Performance analysis of hierarchical group key management integrated with adaptive intrusion detection in mobile ad hoc networks

We develop a mathematical model to quantitatively analyze a scalable region-based hierarchical group key management protocol integrated with intrusion detection to deal with both outsider and insider security attacks for group communication systems (GCSs) in mobile ad hoc networks (MANETs). Our proposed adaptive intrusion detection technique is based on majority voting by nodes in a geographical region to cope with collusion of compromised nodes, with each node preloaded with anomaly-based or misuse-based intrusion detection techniques to diagnose compromised nodes in the same region. When given a set of parameter values characterizing operational and environmental conditions, we identify the optimal intrusion detection rate and the optimal regional area size under which the mean time to security failure of the system is maximized and/or the total communication cost is minimized for GCSs in MANET environments. The tradeoff analysis in performance versus security is useful in identifying and dynamically applying optimal settings to maximize the system lifetime for scalable mobile group applications while satisfying application-specific performance requirements.     

Ad Hoc网络中一种组密钥协商协议

移动Ad Hoc网络是一种新型的移动多跳无线网络。在网络中构建组密钥协商协议时应尽量减少节点的资源开销。该文提出一种新的多层组密钥协商协议,MTKA-ECC协议。该协议在多层组模型结构上,采用椭圆曲线密码体制实施密钥协商和分配,使得节点在密钥协商过程中具有低计算开销与低通信开销的优势。与GDH, TGDH组密钥协商协议相比,该协议有效地降低了节点在密钥协商过程中的计算和通信开销,适用于移动Ad Hoc网络。     

Bi-objective mixed-integer nonlinear programming for multi-commodity tri-echelon supply chain networks

The competitive market and declined economy have increased the relevant importance of making supply chain network efficient. Up to now, this has resulted in great motivations to reduce the cost of services, and simultaneously, to improve their quality. A mere network model, as a tri-echelon, consists of Suppliers, Warehouses or Distribution Centers (DCs), and Retailer nodes. To bring it closer to reality, the majority of parameters in this network involve retailer demands, lead-time, warehouses holding and shipment costs, and also suppliers procuring and stocking costs which are all assumed to be stochastic. The aim is to determine the optimum service level so that total cost is minimized. Obtaining such conditions requires determining which supplier nodes, and which DC nodes in network should be active to satisfy the retailers’ needs, an issue which is a network optimization problem per se. The proposed supply chain network for this paper is formulated as a mixed-integer nonlinear programming, and to solve this complicated problem, since the literature for the related benchmark is poor, three numbers of genetic algorithm called Non-dominated Sorting Genetic Algorithm (NSGA-II), Non-dominated Ranking Genetic Algorithm (NRGA), and Pareto Envelope-based Selection Algorithm (PESA-II) are applied and compared to validate the obtained results. The Taguchi method is also utilized for calibrating and controlling the parameters of the applied triple algorithms.     

Path planning in GPS-denied environments via collective intelligence of distributed sensor networks

This paper proposes a framework for reactive goal-directed navigation without global positioning facilities in unknown dynamic environments. A mobile sensor network is used for localising regions of interest for path planning of an autonomous mobile robot. The underlying theory is an extension of a generalised gossip algorithm that has been recently developed in a language-measure-theoretic setting. The algorithm has been used to propagate local decisions of target detection over a mobile sensor network and thus, it generates a belief map for the detected target over the network. In this setting, an autonomous mobile robot may communicate only with a few mobile sensing nodes in its own neighbourhood and localise itself relative to the communicating nodes with bounded uncertainties. The robot makes use of the knowledge based on the belief of the mobile sensors to generate a sequence of way-points, leading to a possible goal. The estimated way-points are used by a sampling-based motion planning algorithm to generate feasible trajectories for the robot. The proposed concept has been validated by numerical simulation on a mobile sensor network test-bed and a Dubin’s car-like robot.     

