基于缓存管理的网络编码中继传输方案

针对中继协作无线网络中节点缓存空间有限以及传输和缓存数据包都存在开销等问题进行了研究,提出了一种基于缓存管理的网络编码中继传输方案。在传输过程中该方案以最小化系统开销为目标,考虑多流综合优化问题,利用马尔可夫链对缓存队列进行建模分析。结合编码流速率增加编码机会,获得中继处不同流的缓存阈值,更合理地实现了编码决策。分析与仿真结果表明该方案能有效权衡编码机会和开销,相比其他方案能有效降低时延且提高网络吞吐量。     

SDN中基于时延优化的多控制器部署方案

针对SDN在广域网中部署时,单一集中式的控制器无法满足整个网络性能需求这一问题,提出一种多控制器部署方案。评估给定网络拓扑所需部署的控制器个数,使用聚类方法将控制器初步部署到网络中,向网络中输入动态数据流,根据蜂群算法思想,以最小化流表建立时间和控制器之间的同步时延开销为目标进一步优化控制器的部署。仿真结果表明,该方案在优化流表建立时间的同时,能够获得较小的控制器间同步时延开销。     

基于网格部署模型的WSN密钥分配方案

针对现有密钥预分配方案中网络连通性差、存储开销大、节点抗攻击能力不强等问题,提出一种基于网格部署模型的无线传感器网络密钥分配方案。该方案将部署区域划分为相互不重叠的六边形网格,为每个网格分配多个不同的密钥空间,且使任意相邻的网格之间仅共享一个密钥空间。根据节点的部署信息和已知的区域信息为其分配密钥信息,从存储开销、网络连通性和安全性方面对方案进行性能分析。实验结果表明,与已有密钥分配方案相比,该方案的网络连通率为1,不仅能降低节点内存需求,而且增强了无线传感器网络中节点抗随机攻击和区域攻击的能力。     

基于元胞自动机的无线传感器网络抗毁性分析

因能耗敏感与有效连通性特征等所造成的网络抗毁性能低下是制约无线传感器网络规模应用的主要技术瓶颈之一。针对该问题,利用二维元胞自动机考虑能耗失效、连通性失效等五种失效情形,建立无线传感器网络拓扑演化规则,并基于随机性失效策略与选择性失效策略对网络抗毁性能展开分析。研究表明,网络面临随机失效时抗毁性能明显优于选择性失效。通过失效节点构成分析,在随机失效策略下,能耗失效为造成网络失败主因,而在选择性失效策略下,连通性失效对性能影响更为显著。基于所得结论,为进一步研究网络抗毁性能提升方法提供有益借鉴。     

权重感知的三维室内无线传感器网络部署算法

已有室内受限空间无线传感器网络部署问题的研究均未综合考虑各种部署应用需求以及障碍物对无线传感器信号的干扰,导致传感器感知与通信能力的浪费。为解决上述问题,提出了一种基于启发式算法的无线传感器网络部署算法,该算法利用贪心策略在有障碍的三维室内环境中进行部署,并在此基础上设计了权重感知的遗传算法优化策略用以求解全局最优部署方案。部署算法利用分权的方式描述不同空间区域的重要性,利用带方差的对数正态阴影模型建模信号衰减过程,在获得最大覆盖效果的同时最小化部署开销,并保证空间k覆盖和网络连通性。实验结果表明,障碍物对无线传感器节点造成一定影响时,提出的WCRH算法与OWCRG算法的性能均优于使用传统Lineof-Sight(LoS)模型的基于面积开销比的启发式算法。     

基于重叠区域的无线传感反应网络连接性恢复机制

针对无线传感反应网络(WSAN)中反应节点的失效导致的网络连接性被破坏问题,提出了一种新的网络连接性恢复机制。反应节点首先根据2跳网络拓扑信息来确定是否为局部关键节点,然后利用反应节点间存在的管理区域的重叠性来计算新的移动位置,最后采用局部级联重定位方式来实现连接性的恢复。通过NS2仿真结果表明,该机制能够正确恢复网络的连接性并实现较小的恢复开销。     

