基于移动设备手写签名认证系统的设计与实现

由于移动设备具有通过外部的无线网络访问数据、体积小容易丢失等特征，给操作带来方便的同时．也给后台数据库带来很大的安全隐患。文章针对基于移动设备的无线网络应用系统，在Windows2000和Windows Mobile2003操作平台上．利用Microsoft的Visual Studio．Net2003和．NET Compact Framework开发环境，设计和实现了基于移动设备手写签名认证系统。实验结果表明：在少量样本数据情况下，对于非专业模仿签名的错误接受率FAR为3．65％．而错误拒绝率FRR为2．9％。该系统增强移动设备访问数据的安全性，提高操作员认证的效率．具有很强的舅用性。     

Performance analysis of an improved soft preemptive scheme for unevenly distributed traffic in optical wavelength-division multiplexing networks

In optical wavelength-division multiplexing (WDM) networks, traffic can be unevenly distributed across the network causing inefficient utilization of resources. To solve this problem, an improved soft preemptive (SP) scheme is proposed by considering dynamic resource distribution to deal with the uneven network utilization. A novel unevenly distributed traffic model in cross-time-zone networks is also presented to evaluate the efficiency of the new scheme. Compared with other schemes such as normal shortest path first (SPF) routing and wavelength conversion (WC), the new proposed scheme results demonstrate significantly better performance with respect to the network utilization and overall network blocking probability.

基于生成树的无线传感器网络分布式路由协议

在无线传感器网络中,节点具有有限的电池能量,为了延长网络的生存时间,提出了一种基于生成树的分布式路由协议STRP及其具有能量意识的改进版本STRP-PA.每个传感器节点根据相邻节点与基站的距离、剩余能量等信息寻找父节点,构造一棵以基站为根的近优最小生成树,节点采集的数据沿树传输,并在树杈节点进行聚合.仿真实验结果表明:STRP-PA协议能够节省网络能量,显著延长网络稳定工作的时间,性能明显好于LEACH协议.     

High throughput route selection in multi-rate wireless mesh networks

Most existing Ad-hoc routing protocols use the shortest path algorithm with a hop count metric to select paths. It is appropriate in single-rate wireless networks, but has a tendency to select paths containing long-distance links that have low data rates and reduced reliability in multi-rate networks. This article introduces a high throughput routing algorithm utilizing the multi-rate capability and some mesh characteristics in wireless fidelity （WiFi） mesh networks. It uses the medium access control （MAC） transmission time as the routing metric, which is estimated by the information passed up from the physical layer. When the proposed algorithm is adopted, the Ad-hoc on-demand distance vector （AODV） routing can be improved as high throughput AODV （HT-AODV）. Simulation results show that HT-AODV is capable of establishing a route that has high data-rate, short end-to-end delay and great network throughput.     

A comparative study of name resolution and routing mechanisms in information-centric networks

Information-Centric Networking (ICN) is an innovative paradigm for the future internet architecture, which addresses IP network limitations in supporting content distribution and information access by decoupling content from hosts and providing the ability to retrieve a content object by its name (identifier), rather than its storage location (IP address). Name resolution and routing is critical for content retrieval in ICN networks. In this research, we perform a comparative study of two widely used classes of ICN name resolution and routing schemes, namely flooding and Distributed Hash Table (DHT). We consider the flooding-based routing in Content-Centric Networks due to its wide acceptance. For the DHT scheme, we design a multi-level DHT that takes into account the underlying network topology and uses name aggregation to further reduce control overhead and improve network efficiency. Then, we compare the characteristics and performance of these two classes of name resolution and routing through extensive simulations. The evaluation results show that the performances of these two approaches are reliant on several factors, including network size, content location dynamics, and content popularity. Our study reveals insights into the design tradeoffs and offers guidelines for design strategies.     

A novel energy‐aware routing mechanism for SDN‐enabled WSAN

Energy consumption is one of the most important design constraints when building a wireless sensor and actuator network since each device in the network has a limited battery capacity, and prolonging the lifetime of the network depends on saving energy. Overcoming this challenge requires a smart and reconfigurable network energy management strategy. The Software‐Defined Networking (SDN) paradigm aims at building a flexible and dynamic network structure, especially in wireless sensor networks. In this study, we propose an SDN‐enabled wireless sensor and actuator network architecture that has a new routing discovery mechanism. To build a flexible and energy‐efficient network structure, a new routing decision approach that uses a fuzzy‐based Dijkstra's algorithm is developed in the study. The proposed architecture can change the existing path during data transmission, which is the key property of our model and is achieved through the adoption of the SDN approach. All the components and algorithms of the proposed system are modeled and simulated using the Riverbed Modeler software for more realistic performance evaluation. The results indicate that the proposed SDN‐enabled structure with fuzzy‐based Dijkstra's algorithm outperforms the one using the regular Dijkstra's and the ZigBee‐based counterpart, in terms of the energy consumption ratio, and the proposed architecture can provide an effective cluster routing while prolonging the network lifetime.     

