Optimal sub-tree scheduling for wireless sensor networks with partial coverage

In this paper, we consider the problem of scheduling optimal sub-trees at different time intervals for wireless sensor network (WSN) communications with partial coverage. More precisely, we minimize the total power consumption of the network while taking into account time dimension and multichannel diversity where different disjoint subsets of nodes are required to be active and connected under a tree topology configuration. Optimization problems of these types may arise when designing new wireless communication protocols in order to increase network lifetime. We propose mixed integer quadratic and linear programming (resp. MIQP and MILP) models to compute optimal solutions for the problem. Subsequently, we propose Kruskal-based variable neighborhood search (VNS) and simulated annealing (SA) meta-heuristic procedures. In particular, we introduce a new embedded guided local search strategy in our VNS algorithm to further strengthen the solutions obtained. Our numerical results indicate that some of the proposed models allow to obtain optimal solutions with CPLEX in significantly less CPU time. Similarly, VNS and SA algorithms proved to be highly efficient when compared to the optimal solutions and allow to obtain near optimal solutions for large instances. In particular, VNS and guided VNS strategies allow to obtain solutions in less CPU time whilst SA methods can reach better solutions at higher CPU times. Finally, optimizing over time dimension allows one to obtain important reductions in power savings which has never been reported before in the literature.     

Periphery deployment for wireless sensor systems with guaranteed coverage percentage

With the availability of tiny wireless sensors, it is now possible to track moving objects by placing such sensors on the targets, collecting needed data, and transmitting sensed data back to the sink for storage and analysis. For applications such as vessel clearance surveillance, landslide detection, conveyer monitoring, and body gesture tracking, the motions of the targets are often confined to a certain region, such as the water way or the mountain slope. To collect the data from the wireless sensors, base stations are usually needed, which are deployed at fixed positions around the monitored region. Unfortunately, due to issues such as potential interference, high packaging and deployment cost, and low reliability, many such applications could only deploy the base stations on the periphery of the monitored region. The question is how to deploy the base stations on the periphery so that they can cover the most area inside the monitored area. We formulate the periphery deployment problem and analyze the performance bound in terms of coverage percentage under both ideal and practical deployment conditions. Then, we describe a deployment procedure to solve the periphery deployment problem in polynomial time. The proposed algorithms are evaluated through extensive simulations drawn from a watercourse monitoring system. The results show that the proposed algorithms can reduce the size of the deployment set by 17% compared to the traditional area-coverage algorithms, and the coverage percentage is improved by 1.18 times.     

A survey on coverage and connectivity issues in wireless sensor networks

A wireless sensor network (WSN) is composed of a group of small power-constrained nodes with functions of sensing and communication, which can be scattered over a vast region for the purpose of detecting or monitoring some special events. The first challenge encountered in WSNs is how to cover a monitoring region perfectly. Coverage and connectivity are two of the most fundamental issues in WSNs, which have a great impact on the performance of WSNs. Optimized deployment strategy, sleep scheduling mechanism, and coverage radius cannot only reduce cost, but also extend the network lifetime. In this paper, we classify the coverage problem from different angles, describe the evaluation metrics of coverage control algorithms, analyze the relationship between coverage and connectivity, compare typical simulation tools, and discuss research challenges and existing problems in this area.     

无线传感器网络部分覆盖算法及连通性研究

研究了无线传感器网络在部分覆盖下的节点配置及网络连通性问题。首先,基于最优正六边形拓扑架构,给出了节点密集分布条件下的覆盖率与相邻工作节点间距的解析关系,并在已有的最优完全覆盖算法OGDC的基础上进行了扩展和改进,从而得到了一种新的网络节点配置算法EGDC（Extended OGDC Algorithm）。该算法可以有效地选择出合适的工作节点以达到任意给定覆盖率下的部分覆盖。此外,还给出了一种检验和评价网络连通性的方法,通过该方法可以对网络的连通性进行量化分析,并给出了一项评价网络连通性的指标。仿真表明,EGDC可以有效地实现任意期望覆盖率下的网络配置并保持网络的连通。     