面向级联失效的加权网络负载容量非线性模型鲁棒性优化

在考虑网络负载容量关系的情况下,研究加权网络中的级联失效现象。提出了负载容量非线性模型,并针对模型参数的多目标优化问题,通过理论分析确定其影响因素。以级联失效前后网络连通性测度的比值作为鲁棒性测度,以网络容量与负载的比值平均数作为网络成本测度,采用基于拥挤距离排序的多目标粒子群优化算法(MOPSO-CD)对参数进行优化。最后通过在模拟网络和实际网络中进行的仿真比较,验证了优化后的负载容量非线性模型可以在有限的网络成本下更好地提高网络对级联失效的抵御能力。     

基于代数连通性的复杂网络社区发现研究

网络的代数连通性是拉普拉斯矩阵的第二小特征值,它可以用于测量网络的连通程度。为改善复杂网络分割算法的时间复杂度,基于代数连通性提出一种谱优化模型,并将其应用于复杂网络的小社区发现中。通过最小化网络连通性函数在候选边集中选择要删除的边集。该凸优化问题可由半正定规划解决,但其时间复杂度高,所以只能处理规模适中的复杂网络。为解决这个模型优化问题,采用贪婪策略优化方法,使该算法可以应用于大规模复杂网络。另一方面,社区边界的边影响代数连通性函数的优化效果,根据费德勒向量为每条边设定权重来解决这一问题。最后应用该模型对模拟复杂网络和真实复杂网络实例进行验证,结果表明该模型有效降低了GN算法的迭代次数,从而降低其时间复杂度,并有效保持其分割效果。     

基于模糊身份密码学的机会网络身份认证方案

针对机会网络的自组织性、开放性、连通性差等特点以及现有的基于上下文的路由协议中可能存在的隐私泄露等安全问题,提出了一种基于模糊身份密码学的身份认证方案F-ONIAS(Identity Authentication Scheme in Opportunistic Network Based on Fuzzy-IBE)。该方案通过一个无需实时在线的PKG为用户颁发私钥来解决机会网络中因节点无法实时连通而导致的传统非对称密码学方案不适用的问题。同时,将节点的生物信息作为身份标识,避免了传统身份密码学中身份信息可能被伪造而带来的安全隐患。仿真实验表明,在存在恶意节点的网络环境下,本方案比现有的经典路由协议方案拥有更高的报文投递率和更低的路由开销率,并且未对报文平均时延造成明显影响。     

蓝牙无线个人局域网的拓扑优化

本文提出了一种蓝牙无线个人局域网（BT-WPAN）的拓扑优化方法。该方法是基于BT-WPAN技术的一个约束模型。通过使用min-max公式表示,它提供全网的连通性;通过最小化网络中最拥挤的节点的通信量负载,实现通信量的需求和系统规范约束。由于问题的复杂性,优化方案限于集中方式,但提供了一个与分布式试探法相对应的有益的方法。     

Movement-Assisted Connectivity Restoration in Wireless Sensor and Actor Networks

Recent years have witnessed a growing interest in applications of wireless sensor and actor networks (WSANs). In these applications, a set of mobile actor nodes are deployed in addition to sensors in order to collect sensors' data and perform specific tasks in response to detected events/objects. In most scenarios, actors have to respond collectively, which requires interactor coordination. Therefore, maintaining a connected interactor network is critical to the effectiveness of WSANs. However, WSANs often operate unattended in harsh environments where actors can easily fail or get damaged. An actor failure may lead to partitioning the interactor network and thus hinder the fulfillment of the application requirements. In this paper, we present DARA, a Distributed Actor Recovery Algorithm, which opts to efficiently restore the connectivity of the interactor network that has been affected by the failure of an actor. Two variants of the algorithm are developed to address 1- and 2-connectivity requirements. The idea is to identify the least set of actors that should be repositioned in order to reestablish a particular level of connectivity. DARA strives to localize the scope of the recovery process and minimize the movement overhead imposed on the involved actors. The effectiveness of DARA is validated through simulation experiments.     