Physical Path Planning Using a Pervasive Embedded Network

We evaluate a technique that uses an embedded network deployed pervasively throughout an environment to aid robots in navigation. The embedded nodes do not know their absolute or relative positions and the mobile robots do not perform localization or mapping. Yet, the mobile robot is able to navigate through complex environments effectively. First, we present an algorithm for physical path planning and its implementation on the Gnats, a novel embedded network platform. Next, we investigate the quality of the computed paths. We present quantitative results collected from a real-world embedded network of 60 nodes. Experimentally, we find that, on average, the path computed by the network is only 24% longer than the optimal path. Finally, we show that the paths computed by the network are useful for a simple mobile robot. Results from a network of 156 nodes in a static environment and a network of 60 nodes in a dynamic environment are presented.     

Intra domain route optimization for ubiquitous network

The main advantage of a wireless network is user mobility, which calls for efficient routing support at the network layer. An architecture combines hierarchical mobile IPv6 and network mobility for a network mobile and mobile nodes move in tandem and make a hierarchy in the wireless network to management of micro-mobility and seamless handoff. But the capability of the architecture for intra domain route optimization is impaired. So we propose functionality in domain nodes to enable intra domain path optimization for ubiquitous network. It is shown that intra domain cost effect is beneficial in every hierarchical domain that spans mesh network topology. We address the key function for our proposed scheme and analyze the usefulness of our proposed method using mathematically. We show that our proposed scheme performs much better than Network Mobility protocol, especially when the number of mobile nodes or mobile routers or correspondent nodes increases in hierarchically nested in ubiquitous networks.     

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 artificial immune system approach with secondary response for misbehavior detection in mobile ad hoc networks

In mobile ad hoc networks, nodes act both as terminals and information relays, and they participate in a common routing protocol, such as dynamic source routing (DSR). The network is vulnerable to routing misbehavior, due to faulty or malicious nodes. Misbehavior detection systems aim at removing this vulnerability. In this paper, we investigate the use of an artificial immune system (AIS) to detect node misbehavior in a mobile ad hoc network using DSR. The system is inspired by the natural immune system (IS) of vertebrates. Our goal is to build a system that, like its natural counterpart, automatically learns, and detects new misbehavior. We describe our solution for the classification task of the AIS; it employs negative selection and clonal selection, the algorithms for learning and adaptation used by the natural IS. We define how we map the natural IS concepts such as self, antigen, and antibody to a mobile ad hoc network and give the resulting algorithm for classifying nodes as misbehaving. We implemented the system in the network simulator Glomosim; we present detection results and discuss how the system parameters affect the performance of primary and secondary response. Further steps will extend the design by using an analogy to the innate system, danger signal, and memory cells.     

A cost matrix agent for shortest path routing in ad hoc networks

Wireless ad hoc networks do not rely on an existing infrastructure. They are organized as a network with nodes that act as hosts and routers to treat packets. With their frequent changes in topology, ad hoc networks do not rely on the same routing methods as for pre-established wired networks; they require routing methods for mobile wireless networks. To select a path from a source to a destination in dynamic ad hoc networks, an efficient and reliable routing method is very important. In this paper, we introduce a cost-matrix-based routing algorithm. An agent node creates topology information in the form of the adjacency-cost matrix which shows link costs of the network.Based on the adjacency-cost matrix, the minimum-cost matrix and the next-node matrices can be calculated. Based on the minimum-cost matrix and the next-node matrices, the minimum cost between source and destination nodes and between intermediate nodes on the minimum-cost paths can be calculated.The matrices are periodically distributed by the agent to the other nodes. Based on the minimum-cost matrix and the next-node matrices, each node decides the minimum-cost path to its destination. Because none of the nodes except the agent needs to gather network topology information, the control overhead of the proposed method is small compared with those of the general table-driven routing protocols.     