无线传感器网络中基于网络覆盖的节点睡眠调度机制

在无线传感器网络中,节点睡眠-唤醒调度机制对于延长其生命周期至关重要。在现有的节点睡眠调度机制中,节点能耗是调度机制的唯一考虑目标。然而这种以节省节点能耗为目的调度机制很容易导致传感网络无法完全覆盖监测区域,导致严重后果。本文基于现有调度机制的不足,提出一种考虑到网络覆盖面的节能调度机制。这种机制既能降低网络能耗也能够兼顾到网络的监测覆盖情况。仿真结果表明该机制能在保证较高的网络覆盖面的前提下有效提高网络生命周期。     

一种新型无线传感器网络节能覆盖方案

针对一种实际地理环境下的生态监测问题,把拓扑控制中的功率控制思想引入到节能覆盖的研究中,建立感知半径之和最小的数学模型,并用遗传算法求解该模型,得到最优覆盖解。最后,对该方案进行能耗分析和仿真实验,结果表明该算法不仅节能,而且可以获得较高覆盖率,降低信道通讯干扰并提高网络的抗毁性。     

无线传感器网络节点自调度冗余覆盖算法

对于能量受限的无线传感器网络,延长网络存活的时间很关键。针对这个问题,提出了一种基于能量均衡的传感器节点自调度冗余覆盖协议（SRCP）,通过仿真实验对该算法的有关性能进行了评价,性能评价表明：这种算法能有效使用节点能力,延长网络存活时间。     

A column generation approach to extend lifetime in wireless sensor networks with coverage and connectivity constraints

This paper addresses the maximum network lifetime problem in wireless sensor networks with connectivity and coverage constraints. In this problem, the purpose is to schedule the activity of a set of wireless sensors, keeping them connected while network lifetime is maximized. Two cases are considered. First, the full coverage of the targets is required, and second only a fraction of the targets has to be covered at any instant of time. An exact approach based on column generation and boosted by GRASP and VNS is proposed to address both of these problems. Finally, a multiphase framework combining these two approaches is built by sequentially using these two heuristics at each iteration of the column generation algorithm. The results show that our proposals are able to tackle the problem efficiently and that combining the two heuristic approaches improves the results significantly.     

多宿点无线传感器网络时分多址时隙优化分配算法

针对单宿点无线传感器网络的时延大、容易出现传输瓶颈等问题,提出了多宿点无线传感器网络模型以及该模型的基于遗传算法(GA)的时分多址(TDMA)时隙分配算法。该算法根据宿点的数量以及位置将整个传感器网络划分成多个小传感器网络,并采用遗传算法对时隙分配结果进行优化。仿真结果表明,基于遗传算法的多宿点无线传感器网络TDMA时隙分配算法得到的时隙分配结果在时隙分配帧长度、数据包平均时延以及节点平均能耗方面均要优于图着色算法。     

A proportional fairness scheduling for wireless sensor networks

This paper describes a packet scheduling algorithm for wireless sensor networks (WSNs) that meets the proportional fairness principle. Based on the weighted round-robin strategy, the proposed scheduling algorithm allocates a different service quota to different traffic according to the average packet arrival rate. This guarantees proportional fairness in terms of the average packet delivery delay and the average packet loss ratio. Since the scheduling algorithm does not perform high-load operations such as time stamping and sorting, it can be implemented easily and is suitable for resource-limited WSNs. The proposed scheduling algorithm is tested in a WSN and is found to guarantee the proportional fairness of the average packet delivery delay when this is used as the performance metric, and to realize proportional fairness in the average packet loss ratio when all the queues are overflowing and the average packet loss ratio is used as the performance metric.     

