基于活动区域的移动无线传感器网络路由协议

为了解决移动无线传感器网络中能量效率问题,提出了一种基于活动区域的移动无线传感器网络（WSN）路由协议。本方法使用源和sink节点相对位置来形成路由的活动区域,网络中的移动节点使用睡眠唤醒模式来节约能源。移动向量信息（如当前位置、方向和速度）以及节点的剩余能量,用于选择能够提供最大连接保留时间的邻居,移动向量信息也被用来唤醒活动区域中的移动节点。实验表明,与其他路由协议进行比较,该方法在分组传输过程中具有更高的可靠性。     

MIKE21模型在南新联圩洪水模拟中的应用

为了分析江西省南新联圩防洪保护区在圩提溃决后洪水在区内的演进过程,根据南新联圩防洪保护区周围湖泊、河流及圩区情况,建立了模拟保护区内洪水演进的MIKE21模型。分别采用2010年和2012年实测洪水资料对模型进行率定和验证,结果表明模型具有较高的模拟精度。在赣江50 a一遇洪水叠加湖口22.5 m洪水位(1954年型)的工况下,利用所建立的模型对防洪保护区内的淹没水深、流速和洪水演进过程等进行计算分析,获得了南新联圩防洪保护区发生溃堤后的受灾发展情况。研究成果可为南新联圩防洪预警及时发布、转移财产、逃生避险等提供技术支撑。     

An immune orthogonal learning particle swarm optimisation algorithm for routing recovery of wireless sensor networks with mobile sink

The growth of mobile handheld devices promotes sink mobility in an increasing number of wireless sensor networks (WSNs) applications. The movement of the sink may lead to the breakage of existing routes of WSNs, thus the routing recovery problem is a critical challenge. In order to maintain the available route from each source node to the sink, we propose an immune orthogonal learning particle swarm optimisation algorithm (IOLPSOA) to provide fast routing recovery from path failure due to the sink movement, and construct the efficient alternative path to repair the route. Due to its efficient bio-heuristic routing recovery mechanism in the algorithm, the orthogonal learning strategy can guide particles to fly on better directions by constructing a much promising and efficient exemplar, and the immune mechanism can maintain the diversity of the particles. We discuss the implementation of the IOLPSOA-based routing protocol and present the performance evaluation through several simulation experiments. The results demonstrate that the IOLPSOA-based protocol outperforms the other three protocols, which can efficiently repair the routing topology changed by the sink movement, reduce the communication overhead and prolong the lifetime of WSNs with mobile sink.     

LDBR: Low-deflection bufferless router for cost-sensitive network-on-chip design

In network-on-chip (NoC) designs, the bufferless router is more energy-efficient than the conventional router with buffers. However, in the bufferless network, deflections cause great performance loss. In this paper, three deflection models are firstly constructed for analyzing the causes of deflections. Then, we propose a low-deflection bufferless router (LDBR), in which a multi-channel network interface and a novel deflection routing based on turn model are designed for reducing the deflections during packet transmissions. Finally, LDBR is evaluated against the latest bufferless routers using synthetic and real-world traffic patterns. The experimental results exhibit that the deflection rate of LDBR network is reduced by 41% compared to other bufferless networks, and LDBR also shows superiority in cost and power consumption across all workloads.     

Non-derivative algorithm design for efficient routing over unreliable stochastic networks

We study the question of routing for minimum average drop rate over unreliable servers that are susceptible to random buffer failures, which arises in unreliable data or manufacturing networks. Interestingly, we first reveal that the traditional Join-the-Shortest-Queue (JSQ) or optimal Randomized Splitting (RS) strategies are consistently outperformed by the Constant Splitting Rule (CSR) where the incoming traffic is split with a constant fraction towards the available servers.This finding motivates us to obtain the optimal splitting fraction under CSR. However, the objective function to be minimized depends on the mean queue length of the servers, whose closed-form expression is not available and often intractable for general arrival and service processes. Thus, we use non-derivative methods to solve this optimization problem by approximately evaluating the objective value at each iteration. To that end, we explicitly characterize the approximation error by utilizing the regenerating nature of unreliable buffers. By adaptively controlling the precision of this approximation, we show that our proposed algorithm converges to an optimal splitting decision in the almost sure sense. Yet, previous works on non-derivative methods assume continuous differentiability of the objective function, which is not the case in our setup. We relax this strong assumption to the case when the objective function is locally Lipschitz continuous, which is another contribution of this paper.     