基于虚拟力的混合感知网节点部署

感知网一般是由静态的或移动的节点组成,为保证感知网的感知功能,节点应该有自部署和自修复能力.然而全部由移动传感器组成的感知网的成本太高,为保证感知网的覆盖功能和低成本,提出了一种在静态传感器节点中加入移动传感器节点的混合感知网形式.为了更好地部署这些节点,最大化覆盖待感知区域,提出了一种基于节点间虚拟力的移动节点部署方法,利用静态节点和移动节点以及移动节点之间的虚拟人工势场产生的作用力来控制移动节点的运动,使移动节点能够在较短的时间内,以较少的能量消耗到达自己合适的位置.在理论上分析了算法的可行性,用仿真实验验证了此算法的有效性,并和其他3种类似算法进行了性能比较.     

基于口令应答的协作式WSNs移动复制节点检测方法研究

目前,针对无线传感器网络复制节点攻击研究主要集中在对静态网络中复制节点的检测。WSNs的应用中,节点部署在一定区域形成静态网络并采集信息,为了减少节点间通信量、降低能耗,若干个节点形成一个簇,簇内选举簇头节点作为簇间通信人。静态网络采集的信息通常由汇聚节点回收,为了方便,汇聚节点通常采用移动形式加入网络,收集完后离开。如果这类在移动中收集信息的节点是复制节点,对整个WSNs的威胁比静态网络中的复制节点威胁更大。在借鉴已有的移动网络检测方案的基础上,针对静态网络分簇和移动节点位置经常变换的特点,提出了基于口令应答的协作式WSN移动复制节点检测方法CRCDS（Challenge/Response and Collaborative Detection Scheme）,有效利用静态网络的存储空间,采取静态网络和移动节点相互协作的方式,规避因移动节点位置变化对检测结果的影响,并从理论和实验上分析了该检测方法的安全性和可行性。     

Environment Analysis as a Basis for Designing Multimodal and Multidevice User Interfaces

In this article, we present a practical approach to analyzing mobile usage environments. We propose a framework for analyzing the restrictions that characteristics of different environments pose on the user's capabilities. These restrictions along with current user interfaces form the cost of interaction in a certain environment. Our framework aims to illustrate that cost and what causes it. The framework presents a way to map features of the environment to the effects they cause on the resources of the user and in some cases on the mobile device. This information can be used for guiding the design of adaptive and/or multimodal user interfaces or devices optimized for certain usage environments. An example of using the framework is presented along with some major findings and three examples of applying them in user interface design.     

大规模Ad hoc网络中一种高效的组密钥协商协议*

移动Ad hoc网络自身的特点决定了该网络中节点资源的有限性,所以在移动Ad hoc网络中构建组密钥协商协议时,应尽量减少节点的资源开销。为了解决这个问题,提出了一种基于分簇-K叉树组模型结构的组密钥协商协议——CKT-ECC协议。该协议在分簇-K叉树组模型结构上,采用椭圆曲线密码体制实施密钥协商和分配,使得节点在密钥协商过程中具有低计算开销和低通信开销的优势。与GDH、TGDH组密钥协商协议相比,本协议有效地降低了节点在密钥协商过程中的计算开销和通信开销,适用于大规模移动Ad hoc网络。     

无线传感器网络移动Agent的应用

节点计算模式对网络性能影响很大。移动Agent计算模式在下一代网络中具有广阔应用前景。该文分析了移动Agent在无线传感器网络中的应用背景。从网络和节点两个层面提出一种基于移动Agent的传感器网络框架模型,阐述了模型组成、功能定义和交互接口等。给出一种基于定向扩散的移动Agent机制实现方法,并对其特点进行了分析和讨论。     

Performance Monitoring of Remote Websites Using Mobile Agents

In this paper, a mobile agent based approach is investigated to provide the underlying framework for monitoring the performance tests at a remote website. Mobile agents are autonomous and dynamic entities that can migrate between various nodes in the network. They offer many advantages over traditional design methodologies, including: reduction in network load, overcoming network latency and disconnected operations. This research aims to explore the adaptability of the mobile agent approach for website performance testing. It analyses the applicability of mobile agents in carrying out a monitoring task. We have designed and implemented the monitoring framework. The performance of mobile agents is compared with the non-agent approach. Analyzing the results for the same purpose and environments, the mobile agent approach performs better in reducing the load on the host server and saving communication bandwidth than the traditional approaches.     

