在传统的混合高斯背景建模的基础上,引入了一种新的混合高斯模型高斯成分个数的自适应选择策略以提高建模的效率。其次,根据阴影在HSV向量空间的特点,融入了一种新的阴影消除方法,以检测出带阴影的运动目标。该方法能够快速准确地建立背景模型,准确分割前景目标。与传统的阴影消除方法相比,该方法可以在不需要设置阂值的情况下,对运动目标的阴影进行很好的消除,有很好的鲁棒性和实用性。     

基于统计特征和马尔可夫特征的图像拼接盲检测

数字图像真实性检测在司法鉴定等领域有着重要的作用.常见的图像拼接篡改会降低图像像素直接的相关性,这可以通过一些统计特征反映出来.采用特征提取-分类的方法,提取矩特征、基于二维相位一致性的统计特征,结合DCT域的马尔可夫特征,利用SVM分类器进行分类,实现了拼接图像的盲检测.实验结果表明,该方法有较好的鉴别准确率,可达91.75%.     

基于PLC的立体仓储控制系统及组态监控设计

本文主要介绍运用PLC技术设计开发的立体仓库。系统采用松下FP0系列PLC,结合组态王软件的远程监控,实现了计算机的实时控制,提高了系统运行的效率及安全可靠性。     

基于OGRE的煤矿安全虚拟现实3D软件设计与实现

随着煤矿安全的数字化管理,基于3D技术的煤矿系统虚拟现实成为煤矿安全中进行安全培训的重要技术手段。本文以OGRE引擎为软件开发环境设计煤矿安全虚拟现实3D软件,阐述OGRE的软件结构、煤矿安全虚拟现实3D软件的构成、3D模型的建模方法和实现方式,设计具有运动功能的3D模型的操作和控制方法。对煤矿安全管理和数字化煤矿的建设具有现实意义。