Caching and optimized request routing in cloud-based content delivery systems

Geographically distributed cloud platforms enable an attractive approach to large-scale content delivery. Storage at various sites can be dynamically acquired from (and released back to) the cloud provider so as to support content caching, according to the current demands for the content from the different geographic regions. When storage is sufficiently expensive that not all content should be cached at all sites, two issues must be addressed: how should requests for content be routed to the cloud provider sites, and what policy should be used for caching content using the elastic storage resources obtained from the cloud provider. Existing approaches are typically designed for non-elastic storage and little is known about the optimal policies when minimizing the delivery costs for distributed elastic storage.In this paper, we propose an approach in which elastic storage resources are exploited using a simple dynamic caching policy, while request routing is updated periodically according to the solution of an optimization model. Use of pull-based dynamic caching, rather than push-based placement, provides robustness to unpredicted changes in request rates. We show that this robustness is provided at low cost. Even with fixed request rates, use of the dynamic caching policy typically yields content delivery cost within 10% of that with the optimal static placement. We compare request routing according to our optimization model to simpler baseline routing policies, and find that the baseline policies can yield greatly increased delivery cost relative to optimized routing. Finally, we present a lower-cost approximate solution algorithm for our routing optimization problem that yields content delivery cost within 2.5% of the optimal solution.     

基于MIKE Flood的中小河流溃堤洪水演进数值模拟

针对水文资料缺乏的中小河流,以贵溪市罗塘河下游段为例,应用MIKE软件对河流溃堤洪水演进进行了研究。采用瞬时单位线法推求断面各频率的设计洪水,并将其作为洪水演进模型的输入;利用MIKE软件建立了贵溪市罗塘河下游段的一、二维耦合水动力模型,对该河下游段溃堤洪水演进过程进行了模拟;通过模拟分析,得到了溃口流量过程和堤防保护区洪水淹没过程。研究成果可为中小河流洪水风险分析和灾害损失评估提供技术支撑。     

A data porting tool for coupling models with different discretization needs

The presented work is part of a larger research program dealing with developing tools for coupling biogeochemical models in contaminated landscapes. The specific objective of this article is to provide researchers with a data porting tool to build hexagonal raster using information from a rectangular raster data (e.g. GIS format). This tool involves a computational algorithm and an open source software (written in C). The method of extending the reticulated functions defined on 2D networks is an essential key of this algorithm and can also be used for other purposes than data porting. The algorithm allows one to build the hexagonal raster with a cell size independent from the geometry of the rectangular raster. The extended function is a bi-cubic spline which can exactly reconstruct polynomials up to degree three in each variable. We validate the method by analyzing errors in some theoretical case studies followed by other studies with real terrain elevation data. We also introduce and briefly present an iterative water routing method and use it for validation on a case with concrete terrain data.     

LBMBS： A Load-Balanced Moveable Bubble Scheme for Tori Interconnection Networks

Moveable bubble flow control is an efficient technique to avoid deadlock for torus networks. However, it does not take into consideration the load balance feature. Therefore, this leads to inefficient resources utilization. Moreover, packets may be discarded due to the congestion of a network area. On the other hand, there are other algorithms that consider load balancing such as rHALB （r hop adaptive load-balanced）routing technique. Nonetheless, rHALB detects deadlock using the timeout threshold. This concept of deadlock detection may give incorrect responses in case the traffic is high. Therefore, packets are dropped although there is no deadlock. At the end, this affects the whole performance of the network. This paper proposes a new routing algorithm for tori interconnection networks, namely, the LBMBS （load-balanced moveable bubble scheme）. LBMBS integrates both concepts of moveable bubble and rHALB in order to provide at the end a load-balanced efficient deadlock-free algorithm. The protocol details are given and compared against other routing algorithms in the literature.     

改进型蚁群算法参数优化研究

研究在不使用局部搜索情况下参数组合对改进型蚁群算法的影响。以带时间窗的车辆路径问题为例,针对基于最大最小蚁群算法的改进蚁群算法中的五个参数,运用均匀设计法对最优参数配置问题进行了研究。仿真实验表明改进的蚁群算法效果明显,能有效解决Solomon数据集中的R类和RC类问题,且具有较强的鲁棒性。对最优参数的局部调整没有明显提高算法获取最优解能力的问题,分析了其可能的原因。