Localized motion-based connectivity restoration algorithms for wireless sensor and actor networks

In wireless sensor and actor networks maintaining inter-actor connectivity is very important in mission-critical applications where actors have to quickly plan optimal coordinated response to detected events. Failure of one or multiple actors may partition the inter-actor network into disjoint segments, and thus hinders the network operation. Autonomous detection and rapid recovery procedures are highly desirable in such a case. This paper presents DCR, a novel distributed partitioning detection and connectivity restoration algorithm to tolerate the failure of actors. DCR proactively identifies actors that are critical to the network connectivity based on local topological information, and designates appropriate, preferably non-critical, backup nodes. Upon failure detection, the backup actor initiates a recovery process that may involve coordinated relocation of multiple actors. We also present an extended version of DCR, named RAM, to handle one possible case of a multi-actor failure. The proposed algorithms strive to avoid procrastination, localize the scope of recovery and minimize the movement overhead. Simulation results validate the performance of the proposed algorithms.     

Maximizing connected coverage via controlled actor relocation in wireless sensor and actor networks

Wireless sensor and actor networks (WSANs) have recently emerged with the idea of combining wireless sensor networks (WSNs) and mobile ad hoc networks (MANETs). In addition to resource constrained sensors, resource rich and mobile actor nodes are employed in WSANs. These actors can collect data from the sensors and perform appropriate actions as a result of processing such data. To perform the actions at all parts of the region in a timely manner, the actors should be deployed in such a way that they might be able to communicate with each other and cover the whole monitored area. This requires that the actors should be placed carefully prior to network operation in order to maximize the coverage and maintain the inter-actor connectivity. In this paper, we propose a distributed actor deployment algorithm that strives to maximize the coverage of actors without violating the connectivity requirement. The approach applies repelling forces between neighboring actors and from the sensors that sit on the boundaries in order to spread them in the region. The spreading of the nodes is done using a tree of actors which can provide more freedom for the movement of the nodes but at the same time maintain the required connectivity among the nodes. We present two techniques for creation of such an actor tree which are based on local pruning of the actor links and spanning tree of the inter-actor network. The performance of our approach is validated both analytically and experimentally.     

无线感知执行网的智能协作机制研究

针对无线感知执行网中的节点协作问题,提出了多目标智能协作策略。在感知节点不完全连通的WSANs中,设计局部感知节点成簇算法,实现感知节点间的通信协作;以网络能耗均衡和信息传输时延为目标,应用离散多目标自由搜索算法对WSANs进行实时路径规划,实现簇头节点和执行节点间的协作,并通过路径惩罚策略和路径均衡策略,保证寻优结果的有效性、均衡执行节点之间的能耗。仿真实验表明:无线感知执行网智能协作机制能有效地选择多执行节点路径,实现网络协作的实时需求与能量消耗之间的平衡。     

无线传感器/执行器网络中能量有效的实时分簇路由协议

无线传感器/执行器网络(WSANs)主要应用于自动控制领域,实时性问题是其面临的首要挑战.根据实际环境中的节点部署情况,建立了系统模型;研究了分簇策略与功率控制技术对于自组织网络实时性的影响,提出了一种可适用于WSANs的能量有效的实时分簇路由协议--RECRP协议.该协议采用二级成簇策略使网络中的各类节点稳定分簇.分簇后的各类节点具有不同发射功率,利用执行器节点的强大通信能力有效降低网络延时.采用能量有效性算法使网络中的传感器节点轮换担任簇首,从而使网络能量均匀消耗,延长网络的生存时间.实验结果证明,在WSANs中RECRP协议可使网络稳定分簇,并且在网络的实时性与能量有效性方面与现有典型路由协议相比具有更优越的性能.     

Clustering of wireless sensor and actor networks based on sensor distribution and connectivity

Wireless Sensor and Actor Networks (WSANs) employ significantly more capable actor nodes that can collect data from sensors and perform application specific actions. To take these actions collaboratively at any spot in the monitored regions, maximal actor coverage along with inter-actor connectivity is desirable. In this paper, we propose a distributed actor positioning and clustering algorithm which employs actors as cluster-heads and places them in such a way that the coverage of actors is maximized and the data gathering and acting times are minimized. Such placement of actors is done by determining the k-hop Independent Dominating Set (IDS) of the underlying sensor network. Basically, before the actors are placed, the sensors pick the cluster-heads based on IDS. The actors are then placed at the locations of such cluster-heads. We further derive conditions to guarantee inter-actor connectivity after the clustering is performed. If inter-connectivity does not exist, the actors coordinate through the underlying sensors in their clusters to adjust their locations so that connectivity can be established. The performances of the proposed approaches are validated through simulations.     