基于方向决策的移动锚节点动态路径规划方法

在基于移动锚节点的无线传感器网络定位过程中,移动锚节点的路径规划问题对定位性能有着重要的影响,但现有的路径规划方法没有充分考虑到网络内未知节点的密度以及分布情况,定位效率低且成本大,因此提出了一种基于方向决策的移动锚节点动态路径规划方法CWDP(Dynamic Path Planning Based on Orientation Decision-Classed Weighted).首先网络内的未知节点根据连通度阈值对自身进行分级处理,当移动锚节点进入网络区域后,根据通信范围内未知节点的反馈信息,再利用分级权重系数实时决策下一目标的移动方向.仿真结果表明,该方法有效地提高了网络内未知节点的定位覆盖率和降低了定位误差,并节约了定位成本.     

Real-time communications over wired/wireless PROFIBUS networks supporting inter-cell mobility

PROFIBUS is an international standard (IEC 61158, EN 50170) for factory-floor communications, with several thousands of installations worldwide. Taking into account the increasing need for mobile devices in industrial environments, one obvious solution is to extend traditional wired PROFIBUS networks with wireless capabilities. In this paper, we outline the major aspects of a hybrid wired/wireless PROFIBUS-based architecture, where most of the design options were made in order to guarantee the real-time behaviour of the overall network. We also introduce the timing unpredictability problems resulting from the co-existence of heterogeneous physical media in the same network. However, the major focus of this paper is on how to guarantee real-time communications in such a hybrid network, where nodes (and whole segments) can move between different radio cells (inter-cell mobility). Assuming a simple mobility management mechanism based on mobile nodes performing periodic radio channel assessment and switching, we propose a methodology to compute values for specific parameters that enable an optimal (minimum) and bounded duration of the handoff procedure.     

Efficient distributed low-cost backbone formation for wireless networks

Backbone has been used extensively in various aspects (e.g., routing, route maintenance, broadcast, scheduling) for wireless ad hoc or sensor networks recently. Previous methods are mostly designed to minimize the size of the backbone. However, in many applications, it is desirable to construct a backbone with small cost when each wireless node has a cost of being in the backbone. In this paper, we first show that previous methods specifically designed to minimize the backbone size may produce a backbone with large cost. Then, an efficient distributed method to construct a weighted backbone with low cost is proposed. We prove that the total cost of the constructed backbone is within a small constant factor of the optimum for homogeneous networks when either the nodes' costs are smooth (i.e., the maximum ratio of costs of adjacent nodes is bounded) or the network maximum node degree is bounded. We also show that, with a small modification, the backbone is efficient for unicast: the total cost (or hop) of the least cost (or hop) path connecting any two nodes using backbone is no more than three (or four) times the least cost (or hop) path in the original communication graph. Our theoretical. results are corroborated by our simulation studies. Finally, we discuss several possible ad hoc network applications of our proposed backbone formation algorithms.     

Similarity search in sensor networks using semantic-based caching

Sensor networks build temporary wireless connections in environments where the stationary infrastructures are either destroyed or too expensive to construct. Most of the previous research in sensor networks focuses on routing protocols that adapt to the dynamic network topologies, and not much work has been done on data accessing. One important data accessing application is similarity search, which provides the foundation of content-based retrieval. Many traditional similarity search algorithms are based on centralized or flooding mechanisms, which are not effective in wireless sensor network environments due to the multiple limitations such as bandwidth and power. In this paper we tackle the problem of similarity search by using semantic-based caching to reflect the data content distribution in the network. The basic idea is analyzing the cached results of earlier queries and trying to resolve the later queries within a small collection of content-related mobile nodes. Based on a Hilbert space-filling curve, the data points in a multi-dimensional semantic space are described as a linear representation. These data points are further cached to facilitate query processing. Through extensive simulations, we show that our method can perform similarity search with improved performance in terms of search cost and response time.