一种无线多媒体传感器网络分区链路调度算法

链路干扰是无线多媒体传感器网络实现大容量、实时、可靠传输的主要困难。为提高多跳传输模式下无线网络性能,基于MAC层的调度算法得到了广泛关注。调度算法为每条链路分配合理的传输时槽,降低了冲突和重传次数,能显著提高网络传输性能。但随着网络规模的增大,无论是集中式还是分布式调度算法,都存在调度开销增大和性能降低的问题。针对这一问题,根据节点分布密度和承载网络流量大小,将网络划分为密集区域和稀疏区域。稀疏区域的节点传输冲突较小,直接采用CSMA的协议。密集区域的节点传输冲突大,采用基于队列长度的分布式调度。分区调度能够有效降低网络规模扩大导致的调度算法复杂性增大的问题。仿真实验表明,分区调度算法无论是在队列长度,还是在延时性能上,较传统算法有明显改善。     

Quantifying connectivity in wireless sensor networks with grid-based deployments

Measuring network connectivity under grid-based deployment in 3D space is a challenging problem in wireless sensor networks (WSNs). Solving such a problem becomes an even more intricate task with realistic deployment factors such as placement uncertainty and hindrances to wireless communication channels. While much work has been published on optimizing connectivity, only a few papers have addressed such realistic aspects which cause severe connectivity problems in practice. In this paper, we introduce a novel grid-based deployment metric, called Average Connectivity Percentage in order to characterize the deployed network connectivity when sensor placements are subject to random errors around their corresponding grid locations. A generic approach is proposed to assess and evaluate the proposed metric. This generic approach is independent of the grid-shape, random error distributions, and different environment-based channel characteristics. We apply the generic approach in two practical deployment scenarios: the grid-based deployment with bounded uniform errors and with unbounded normal errors. In both cases, the average connectivity percentage is computed numerically and verified via extensive simulations. Based on the numerical results, quantified effects of positioning errors and grid edge length on the average connectivity percentage are outlined.     

Sensor deployment optimization methods to achieve both coverage and connectivity in wireless sensor networks

In this study, we aim to cover a sensing area by deploying a minimum number of wireless sensors while maintaining the connectivity between the deployed sensors. The problem may be reduced to a two-dimensional critical coverage problem which is an NP-Complete problem. We develop an integer linear programming model to solve the problem optimally. We also propose a local search (LS) algorithm and a genetic algorithm (GA) as approximate methods. We verify by computational experiments that the integer linear model, using Cplex, is able to provide an optimal solution of all our small and medium size problems. We also show that the proposed methods outperform some regular sensor deployment patterns.     

无线传感器网络栅栏覆盖改进

栅栏覆盖是无线传感器网络中的研究热点,鉴于移动节点的高昂造价以及在移动过程中的巨大能耗,针对高效节能的修复栅栏漏洞问题进行研究.建立静止节点的权重图,并利用迪杰斯特拉算法(Dijkstra)寻找所需最少数目的移动节点和构建栅栏覆盖的最短路径.根据构建栅栏覆盖的最短路径和基于路径上的每个栅栏漏洞所需的最少移动节点,将栅栏漏洞划分为简单情况和一般情况,借助于最大权匹配算法(Kuhn-Munkres)求解移动节点的最短移动距离.仿真实验表明,所提出算法明显减少了移动节点的移动距离,实现了栅栏覆盖.     

一种连通性覆盖的无线传感器网络节点调度算法

研究传感器节点随机部署于监测区域内,无节点地理位置信息情况下,如何能量有效地保证网络的通信连通与感知覆盖;节点采用基于概率的联合感知模型。提出CDS-based SSCA算法,其为一种基于连通支配集构造树的节点调度机制,每个节点根据剩余能量和与父节点的距离来设置等待时间及成为候选节点优先级。模拟实验结果显示,本算法能够能量有效地满足感知覆盖和连通覆盖要求;与ASW算法相比较,工作节点个数较少,网络生命周期明显延长,降低了网络整体耗能。     

无线传感网络中覆盖能效动态控制优化策略

能量约束是无线传感网络测量控制的关键问题之一.本文针对移动节点位置优化问题,提出了无线传感网络通信能耗评价指标,采用微粒群优化策略更新节点位置,使无线传感网络具有更强的灵活性和能效性.利用Dijkstra算法获得网络最优通信路径计算能耗评价指标.采用动态能量控制策略使空闲节点进入睡眠状态减少网络运行能耗.通过优化能量指标降低了通信能耗,实现了无线传感网络覆盖与通信能量消耗的合理均衡.对移动目标跟踪仿真表明,覆盖能效优化算法与动态能量控制策略相结合提高了无线传感网络覆盖的能效性.