TSLBS: A Time-Sensitive and Load Balanced Scheduling Approach to Wireless Sensor Actor Networks

Existing works on scheduling in Wireless Sensor Actor Networks (WSANs) are mostly concerned with energy savings and ignore time constraints and thus increase the make-span of the network. Moreover, these algorithms usually do not consider balance of workloads on the actor nodes and hence, sometimes some of the actors are busy when some others are idle. These problem causes the actors are not utilized properly and the actors’ lifetime is reduced. In this paper we take both time awareness and balance of workloads on the actor in WSANs into account and propose a convex optimization model (TAMMs) to minimize make-span. We also propose a protocol called LIBP to improve load balancing that allocates tasks to actors according to their measured capabilities in such a way to enhance balances of workloads on the actors. Finally, by combination of TAMMs and LIBP, a time-sensitive and load balanced scheduling approach (TSLBS) is proposed. TSLBS considers both local and global tasks and the distribution requirements of WSANs (i.e. WSANs with hybrid architecture). The results of simulations on typical scenarios shows that TSLBs is more efficient in terms of both the make-span and load balancing compared to stochastic task scheduling algorithm (STSA). We also show that TSLBs performs significantly better than STSA in terms of actor’s lifetime.     

SubCast: A distributed addressing and routing system for large scale wireless sensor and actor networks

Wireless sensor and actor networks (WSANs) are made up of a large number of sensing devices which are resource-impoverished nodes and powerful actuation devices: both are equipped with computation and communication capabilities. These devices cooperate to manage sensing and perform acting tasks. Numerous work conducted in the field of WSANs assumes the existence of addresses and routing infrastructure to validate their proposals. However, assigning addresses and delivering detected events in these networks remains highly challenging, specifically due to the sheer number of nodes. To address these issues, this paper proposes SubCast, a novel distributed address assignment and routing scheme based on a topic clustering system and fractal theory iterated function systems. In order to minimize data delivery costs among actors, the proposed architecture first builds an actor overlay network before allocating addresses to network nodes. Location information in the allocated addresses allows establishing data delivery paths. Simulation results confirm that the proposed system efficiently guarantees the allocation of unique addresses and performs efficient data delivery while reducing communication costs, delays as well as the impact of imprecise locations.     

Dynamic Coverage with Wireless Sensor and Actor Networks in Underwater Environment

This paper studies the problem of dynamic coverage with wireless sensor and actor networks (WSANs) in underwater environment. Different from most existing works, the WSANs consist of two kinds of nodes, i.e., sensor nodes (SNs) which cannot move autonomously and actor nodes (ANs) which can move autonomously according to the performance requirement. The problem of how to coordinate two kinds of nodes to facilitate dynamic coverage in underwater environment is challenging due to their heterogeneous capabilities. To reduce redundancy of communication links and improve connectivity between ANs and SNs in underwater WSANs, a min-weighted rigid graph based topology optimization scheme is first developed, such that the underwater communication energy consumption can be saved. With the optimized topology, a dynamic coverage strategy is proposed to improve the coverage among SNs and ANs for underwater WSAN where underwater fluid motions are considered. Furthermore, it is proved that the network coverage area is connected by using the min-weighted rigid graph. Finally, simulation results are presented to show the effectiveness of the main results.      

传感反应网络中单反应节点任务分配问题的研究

无线传感反应网络由大量资源受限的传感节点和少量资源丰富的反应节点通过无线通信自主形成的。其中,传感节点负责收集外界的事件信息,而反应节点依据传感节点探测到的信息做出决策,并对外界做出响应。本文主要研究WSANs中单反应节点任务分配的问题,并提出集中式和分布式两种算法,最后用J-Sim评估两种算法的性能。