Nature‐inspired meta‐heuristic algorithms for solving the load balancing problem in the software‐defined network

The growth of the networks has difficult network management. Recently, a concept called software‐defined network (SDN) has been proposed to address this issue, which makes network management more adaptable. Control and forwarding planes are separated in SDN. The control plane is a centralized logical controller that controls the network. The forwarding plane that consists of transfer devices is responsible for transmitting packets. Because the network resources are limited, optimizing the use of resources in the networks is an important issue. Load balancing improves the balanced distribution of loads across multiple resources in order to maximize the reliability and network resources efficiency. SDN controllers can create an optimal load balancing compared to traditional networks because they have a network global view. The load‐balancing problem can be solved using many different nature‐inspired meta‐heuristic techniques because it has the NP‐complete nature. Hence, for solving load balancing problem in SDN, nature‐inspired meta‐heuristic techniques are important methods. However, to the best of our knowledge, there is not a survey or systematic review on studying these matters. Accordingly, in the area of the load balancing in the SDN, this paper reviews systematically the nature‐inspired meta‐heuristic techniques. Also, this study demonstrates advantages and disadvantages regarded of the chosen nature‐inspired meta‐heuristic techniques and considers their algorithms metrics. Moreover, to apply better load balancing techniques in the future, the important challenges of these techniques have been investigated.     

An efficient weighted trust‐based malicious node detection scheme for wireless sensor networks

The aim of wireless sensor networks (WSNs) is to gather sensor data from a monitored environment. However, the collected or reported information might be falsified by faults or malicious nodes. Hence, identifying malicious nodes in an effective and timely manner is essential for the network to function properly and reliably. Maliciously behaving nodes are usually detected and isolated by reputation and trust‐based schemes before they can damage the network. In this paper, we propose an efficient weighted trust‐based malicious node detection (WT‐MND) scheme that can detect malicious nodes in a clustered WSN. The node behaviors are realistically treated by accounting for false‐positive and false‐negative instances. The simulation results confirm the timely identification and isolation of maliciously behaving nodes by the WT‐MND scheme. The effectiveness of the proposed scheme is afforded by the adaptive trust‐update process, which implicitly performs trust recovery of temporarily malfunctioning nodes and computes a different trust‐update factor for each node depending on its behavior. The proposed scheme is more effective and scalable than the related schemes in the literature, as evidenced by its higher detection ratio (DR) and lower misdetection ratio (MDR), which only slightly vary with the network's size. Moreover, the scheme sustains its efficient characteristics without significant power consumption overheads.     

A low complexity mechanism for congestion notification in rural IPSec‐enabled heterogeneous backhaul networks

Management in wireless backhaul networks is a challenging task, especially in rural and isolated environments. In these scenarios, the backhaul network usually consists of a set of heterogeneous wireless links that provide limited and variable bandwidth to the access networks, often 3G/4G small cells. Because of the highly constrained nature of this type of backhaul network, intelligent and joint management in both the backhaul network and the access network is crucial in order to avoid performance degradation caused by traffic congestion. In order to avoid the saturation in the backhaul network, access networks should consider the backhaul state when taking decisions in the admission control and scheduling procedures. However, no standardized mechanisms currently exist for sharing management information between both networks. In this work, we propose to use the Explicit Congestion Notification (ECN) bit in the outer IP headers present in the Iuh 3GPP IPSec‐enabled interfaces in order to notify the backhaul congestion state to the access network. We analyze for the referred scenario, compatibility and security details, validating our approach by running numerically simulations and implementing the notification mechanism. Our low complexity approach offers 2% accuracy and backhaul update latency lower than 10 ms during 80% of the time, which makes the solution appropriate for admission control and scheduling intervals in small cells.     

Fault diagnosis in wireless sensor network using clonal selection principle and probabilistic neural network approach

The fault diagnosis in wireless sensor networks is one of the most important topics in the recent years of research work. The problem of fault diagnosis in wireless sensor network can be resembled with artificial immune system in many different ways. In this paper, a detection algorithm has been proposed to identify faulty sensor nodes using clonal selection principle of artificial immune system, and then the faults are classified into permanent, intermittent, and transient fault using the probabilistic neural network approach. After the actual fault status is detected, the faulty nodes are isolated in the isolation phase. The performance metrics such as detection accuracy, false alarm rate, false‐positive rate, fault classification accuracy, false classification rate, diagnosis latency, and energy consumption are used to evaluate the performance of the proposed algorithm. The simulation results show that the proposed algorithm gives superior results as compared with existing algorithms in terms of the performance metrics. The fault classification performance is measured by fault classification accuracy and false classification rate. It has also seen that the proposed algorithm provides less diagnosis latency and consumes less energy than that of the existing algorithms proposed by Mohapatra et al, Panda et al, and Elhadef et al for wireless sensor network.